Morphology of the Collateral Sulcal Complex and Discrimination of Functional Activation During Navigation in the Parahippocampal Gyrus of the Human Brain

Morphology of the collateral sulcal complex and discrimination of functional activation during navigation in the parahippocampal gyrus of the human brain

Sonja Christina Huntgeburth Department of Psychology McGill University, Montreal, Quebec, Canada

Initial submission October 5, 2015 Final submission December 10, 2015

A thesis submitted to McGill University in partial fulfillment of the requirements of the degree of Doctor of Philosophy, Clinical Psychology © Sonja C. Huntgeburth, 2015

Table of Contents

Abstract ...... 8 Résumé ...... 10 List of Tables ...... 15 List of Figures ...... 16 Chapter One ...... 18 1. General Introduction ...... 18 1.1 Sulcal morphology laterally delimiting the parahippocampal gyrus ...... 30 1.2 Cytoarchitectonic organization and connectivity of the parahippocampal gyrus ...... 34 1.3 Parahippocampal gyrus and spatial information processing ...... 41 1.4 Probability maps in standard stereotaxic space ...... 51 1.5 Aims and Overview ...... 54 1.6 Figures ...... 56 Chapter Two ...... 59 2. Morphological patterns of the collateral sulcus in the human brain ...... 59 2.1 Abstract ...... 60 2.2 Introduction ...... 61 2.3 Materials and methods ...... 63 2.4 Results ...... 65 2.5 Discussion ...... 71 2.6 References ...... 85 2.7 Acknowledgements ...... 92 2.8 Abbreviations ...... 92 2.9 Tables ...... 93 2.10 Figures ...... 98 Chapter Three ...... 114 3. Three-dimensional probability maps of the rhinal and the collateral sulci in the human brain...... 114 3.1 Prelude ...... 115 3.2 Abstract ...... 116 3.3 Introduction ...... 117 3.4 Materials and methods ...... 119 3.5 Results ...... 122 3.6 Discussion ...... 128 3.7 References ...... 139 3.8 Acknowledgements ...... 150 3.9 Tables ...... 151 3.10 Figures ...... 156 Chapter Four ...... 165 4. Local morphology informs location of activation during navigation within the parahippocampal region of the human brain ...... 165 4.1 Prelude ...... 166 4.2 Abstract ...... 168 4.3 Introduction ...... 169

4.4 Materials and methods ...... 171 4.5 Results ...... 177 4.6 Discussion ...... 180 4.7 References ...... 185 4.8 Acknowledgements ...... 190 4.9 Tables ...... 191 4.10 Figures ...... 196 Chapter Five ...... 202 5. Consequences of mild traumatic brain injury on functional activation patterns during navigation in a virtual-reality environment: an fMRI study ...... 202 5.1 Prelude ...... 203 5.2 Abstract ...... 204 5.3 Introduction ...... 205 5.4 Materials and methods ...... 208 5.5 Results ...... 214 5.6 Discussion ...... 218 5.7 References ...... 222 5.8 Acknowledgements ...... 230 5.9 Tables ...... 231 5.10 Figures ...... 234 Chapter Six ...... 238 6. General Discussion ...... 238 6.1 The morphology of the collateral sulcal complex ...... 241 6.2 Linking anatomy and function in the parahippocampal gyrus ...... 250 6.3 Anatomo-functional relationships from the healthy brain to the study of a clinical population ...... 255 6.4 Conclusion ...... 258 List of References for Introduction and Discussion ...... 259 Appendices ...... 286

Dedication

I dedicate my thesis to my loving parents, Christel and Helmut Huntgeburth. You are the best parents a daughter could ever wish for.

Acknowledgements

Immeasurable appreciation and deepest gratitude for their help and support are extended to the following persons who in one way or another have contributed to my personal and professional development throughout graduate school to where I am today.

Dr. Michael Petrides, my thesis advisor: Thank you for the valuable experience I received throughout the years in your lab, for your continuous guidance and mentorship, for the inspiring discussions, and for making me appreciate the immense importance of a solid understanding of neuroanatomy, which forms the corner stone of neuroscience. I admire your precision in scientific thinking and writing, which continues to make me grow as a researcher and a clinician. On that note, I shall never split an infinitive again.

Dr. Alain Ptito, my thesis co-advisor: Thank you for giving me the opportunity to further my knowledge of neuropsychology, and integrate clinical work with experimental research. The clinical experience I have gained under your guidance, has allowed me to mature as a psychologist. In addition, I am grateful for your valuable feedback and support during the manuscript and thesis preparation.

Dr. Jen-Kai Chen, my collaborator, colleagues, and friend: Thank you for collaborating with me on the two functional neuroimaging studies that form a part of this thesis. Your great support and friendship means a lot to me.

Dr. Denise Klein and Dr. Viviane Sziklas, my graduate committee, as well as Dr. Louis Collins: Thank you for your continuous encouragement and feedback on my work throughout my time in graduate school.

Dr. Marco Sinai and Dr. Jennifer Russel, my clinical training supervisors: You have helped and supported my professional development and our work together has shaped me as clinical psychologist.

A tremendous thank you to all graduate professors who helped shape my critical thinking and saw me grow through the years.

My friends and colleagues from the Petrides lab, past and present: Veronika, Emily, Jennifer, Callah, Trisanna, Catherine, Delphine, Celine, Anne-Sophie, Penelope, Scott, Steve, Vikas, Georgia, Jürgen, and Rhea. Thank you for your encouragements, support, and advice.

Administrative staff at the Montreal Neurological Institute, Annie Lebire and Line Gingras, as well as at the Psychology Department, Giovanna Locascio and Chantale Bousquet, and at the Allan Memorial Institute during my pre-doctoral internship, Sandy Iasenza, for your consistent help and support and for always making yourselves available to me for any question I had, no matter how big or small. I always felt much supported by your guidance.

Claude Lepage: Thank you for always being there when I needed any help or support with my MRI data processing, and for all the tomato plants you have given me over the past several years; you have supported me in growing a green thumb.

My clinical cohort, Whitney, Marina, Mallak, Natsumi, Cory, and Phil: Thank you for the unforgettable times we had together in the clinical psychology program.

My dear, dear friends, who have been there at all times, no matter what, with unconditional love: Sylvia and Chris, Julie, Veronika, Jerome, Laurence and Fred, Emily, Jennifer, Beth, Alex and Danielle, Catherine, Daphne, the UCN crew, Chrissy and Bernd-Achim, Celina, Dirk, Julia and Xiaohong, Dirk-Jan, Anna and Jan Willem, Marianne and Marc, Wouter and Magda, Efrain, Steph and Dale, Anca, and many others. You make me smile when I am sad, you help me stand up when I have fallen, and you encourage me in moments of doubt. Thank you.

A big and special thank you goes to Dr. Veronika Zlatkina, who supported me throughout, but especially in the final hours before thesis submission.

My family: my parents, Christel and Helmut, my brother Michael, my sister-in- law Jennifer, and my beautiful niece Mila: Thank you for standing by me in good and difficult times. You are always there, and although we are an ocean apart, you are with me in spirit always.

Abstract

A comprehensive study of the functional organization of the parahippocampal gyrus (PHG) in the human brain requires a clear understanding of the sulcal-gyral morphology and its variability in individual cerebral hemispheres. This is imperative, given the cytoarchitectonic and functional heterogeneity of the cortical areas that make up the PHG. The collateral sulcal complex comprises a number of sulci that laterally delineate the rostrocaudal extent of the entorhinal cortex and the parahippocampal cortex (PHC) that occupy the surface of the PHG. In non-human primates, the rhinal sulcus refers to a sulcus that laterally delimits the extent of the entorhinal cortex. In contrast, in the human brain, the term rhinal sulcus has been used ambiguously. Some researchers have called a small dimple at the anteriormost part of the PHG the rhinal sulcus, referring to the sulcus laterally bordering the entorhinal cortex as part of the collateral sulcus. This usage of the term rhinal sulcus implies that, in the human brain, the rhinal sulcus bears only a partial relationship with the most anterior part of the entorhinal cortex. In the research carried out for this thesis, the details of the morphology, i.e. the sulcal patterns and variability, of the sulci that make up the collateral sulcal complex are defined in individual subjects on structural magnetic resonance images (MRIs) in the standard stereotaxic space of the Montreal Neurological Institute. We found that the anterior sulcal segment of the collateral sulcal complex, which we refer to as the rhinal sulcus, delimits laterally the entorhinal cortex and, posteriorly, the collateral sulcus proper provides the lateral border of the PHC. In addition, we identified a short sulcus, the parahippocampal extension of the collateral sulcus, which runs transversely into the PHG and provides its posterior border. Further caudally, the occipital branch of the collateral sulcus lay in the lingual gyrus of the occipital lobe, bearing no relationship to the PHG. Next, sulcal probability maps were established for the sulci that laterally delineate the PHG (i.e. the rhinal sulcus, collateral sulcus proper, and parahippocampal extension of the collateral sulcus) to aid accurate identification of the sulcal segments and the location of activation peaks in functional neuroimaging studies.

Together these anatomical investigations showed that, in the human brain, a sulcus exists that laterally delineates the extent of the entorhinal cortex and that, therefore, this sulcus should be termed the rhinal sulcus, consistent with the non- human primate literature. The level at which the collateral sulcus proper can be separated from the occipital extent of the collateral sulcus may be a potential candidate for a morphological landmark distinguishing the PHC of the medial temporal lobe, involved in mnemonic information processing, from the lingual gyrus of the occipital lobe, involved in processing visual information. The location of functional activation peaks obtained during the performance of a navigation task in a functional MRI (fMRI) study were related to the morphology of the sulcal segments of the collateral sulcal complex that had been identified in the anatomical studies. Based on these morphological studies, it was possible to show that the middle and posterior parts of the PHC, and not the anterior PHC or entorhinal cortex, were involved when scene-selective information necessary for navigation was processed. Moreover, a similar fMRI study in patients with mild traumatic brain injury revealed that such structure- function relationships could aid the identification of subtle consequences on functional activation in the right posterior and left middle PHC. Without a detailed understanding of the sulcal segments of the collateral sulcal complex, the correct interpretation of the activation peaks observed in the fMRI studies in the healthy and clinical populations would not have been possible.

Résumé

La compréhension de l’organisation fonctionnelle du gyrus parahippocampique (GPH) dans le cerveau humain nécessite une étude détaillée, sujet par sujet, de la morphologie des sillons et gyrus et de leur variabilité. Ceci est impératif, compte tenu de l'hétérogénéité des aires corticales cytoarchitectoniques et fonctionnels qui constituent le GPH. La morphologie du complexe du sillon collatéral consiste de plusieurs sillons qui délimitent dans sa partie latérale le cortex entorhinal et le cortex parahippocampique (CPH).Chez des primates non humains, le terme sillon rhinal est utilisé pour désigner un sillon qui délimite latéralement l’étendue du cortex entorhinal. Par contre, chez l’homme le terme pour le sillon rhinal a été utilisé de façon ambiguë. Certaine chercheurs ont attribué à une petite «fossette» dans la partie la plus antérieure du GPH, le nom de sillon rhinal, identifiant ainsi le sillon qui borde latéralement le cortex entorhinal comme faisant partie du sillon collatéral. Cette utilisation du terme de sillon rhinal implique que, chez l’homme, ce sillon n’est qu’en correspondance partielle avec la limite la plus antérieure du cortex entorhinal. Dans les études présentées dans cette thèse, l’imagerie résonance magnétique (IRM) a été utilisée dans des analyses sujet par sujet pour faire avancer notre connaissance de la morphologie, c.à.d.des motifs de replis corticaux et de leurs variabilités, du complexe du sillon collatéral qui délimite dans sa partie latérale le GPH. Nos résultats ont montré que le segment antérieur du complexe du sillon collatéral, appelé le sillon rhinal, marque de manière fiable l'étendue latérale du cortex entorhinal et le sillon collatéral propre délimite latéralement l’extension du CPH.De plus, notre recherche a identifié un sillon, l’extension parahippocampique du sillon collatéral, qui se situe en position transversale au GPH et qui le fusionne, marquant ainsi son extrémité la plus caudale.La division occipitale du sillon collatéral se trouve dans le gyrus lingual du lobe occipital et n’a aucun rapport avec le GPH. Ensuite, nous avons créé des cartes de probabilité des sillons qui délimitent latéralement le GPH (c.à.d.le sillon rhinal, le sillon collatéral propre, et l’extension parahippocampique du sillon collatéral) pour

permettre l'identification précise des valeurs maximales d'activation obtenues par les études de neuro-imagerie fonctionnelle. Nos études anatomiques ont démontré qu’un sillon existe dans le cerveau humain qui forme un point de repère latérale fiable du cortex entorhinal comme dans des autre primates non humains et que ce sillon devrait été appelé sillon rhinal. Le niveau auquel le sillon collatéral adéquat et la partie occipitale du sillon collatéral sont séparés, semble correspondre à l'extrémité caudale du CPH, impliqué dans le traitement de l’information mnémonique, et à la frontière antérieure du gyrus lingual, impliqué dans le traitement de l'information visuelle. La localisation des modèles d’activation fonctionnelle obtenus lors de la navigation spatiale en IRM fonctionnelle (IRMf) a été étudiée en lien avec les repères fournit par la morphologie des sillons du complexe du sillon collatéral identifiées dans les études anatomiques. Plus précisément, les parties médiane et postérieure du CPH et non le CPH antérieur ni le cortex entorhinal, ont été impliqué pour le traitement mnémonique de l'information liée à des scènes nécessaires à la navigation. De plus, une étude IRMf chez des patients qui ont subi un traumatisme crânien léger a démontré qu’une relation entre la structure et le fonctionnement pouvait aider à l’identification des conséquences subtiles de l’activation fonctionnelle dans la partie médiane et postérieure du CPH. Sans une compréhension détaillée des segments du complexe du sillon collatéral, cette interprétation des modèles d’activation fonctionnelle obtenue lors de l’étude de l’IRMf n’aurait pas été réalisable dans des populations saine et clinique.

Funding and support

An expression of my sincere gratitude goes to the Fonds de la recherche de santé du Québec (FRSQ) for granting me the ‘bourse de formation de maîtrise‘, a scholarship for my Masters of Science education. Furthermore, I thank McGill University for awarding me the Recruitment Excellence Fellowship, a graduate student entrance award. I would also like to express my appreciation to the Canadian Institutes of Health Research in acknowledgment for the grants MOP- 14620 and MOP-130361 awarded to Dr. Michael Petrides, as well as MOP-64271 granted to Dr. Michael Petrides and Dr. Alain Ptito, which supported the research presented in this thesis.

Statement of originality

The studies present novel findings about the morphology of the collateral sulcal complex (Chapters 2 and 3), the relation of the different sulcal segments of the collateral sulcal complex as markers of the precise location of activation patterns in the parahippocampal region during navigation in a virtual environment (Chapter 4), as well as about the functional activation patterns during navigation of participants who had suffered mild traumatic brain injury (Chapter 5). The studies have been or will be submitted for publication in peer-reviewed journals. The study presented in Chapter 2 has been published in the European Journal of Neuroscience. The second and third studies (Chapters 3 and 4) have been submitted for publication in peer reviewed journals. The fourth study in Chapter 5 will be submitted soon. These studies were also presented at various international conferences, including: the 37th annual meeting of the Society for Neuroscience (in San Diego, CA, USA, 2007), the 3rd International Congress on Brain and Behaviour (in Thessaloniki, Greece, 2007), the 17th annual meeting of the Organization for Human Brain Mapping (in Quebec City, Quebec, Canada, 2011), the World Congress on Brain, Behavior and Emotions (in Montreal, Quebec, Canada, 2014), and the Canadian Neuroscience Conference (in Montreal, Quebec, Canada, 2014), as well as the local annual Neuropsychology Day poster presentations at the Montreal Neurological Institute (in Montreal, Quebec, Canada).

Contribution of authors

The studies reported in Chapters 2 and 3 were designed with Dr. Michael Petrides. The structural magnetic resonance images used in study one (Chapter 2) were taken from the International Consortium for Brain Mapping (ICBM) (funded by National Institute of Biomedical Imaging and BioEngineering; principal investigator: John Mazziotta, MD, Ph.D.). I conducted the sulcal identification and carried out the data analysis in these two studies under the guidance of Dr. Petrides. The findings of studies two and three were discussed and interpreted together with Dr. Petrides. The manuscripts were then co-authored with Dr. Petrides. Dr. Jen-Kai Chen and Dr. Alain Ptito are co-authors on the studies presented in both Chapters 4 and 5. The particular experiment that forms the basis of the studies presented in Chapters 4 and 5 was designed by Dr. Michael Petrides, Dr. Alain Ptito and Dr. Jen-Kai Chen. The functional magnetic resonance imaging data used in these two studies (Chapter 4 and 5) were acquired and processed with the in-house fMRI analysis software fMRIstat, developed by Dr. Keith Worsley, by Dr. Jen-Kai Chen. For the study presented in Chapter 4, I examined the sulcal patterns on a subject-by-subject and carried out the analysis. This involved the examination of the morphology of the collateral sulcal complex based on the findings of the morphological study presented in Chapter 2 and the probabilistic maps presented in Chapter 3, as well as the identification of the locus of the peaks of functional activation in relation to the morphology of the sulcal segments of the collateral sulcal complex. For the study presented in Chapter 5, Dr. Jen-Kai Chen and I performed the group analyses, and I examined the statistical t-maps of the functional activation and identified and interpreted the location of the functional activation foci of the mild traumatic brain injury and the healthy control group. The manuscripts of studies 3 and 4 (Chapters 4 and 5) were then co-authored with Drs. Petrides, Jen-Kai Chen, and Alain Ptito.

List of Tables

Chapter Two Table 2.9.1 ...... 93 Table 2.9.2 ...... 94 Table 2.9.3 ...... 96

Chapter Three Table 3.9.1 ...... 151 Table 3.9.2 ...... 152 Table 3.9.3 ...... 153 Table 3.9.4 ...... 155

Chapter Four Table 4.9.1 ...... 191 Table 4.9.2 ...... 192 Table 4.9.3 ...... 193 Table 4.9.4 ...... 194

Chapter Five Table 5.9.1 ...... 231 Table 5.9.2 ...... 232

List of Figures

Chapter One Figure 1.6.1 ...... 56 Figure 1.6.2 ...... 57 Figure 1.6.3 ...... 58

Chapter Two Figure 2.10.1 ...... 98 Figure 2.10.2 ...... 100 Figure 2.10.3 ...... 102 Figure 2.10.4 ...... 104 Figure 2.10.5 ...... 106 Figure 2.10.6 ...... 108 Figure 2.10.7 ...... 110 Figure 2.10.8 ...... 111 Figure 2.10.9 ...... 112

Chapter Three Figure 3.10.1 ...... 156 Figure 3.10.2 ...... 157 Figure 3.10.3 ...... 159 Figure 3.10.4 ...... 160 Figure 3.10.5 ...... 161 Figure 3.10.6 ...... 162 Figure 3.10.7 ...... 163 Figure 3.10.8 ...... 164

Chapter Four Figure 4.10.1 ...... 196 Figure 4.10.2 ...... 197

Figure 4.10.3 ...... 199 Figure 4.10.4 ...... 200 Figure 4.10.5 ...... 201

Chapter Five Figure 5.10.1 ...... 234 Figure 5.10.2 ...... 235 Figure 5.10.3 ...... 236 Figure 5.10.4 ...... 237

Chapter One 1. General Introduction The parahippocampal gyrus of the human brain is a complex anatomical structure in the medial temporal lobe (see Fig. 1.6.1) that comprises the entorhinal, perirhinal, and parahippocampal cortex (Van Hoesen, 1995). Anteriorly, the entorhinal cortex lies on the rostral part of the parahippocampal gyrus, posterior to which the parahippocampal cortex covers the surface of the posterior portion of the parahippocampal gyrus. The perirhinal cortex forms the border between the entorhinal cortex medially and the fusiform gyrus laterally and it extends rostrocaudally alongside the entorhinal cortex in the medial bank of the sulcal complex that laterally delineates the parahippocampal gyrus. Together with the hippocampal formation, which is folded medially under the hippocampal fissure (i.e. the medial boundary of the parahippocampal gyrus) (Van Hoesen, 1995), these anatomical regions form the medial temporal lobe memory system (Scoville & Milner, 1957; Squire & Zola-Morgan, 1991). Bilateral damage to the medial temporal lobe, which includes the hippocampus and the cortex on the surface of the parahippocampal gyrus, causes severe anterograde amnesia, i.e. an inability to form new memories (Scoville & Milner, 1957, 2000). In particular right hemisphere damage to this region leads to a specific memory impairment in object-location memory (Ploner et al., 2000; Smith et al., 2011; Smith & Milner, 1981, 1989), and impaired navigational abilities (Bohbot et al., 2000; Bohbot & Corkin, 2007; Bohbot et al., 1998; Habib & Sirigu, 1987). Researchers have focused on disentangling the differential functional contributions of the various regions of the parahippocampal gyrus, using a variety of methods (e.g. lesion studies in the brains of non-human primates, examining patients with brain damage, and functional neuroimaging techniques investigating the human brain in-vivo). Lesion studies in the non-human primate, such as the macaque monkey, allow us to study the effects of well-defined ablations to specific parts of the brain, while leaving others intact. In lesion studies in patients, damage is often more widespread and lesion sites are less controlled. Research using structural magnetic resonance imaging permits the examination of the

integrity and three-dimensional nature of the human brain in-vivo, and functional neuroimaging enables us to visualize brain activity during engagement in a specific experimental task. In functional neuroimaging, increases in blood-oxygen uptake, measured indirectly by the levels of deoxygenated haemoglobin, reflect greater cognitive demands of one region in the brain versus another. This is taken as an indirect measure of functional activation (i.e. brain activity) required by the cognitive/behavioural process that is being tested by the experimental paradigm. The location of such functional changes in brain activity is generally expressed within a standard coordinate system that presents the activation location as a specific point within three-dimensional space (i.e. the sagittal plane (x coordinate), coronal plane (y coordinate), and horizontal plane (z coordinate)). Given that statistical analyses of the levels of deoxygenated haemoglobin are often computed at the group level, as opposed to the individual subject level, the resulting brain activity location coordinates reported in the scientific literature are often average coordinates for a particular group given a specific task comparison. Within the neuroscience community, the standard coordinate system is a common reference frame that allows for comparisons of functional activation and its anatomical location between brains, and by extension, studies. However, due to large variability in the morphology of the sulci, even after registration into a standard space, functional activation peaks that may relate to different cognitive processing may not be differentiated at the group-level average (Amiez et al., 2006). In a functional neuroimaging study by Amiez and colleagues (2006), the activation coordinate representing the hand-arm conditional association motor response at the group-level fell within the same general average coordinate location as the group-level activation coordinate for the frontal-eye-field. However, when these investigators examined the brains at the individual subject level, they found that the location of the activation peaks for the hand-arm conditional association task could be separated from the locus of the activation peaks for the frontal eye field based on the local morphology. The activation peaks from the hand-arm conditional association task consistently fell along the dorsal branch of the superior precentral sulcus, whereas the activation peaks for

the frontal eye field task related to the ventral branch of the superior precentral sulcus (Amiez et al., 2006) (for an example see Fig 1.6.2 of this thesis). The average coordinates at the group level thus had only provided an estimated location of the functional activation peaks without taking into account the local cortical folding pattern, which offered valuable information for a more precise determination of location. Therefore, the average standard coordinates in a group of subjects may not always be the most accurate way of describing and distinguishing the location of different functional activation peaks. In order to circumvent the issue of variability in local morphology, some researchers have developed a methodology called functional localizer scans in functional magnetic resonance imaging (fMRI). Here, first a functional region of interest is identified. For instance, to identify the functionally defined region of interest for the parahippocampal place area (PPA), i.e. a region showing a category-selective response preference for stimuli of places and scenes (Epstein and Kanwisher (1998)), a contrast between images of places/scenes and pictures of objects, faces, and/or scrambled objects is commonly used. The region of activation observed as a result of this contrast subsequently forms the basis for testing specific hypotheses about the function of that region. Such functional localizers have been applied to identify various functionally distinct brain regions, the most well-known being the category-selective region for processing of face- relevant information, called the fusiform face area (FFA) (Kanwisher et al., 1997), and the place/scene-selective region, referred to as the parahippocampal place area (PPA) (Epstein & Kanwisher, 1998). A principal motivation for using the functional localizer approach in functional neuroimaging is the inter-subject variability in brain morphology which poses challenges when relating function to structure in group-based data (Saxe et al., 2006). However, the functional localizer approach does not take into account brain anatomy and, therefore, does not offer information about variations in functional anatomy across subjects (Friston & Henson, 2006; Friston et al., 2006); information that is important if one tries to understand better how the brain works. The main point of the critique on the approach of localizers, however, is the statistical basis on which functional

localizers are based (for a detailed discussion, see Friston et al. (2006), Saxe et al. (2006), Friston and Henson (2006)). Important for the present introduction is that such functional regions-of-interest may ‘fuse’ together into functional units two (or more) regions which, on the basis of our knowledge of the local anatomy and connectivity, should be considered separate regions. For instance, in a recent study, Baldassano and colleagues (2013) identified the PPA with the help of the functional localizer method and subsequently used this functionally defined region as a seed region for a connectivity analysis. The authors concluded that there were two functionally distinct subregions making up the PPA, an anterior subregion exhibiting a stronger connectivity with the retrosplenial cortex and caudal inferior parietal lobule, and a posterior subregion that shows a stronger connectivity with the lateral occipital complex and transverse occipital sulcus. However, the illustrations provided in the publication of this study (e.g. Figure 3, p.233) suggest that the seed region of the PPA comprised the posterior part of the parahippocampal cortex and the adjacent fusiform and lingual gyrus (Baldassano et al., 2013). Including these regions in the same seed mask may have influenced the connectivity results and may explain why Baldassano and colleagues (2013) observed a similarity in response-preferences to scenes in both PPA subregions. The initial localizer scan by Baldassano and colleagues (2013), which formed the basis for their subsequent connectivity examination in this region-of-interest, likely reflects a ‘fusion’ of regions (i.e. the parahippocampal cortex, the fusiform, and lingual gyrus) which should be considered anatomically and functionally distinct. Therefore, the functional localizer approach may not form a precise method for examining the location of functional differences of the brain for structures that lie close to each other. In contrast, the examination of functional activation patterns in the individual brain may provide more accurate information about the anatomical locus of activation peaks, provided that a detailed description of the local morphology of the region of interest has been established. For instance, in the study mentioned earlier, Amiez and colleagues (2006) were able to differentiate the location of activation peaks during the hand-arm conditional association task

from the activity representing the frontal eye field by examining the activity peaks in the individual brains because of the detailed morphological analysis of the sulci of the precentral sulcal complex (Germann et al., 2005) (see Fig. 1.6.2). As the study by Amiez and colleagues (2006) illustrates, functional activity peaks can be described as lying within, anterior, posterior, medial, lateral, dorsal, or ventral to a specific sulcus and/or sulcal segment. Therefore, a detailed analysis of the local morphology, its variability and different sulcal patterns is necessary for a subsequent establishment of the locus of functional activation in relation to the local sulcal-gyral anatomy of the cerebral cortex (Petrides, 2012). Further evidence illustrating the importance of applying such specific knowledge of the local morphology within the individual brain when examining the locus of functional activation patterns comes from the establishment of three cingulate motor areas in the human brain (Amiez & Petrides, 2014), the location of the hand region in the primary motor cortex (Yousry et al., 1997), the location of reading- elicited activity in the angular gyrus region (Segal & Petrides, 2013), and the differentiation of sensorimotor function along the sulcal segments of the postcentral sulcal complex (Zlatkina et al., 2015). At this point, it should be noted that a complementary approach to the detailed examination of the local morphology within single subjects for the identification of consistent sulcal patterns comes in the form of probability maps. Such maps allow for a more accurate identification of the location of functional activation obtained with neuroimaging, as they provide a quantitative measure of the location variability of individual sulcal segments. When such sulcal probability maps are constructed over large enough samples, they provide valuable information of the location of particular sulci, and this approach offers a reference frame, in which inter-individual differences are quantitatively described, which may be directly applied to identify local morphological landmarks. In-spite of a large body of research, there is still a lack of a systematic examination of the variability of the sulci that laterally delineate the region of the medial temporal lobe in the human brain that is involved in memory, i.e. the parahippocampal region (Scoville & Milner, 1957, 2000). Examination of the

cortical folding pattern that marks the lateral limit of the parahippocampal cortex is crucial, as this sulcal complex delineates the cortex of the medial temporal lobe related to mnemonic information processing from the laterally adjacent cortex of the fusiform and lingual gyri, associated with the processing of visual information. As we have seen from the descriptions above, a detailed understanding of the local gyral-sulcal anatomy can offer a more precise approach to disentangling the relative functional contributions of the various structures of the medial temporal lobe (e.g. the entorhinal and parahippocampal cortex) to memory. In order to create a common understanding of the local morphology, it is important to consider that the complex of sulci that delineates the parahippocampal gyrus from the adjacent fusiform gyrus has lacked consensus in the nomenclature. In light of the fact that the parahippocampal gyrus is such an anatomically (Economo & Koskinas, 1925) and functionally heterogeneous region (Aminoff et al., 2007; Köhler et al., 2002; Litman et al., 2009), the issue is not merely one of nomenclature. For instance, while in the monkey, the term rhinal sulcus is used to refer to the sulcus that laterally delimits the entorhinal cortex (Amaral et al., 1987; Gloor, 1997; Insausti & Amaral, 2004; Van Hoesen, 1995), in the human brain, the term rhinal sulcus has been used ambiguously. Some researchers have called the sulcus that laterally binds the entorhinal cortex the rhinal sulcus (Economo & Koskinas, 1925; Gloor, 1997; Retzius, 1896), while others have referred to the same sulcus as forming part of the collateral sulcus (Duvernoy, 1999; Insausti & Amaral, 2004; Insausti et al., 1998; Insausti et al., 1995). In the case where the sulcus that laterally delimits the entorhinal cortex is considered part of the collateral sulcus, the term rhinal sulcus is used to refer to a small sulcal dimple located in the most anterior part of the parahippocampal gyrus that comprises only the most rostral portion of the entorhinal cortex (Duvernoy, 1999; Insausti & Amaral, 2004; Insausti et al., 1998; Insausti et al., 1995). Importantly, when the term rhinal sulcus is used in this way, it implies that, in the human, as compared to other mammals, the entorhinal cortex is not bound by the rhinal sulcus. This illustrates that the issue is not mere one of nomenclature, but

the importance of identifying in the human brain a sulcus that may be homologous to the sulcus that is called rhinal sulcus in the monkey (Gloor, 1997; Petrides, unpublished observations). Therefore, a careful and systematic examination of the cortical folding pattern of the sulci that laterally delimit the parahippocampal gyrus may provide a better understanding of whether or not a sulcus exists in the human brain that is comparable to the rhinal sulcus in the monkey. Another important reason for a thorough investigation of this sulcal complex is because the entorhinal cortex and the cortex that lies posterior to it on the posterior part of the parahippocampal gyrus (i.e. the parahippocampal cortex) are anatomically (Economo & Koskinas, 1925) and functionally distinct (Aminoff et al., 2007; Köhler et al., 2002; Litman et al., 2009). Some researchers have considered the sulcus that laterally delimits the parahippocampal cortex (i.e. posterior to the entorhinal cortex) a separate sulcus from the rostrally located rhinal sulcus (Economo & Koskinas, 1925; Gloor, 1997; Retzius, 1896), while others have considered both sulcal entities to be one continuous sulcus (Duvernoy, 1999; Insausti & Amaral, 2004; Insausti et al., 1998; Insausti et al., 1995). The cortex that lines the parahippocampal gyrus is anatomically and functionally heterogeneous. Specifically, anteriorly, the perirhinal cortex is distinct from the entorhinal cortex in terms of its cytoarchitectonic organization (Economo and Koskinas, 1925; Augustinack et al., 2013) and function (Buffalo et al., 1999; Köhler et al., 2002). Posteriorly, the cortex of the fusiform and lingual gyri differs anatomically (Economo and Koskinas, 1925) and functionally from that of the parahippocampal cortex (Kanwisher et al., 1997; Epstein and Kanwisher, 1998; Downing et al., 2001; Grill-Spector et al., 2004). Therefore, also identifying the local morphological patterns of the sulcus or sulci that laterally delimit the parahippocampal cortex, will also greatly contribute to a better understanding of the function and anatomy of the regions of the parahippocampal gyrus and, by extension, the cortex that surrounds it. Functional neuroimaging has contributed towards our understanding of the role of the medial temporal lobe in memory. For instance, fMRI studies have shown greater activation for the mnemonic processing of objects along the

anterior part of the parahippocampal gyrus (i.e. the region that contains the entorhinal cortex) and of places and scenes along the posterior part of the parahippocampal gyrus (i.e. posterior to the entorhinal cortex along the parahippocampal cortex) (Köhler et al., 2002; Litman et al., 2009; Staresina et al., 2011). This is consistent with impairments in object-location memory seen in patients who have damage to the parahippocampal gyrus that extends beyond the entorhinal cortex to include the parahippocampal cortex (Bohbot et al., 1998; Ploner et al., 2000; Smith & Milner, 1981, 1989; Smith et al., 2011). A particular role of the posterior part of the parahippocampal gyrus, i.e. along the parahippocampal cortex, in the preferential processing of stimuli of places and scenes, compared to stimuli such as faces and objects, has been shown by Epstein and Kanwisher (1998), who referred to this region as the ‘parahippocampal place area’. Habib and Sirigu (1987) reported four cases with damage to the region of the posterior parts of the parahippocampal gyrus (and underlying cortex of the hippocampus) and the lingual gyrus that demonstrated topographical disorientation. One patient (case 2) presented with a more restricted lesion than the other cases, showing damage primarily to the posterior hippocampal and parahippocampal cortex, and sparing the anterior parahippocampal gyrus where the entorhinal cortex lies. This patient (case 2), like the other three patients, showed ‘topographical amnesia’, which refers to the inability to derive the information relevant for orientation purposes from the visual environmental landmarks within novel or unfamiliar places (while showing no orientation problems in familiar places). This patient showed no impairments on tests that assessed geographical knowledge, required the patient to locate cities on a map, and assessed her spatial span (e.g. using the Corsi blocks). In addition, the patient was able to perform a memory task for object-location (as tested using the procedure of Smith and Milner (1981); however, no details were given by Habib and Sirigu (Habib & Sirigu, 1987) about the patient’s specific performance on the immediate and delayed recall, and/or performance on recall of relative versus absolute location. Such additional information on test performance of the object- location memory task by Smith and Milner (1981) would have allowed more

insight into the aspects of memory processing that were tested in this case). Based on their findings, Habib and Sirigu (1987) hypothesized that a specific region of the posterior parahippocampal gyrus, posterior to the entorhinal cortex, is involved in memory for topographical information related to landmarks (Habib & Sirigu, 1987). Given the functional implications of the research reviewed above, the parahippocampal cortex (within the posterior part of the parahippocampal gyrus), plays a pivotal role in topographical learning and the retrieval of topographical information from memory. Functional neuroimaging studies have reported increased activation patterns in the parahippocampal cortex when the subjects were engaged in a navigation paradigm in virtual reality environment (Aguirre et al., 1996; Boccia et al., 2014; Brewer et al., 1998; Epstein, 2008; Hirshhorn et al., 2012; Iaria et al., 2007; Maguire et al., 1998; Rosenbaum et al., 2004), especially within recently learned environments (Boccia et al., 2014). However, while increasing evidence indicates that the parahippocampal gyrus plays a key role in memory in general, and spatial memory in particular, a clear relationship between the functional involvement of the regions that make up the parahippocampal gyrus, and where along this gyrus they lie (i.e. their relationship to the local anatomy) is still needed. Specifically, it would be useful to investigate whether our knowledge of the local morphological characteristics (i.e. sulcal pattern) can aid the more accurate identification of the location of activations seen in functional neuroimaging studies on navigation. Because of the ridge created by the sphenoid bone which separates the anterior and the middle cranial fossa in the brain, the anterior and medial parts of the temporal lobe, as well as the inferior and posterior portions of the frontal lobe, are particularly vulnerable to damage in external trauma to the head (Bigler, 2000). Several anatomical changes have been observed as a result of head trauma (ranging from mild to severe), such as the enlargements of the temporal horn of the lateral ventricle and hippocampal volume atrophy. Some of these changes (i.e. lateral ventricle enlargement) were observed within the initial 100 days post- injury, while the effect on the hippocampus was found to occur much later, and was only measurable after 100 days post-injury (Bigler et al., 1997). Given that

hippocampal atrophy only became apparent at a later point in time, this highlights the importance of early detection of subtle brain differences that may be indicative of the development of more severe and persistent impairments following the passage of time. Given the involvement of the medial temporal lobe in navigation, little is known to date about the influence of mild traumatic brain injury on the functional activation patterns in the medial temporal lobe during the retrieval of a mental representation of an environment from memory. Two studies have examined the consequences of mild traumatic brain injury on the functional activation pattern during navigation (Saluja et al., 2015; Slobounov et al., 2010). The study by Slobounov and colleagues (2010) examined memory encoding and retrieval during navigation using fMRI. Their results showed no differences in performance speed with the healthy control group. However, during the encoding of the environmental information (i.e. the learning of a specific route to a target landmark) Slobounov and colleagues (2010) observed increased functional activation in the parietal cortex, right dorsolateral prefrontal cortex, and right hippocampus in the mild traumatic brain injured group but not the control group. No difference in the signal strength of the functional activation was observed between the groups during the retrieval phase, when the subjects were asked to recall the specific path learned in the encoding phase (Slobounov et al., 2010). In contrast, Saluja and colleagues (2015) found a decrease in the activation signal in the mild traumatic brain injured group, compared to the control subjects, during navigation. Successful navigation required the retrieval of information from a cognitive map of the environment which was formed prior to scanning in a training session. Decreased activation in the mild traumatic brain injured group was found in the retrosplenial cortex, the thalamus, and posterior parahippocampal cortex, bilaterally, and in the right dorsolateral prefrontal cortex and left precuneus. In addition, increased activation was observed in the mild traumatic brain injured group, compared to the healthy controls, in the left hippocampus and right middle temporal gyrus. Furthermore, the signal strength of the activation in the mild traumatic brain injured group in the left premotor cortex, parietal lobe, and parahippocampal gyrus correlated negatively with subjective

reports of the post-concussive symptoms (e.g. headache, trouble concentrating and remembering) (Saluja et al., 2015). Similar to Slobounov and colleagues (2010), Saluja and colleagues (2015) did not observe differences in task performance. Yet both studies showed that, in addition to decreased activation, sustaining a mild traumatic brain injury may lead to the recruitment of additional, compensatory cortical regions compared to healthy control subjects (Saluja et al., 2015; Slobounov et al., 2010). Several factors may have led to the differences in results found by these two studies. First, different populations were investigated. Slobounov et al. (2010) examined adults who sustained a mild traumatic brain injury and the study by Saluja et al. (2015) looked at adolescents between the ages of 10 and 17 years. Second, the studies differed in task demands, i.e. following a set path to the target (Slobounov et al., 2010) versus recalling scene-relevant information from memory, which had been encoded by free exploration prior to scanning, in order to find the most direct way to a landmark (Saluja et al., 2015). Furthermore, the study by Saluja and colleagues (2015) found a decrease in activation along the parahippocampal gyrus. The two studies referred to earlier illustrate subtle changes that occur as a consequence of mild traumatic brain injury during navigation. Given the involvement of the medial temporal lobes in navigation, and this region’s susceptibility to damage following trauma, it is of interest to see whether a more detailed understanding of the local morphology may help identify more accurately changes in activation patterns along the parahippocampal gyrus in a mild traumatic brain injured group. Being able to identify subtle changes within the medial temporal lobe memory system in a clinical population would be of immense importance, especially in the light of progressive effects with a late manifestation, such as the hippocampal atrophy found by Bigler and colleagues (1997). The aim is to find anatomical and functional biomarkers that may aid in the early identification of subtle changes in the functional activation patterns exhibited by this clinical population. To provide further background on the questions raised in the previous paragraphs, the subsequent sections will start a brief review of the literature pertinent to this thesis. First, a review will be provided about the morphology of

the collateral sulcal complex (section 1.1). Then, a summary will be given on the cytoarchitectonic organization of the parahippocampal gyrus, and its connectivity with other regions of the brain (section 1.2). Subsequently, the functional involvement of the parahippocampal gyrus will be introduced (section 1.3). Next, the importance of probabilistic maps in standard stereotaxic space will be reviewed (section 1.4). The specific aims of each of the studies that make up the present thesis are summarized at the end of this introduction (section 1.5)..

1.1 Sulcal morphology laterally delimiting the parahippocampal gyrus This section will review the available literature on the sulcal morphology that laterally delimits the parahippocampal gyrus, which forms an important basis for the understanding of the investigations conducted in studies 1 and 2 of the present thesis (see Chapters 2 and 3). The collateral sulcus is a prominent sulcal landmark laterally delineating the entorhinal cortex and parahippocampal cortex on the parahippocampal gyrus, involved in processing mnemonic information (Bohbot et al., 2000; Bohbot et al., 1998; Habib & Sirigu, 1987; Iaria et al., 2007; Iaria et al., 2003; Malkova & Mishkin, 2003; Scoville & Milner, 1957; Smith et al., 2011; Smith & Milner, 1981, 1989; Zola-Morgan et al., 1994) from the adjacent fusiform gyrus, involved in processing visual perceptual information (Fox et al., 1987; Haxby et al., 1991; Kanwisher et al., 1997). The collateral sulcus runs laterally along the parahippocampal gyrus, from the anterior part of the medial temporal lobe rostrally into the lingual gyrus of the occipital lobe caudally (Duvernoy, 1999; Heckers et al., 1990; Insausti & Amaral, 2004). Early studies on the morphology of the sulci of the human brain date back at least a century (Brodmann, 1909; Economo & Koskinas, 1925; Retzius, 1896; Smith, 1904). The method of examining the folding pattern of the brain in those days was restricted to post-mortem surface investigations. Using such surface inspection, Retzius (1896) described two sulci as laterally binding the parahippocampal gyrus. Anteriorly marking the extent of the uncus (i.e. the anterior part of the parahippocampal gyrus that comprises most of the entorhinal cortex), he depicted the rhinal sulcus. Caudal to the rhinal sulcus, he illustrated the sulcus he called the collateral sulcus which continues posteriorly into the occipital lobe. Similarly, Smith (1904) and Brodmann (1909) reported a sulcus alongside the uncus extending approximately up to the caudal limit of the uncus (Smith, 1904), or extending just slightly posterior to the caudal limit of the uncus (Brodmann, 1909). These investigators referred to this as the rhinal sulcus (Brodmann, 1909; Smith, 1904) or ‘posterior’ rhinal sulcus (Brodmann, 1909). Posterior to this sulcus, Smith (1904) and Brodmann (1909) depicted an independent sulcus that continues posteriorly alongside the parahippocampal

gyrus, which was termed collateral sulcus (Smith, 1904) or occipitotemporal sulcus (Brodmann, 1909). Economo and Koskinas (1925) reported similar observations referring to the anterior sulcus as the rhinal fissure while calling a separate and posteriorly located sulcus both the occipitotemporal and the collateral fissure. Furthermore, Ono and colleagues (1990) examined post-mortem brains by carefully pulling apart the cortical fissures to examine the in-depth nature of the sulci and published an atlas of the cerebral sulci of the human brain, therein describing the surface inspection as well as sulcal segmentation due to submerged gyri of the major sulci of the human brain. They parallel the observations made by Retzius (1896), Smith (1904), Brodmann (1909), and Economo and Koskinas (1925), in identifying an anterior sulcus, called rhinal sulcus, which runs alongside the uncus, and a posterior sulcus called the collateral sulcus, which continues to demarcate the lateral boundary of the parahippocampal cortex posteriorly. While these investigators seem to paint a clear picture of the location of the rhinal and the collateral sulcus proper, not all researchers have adapted this view, or the terminology for the different parts of the sulci (i.e. rhinal and collateral sulci). One major neuroanatomy text book (Duvernoy, 1999) depicts one long, continuous sulcus that marks the lateral limit of the parahippocampal gyrus from the rostralmost extent of the temporal lobe anteriorly all the way to the lingual gyrus of the occipital lobe posteriorly. As presented earlier in this introduction, the term ‘rhinal sulcus’ was reserved by these researchers (Duvernoy, 1999; Hanke, 1997; Insausti & Amaral, 2004; Insausti et al., 1998; Insausti et al., 1995) for a small sulcal dimple on the most anterior part of the parahippocampal gyrus, which by others has been referred to as the temporal incisure (Brodmann, 1909; Economo & Koskinas, 1925; Retzius, 1896). Given the heterogeneity of the regions on the parahippocampal gyrus, this is not a mere question of terminology, as the use of the term ‘rhinal sulcus’ for the small dimple in the anterior parahippocampal gyrus would imply that in other mammals, except for humans, the rhinal sulcus laterally delineates the entorhinal cortex. In order to shed light on this debate, a detailed examination of the sulcal morphology is imperative.

Furthermore, not much is known regarding the posterior limit of the collateral sulcus. The caudal extent of the collateral sulcus is said to show great variability (Pruessner et al., 2002). As such, the posterior course of the collateral sulcus has been described as continuing into the lingual gyrus (Duvernoy, 1999), as connecting caudally with the lingual sulcus (Ono et al., 1990; Retzius, 1896), or as being an independent entity from the lingual sulci (Economo & Koskinas, 1925; Sarkissov et al., 1955). Due to the in-depth nature of the sulcal folding patterns of the brain, inspection solely based on visual surface analysis is not sufficient when examining brain morphology. For instance, while a sulcus may appear continuous from the surface, and hence to visual inspection, an in-depth inspection may reveal that the sulcal fundus may contain one or more submerged gyri that form bridges in the depth of the sulcus (Regis et al., 2005), thereby indicating several sulcal segments. Such gyral bridges are also often referred to as ‘plis de passage’ (Gratiolet, 1854; Regis et al., 2005). The development of neuroimaging technology has enabled us to bridge some of these gaps. Interactive neuroimaging software that allows for a simultaneous visualization of the brain in a series of continuous two-dimensional sections in the coronal, sagittal, and horizontal plane, in which one’s position is continuously updated online in all three planes, has made the examination of the in-depth nature of the course made by the various cerebral sulci easily accessible. Such software also offers a three-dimensional visualization of the reconstructed surface of the brain in relation to the in-depth two-dimensional visualizations. Using such an approach, Germann and colleagues (2005) established that the superior precentral sulcus could be reliably separated from the inferior precentral sulcus and reported on the variability of the various sulcal patterns expressed by the precentral sulcus. Similar examinations and description of the sulcal-gyral morphology have been made for various parts of the brain, including the sulci of the orbitofrontal cortex (Chiavaras et al., 2001), the sulci of the occipital lobe (Iaria & Petrides, 2007), the branches of the superior temporal sulcus (Segal & Petrides, 2012), the post-central sulcus (Zlatkina & Petrides, 2010) and the intraparietal sulcus and the intermediate parietal sulcus of

Jensen (Zlatkina & Petrides, 2014). A detailed examination of the folding patterns of the sulcus or sulci of the collateral sulcal complex, that mark the lateral boundary of the parahippocampal gyrus, has not yet been conducted. Given the heterogeneity of the parahippocampal gyrus, identifying the local morphological patterns of the sulcus or sulci that laterally delimit this region will greatly contribute to a better understanding of its function and anatomy.

1.2 Cytoarchitectonic organization and connectivity of the parahippocampal gyrus Microscopic examinations of human and non-human primate histological brain sections have provided us with great insights into the cytoarchitectonic organization of different parts of the cortex. Furthermore, cytoarchitectonically different areas may present with distinct connectivity patterns to other parts of the brain. Many studies to date have examined the cytoarchitectonic organization in the human and the non-human primate brain, while the majority of our knowledge about the connectivity of the brain comes from studies on non-human primates (Amaral et al., 1987; Goldman-Rakic et al., 1984; Insausti, 1993; Insausti et al., 1987a, 1987b; Insausti et al., 1998; Insausti et al., 1995; Krimer et al., 1997; Lavenex et al., 2004; Petrides, 2005a; Petrides & Pandya, 1999, 2002b; Suzuki & Amaral, 1994b, 2003; Van Hoesen & Pandya, 1975; Van Hoesen et al., 1972; von Bonin & Bailey, 1947). A brief review of the cytoarchitectonic findings of the parahippocampal gyrus is important to provide the framework for understanding whether a sulcus that laterally delimits the entorhinal cortex in the human brain should be called ‘rhinal sulcus’ as it is in the non-human primate brain. Furthermore, the knowledge of the cytoarchitectonic organization and the connectivity between regions is necessary to further our understanding of the brain, particularly if we seek to investigate and attribute functional properties to these regions.

Entorhinal cortex The entorhinal cortex occupies the anterior surface of the parahippocampal gyrus and comprises dorsal area 34 and ventral area 28 (Brodmann, 1909). Ventral area 28 has been divided into two regions, area 28a and 28b, based on the differences in cell-arrangement (Brodmann, 1909; Van Hoesen et al., 1972) and the efferent and afferent projections (Van Hoesen et al., 1972). According to Van Hoesen and colleagues (1972), area 28a occupies the posterior portion of the entorhinal cortex and stretches from the hippocampal fissure medially to the rhinal sulcus laterally. Area 28b forms most of the rostral portion of the entorhinal cortex and is laterally

bound by the anterior part of the ‘rhinal sulcus’ (Van Hoesen et al., 1972). It should be noted that in contrast to the subdivisions that Brodmann (1909) called areas 28a and 28b, the denominations ‘a’ and ‘b’ by van Hoesen (1972) are used inversely (i.e. area 28b by van Hoesen occupies the anterior portion and 28a the posterior, while in Brodmann (1909) the anterior part of the entorhinal cortex is denoted as 28a, and the posterior part as 28b). Despite some differences in the identification of different subdivisions (Amaral & Insausti, 1990; Beall & Lewis, 1992; Insausti et al., 1995; Krimer et al., 1997), the entorhinal cortex in humans shows large similarities with the non-human primate. The rostral border of the entorhinal cortex in the human brain has been identified two to three millimeters posterior to the limen insulae (i.e. the rostralmost point where the frontal and temporal lobes join; also called fronto-temporal junction) (Insausti et al., 1995; Krimer et al., 1997). The caudal boundary of the entorhinal cortex lies at the level of the anteriormost limit of the lateral geniculate nucleus, which coincides with the posterior boundary of the uncus (Insausti et al., 1995) and the level of the hippocampal head as observed in coronal sections (Krimer et al., 1997). While in the non-human primate, the lateral limit of entorhinal area 28 extends into the medial bank of the rhinal sulcus, in the human brain, the lateral limit of the entorhinal cortex is said not to be linked to any gross morphological features (Amaral et al., 1987; Krimer et al., 1997). Nevertheless, human entorhinal area 28 has been reported to extend with some variability onto the medial bank of what has by these authors (Amaral et al., 1987; Insausti et al., 1995; Krimer et al., 1997) been termed the collateral sulcus, occupying at times almost half of the medial bank (Krimer et al., 1997). In addition, agreement exists that the entorhinal cortex roughly extends into the medial bank of the collateral sulcus, where it borders the perirhinal cortex (Brodmann, 1909; Insausti et al., 1995; Krimer et al., 1997). Furthermore, Krimer and colleagues (1997) identified a transition entorhinal area (area 28S) along the lateral limit of the other entorhinal cortex subdivisions and reported that this area parallels the course of the collateral sulcus (Krimer et al., 1997). The posterior limit of the entorhinal cortex has been said to be identifiable only at the microscopic level, with no macroscopic landmarks

aiding boundary identification. The entorhinal cortex is described as forming a narrow strip caudally, towards the rostral origin of the hippocampal fissure, where it terminates and gives way to the posterior part of the perirhinal cortex and the posterior parahippocampal cortex (Insausti et al., 1995; Krimer et al., 1997). In contrast, on the macroscopic level, in the monkey, the entorhinal cortex has been described to relate to local morphological landmarks, and to continue for a short distance beyond the caudal end of the rhinal sulcus (Amaral et al., 1987), thereby corresponding approximately to the caudalmost end of the rhinal sulcus (Gloor, 1997).

Perirhinal cortex The perirhinal cortex, area 35 (Brodmann, 1909), lies immediately adjacent to the entorhinal cortex and occupies the lateral bank of the rhinal sulcus in the monkey brain (Amaral et al., 1987; Insausti et al., 1998; Insausti et al., 1995; Van Hoesen et al., 1972). Rostrally, the perirhinal cortex may even extend onto the medial bank of the rhinal sulcus (Insausti et al., 1998), while caudally, and along the major portion of the rhinal sulcus, the medial bank of the rhinal sulcus is occupied by the entorhinal cortex (Amaral et al., 1987; Van Hoesen & Pandya, 1975). Lavenex and colleagues (2002) included areas 35 and 36 in their definition of the perirhinal cortex, where area 35 occupies the banks of the rhinal sulcus and area 36, composed of subdivisions, lies lateral to area 35 and is bound laterally by unimodal visual areas TE and TEO (Lavenex et al., 2002). Brodmann (1909) restricted the use of the term perirhinal cortex to area 35. Similar to the monkey, the rostral limit of the human perirhinal cortex has been identified just anterior to the fronto-temporal junction. The lateral border of the perirhinal cortex which is formed by temporal lobe neocortex lies along the lateral bank of anterior part of the deep furrow that by the authors is referred to as collateral sulcus (Insausti et al., 1998), called rhinal sulcus by others (Brodmann, 1909; Economo & Koskinas, 1925; Ono et al., 1990; Retzius, 1896). The posterior limit of the perirhinal cortex has been identified slightly posterior to the caudal limit of the rhinal sulcus (Brodmann, 1909), at the level of the caudal end of the uncus (i.e. gyrus

intralimbicus), two to four millimeters posterior to the caudal limit of the entorhinal cortex (Insausti et al., 1998).

Parahippocampal cortex The cytoarchitectonic organization of the parahippocampal cortex in the human brain is not entirely understood to date. In the human brain, the parahippocampal cortex is defined as comprising area TH, which lies caudal to the entorhinal cortex and covers the parahippocampal gyrus form the hippocampal fissure medially to the sulcus that laterally delimits it (Economo & Koskinas, 1925; Gloor, 1997). A cytoarchitectonically distinct area, called area TF, occupies the adjacent cortex of the lateral fusiform gyrus (Economo & Koskinas, 1925; Gloor, 1997). Other researchers, when referring to the parahippocampal cortex, include presubicular area 27, which runs in parallel to the hippocampal fissure, and ectorhinal area 36 (Brodmann, 1909; Vogt et al., 2001). In this case, area 36 of the human parahippocampal cortex lies caudal to the entorhinal cortex and caudo-medially borders a transitional parahippocampal area on the anterior part of the isthmus of the cingulate gyrus, referred to as area 36´, thereby caudally separating parahippocampal area 36 from the retrosplenial cortex (Vogt et al., 2001). Vogt and colleagues (2001) provide a thorough description of the caudomedial limit of the parahippocampal cortex in the human brain. Other boundaries of the human parahippocampal cortex, including a detailed report of the caudolateral boundary of the parahippocampal cortex with the lingual gyrus (Insausti & Amaral, 2004; Insausti et al., 1998), the medial limit with the parasubiculum, and the lateral limit with the fusiform gyrus remain ill defined. Furthermore, the posterior boundaries have often been described as ‘fusing’ into the neighboring gyri because of similarities in cytoarchitectonic organization (Brodmann, 1909; Economo & Koskinas, 1925).

Connections of the entorhinal cortex The entorhinal cortex forms major bidirectional connections with the hippocampal formation through a pathway called the perforant pathway (Gloor, 1997; Van

Hoesen, 1982). The hippocampal formation can transfer information to other regions indirectly via the entorhinal cortex, as projections from the entorhinal cortex pass through the different hippocampal subregions and subsequently connect back to the entorhinal cortex (Gloor, 1997). Therefore, the entorhinal cortex has been compared to a relay station or hub of information flow to the hippocampal formation. In the non-human primate, it has been proposed that the rostral and medial parts of the entorhinal cortex (area 28b of Van Hoesen et al. (1972)) send projections to the anterior portion of the hippocampus (i.e. the dentate gyrus), while the caudal parts of the entorhinal cortex (area 28a of Van Hoesen et al. (1972)) send projections to the posterior portion of the hippocampus (Insausti, 1993). In addition to sending efferent information directly to the hippocampal formation (Squire & Zola-Morgan, 1988, 1991; Suzuki, 1996; Van Hoesen et al., 1972) via the perforant pathway (Squire & Zola-Morgan, 1988, 1991; Van Hoesen et al., 1972), afferent projections from the hippocampal formation are in turn relayed back to the entorhinal cortex and from there they are directed to many different parts of the neocortex. This occurs in part indirectly via the perirhinal and parahippocampal cortex (Squire & Zola-Morgan, 1988, 1991). The perirhinal and parahippocampal cortex provide an important source of input to the entorhinal cortex (Gloor, 1997). Furthermore, entorhinal area 28a receives major projections from parahippocampal area TH and some projections from the olfactory pyriform cortex. Area 28b receives its main cortical input from the prepyriform cortex (area 51) and orbitofrontal association areas 12 and 13 (Van Hoesen et al., 1972). The entorhinal cortex has been said to receive no direct input from unimodal regions, except for direct projections from the olfactory cortex (Insausti et al., 1987a). Figure 1.6.3 provides a schematic illustration of the cortical connections of the various regions of the parahippocamapl gyrus as published by Buffalo and colleagues (Buffalo et al., 2006).

Connections of the perirhinal cortex The perirhinal cortex in the non-human primate (areas 35 and 36 according to Suzuki and Amaral (1994a)) receives major input from adjacent unimodal visual

association cortex, areas TEO and TE, and from area TF (Suzuki, 1996; Suzuki & Amaral, 1994a). The projections from area TF to the perirhinal cortex are found to be substantial and are described as ‘feedforward’ projections (Lavenex et al., 2004), whereas, projections from the perirhinal cortex to the area TF are described as sparse (Suzuki, 1996; Suzuki & Amaral, 1994a) and classified as ‘feedback’ projections (Lavenex et al., 2004). The perirhinal cortex is found to receive audio and visual information through projections from the superior temporal gyrus (Suzuki, 1996), somatsensory information from the insular cortex, projections from area 13 of the orbitofrontal cortex (Suzuki, 1996; Suzuki & Amaral, 1994a), and it has bidirectional connection with the amygdala (Stefanacci et al., 1996). The perirhinal cortex also projects to the entorhinal cortex, as mentioned above (Figure 1.6.3).

Connections of the parahippocampal cortex The major efferent connections from area TH and area TF go to the entorhinal cortex, with additional projections from areas TH and TF to the perirhinal cortex (Suzuki, 1996; Suzuki & Amaral, 1994a). The parahippocampal cortex receives afferent projections from various unimodal and polymodal cortical regions (Figure 1.6.3). For instance, area 22 on the lateral surface of the temporal lobe carries auditory information, area 7 of the parietal lobe carries somatovisual, and area 19 of the occipital lobe and area 20 of the inferior temporal lobe carry visual information to parahippocampal areas of the monkey brain (Van Hoesen, 1982). Areas TH and TF both project to the amygdala, albeit less than the perirhinal cortex. Projections from the amygdala are only observed back to area TF and not area TH (Stefanacci et al., 1996). The retrosplenial cortex also provides direct input to the parahippocampal cortex. Via the retrosplenial cortex, the parahippocampal cortex may receive indirect information from the cingulate area 24 (Van Hoesen, 1982) and from prefrontal cortical areas (Goldman-Rakic et al., 1984; Petrides, 2005a; Petrides & Pandya, 1999), such as the dorsolateral prefrontal and frontopolar cortex (Petrides, 2005b; Petrides & Pandya, 1999). The dorsolateral prefrontal cortex in the monkey is found to connect to entorhinal area

28 and perirhinal area 35 in the rhinal sulcus and to the parahippocampal area TH, while connecting to area TF to a much lesser degree (Goldman-Rakic et al., 1984). The ventrolateral prefrontal cortex, area 47/12, may send information to the perirhinal and rostral parahipppocampal gyrus (Petrides, 2005b; Petrides & Pandya, 2002a). Area TF receives visual information from adjacent areas V4, TEO and TE and visuospatial information from the posterior parietal cortex. In addition, area TF receives input from the retrosplenial cortex, the dorsal bank of the superior temporal sulcus, the insular cortex, and the frontal cortex (i.e. areas 45, 46, 9, and 13 (Suzuki, 1996)). Area TH, in contrast, receives less diverse input compared to area TF. Area TH receives most of its afferent projections (about 50 percent) from adjacent area TF (Suzuki, 1996; Suzuki & Amaral, 1994a), followed by the retrosplenial cortex (areas 23, 29, and 30) which provides the second largest input (about 24%) (Suzuki, 1996; Suzuki & Amaral, 1994a). Further input to area TH comes from the auditory and polymodal association areas of the superior temporal gyrus (Suzuki, 1996). Only minor input is received by area TH from visual areas V4, TEO and TE, the insular cortex (Suzuki, 1996), frontal cortex (Suzuki, 1996; Suzuki & Amaral, 1994a), perirhinal cortex (areas 35 and 36), and the subiculum (Suzuki & Amaral, 1994a). When examining functional activation patterns, it is important to keep in mind the underlying cytoarchitectonic organization as well as the differential patterns of efferent and afferent projections which the regions under investigation exhibit. The underlying idea is that the connections of a particular region determine the functional properties this region can subserve (Passingham et al., 2002). Hence, it may serve as a guide when attempting to make sense of functional activation peaks within the cognitive framework of the experimental paradigm that was applied in a particular study.

1.3 Parahippocampal gyrus and spatial information processing The ability to navigate within our environment is crucial, as impairment in navigation will pose significant challenges to our day-to-day functioning leaving us unable to complete seemingly simple tasks such as going for a walk and finding our way home. Although navigating within a highly familiar environment can be performed without conscious recollection, by learning particular turn patterns (Iaria et al., 2003; O'Keefe & Nadel, 1978), learning to orient oneself in a new environment or adjusting one’s path due to obstacles is closely tied to the ability to remember consciously (Hartley et al., 2003; Hirshhorn et al., 2012; Iaria, Fox, et al., 2008). The formation of long-term declarative memories, that is memories for facts and events (i.e. semantic and episodic memory, respectively) (Schacter & Tulving, 1994), and of spatial memories, appears to be in large part based on similar neural substrates. Support for this comes from observations that damage to similar regions causes impairment of both memory for events and space (Corkin, 2002; O'Keefe & Nadel, 1978). Previous work on the neuroanatomical basis of memory goes back to the work of Scoville and Milner (1957, 2000) who showed that the medial temporal lobes are crucial to long-term memory formation, and also to the ability of way finding. In their reports, patient H.M., who had had bilateral removal of the medial temporal lobes for the treatment of intractable epilepsy, exhibited severe anterograde amnesia, and was described as being unable to form new long-term declarative memories post- surgery (Scoville & Milner, 1957). At the same time, H.M. presented with intact general intellect, visual perceptual abilities, and immediate memory processing and recall of memories formed before the surgery, as well as the ability to acquire some new implicit memories (Corkin, 2002; Scoville & Milner, 1957). The global memory impairment exhibited by H.M. was specific to the ability to judge whether some information had been previously encountered (i.e. recall and recognition memory) (Scoville & Milner, 1957; Zola-Morgan et al., 1994). In addition, H.M. was unable to learn to navigate within a visual (Milner, 1965) and tactile maze task (Corkin, 1965), showing a severe impairment of memory for spatial information (Scoville & Milner, 1957; Zola-Morgan et al., 1994). Other

studies have found that lesions that included the posterior part of the parahippocampal gyrus severely impaired navigational abilities (Bohbot et al., 2000; Bohbot & Corkin, 2007; Habib & Sirigu, 1987) and object-location memory (Bohbot et al., 1998; Smith et al., 2011; Smith et al., 1995; Smith & Milner, 1981, 1989). The question of the functional contribution of the different structures of the medial temporal lobe to the processing of mnemonic and spatial information, however, was not resolved at the time. Lesion studies in monkeys (Malkova & Mishkin, 2003; Mishkin, 1978; Parkinson et al., 1988; Suzuki et al., 1993; Zola-Morgan et al., 1989) and humans (Bohbot et al., 2000; Bohbot & Corkin, 2007; Bohbot et al., 1998; Habib & Sirigu, 1987; Scoville & Milner, 1957; Smith & Milner, 1981; Zola-Morgan et al., 1986a), as well as single cell recordings in rats, monkeys, and humans (Boccara et al., 2010; Ekstrom et al., 2003; Georges-François et al., 1999; Hafting et al., 2005; Killian et al., 2012; Miller et al., 2013; O'Keefe & Dostrovsky, 1971; Rolls & O'Mara, 1995; Rolls et al., 1997; Solstad et al., 2008; Taube et al., 1990) and functional neuroimaging studies in the human brain (Aguirre & D'Esposito, 1997; Andrews et al., 2010; Arnold et al., 2013; Epstein et al., 2003; Epstein et al., 1999; Epstein & Kanwisher, 1998; Henderson et al., 2008; Iaria et al., 2007; Iaria et al., 2003; Janzen & van Turennout, 2004; Köhler et al., 2002; Maguire et al., 1998; Maguire et al., 1997; Pihlajamaki et al., 2004; Staresina et al., 2011; Sulpizio et al., 2013) have shed light onto what the individual contributions of the various structures of the medial temporal lobe may be.

The hippocampal formation and spatial information processing While the hippocampal formation does not form the focus of this thesis, its involvement in spatial memory is pivotal and therefore deserves to be included in this review. Following the observations of Scoville and Milner (1957, 2000), many studies set out to examine the functional role played by the hippocampus (Mishkin, 1978; Morris et al., 1999; O'Keefe & Dostrovsky, 1971; Squire & Zola- Morgan, 1988; Zola-Morgan et al., 1986a). Damage to the hippocampus causes severe and long-lasting memory impairments (Corkin, 2002; Mishkin, 1978;

Parkinson et al., 1988; Scoville & Milner, 1957, 2000; Smith & Milner, 1981; Zola-Morgan et al., 1986b) especially on tasks of visuo-spatial memory (Bohbot et al., 1998; Mishkin, 1978; O'Keefe & Dostrovsky, 1971; Parkinson et al., 1988; Smith et al., 2011; Smith et al., 1995; Smith & Milner, 1981, 1989). With the discovery of place cells in the rat hippocampus (O'Keefe & Dostrovsky, 1971), that is cells which fire when the animal is present in a specific place of a testing arena, the cognitive map theory was formulated which posits that the hippocampus is the key element in spatial memory (O'Keefe & Nadel, 1978). A cognitive map refers to a flexible mental representation of the environment. In the rat, the hippocampus is thought to encode and maintain such a mental representation of its environment, by firing place cells for specific positions of the animal within the environment. Together, the various place cells create a topographical map of the rat’s environment (O'Keefe & Nadel, 1978). This type of spatial information is referred to as allocentric and it represents the relationship between objects and landmarks relative to each other. Allocentric is often contrasted with egocentric representations, which refer to the relationship between the self/viewer and the objects or landmarks in the environment; egocentric representations therefore depend on a particular perspective rather than being viewer-independent (O'Keefe & Nadel, 1978). Single cell recordings in the non- human brain have found neurons that respond preferentially to the view of a scene that the monkey could see independently of his head or eye-movements. These cells are called spatial view cells and have been thought to be similar to the place cells of the rat (Georges-François et al., 1999; Rolls & O'Mara, 1995; Rolls et al., 1997). In the human brain, it has been much more challenging to identify place cells. However, a study by Ekstrom and colleagues (2003) has examined the human brain and has observed what may be considered the human homologue of rat place cells. In their study, the investigators measured the response of single cells by means of direct recordings of neurons while the patients were engaging in a spatial navigation task. They observed, just as in the rat (O'Keefe & Dostrovsky, 1971), cells in the hippocampus that specifically responded when the patient visited specific spatial locations within a virtual environment (Ekstrom et al.,

2003). This was confirmed more recently, when place cells were identified in a single cell recording study of the human hippocampus during the performance of a navigation experiment (Miller et al., 2013). Functional neuroimaging supports the involvement of the hippocampus, particularly mnemonic processing of allocentric representation of space (Hartley et al., 2003; Iaria et al., 2007; Iaria et al., 2003; Maguire et al., 1998; Maguire et al., 2000).

The entorhinal cortex and spatial information processing The entorhinal cortex is in a key position to integrate information that subsequently enters the hippocampal formation. The discovery of grid cells in the non-human primate support this idea (Hafting et al., 2005). Grid cells, first discovered in the rat entorhinal cortex (Fyhn et al., 2004), fire when the animal observes a particular location, however, the neuronal firing response comprises the area of several hippocampal place cells within a specific geometric relation, representing a hexagonal pattern. Grid cells have been observed in the medial entorhinal cortex of the monkey (Hafting et al., 2005). Other types of cells that respond preferentially to being at a specific distance from different borders present within the environment, referred to as border cells, have also been observed in the entorhinal cortex of the rat (Solstad et al., 2008) and the monkey (Killian et al., 2012). In addition, neurons known as saccade direction cells have been observed in the monkey entorhinal cortex, referring to neurons that selectively responded to the angles of saccades made (Killian et al., 2012). In the human entorhinal cortex, Jacobs and colleagues (2010) recorded from single neurons in patients engaged in a navigation task within a virtual environment and observed that the neurons coded for the direction a patient was moving in within the environment (Jacobs et al., 2010). Furthermore, a recent study also identified grid cells in the human entorhinal cortex that encoded location information within a triangular formation (Jacobs et al., 2013), similar to that observed in the monkey (Hafting et al., 2005). A functional differentiation into a medial entorhinal and a lateral entorhinal region has been proposed (Reagh & Yassa, 2014; Van Cauter et al., 2013), with the medial entorhinal cortex involved in processing spatial

information, while the lateral entorhinal cortex processes both spatial and nonspatial information (Van Cauter et al., 2013). A recent fMRI study of the human brain by Reagh and Yassa (2014) showed that medial entorhinal cortex is involved to a greater extent in mnemonic processing of spatial information than non-spatial information (Reagh & Yassa, 2014). In addition, the lateral entorhinal cortex was found to be involved in object recognition (i.e. deciding whether a particular stimulus was different from the one previously presented) to a greater extent than it was in spatial memory (i.e. deciding whether an object was located in a different place than when it had been previously presented) (Reagh & Yassa, 2014). How exactly the entorhinal cortex codes for recognition memory, though, is still a matter of debate, as shown by a recent study by Barry and colleagues (2012), which observed an expansion in the grid cell firing range when novel environmental information was presented and a subsequent reduction of the grid as the environment became familiar.

The perirhinal cortex and spatial information processing Functions of familiarity judgment and object-recognition, that is, the ability to identify a stimulus as familiar (previously seen) or novel, have been attributed largely to the perirhinal cortex (Buffalo et al., 1998; Meunier et al., 1993; Murray & Mishkin, 1986; Suzuki et al., 1993; Zola-Morgan & Squire, 1993; Zola-Morgan et al., 1989). Damage to the perirhinal cortex impairs performance on tests of visual recognition memory (Bachevalier & Nemanic, 2008; Buffalo et al., 1999; Meunier et al., 1993; Murray & Mishkin, 1986; Suzuki et al., 1993; Zola-Morgan & Squire, 1993; Zola-Morgan et al., 1989). Meunier and colleagues (1993) showed that removal of the perirhinal and not the entorhinal cortex resulted in severe deficits in recognition memory, whereas removal of the entorhinal cortex produced only a mild impairment. A study by Buffalo and colleagues (1999) examined monkeys with ablations to either the perirhinal cortex or area TE of the inferior temporal lobe. A dissociation was found, namely animals with perirhinal cortex lesions showed impaired recognition memory when a delay was more than 10 seconds, as well as demonstrated an impairment on simple object

discrimination task but not concurrent discrimination. Lesions to area TE impaired the animal on tests of visual perception even at very short delays, as well as on a task of concurrent discrimination, but no impairment on a task of object discrimination, which shows the importance of area TE in the processing of visual perceptual information (Buffalo et al., 1999). In the human brain, patients with damage to the perirhinal cortex were impaired on a visual recognition test, where the subjects had to determine whether a stimulus pattern had been seen prior to a delay period (Buffalo et al., 1998). Patients performed well with short delays but when the delay was longer than 25 seconds, patients showed impaired memory performance, thereby showing that the deficits were not due to impaired visual processing and/or immediate (short-term) memory processing (Buffalo et al., 1998). Several fMRI studies confirmed the role of the perirhinal cortex in processing novelty/familiarity of a stimulus (Bogacz et al., 2001; Haskins et al., 2008; Pihlajamaki et al., 2004). Furthermore, an fMRI study by Litman and colleagues (2009) reported involvement of the perirhinal cortex in the processing of objects as opposed to spatial arrangements. This is a similar to the findings of Staresina and colleagues (2011) who reported a double dissociation between the perirhinal cortex and the parahippocampal cortex, with the perirhinal cortex involved in the mnemonic processing of object information and the parahippocampal cortex related to memory for scene information.

The parahippocampal cortex and spatial information processing The parahippocampal cortex has been implicated in processing memory for place (Arnold et al., 2013; Bohbot et al., 2000; Bohbot et al., 1998) and scene-selective information (Epstein & Kanwisher, 1998) as well as in navigating the environment (Iaria et al., 2007; Iaria, Fox, et al., 2008; Janzen & van Turennout, 2004; Schinazi & Epstein, 2010; Spiers & Maguire, 2006). Single cell recordings have identified head-direction cells in the pre- and parasubiculum of the rat (Boccara et al., 2010; Taube et al., 1996; Taube et al., 1990) as well as the pre- subiculum in the monkey, structures which are considered part of the parahippocampal region (Robertson et al., 1999; Rolls et al., 1997). Such cells

fired independently of the place that the animal was in and independently of the spatial view and the eye-movements of the animal (Robertson et al., 1999; Rolls et al., 1998), which suggests the encoding of allocentric spatial information of the environment, such as the spatial location of objects. In addition, some grid cells and border cells were also found in the pre- and parasubiculum of the rat, similar to the medial entorhinal cortex (Boccara et al., 2010), clearly supporting a role of the posterior parahippocampal region in the processing of spatial information. In the human brain, Ekstrom and colleagues (2003) observed neurons in the parahippocampal region (defined as the pre- and parasubiculum, entorhinal, perirhinal, and parahippocampal cortex) which responded to views of specific landmarks, independent of their location much more than to a landmark in a specific location. In addition, other cells which selectively fired when viewing a landmark that was the target to be reached (i.e. view-dependent goal cells) were observed across the hippocampus, amygdala, parahippocampal region and frontal cortex (Ekstrom et al., 2003). Based on these results, Ekstrom and colleagues (2003) hypothesized that prior to spatial information being processed and bound together in the hippocampus to form a mental representation of the environment, the parahippocampal region functions as a key region involved in extracting factual information about the allocentric arrangement from landmarks within the environment. Rats with postrhinal cortical lesions were impaired when judgments concerned spatial location and not impaired when discriminations had to be made based on object features (Gaffan et al., 2004). A subsequent study confirmed this finding and proposed that the function of the rat postrhinal cortex is related to location of features within a scene (Eacott & Gaffan, 2005). The postrhinal cortex in the rat has been proposed to being the homologue of the parahippocampal cortex in the primate brain (Burwell et al., 1995). It is assumed that severe memory impairment, as seen in amnesic patients (Scoville & Milner, 1957, 2000) is produced by combined damage to the hippocampal formation and adjacent cortex, including the entorhinal, perirhinal, and parahippocampal cortex (Malkova & Mishkin, 2003; Suzuki et al., 1993; Zola-Morgan et al., 1989). Malkova and

Mishkin (2003) performed lesions of the parahippocampal cortex, including the pre- and parasubiculum and concluded that successful completion of a spatial place memory task critically depended on the posterior parahippocampal region (Malkova & Mishkin, 2003). In the human brain, lesions in patients that include the right parahippocampal cortex impair the learning and subsequent use of visual information to navigate to a target within a novel environmental (Aguirre et al., 1996; Aoki et al., 2003; Bohbot et al., 1998; Habib & Sirigu, 1987; Maguire et al., 1996; Ploner et al., 2000; Rosenbaum et al., 2004; Shelton & Gabrieli, 2002). Maguire and colleagues (1996) examined the patients with unilateral lesion to the parahippocampal cortex while they were engaging in a route learning experiment. The patients were impaired in judgments of allocentric spatial representations and the learning of new routes, while not showing any deficits in topographical knowledge pre-lesion. While the patients with lesions in either hemisphere presented similar deficits in their performance (Maguire et al., 1996), Bohbot and colleagues (1998) found a large impairment after a testing delay of 30 minutes in patients with right parahippocampal cortex lesions on the invisible sensor task, a human equivalent of the Morris water maze (Morris, 1981). This was not seen in patients with damage to the left parahippocampal cortex, the right or left hippocampus, and/or epileptic control subjects, suggesting that the right parahippocampal cortex plays an important role in spatial memory (i.e. topographical learning and retrieval) (Bohbot et al., 1998). Given the fact that the posterior parahippocampal cortex in patient H.M. was shown to have been left intact (Corkin et al., 1997), Bohbot and Corkin (2007) re-examined H.M.’s performance on a task of spatial learning. In an invisible sensor task, a version of the Morris Water Maze task (Morris, 1981) adapted for human testing, H.M. was asked to find a platform which was hidden from view and was only identifiable by sound when stepped on. H.M.’s performance showed he was capable of learning the task and that his knowledge was kept in memory to influence his future performance (following a 24-hour delay). Furthermore, it was shown by his rapid learning on parts of the task that he relied on allocentric spatial processing which

is thought to be subserved by the parahippocampal cortex (Bohbot & Corkin, 2007). Functional neuroimaging studies in the human brain confirm a pivotal role of the parahippocampal cortex in topographical learning and the retrieval of topographical information from memory (Aguirre et al., 1996) and in navigation (Aguirre et al., 1996; Brewer et al., 1998; Rosenbaum et al., 2004). In an fMRI experiment by Rosenbaum and colleagues (2004), participants were asked to perform different judgment tasks (e.g. distance/proximity judgments between pairs of landmarks, sequencing of landmarks, and landmark information in the case of blocked-routes) while engaging in a mental navigation task. Their results showed that the right parahippocampal cortex was activated across tasks, while the left parahippocampal cortex was only active when participants performed a blocked-route condition (i.e. participants were asked to indicate whether a particular street would be passed or not given a route-block at a certain location) (Rosenbaum et al., 2004). Furthermore, a specific functional role in processing specific scene-relevant information has been attributed to a part of the parahippocampal cortex. An fMRI study by Epstein and colleagues (Epstein et al., 2003) showed strong response preferences to changes in the viewpoint of a scene compared to changes of specific features within a scene in a region along the posterior parahippocampal gyrus, which the authors referred to as the parahippocampal place area (Epstein & Kanwisher, 1998). Such a category- selective region along the posterior parahippocampal cortex of the human brain has been observed by various functional neuroimaging studies when engaged in the viewing of place and scene stimuli (Aguirre & D'Esposito, 1997; Epstein & Kanwisher, 1998; Köhler et al., 2002; Pihlajamaki et al., 2004; Staresina et al., 2011), as well as during navigation (Iaria et al., 2007; Iaria, Fox, et al., 2008; Janzen & van Turennout, 2004; Schinazi & Epstein, 2010; Spiers & Maguire, 2006) and this activation has been interpreted to reflect landmark recognition during orientation, which forms an integral part of allocentric information processing (Arnold et al., 2013). However, descriptions of the locus of functional activation peaks along the parahippocampal cortex are often rather vague and

variation exists across all of these studies in terms of the location of the reported peak coordinates (Aguirre & D'Esposito, 1997; Andrews et al., 2010; Arnold et al., 2013; Epstein et al., 2003; Epstein et al., 1999; Epstein & Kanwisher, 1998; Henderson et al., 2008; Köhler et al., 2002; Pihlajamaki et al., 2004; Staresina et al., 2011; Sulpizio et al., 2013). Often the reported activation peaks extend into the adjacent cortex of the lingual gyrus (Andrews et al., 2010; Sulpizio et al., 2013), which has been reported to be sensitive to the visual presentation of building stimuli (Aguirre et al., 1998), forming part of what has been termed the lingual landmark area (Aguirre et al., 1996; Aguirre et al., 1998). Given a rather lose description of the anatomical relationship between the parahippocampal place area and the local morphology, difficulties may arise in using functionally defined regions-of-interest as basis for further studies (e.g. Arcaro et al. (2009)). Alternatively, some researchers avoid an anatomical distinction by referring to the activation location involved in spatial mnemonic information processing as falling on the lingual/parahippocampal gyrus (Sulpizio et al., 2013). Recent studies have proposed the hypothesis of sub-regions along the parahippocampal cortex (Aminoff et al., 2007; Baldassano et al., 2013; Epstein, 2008; Litman et al., 2009; Sato & Nakamura, 2003; Staresina et al., 2011; Xu et al., 2010), with the parahippocampal place area being a good candidate for one such subdivision (Epstein & Kanwisher, 1998). However, as is the case with the parahippocampal place area, the lack of a clear definition of this region along the parahippocampal cortex poses challenges for our understanding of the brain as well as for our ability to draw comparisons with observations made in other studies and/or in other species.

1.4 Probability maps in standard stereotaxic space The purpose of probability maps in standardized stereotaxic space is to provide a reference frame to allow comparison of the anatomical location of functional activation peaks obtained from functional neuroimaging examinations across studies and laboratories. Probability maps provide an indication of the likelihood that a given voxel forms part of a particular anatomical landmark, thereby forming a quantification of the inter-subject variability of the location of this landmark. In order to create probability maps, each landmark voxel is identified within the individual brain. Each brain and each voxel or landmark label are then transformed into standardized space and a group average is subsequently formed to quantify the variability of the landmark across brains. Two coordinate systems have been widely used in the neuroscience community and offer such a standard space for probability maps: One is the standard proportional space by Talairach and Tournoux (1988) and the second is the standard stereotaxic space of the Montreal Neurological Institute (MNI). The standard space of Talairach and Tournoux (1988) is the older of the two. It is considered a proportional coordinate system, as it attempts to minimize anatomical variability by parcelling the brain into twelve linear volumes which are subsequently scaled by means of a piecewise linear transformation (Collins et al., 1994; for a thorough review see Collins in Petrides, 2012). The midline of this coordinate system, which divides it into the right and the left side, runs as a straight line through the anterior and posterior commissures (AC-PC line). A registration along the AC-PC line successfully reduces variability for subcortical structures (Collins in Petrides, 2012). However, variability of the surface features of the brain remains great (Mazziotta et al., 1995; Penhune et al., 1996). The twelve volumes are defined for both hemispheres as: (1) from AC to the frontal pole, (2) from PC to the occipital pole, (3) from AC to PC, (4) from AC-PC to the lateralmost point of the brain, (5) from AC-PC to the dorsalmost point of the brain, and (6) from AC-PC to the ventralmost point of the brain (Collins in Petrides, 2012). For each brain that is to be transformed into the space of Talairach and Tournoux (1988), the appropriate points need to be identified in

order to define the outlines of the twelve volumes and each volume will subsequently be scaled to fit the template brain. The post-mortem brain that was used by Talairach and Tournoux (1988) as a template for the standard space was from a 60 year-old female, of which both hemispheres were sectioned in slices of varying thickness and one hemisphere was cut coronally and the other sagittally (Collins, 2012). Given that this template is based on a single brain and that, the aim of a standard space is to allow comparison between individuals, such a template may not provide an optimal model of the population, and it cannot capture the variability between the brains. Furthermore, this template may not represent the younger population that the majority of neuroscience research is based on (Collins in Petrides, 2012). The standard stereotaxic space of the Montreal Neurological Institute (MNI) is based on the atlas of Talairach and Tournoux (1988) in that it offers a common reference coordinate system to the neuroimaging community (Collins in Petrides, 2012). The MNI space provides a preferred alternative to the space of Talairach and Tournoux (1988) as it addresses many of the drawbacks presented above (Collins in Petrides, 2012). Therefore, it is currently the space most widely used in the software packages used for analysis of neuroimaging data (e.g. Statistical Parametric Mapping (Penny et al., 2001), FSL (Jenkinson et al., 2012), fmristat (Worsley et al., 2002)). The space of the MNI is based on a more representative sample of the population participating in the majority of neuroimaging studies. The template of the MNI space is based on an average of the brains of a large sample of young individuals with no history of neurological illness (i.e. Average 250T1 model, Evans et al. (1989)). Several amended templates have been created over the years (e.g. Average305T1 model, ICBM152), all building on the same MNI space model, yet each successive template incorporates improvements based on the development of new techniques to address the needs of the neuroscience community (e.g. increased cortical detail, increased gray-white matter contrast) (Collins et al., 1994; Collins in Petrides, 2012; Mazziotta et al., 2001). The origin of the MNI template lies near the AC (0, 3.4, -2.2 in ICBM brain 118, Collins in Petrides, 2012). Visually, the MNI

standard stereotaxic space can be portrayed as a continuous 3-dimensional average brain model (Collins in Petrides, 2012). Probability maps in standard stereotaxic space of the MNI have been established for several regions of the brain, including the precentral sulcal complex (Germann et al., 2005), occipital sulci (Iaria & Petrides, 2007; Iaria, Robbins, et al., 2008), caudal rami of the superior temporal sulcus (Segal & Petrides, 2012), orbitofrontal sulci (Chiavaras et al., 2001), pars opercularis of the inferior frontal gyrus (Tomaiuolo et al., 1999), and the cingulate, paracingulate and superior rostral sulci (Paus et al., 1996). To date, the sulcal complex that laterally delimits the parahippocampal gyrus has been said to be highly variable between brains to be considered a sulcal landmark (Epstein & Kanwisher, 1998; Insausti et al., 1998; Insausti et al., 1995). A thorough quantification of the sulcal variability of the collateral sulcus is currently lacking and may provide valuable information for anatomical location of activation peaks obtained by functional neuroimaging studies.

1.5 Aims and Overview There are several aims of this thesis. The first objective is to disambiguate the morphology, identify, and describe the sulcal-gyral patterns that make up the collateral sulcal complex in the human brain. This is done in the magnetic resonance images of the brains of healthy human subjects. The aim is to establish an understanding of the collection of sulci that mark the lateral border of the parahippocampal gyrus in order to describe and quantify consistent sulcal patterns. A particular goal is to examine whether the sulcal segment that runs along the lateral limit of the entorhinal cortex can be distinguished from a segment that runs posteriorly along the parahippocampal cortex. This is of great importance in order to resolve a debate that is not simply one of nomenclature (i.e. using the term ‘rhinal sulcus’ to refer to the sulcus that laterally delimits the entorhinal cortex or to refer to a small sulcal indentation at the most anterior part of the parahippocampal gyrus). The second objective is to provide a reference frame for the neuroimaging community by quantifying the variability of the location of several of the segments making up the collateral sulcal complex. Given the importance in the location of the collateral sulcal complex in delimiting the cortex of the parahippocampal gyrus (involved in mnemonic information processing) from the cortex of the fusiform gyrus (involved in the processing of visual information), creating a reference frame in the form of probability maps provides valuable information to the neuroscience community when identifying accurately the location of activation peaks along the parahippocampal gyrus is needed. The third objective is to link the functional activation pattern(s) observed on the parahippocampal gyrus during a navigation task to the local morphology of the collateral sulcal complex within the healthy brain. The aim is to examine whether the detailed information of the sulcal morphological patterns (see aim 1) and the probabilistic maps quantifying the location variability of the sulcal segments making up the collateral sulcus proper (see aim 2) can be used to discriminate the location of functional activation peaks obtained during navigation along the parahippocampal gyrus. The fourth objective is to examine whether the morphological descriptions (see aims 1 and 2) and the information of the

functional activation pattern during navigation along the parahippocampal gyrus in the healthy population (see aim 3) can be applied to the study of a clinical population (i.e. mild traumatic brain injured participants). The gross neuroanatomy (i.e. morphology) and the functional activation are measured using structural and functional magnetic resonance imaging, respectively. Chapter two describes the sulcal-gyral patterns of the collateral sulcal complex that we were able to identify across subjects and in spite of inter- individual variability. In chapter three, we quantify the location variability of the rhinal sulcus, the collateral sulcus proper, and the parahippocampal extent of the collateral sulcus in the form of probability maps based on the morphological description provided in chapter two. These probability maps are presented in the standard stereotaxic space of the Montreal Neurological Institute, which is the reference coordinate space most commonly used by the neuroimaging community. Chapter four applies the information obtained in chapters two and three, and uses the morphological descriptions and probability maps of the sulci of the collateral sulcal complex, to provide a more precise link with the functional activation patterns seen in the parahippocampal cortex following engagement in a navigation task. This study examines the functional activation patterns during navigation on a subject-by-subject basis in healthy participants and is part of a larger study that set out to investigate differences in functional activity during navigation between the healthy subjects and subjects who sustained a mild traumatic brain injury. Chapter five elaborates on the differences and similarities found between these two subject groups, and uses the research results from the studies described in the previous three chapters (chapters 2, 3, and 4) to see if the information obtained in the healthy individuals on a subject-by-subject basis can inform us about changes in functional activity in individuals who sustained a mild head trauma

1.6 Figures

Figure 1.6.1 Schematic representation of the cytoarchitectonic areas of the medial surface of the brain as presented in Fig.86 by Brodmann (1909).

Figure 1.6.2. Figure 5 by Amiez et al. (2006), reprinted with permission. This figure shows an example of the structure-function relationship in the frontal lobe of the human (a) and monkey (b) brain. The premotor hand region is marked in blue and the saccadic eye movement region is identified in red. The sulcal patterns in the dorsal premotor cortex of the human brain are schematically represented (c). The activation peaks from the hand-arm conditional association task related to the dorsal branch of the superior precentral sulcus (SPSd), whereas the activation peaks for the frontal eye field task fell along the ventral branch of the superior precentral sulcus (SPSv). SFS refers to the superior frontal sulcus.

Figure 1.6.3 Fig. 1 by Buffalo et al. (2006), reprinted with permission under the Creative Commons License (Attribution-NonCommercial 4.0 International License; CC BY-NC 4.0). This figure provides a schematic representation of the projections (unimodal and polymodal) to the regions of the medial temporal lobe.

Chapter Two

2. Morphological patterns of the collateral sulcus in the human brain

Huntgeburth, S.C., and Petrides M. (2012) Morphological patterns of the collateral sulcus in the human. The European Journal of Neuroscience, 35 (8), 1295-1311.

2.1 Abstract The collateral sulcal complex is an important landmark on the medial surface of the temporal lobe. Anteriorly, it delineates the limbic regions of the parahippocampal gyrus from the visual-processing areas of the fusiform gyrus. Posteriorly, it continues into the occipital lobe, bearing no relationship to the memory-related limbic regions. Given the considerable extent of the sulcus and functional heterogeneity of the surrounding cortex, an investigation of the morphology of this sulcus was carried out to examine whether it is continuous or a series of sulcal parts, i.e. independent sulci classified together under the name collateral sulcus. We investigated the collateral sulcal complex using magnetic resonance images taking into account the three-dimensional nature of the brain. Our examination demonstrated three separate sulcal segments: (i) an anterior segment, the rhinal sulcus, delineating the uncus from the adjacent temporal neocortex, (ii) a middle segment, the collateral sulcus proper, forming the lateral border of the posterior parahippocampal cortex, and (iii) a caudal segment, the occipital extent of the collateral sulcus, within the occipital lobe. Three relationships exist between the rhinal sulcus and collateral sulcus proper, only one being clearly identifiable from the surface. Posteriorly, the collateral sulcus proper and the occipital collateral sulcus, although appearing continuous on the brain surface, can be separated in the depth of the sulcus in all cases. These results provide quantification of the location and variability within standard stereotaxic space for the three collateral sulcus segments that could be used to aid accurate identification of functional activation peaks derived from neuroimaging studies.

2.2 Introduction The collateral sulcus runs from the anterior part of the human medial temporal lobe along the parahippocampal gyrus into the occipital lobe (Heckers et al., 1990; Duvernoy, 1999; Insausti & Amaral, 2004) (Fig. 2.10.1, Table 2.9.1). It is an important anatomical landmark because it delineates the limbic region involved in memory function (Scoville & Milner, 1957; Mishkin, 1978; Squire & Zola-Morgan, 1991) and, posteriorly, the lingual gyrus involved in visual information processing (Fox et al., 1987; Haxby et al., 1991). Given the extent of this sulcus and the functional diversity of the surrounding cortex, questions arise as to whether it is indeed one continuous sulcus or several segments. An important landmark along the anterior medial temporal lobe in non- human primates is the rhinal sulcus, marking the lateral limit of the entorhinal cortex (Amaral et al., 1987; Van Hoesen, 1995; Gloor, 1997; Insausti & Amaral, 2004). In humans, the term ‘rhinal sulcus’ has been used ambiguously. The classic and several recent investigators applied it to a sulcus laterally binding the uncus (Retzius, 1896; Smith, 1904; Brodmann, 1925; Economo & Koskinas, 1925; Ono et al., 1990; Gloor, 1997; Hanke, 1997; Novak et al., 2002; Kim et al., 2008). Yet, others have considered it to be the anterior part of the collateral sulcus (Insausti et al., 1995, 1998; Duvernoy, 1999; Insausti & Amaral, 2004), restricting the term ‘rhinal sulcus’ to a small dimple in the anteriormost part of the uncus (Insausti et al., 1995, 1998; Duvernoy, 1999; Insausti & Amaral, 2004) (Fig. 2.10.1, Table 2.9.1). The latter usage implies that, in the human, the entorhinal cortex is not bound by the rhinal sulcus. However, cytoarchitectonic analysis shows that the entorhinal cortex extends approximately to the end of the uncus (e.g. Insausti et al., 1995, 1998; Gloor, 1997; Petrides, unpublished observations). Gloor (1997) argued that the sulcus delimiting the entorhinal cortex should be considered the human homologue of the non-human rhinal sulcus. The collateral sulcus (Retzius, 1896; Ono et al., 1990; Kim et al., 2008) continues into the occipital lobe and laterally binds the lingual gyrus linked to visual areas V2, V3, and V4 (Sereno et al., 1995; DeYoe et al., 1996; Tootell et al., 1997; Hadjikhani et al., 1998). The lingual sulcus divides the lingual gyrus

and has been considered by some investigators to be morphologically independent of the collateral sulcus (Economo & Koskinas, 1925; Sarkissov et al., 1955; Duvernoy, 1999), whereas others illustrate a connection between the two (Retzius, 1896; Ono et al., 1990). A coherent description of the human collateral sulcal patterns still eludes us. Examinations of the sulcal depth are necessary to establish whether we can reliably identify segments of the collateral sulcus and the sulcus that laterally delimits the uncus (i.e. the entorhinal cortex). Furthermore, is the part of the collateral sulcus marking the parahippocampal gyrus morphologically continuous with or separate from its occipital extent? What is the relationship between the occipital extent and the lingual sulcus? We provide quantification of the location and variability of the sulcal patterns within standard stereotaxic space to aid interpretation of functional and structural neuroimaging findings.

2.3 Materials and methods Ethics statement This study was approved by the Montreal Neurological Institute’s Research Ethics Board. Informed, written consent was obtained from all participants according to the guidelines set forth by the Ethics Committee of the Montreal Neurological Institute.

Subjects Forty human brains, acquired as part of the International Consortium for Brain Mapping project (Mazziotta et al., 1995a,b), were examined (17 females, 23 males; mean age 25.0 ± 5.0 years), conforming to the Code of Ethics of the World Medical Association (Declaration of Helsinki) as printed in the British Medical Journal (18 July 1964). All subjects were healthy, right handed, with no history of neurological and⁄or psychiatric disorders, and gave written informed consent. Approval was given by the Research Ethics Board of the Montreal Neurological Institute and Hospital.

Magnetic resonance imaging One hundred and sixty contiguous high-resolution T1-weighted magnetic resonance images (1 mm3) were acquired using a 1.5 Tesla Philips Gyroscan scanner [repetition time (Tr), 18 ms; echo delay time (Te), 10 ms; flip angle, 30] with a fast-field echo three-dimensional sequence in the sagittal plane. All were masked (Smith, 2002) to extract the brain, corrected for radiofrequency non- uniformities (Sled et al., 1998), and subsequently stereotaxically registered to the International Consortium for Brain Mapping 152 non-linear sixth generation symmetric target (Grabner et al., 2006) with a 12-parameter affine transformation (Collins et al., 1994; Grabner et al., 2006) using the Corticometric Iterative Vertex-based Estimations of Topology image-processing cortical surface extraction pipeline (Ad-Dab’bagh et al., 2006). This target is the standard stereotaxic space used by the functional neuroimaging community, i.e. the Montreal Neurological Institute standard stereotaxic space that has evolved from the Talairach space (Talairach & Tournoux, 1988).

Additionally, the surfaces of 11 non-pathological post-mortem human brains were examined to study the correspondence between their sulcal patterns and the sulcal patterns of the sample of 40 magnetic resonance imaging (MRI) brains. Two of these post-mortem brains were subsequently scanned using proton- density weighted MRI to examine the in-depth nature of the relationship of the sulci of interest.

Localization of the collateral sulci The interactive software package DISPLAY (MacDonald, 1996), enabling three- dimensional whole-brain as well as two-dimensional sectional (coronal, sagittal, axial ⁄ horizontal) views, was used to examine the sulci. All images were individually examined and the sulcal midline of consecutive images was color coded by an expert in human neuroanatomy. The collateral sulcus was continuously examined anteriorly at the level of the limen insulae and its course followed posteriorly to the level of the body of the calcarine sulcus.

2.4 Results Our results show three distinct sulcal segments making up the collateral sulcal complex: an anterior segment, the rhinal sulcus, a middle segment, the collateral sulcus proper, and a caudal segment, the occipital extent of the collateral sulcus. Furthermore, the relation between the rhinal sulcus, occipitotemporal sulcus, and collateral sulcus proper is acknowledged and hemispheric and gender differences are recognized. Tables 2.9.2 and 2.9.3 and Figs 2.10.2–2.10.9 illustrate our findings.

Rhinal sulcus The rhinal sulcus is the first sulcus that stretches in the rostrocaudal direction lateral to the amygdala and the anterior part of the hippocampus, forming a profound sulcal convexity originating about 1 mm rostral to the level of the limen insulae (rhinal sulcus, rostral origin: mean y-coordinate + 4.7 mm ± 3.82 mm; limen insulae, mean y-coordinate + 3.5 mm ± 1.78 mm). The limen insulae is the point where the anteriormost ventral portion of the insular cortex joins the orbitofrontal cortex. The coordinates of the limen insulae were established in the present study by identifying, within the coronal plane, the most rostral section displaying a connection of fiber tracts between the frontal and temporal lobe, i.e. the point of closing of the lateral sulcus. The anteriormost part of the amygdala can be identified just a few millimeters posterior to this point (post-mortem brain examination in Petrides, 2012; Duvernoy, 1999). The rhinal sulcus courses parallel along the length of the amygdala and the head of the hippocampus, terminating at the mid-level of the hippocampal body (rhinal sulcus, caudal origin: mean y-coordinate -21.4 mm ± 4.63 mm). There were no instances in which the rhinal sulcus terminated before the caudalmost part of the amygdala, continuing along the entire length in 100% of our examinations. Occasionally, in 6.25% of cases, there may be another shallower sulcus parallel to and in-between the anterior part of the rhinal sulcus and the amygdala. However, this sulcus does not continue along the entire length of the amygdala, but rather is only present for approximately 11 mm (anterior sulcus, rostral origin:

mean y-coordinate + 3.0 mm ± 1.58 mm; caudal origin: mean y-coordinate -8.2 mm ± 3.90 mm; Tables 2.9.2 and 2.9.3C).

Collateral sulcus proper The collateral sulcus proper forms a deep rostrocaudally oriented sulcus separating the parahippocampal from the fusiform gyrus. Three main morphological patterns best describe the relationship between the rhinal sulcus and collateral sulcus proper. First, in 63.75% of cases (51 hemispheres), the collateral sulcus proper could be separated on the surface and in-depth from the rhinal sulcus (Type I; Figs 2.10.2A and 2.10.3; Table 2.9.3A). Second, in 33.75% of cases, these sulci seem continuous from the surface of the brain, but they may still be reliably identified as separate within the sulcal depth (Type II; 27 hemispheres; Table 2.9.3A). In 31.25% of cases (25 hemispheres), the collateral sulcus proper develops out of the medial bank of the rhinal sulcus (Type IIb; Figs 2.10.2C and 2.10.5; Table 2.9.3A) and in only 2.5% (2 hemispheres) out of the lateral bank (Type IIa; Figs 2.10.2B and 2.10.4; Table 2.9.3A). Third, only two of all hemispheres studied (2.5%) had a rhinal sulcus and collateral sulcus proper as continuous on the surface and in-depth (Type III; Figs 2.10.2D and 2.10.6; Table 2.9.3A). The rostral origin of the collateral sulcus proper occurred within the depth of the brain, not visible from its surface, in 91% of cases (71 hemispheres), becoming visible on the surface on average 5 mm posterior to its point of origin (collateral sulcus proper visible from the surface: mean y-coordinate -23.7 mm ± 6.16 mm). This proper segment may be one continuous entity or subdivided into two segments, both occurring to the same degree across hemispheres (50%; 39 hemispheres). In 16.67% (13 of 78 hemispheres) of observations in which the collateral sulcus proper was separable from the rhinal sulcus, it originated rather rostrally at a level where the amygdala and the hippocampus were present (collateral sulcus proper originating at the height of the amygdala; rostral origin: mean y-coordinate -6.2 mm ± 1.79 mm; Table 2.9.2). Even here, the rhinal sulcus was the deep

sulcus parallel to the amygdala surrounding its entire length. In 83.33% of cases, the proper segment originated at a y-coordinate of -20.9 mm ± 4.87 mm (collateral sulcus proper excluding the ones that show a distinctively more rostral origin; Table 2.9.2).

Occipital extent of the collateral sulcus At the level of the splenium of the corpus callosum, the collateral sulcus proper and the occipital extent, although appearing continuous from the surface, could be separated in-depth in all cases. In only 8.75% of cases, one furrow was identified as the occipital extent of the collateral sulcus (Pattern 1, Table 2.9.3B), whereas in 91.25% of cases, a medial and a lateral branch were noted (medial or lateral branch, respectively, in the case of two occipital extensions of the collateral sulcus Patterns 2–8, Table 2.9.3B). These two occipital branches were found to develop by bifurcating within the same sulcal bed in 46.25% of cases (37 hemispheres; Pattern 2). In 11.25% of observations (9 of 80 hemispheres), a medial occipital segment shared the sulcal bed with the collateral sulcus proper, although the two were clearly distinguishable. Here a branch developed from the lateral bank of the medial occipital extent (Pattern 3). In 2.5% of cases (two hemispheres), this lateral sulcus developed not in-depth, but at the foot of the medial occipital extent (Pattern 4). In 3.75% of cases (3 of 80 hemispheres), the lateral segment was present but not connected to the medial occipital segment (Pattern 5). In 12.5% of cases (10 of 80 hemispheres), a lateral occipital segment shared the sulcal shaft with the collateral sulcus proper, although being clearly distinguishable. A medial occipital branch then developed from the (medial) bank of the lateral occipital furrow (Pattern 6). In 3.75% of cases (3 of 80 hemispheres), the medial occipital segment developed not in-depth, but at the foot of the lateral segment of the occipital extent (Pattern 7). In 11.25% of cases (nine hemispheres), a medial branch was present, but not connected to the lateral occipital extent (Pattern 8) (see Tables 2.9.2 and 2.9.3B, and Figs 2.10.7 and 2.10.8).

We further identified a short sulcus, which when present arises midway along the collateral sulcus proper, first running parallel and then in a mediolateral direction, connecting with the collateral sulcus proper at the level of the rostralmost tip of the anterior calcarine sulcus, which forms the anterior point of the isthmus, around the height of the splenium. This sulcus, here called the parahippocampal extension of the collateral sulcus, was identified in 56 of 80 hemispheres (70%), being absent in 24 of 80 hemispheres (30%; Table 2.9.3D). On average, this parahippocampal extension originates rostrally at y -34.7 mm ± 2.49 mm and connects with the collateral sulcus at y -41.5 mm ± 2.85 mm, with the rostralmost point of the anterior calcarine sulcus being at y -38.8 mm ± 2.51 mm and the caudalmost point of the splenium across hemispheres being at y -42.0 mm ± 2.59 mm (Table 2.9.2).

Relation between the rhinal sulcus, collateral sulcus proper, and occipitotemporal sulcus The sulcal bed of the collateral sulcus proper shows connection with that of the occipitotemporal sulcus in 25% of cases (20 hemispheres; 27.5% left, 22.5% right hemispheres). In 7.5% of cases (six hemispheres; 10% left, 5% right hemispheres), the sulcal beds of the rhinal and occipitotemporal sulcus were connected. In 2.5% of cases (one right, one left hemisphere), the sulcal beds of the rhinal sulcus, occipitotemporal sulcus, and collateral sulcus proper communicated. In the majority of observations (65%, 52 hemispheres; 60% left, 70% right hemispheres), all three sulci were separated (Table 2.9.3E).

Hemisphere and gender differences A chi-square test of goodness-of-fit to determine the hemispheric differences in 2 segmentation patterns found no differences [Type 1, χ 1 = 0.18 (n = 51), p < 0.05; 2 2 Type 2a, χ 1 = 2.0 (n = 2), p < 0.05; Type 2b, χ 1 = 1.96 (n = 25), p < 0.05; Type 3, 2 χ 1 = 2.0 (n = 2), p < 0.05]. Nevertheless, the Type IIb pattern was observed almost twice as often in left than in right hemispheres (16⁄9 left⁄right occurrences; Table 2.9.3A).

Paired-samples t-tests, using the statistical analysis software SPSS for Windows version 11.0.1, compared landmarks between hemispheres (Table 2.9.2). Significantly more posterior locations in the left than the right hemispheres, significant at the 0.001 level, were seen for the limen insulae (t39 = - 6.35, p < 0.001; right: y-coordinate + 4.1 mm ± 1.75 mm; left: y-coordinate + 2.9 mm ± 1.63 mm), rostral origin of the collateral sulcus proper [cos-all, average of the rostral origin of the cos, across all cos’s, including the ones with and without a more anterior origin (i.e. cos-early and cos-late): t37 = -4.02, p < 0.001; right: y- coordinate -16.3 mm ± 7.38 mm; left: y-coordinate -20.7 mm ± 6.06 mm], and anteriormost point of the anterior calcarine sulcus (t39 = -5.39, p < 0.001; right: y- coordinate -37.6 mm ± 2.15 mm; left: y-coordinate -39.9 mm ± 2.36 mm). At the significance level of 0.05, more posterior origins in the left than right hemispheres were found for the caudalmost point of the rhinal sulcus (t37 = -3.18, p < 0.05; right: y-coordinate -20.1 mm ± 4.66 mm; left: y-coordinate -22.7 mm ± 4.32 mm), point of surfacing of the collateral sulcus proper (t37 = -3.39, p < 0.05; right: y- coordinate -21.8 mm ± 6.51 mm; left: y-coordinate -25.6 mm ± 5.34 mm), and caudal point of the parahippocampal extension of the collateral sulcus (t20 = -2.60, p < 0.05; right: y-coordinate -40.6 mm ± 2.44 mm; left: y-coordinate -42.3 mm ± 3.05 mm). When separated according to gender, the left⁄right hemisphere differentiation remained, except for the point of surfacing of the collateral sulcus proper, being significant only for males (t21 = -2.82, p < 0.05; right: y-coordinate - 20.9 mm ± 7.43 mm; left: y-coordinate -25.5 mm ± 5.19 mm), and the caudal point of the parahippocampal extension of the collateral sulcus, being significant only for females (t10 = -2.77, p < 0.05; right: y-coordinate -40.8 mm ± 2.23 mm; left: y-coordinate -43.4 mm ± 3.80 mm).

Post-mortem examination A visual inspection of 22 post-mortem human brain hemispheres was carried out to examine the relationship between the rhinal and collateral sulcus. A dominant occurrence of the Type I pattern was found in a total of 68% of the 22 hemispheres [i.e. in eight of eleven right (73%) and in seven of eleven left (64%)

hemispheres]. A continuity between the rhinal sulcus and the collateral sulcus proper (Type II or Type III) was present in a total of 32% of the 22 hemispheres [i.e. in three of eleven right (27%) and in four of eleven left (36%) hemispheres]. Further differentiation into Type II (a and b) or Type III patterns is not possible by solely examining the surface of the brain, but requires an investigation of the in- depth nature of these sulci, e.g. in MRI sections. By using proton-density MRI, the sulcal patterns described as Type I, Type IIa, and Type IIb could be identified in post-mortem brain hemispheres (Fig. 2.10.9).

2.5 Discussion According to our findings, the so-called ‘collateral sulcus’, the prominent landmark on the ventromedial aspect of the temporal and occipital lobe, is not a single, morphologically continuous furrow but rather a complex of three sulci. In the temporal lobe, the rhinal sulcus and subsequently the collateral sulcus proper separate the anterior and posterior parts of the parahippocampal gyrus from the fusiform gyrus. Further posteriorly, an occipital segment separates the lingual gyrus from the fusiform gyrus (Fig. 2.10.1).

Rhinal sulcus and collateral sulcus proper Despite inter-individual variability in cortical folding patterns, the rhinal sulcus was reliably identified as separate from the collateral sulcus proper in 78 of 80 hemispheres (97.5%; Table 2.9.3A). Our results are in line with previous investigations that showed an independent sulcus running parallel and lateral to the uncus (Eberstaller, 1890; Retzius, 1896; Brodmann, 1925; Economo & Koskinas, 1925; Ono et al., 1990; Hanke, 1997; Novak et al., 2002; Kim et al., 2008). We have chosen the term ‘rhinal’ for this sulcus, as suggested by Gloor (1997), to emphasize that it is comparable to the sulcus of the same name that is found in non-human primates and is so called because it lies lateral to the part of the uncus where the entorhinal cortex is found (Van Hoesen, 1995; Gloor, 1997; Insausti & Amaral, 2004). We would like to highlight the importance of distinguishing the present use of ‘‘rhinal’’ from the occasional use of the term ‘rhinal sulcus’ to refer to the temporal incisure, a small dimple at the rostralmost tip of the parahippocampal gyrus (Heckers et al., 1990; Insausti et al., 1995, 1998; Van Hoesen, 1995; Duvernoy, 1999; Insausti & Amaral, 2004) (for a detailed discussion, see section ‘Rhinal sulcus and entorhinal cortex’ below). Furthermore, we refer to the middle, non-uncal segment of the collateral sulcal complex as the ‘collateral sulcus proper’ as it forms the lateral border of the posterior portion of the parahippocampal gyrus and it has been consistently labeled as the collateral sulcus in most text books (Table 2.9.1).

Three main patterns describe the relationship between the rhinal sulcus and collateral sulcus proper (Fig. 2.10.2). The first pattern, Type I, identified in 63.75% of cases, is the most prominent, and refers to the cases in which the two sulci are separate on the surface and in the sulcal depth (Table 2.9.3A, Figs 2.10.2A and 2.10.3). The anteriormost portion of the collateral sulcus proper originates in the depth of the cortex in 91% of the observed hemispheres, becoming visible from the surface of the brain only approximately 5 mm posterior to its point of origin (Table 2.9.2). In only 9% of our observations did this segment develop directly at the cortical surface. This is in accordance with Economo & Koskinas (1925), who illustrate two sulcal entities in a rostrocaudal direction along the parahippocampal gyrus (Fig. 2.10.1A): an anterior sulcus, referred to as the rhinal sulcus (corresponding to the rhinal sulcus of the present study), and a posterior sulcus, referred to as the occipitotemporal sulcus or collateral sulcus (corresponding to the collateral sulcus proper of the present study). Gloor (1997) examined a sample of five sectioned brains and also noted such a pattern in four out of the five brains; only in one brain continuity was noted between the two sulcal parts. Gloor (1997), however, notes the small sample size, suggesting that these results may not be generalizable. Retzius (1896) reported that, in the majority of cases, the rhinal and collateral sulcus (proper) do not anastomose but are separated by a cortical bridge, termed the anterior rhinencephalo-fusiform gyrus, pli-temporolimbique by Broca and Dejerine (Retzius, 1896), or gyrus temporolimbicus posterior by Economo & Koskinas (1925), connecting the hippocampal and fusiform gyri. The second pattern, Type II, identified in 33.75% of cases, refers to the cases in which the rhinal and collateral sulcus proper are continuous when viewed from the surface, although a clear separation can be made when examining the depth of the sulcus (Figs 2.10.2B and C, 2.10.4 and 2.10.5). Here, the collateral sulcus proper can originate lateral or medial to the caudal portion of the rhinal sulcus. Together, Type I and Type II patterns comprised 97.5% of our cases, demonstrating that the rhinal and collateral sulcus proper represent two prominent, independent sulci in the human brain.

Novak et al. (2002) examined the rhinal sulcus, the collateral sulcus (proper), and the occipitotemporal sulcus (i.e. a collection of rostrocaudally oriented sulci located lateral to the collateral sulcal complex) using magnetic resonance images in 100 hemispheres of patients with temporal lobe epilepsy. Sulcal maps were created using translucent paper and different colored lines to outline the surface anatomy of the sulci on successive coronal images. The results suggested three types of relationship between the rhinal and collateral sulcus (proper): In Type A (33% of the cases), the rhinal and collateral sulcus proper are connected; in Type B (31% of cases), the rhinal and collateral sulcus proper are separate, with the rostralmost part of the collateral sulcus proper originating anteriorly and for a short distance running parallel to the caudal part of the rhinal sulcus; and in Type C (36% of cases), the rostral origin of the collateral sulcus proper develops posterior to the caudal end of the rhinal sulcus. Although Novak et al. (2002) examined patients with temporal lobe epilepsy, they found no correlation between sulcal patterns and illness characteristics. Our examinations, which investigated healthy individuals, are in line with the results of Novak et al. (2002) (when combining their Type A and B) as we observed a physical separation between the rhinal and the collateral sulcus proper in 63.75% of our cases [64% in Novak et al. (2002)]. Moreover, in our investigation we further classified the remaining 36.25% of cases [Type C observed in 36% of cases by Novak et al. (2002)] into two groups: first, Type II, observed in 33.75% of cases, where the rhinal and collateral sulcus proper appear continuous at the surface of the brain, yet are clearly separable in the sulcal depth, and second, Type III, occurring only occasionally, in 2.5% of cases, where these two segments are continuous at the surface and in-depth (Table 2.9.3A, Figs 2.10.2B–D and 2.10.4– 2.10.6). Although Novak et al. (2002) observed their Type A and Type B patterns to occur more often in male patients and their Type C pattern more often in female patients, no such sex ⁄ pattern differentiation was observed in our study. Nevertheless, not all studies to date have painted such a clear picture. For example, Hanke (1997) examined 184 cadaver hemispheres, that had been fixed by immersion, by taking photographs perpendicular to the surface of the

entorhinal region, and by drawing the outlines of the sulcal patterns for quantification. His results showed the collateral sulcus (proper) being a continuation of the rhinal sulcus in 41.9% of cases. Given that our results are based on the examination of the sulcal depth of the collateral region, we suggest that this investigator may have considered sulcal patterns, such as our Type II pattern, as constituting a continuation, which is the impression given by this pattern at the surface of the brain. Of course, examination of the sulcal depth clearly shows the separation between the sulci (see Type IIa and Type IIb as identified in the present study in Figs 2.10.4 and 2.10.5, respectively). Furthermore, the methodology applied included cadaver brains, sectioned ‘mediosagittally’ and photographed for analysis from which the sulcal patterns were captured (Hanke, 1997), making it possible that narrow in-depth separations of sulci may have remained unnoticed. If only surface information is considered, their percentage of a continuous sulcal pattern is close to that of our study (Type II and III together). An in-depth examination of the folding pattern such as that conducted in the present study would have revealed that both sulci could reliably be separated. In addition, Kim et al. (2008) investigated the morphology of the basomedial temporal lobe in healthy subjects and patients with epilepsy. Sulcal patterns were extracted from the cortical surface using a classification of gray matter, white matter, and cerebrospinal fluid, and were automatically labeled based on a database containing information from manually identified sulci. Four sulcal patterns were identified describing the course of the rhinal, occipitotemporal, and collateral sulcus (proper). Their results (Types 2, 3 and 4) show the rhinal and collateral sulcus proper separable on the surface and in-depth in 56% of cases, in accordance with the present findings of 63% of cases. Although their ‘Type 1’ pattern describes the two sulci as forming a single branch in 44% of cases, our investigation succeeded in separating the rhinal from the collateral sulcus proper in the majority of our cases, finding the occurrence of a true continuation of the rhinal and collateral sulcus proper in only 2.5% of cases (Table 2.9.3A). Ono et al. (1990) examined sulcal variations in 25 specimens. In

72%, the rhinal sulcus did not connect with the collateral sulcus (proper) and in 28%, the two sulci were connected. No hemispheric differences in the frequency of occurrence were found for these sulcal patterns. This is in accordance with our present findings and shows that, in the majority of cases, the rhinal and the proper segments of the collateral sulcal complex can be separated. In addition, Ono et al. (1990) found no overlap between the rhinal sulcus and the rostral origin of the collateral sulcus (proper) in 28% of the right and 32% of the left hemispheres, and a short overlap was noted in 40% of the right and 24% of the left hemispheres. A long overlapping segment, hence a quite rostral origin of the collateral sulcus (proper), was seen in 12% of the right and 16% of the left hemispheres (Ono et al., 1990). Our observations concur, showing that in 16.67% of cases (i.e. in 13 out of the 78 hemispheres that have been classified as showing either the Type I or Type II patterns) the collateral sulcus proper has its rostral origin quite anteriorly (at a mean y-coordinate of -6.2 mm ± 1.79 mm; Table 2.9.2). The third pattern, Type III, observed in the present study refers to the cases in which the rhinal and collateral sulcus proper are continuous on the surface and in the depth of the cortex, occurring in 2.5% of cases (Table 2.9.3A; Figs 2.10.2D and 2.10.6). This concurs with the work of Economo & Koskinas (1925), who reported the possibility of the rhinal and the occipitotemporal fissure (i.e. their term for our collateral sulcus proper) being fused, forming a single furrow. As these authors pointed out, the anterior part of this ‘occipitotemporal fissure’ would then correspond to the rhinal sulcus of the present investigation. Retzius (1896) also noted this fusion between the rhinal and the collateral fissures. Duvernoy (1999) and Insausti & Amaral (2004) describe the collateral sulcus (i.e. the rhinal and proper collateral segments) as one single furrow, forming the lateral boundary along the entire parahippocampal gyrus. This, according to Gloor (1997), is observed in one of five brains (20%) and in 44% according to Kim et al. (2008). One question that may arise in studies with such high incidences of one continuous furrow is whether a thorough in-depth investigation has been conducted. The close sulcal boundaries and merging gray matter tissue may pose

a difficulty when separating the rhinal sulcus from the rostral origin of the collateral sulcus proper. Moreover, automatic tissue classification and sulcus extraction software (Kim et al., 2008) may not be sensitive enough to differentiate between the Type II and III patterns described here. The variation in the course of the rhinal and collateral sulcus proper as observed in our sample of post-mortem human brains is comparable with the results of our in-vivo MRI sample, in terms of the frequency of occurrence of the discontinuous (Type I) and continuous [Type II (a and b) and⁄or Type III] relationships (Figs 2.10.2–2.10.6 and 2.10.9). From the surface, the predominant pattern, observed in 68% of cases, showed a discontinuous relationship between the rhinal and the collateral sulcus proper (Type I) and a continuous relationship was seen in the remaining 32% of cases (Type II and⁄or III). Figure 2.10.9 illustrates the surface views of post-mortem brains and examples of the in-depth identification of Type I, Type IIa, and Type IIb patterns.

Rhinal sulcus and entorhinal cortex The sulcus here called the ‘rhinal sulcus’ marks the entire length of the uncus. It originates around the anteroposterior level of the limen insulae, forming the first prominent incisure lateral to the amygdala and hippocampus, and continuing parallel to these up to the caudalmost point of the uncus, just slightly posterior to the anteroposterior level of the lateral geniculate nucleus. Previous studies have stated that there is an absence of prominent morphological landmarks on the ventromedial surface of the temporal lobe that may relate to the extent of the human entorhinal cortex (Insausti et al., 1995). According to these studies, the entorhinal cortex is rostrally bound by the temporal incisure, which is hypothesized to be the rhinal sulcus as identified in lower mammals (Brodmann, 1925), originating slightly posterior to the limen insulae (Insausti et al., 1995). The lateral and caudal limits of this region in humans have been said to ‘‘extend[s] for some distance in the shoulder and medial bank of the collateral sulcus’’ (Insausti et al., 1995; p. 178). The caudal border of the entorhinal cortex is said to be less defined. It is stated that, posterior to the uncus, the perirhinal

cortex and posterior part of the parahippocampal gyrus start occupying more and more of the cortical surface, pushing the entorhinal cortex medially and limiting it to a slim band that terminates at approximately the posterior portion of the lateral geniculate nucleus (Insausti et al., 1995). Here, the perirhinal cortex is said to lie within the medial bank of the anterior part of the collateral sulcus (i.e. the rhinal sulcus of the present investigation), forming the lateral limit of the entorhinal cortex and creating the boundary between the medially located allocortex and laterally located neocortex (Brodmann, 1925; Van Hoesen, 1995). Although Insausti et al. (1995) do not use the term ‘rhinal’ for the sulcus lateral and in parallel to the entorhinal cortex, they nevertheless point out that the entorhinal cortex in the human brain runs along the edge of the ‘anterior collateral sulcus’. Another histological examination of the human entorhinal cortex by Krimer et al. (1997) also showed that the entorhinal cortex is laterally bound by the sulcus that delimits the uncus. This sulcus is the rhinal sulcus as defined in the classical studies and the present investigation. In the monkey brain, the entorhinal cortex shows a close relationship with the medial bank of the rhinal sulcus (Witter & Amaral, 1991), whereas, in the human brain, the lateral border of the entorhinal cortex may vary in its degree of extension onto the medial bank (Krimer et al., 1997). Differences in the observations of the correspondence between the entorhinal cortex and the sulcus that lies lateral to it (e.g. Insausti, 1993; Insausti et al., 1995; Krimer et al., 1997) are probably due to variations in the definition of the subdivisions of the entorhinal cortex (Krimer et al., 1997). Our finding that the morphological extent of the rhinal sulcus coincides with the anterior⁄posterior boundary descriptions of the human entorhinal cortex (Insausti et al., 1995; Krimer et al., 1997) supports the view of Gloor (1997) that the rostral segment of what is sometimes referred to as the collateral sulcus should be called the rhinal sulcus as it lies in relation to the lateral boundary of the entorhinal cortex. In the rare cases (2.5%) in which the rhinal and the collateral sulci fuse to form a continuous collateral sulcus, the anterior part of the fissure may constitute the homologue of the rhinal sulcus (Gloor, 1997).

In conclusion, as the anterior sulcus identified in the present study forms the lateral boundary of the uncal part of the parahippocampal gyrus, which relates to the histologically defined entorhinal cortex (Insausti et al., 1995), we consider it to correspond to the rhinal sulcus of non-human primates (Petrides, unpublished observations; Gloor, 1997). It should be noted that, in the older neuroanatomical literature, this sulcus was indeed referred to as the ‘fissura rhinica’ (Retzius, 1896), ‘sulcus rhinalis posterior’ (Brodmann, 1925), and ‘fissura rhinalis’ (Smith, 1904; Economo & Koskinas, 1925). Additionally, this usage has continued with some modern investigators (Ono et al., 1990; Novak et al., 2002; Kim et al., 2008).

Relationships with neighboring sulci In 2.5% of our observations, the anterior origin of the collateral sulcus proper and the posterior origin of the rhinal sulcus merged in the depth of the cortex with the anterior branch of the occipitotemporal sulcal complex. Furthermore, in 7.5% of cases, the rhinal sulcus communicated with the anterior branch of the occipitotemporal sulcal complex, although remaining separate from the collateral sulcus proper. In 25% of cases, the collateral sulcus proper communicated with the anterior branch of the occipitotemporal sulcal complex, although remaining separate from the rhinal sulcus. In the majority of our observations (65%), these three sulci were independent of one another (Table 2.9.3E). Kim et al. (2008) noted similar yet slightly higher occurrences in their healthy subject group, reporting a connection between the occipitotemporal and collateral sulcus (proper) in 33% of cases. Ono et al. (1990) observed a connection between the occipitotemporal sulcus and the anterior end of the collateral sulcus (proper) in an average of 32% of their specimens (20% in the right and 44% in the left hemispheres). In contrast, Novak et al. (2002) solely observed an association between the occipitotemporal sulcus and the rhinal sulcus in 1 of 50 patients and between the occipitotemporal and collateral sulcus (proper) in 2 of 50 patients. This, however, may be the result of the subject population investigated (i.e. patients with temporal lobe epilepsy). Kim et al. (2008) also examined this patient

population and found lower incidences [across hemispheres ‘‘an average’’ of 10% for an occipitotemporal and rhinal connection, and approximately 6% for an occipitotemporal and collateral sulcus (proper) connection]. Furthermore, according to Ono et al. (1990), the rhinal sulcus showed a true connection with the occipitotemporal sulcus in only 4% of their specimens. In 4% of the right and 8% of the left hemispheres, the rhinal and occipitotemporal sulcus exhibited what Ono et al. (1990) refer to as a ‘pseudoconnection’. In addition, our present investigation revealed the occasional existence of another sulcus at the level of the anterior part of the rhinal sulcus, lying medial and parallel to it. This sulcus then forms the medial border of the amygdala, not continuing along its entire length, but being present for only a short distance (11 mm). This sulcus is seen in 6.25% of the observations, forming the exception rather than the rule (Table 2.9.3C). Our findings echo those of Ono et al. (1990) who noted such a sulcus in 8% of their examinations, describing it as being either solely a small indentation or a deep furrow. It may be hypothesized that this small dimple or sulcus refers to what has been called the ‘sulcus rhinencephali inferior’ (Retzius, 1896), intrarhinal sulcus (Insausti & Amaral, 2004), or described by Duvernoy (2005) as the ‘‘uncal notch produced by the free edge of the tentorium cerebelli’’ (p. 53).

Collateral sulcus proper and occipital extent of the collateral sulcus Whereas the collateral sulcus proper forms the lateral border of the posterior parahippocampal gyrus, the occipital extent of the collateral sulcus marks the posterior limit of this gyrus and continues within the occipital lobe that is functionally involved in the processing of visual information. The occipital extent can thus be distinguished from the proper collateral sulcus and the rhinal sulcus based on the cortical region that it delineates. Our investigations showed that at the level of the isthmus, which coincides with the anteriormost part of the anterior calcarine sulcus, there is often a bifurcation of the occipital extent of the collateral sulcus into a medial and lateral branch. This was observed in 91.25% of our cases (Table 2.9.3B; Figs 2.10.7 and 2.10.8). In 46.25% of these, the branches

originated evenly within the sulcal fundus, forming a bifurcation (Pattern 2, Fig. 2.10.7 Panel 2). In the remaining 45%, they did not originate within the depth of the sulcal fundus, but were nevertheless still present (Patterns 3–8, Fig. 2.10.7 Panels 3 and 4; Fig. 2.10.8 Panels 5–8). In 8.75% of cases, only one branch marked the occipital extent of the collateral sulcus (Pattern 1, Table 2.9.3B; Fig. 2.10.7 Panel 1). It can be hypothesized that, at the posterior end of the collateral sulcus proper, where the temporal and occipital lobes come together, there may be a transition where an anterior branch of the lingual sulcal complex comes so close to the collateral sulcus proper and the occipital extent of the collateral sulcus that it creates the impression of a bifurcation. The medial segment of the occipital extent may correspond to what Ono et al. (1990) refers to as the posteromedial terminal branch of the collateral sulcus, also called the intralingual ramus (reported in 40% of right and 56% of left hemispheres). In 32% of cases (on average across hemispheres) it forms an independent sulcus within the lingual gyrus. The gross morphological facts observed in our examination suggest that the occipital collateral extent is really a separate sulcus that may be related to the development of the occipital lobe, being independent of the limbic medial temporal lobe involved in memory processing. Although there are some studies on the development of the collateral sulcus in the fetal human brain (Chi et al., 1977; Garel et al., 2001; Dubois et al., 2008; Bajic et al., 2012), a systematic examination of the developing brain with respect to the three segments of the collateral sulcus, as defined here, is lacking. Some support for the idea that the occipital collateral extent may be related to the development of the occipital lobe may come from the study by Chi et al. (1977) who examined perinatal gyral and sulcal development in post-mortem human brains. The collateral sulcus was reported to develop within the temporal and occipital lobe at a gestational age of 20–23 weeks, at the same time as the formation of the parahippocampal gyrus (see Table 1 in Chi et al., 1977). In contrast, the lingual gyrus was found to develop at a later stage, between 24 and 27 weeks of gestation, followed by the formation of the external occipitotemporal gyrus at 30 weeks of gestation (Chi et

al., 1977). However, the sulci that delimit the lingual gyrus and the external occipitotemporal gyrus are not identified (Chi et al., 1977). It may be worthwhile for future research to investigate the development of the occipital part of the collateral sulcus in light of the findings of the present research. The occipital branches of the collateral sulcus can be distinguished from the lingual sulcal complex as identified by Iaria & Petrides (2007), who described the occipital collateral extent as parallel to the body of the calcarine sulcus, forming the lateral border of the lingual gyrus (Iaria & Petrides, 2007). The lingual sulcus, at the level of the body of the calcarine sulcus, divides the lingual gyrus into an inferior and a superior part (Economo & Koskinas, 1925; Iaria & Petrides, 2007; ‘intralingual sulcus’ by Ono et al., 1990). In all but one instance, we identified a collection of lingual sulci lying posterior and dorsal to the medial branch of our occipital collateral segment. Functional neuroimaging studies found the human primary visual area, V1, to lie within the banks of the calcarine sulcus (DeYoe et al., 1996; Tootell et al., 1997; Hadjikhani et al., 1998). The secondary visual areas, V2 and V3, surround V1. Inferomedially, area V2 and ventral area V3 occupy the lingual gyrus (DeYoe et al., 1996; Tootell et al., 1997; Hadjikhani et al., 1998). DeYoe et al. (1996) identified the boundary between the ventroposterior visual area (area VP) and ventral area V4 within either bank of the collateral sulcus (i.e. our occipital extent), noting the importance for clinical practice of understanding anatomical variation in relation to secondary visual areas. Hadjikhani et al. (1998) proposed that, rather than area V4, it is area V8 that is color-selective, occupying according to our description the posterior fusiform gyrus, lateral to the lateral branch of our occipital collateral extent. The coordinates of foveal area V4 (x-, y-, z-coordinates ± 32, -87, -16) of Hadjikhani et al. (1998) fall within or just on the medial side of the lateral branch of our occipital collateral extent, the same location reported as central area V3A (x-, y-, z-coordinates ± 29, -86, -16) of Tootell et al. (1997). Functional imaging studies taking our anatomical features of the collateral sulcal complex into consideration may help to disentangle questions of the functional⁄anatomical relationship.

Although Economo & Koskinas (1925) illustrate a short mediolaterally oriented sulcus connected with the collateral sulcus (proper) at the level of the isthmus (Figs 22 and 24 in Economo&Koskinas, 1925), no such mention is made by Brodmann (1925). Our examination identified such a parahippocampal extension of the collateral sulcus in 70% of cases (Table 2.9.3D). This sulcus connected with the collateral sulcus proper at the level of the rostralmost tip of the anterior calcarine sulcus (Table 2.9.2), which lies close to the transition between the proper and the occipital segment of the collateral sulcus. In 30% of cases, the parahippocampal extension of the collateral sulcus was absent. Support for this is found in Ono et al. (1990), who reported such a collateral side branch, the parahippocampal ramus, in 72% of cases, just anterior (~ 8 mm in the right, ~ 5 mm in the left hemispheres) to the splenium. Two side branches were reported in 12% of their observations, and no ramus in 16% of their right and 8% of their left hemispheres. These authors further noted that ‘‘the posterolateral end of the parahippocampal ramus indicates the posterior end of the hippocampus in the temporal horn’’ (Ono et al., 1990, p. 103).

Sulcal morphology and relevance to functional studies It is noteworthy that the gross sulcal⁄gyral morphology of the brain may be informative of functional organization. For instance, Amiez et al. (2006) examined structure⁄function relationships in the human dorsal premotor cortex, demonstrating a good relationship between functional activity and sulcal ⁄ gyral patterns. In this functional MRI study, the activation peaks derived from visuomotor hand conditional task performance were related to the dorsal branch of the superior precentral sulcus, whereas the peaks from frontal eye movement performance were associated with the ventral branch of the superior precentral sulcus. A good understanding of the sulcal morphology of the brain can aid the localization and interpretation of functional neuroimaging data. Functional neuroimaging studies have shown that distinct regions within the medial temporal lobe make different contributions to the processing of stimuli. The anterior medial

temporal lobe, for example, has been linked to the processing of novelty- and familiarity-based information (e.g. Henson et al., 2003), and the ability to recall object-related information (e.g. Staresina et al., 2011), presumably by means of determining familiarity (e.g. Henson et al., 2003). The coordinates of the reported activation peaks are similar (x-, y-, z-coordinates +22, -6, -28 in Henson et al., 2003; x-, y-, z-coordinates +33, -6, -30 in Staresina et al., 2011). These coordinates map along the anterior sulcal segment, the rhinal sulcus, as identified in the present study, which delimits the uncus, suggesting that these activation peaks were in the rhinal cortical areas. By contrast, other functional neuroimaging studies have linked activation peaks in the posterior parahippocampal cortex to the processing of space- and⁄or scene-relevant information (Epstein & Kanwisher, 1998; Köhler et al., 2002; Yue et al., 2007; Staresina et al., 2011). More precisely, the majority of peak coordinates reported (x-, y-, z-coordinates +27, -36, -9 in Staresina et al., 2011) and⁄or visual illustrations provided (right parahippocampal place area: x-, y-, z-coordinates +21, -35, -11 and left parahippocampal place area: x-, y-, z-coordinates -12, -42, -2, see Fig. 1 in Köhler et al., 2002; no report of peak coordinates, see Fig. 2a in Yue et al., 2007) relate well to our present morphological descriptions, as they all lie along the posterior portion of the collateral sulcus proper, just anterior to and bordering the rostralmost portion of the occipital extent of the collateral sulcus. Failure to identify these sulci correctly may lead to confusion of the fusiform gyrus with the posterior parahippocampal gyrus. For instance, in a study examining the effects of cognitive-behavior therapy on the neural substrates of a specific phobia, the parahippocampal gyrus was identified as the site of activation (Paquette et al., 2003), although visual inspection of the sulcal morphology clearly shows the activation peak to lie lateral to the collateral sulcus proper, and therefore implicating the cortex of the fusiform gyrus and not the parahippocampal cortex. The collateral sulcus proper provides a valuable landmark of the posterior parahippocampal cortex that is involved in specific aspects of memory, such as topographical information processing (e.g. the parahippocampal place area;

Epstein et al., 1999), whereas the occipital extent of the collateral sulcus may define cortex related to visual processing. Future studies may focus on linking the local morphology of the occipital extent more precisely to particular pre-striate visual areas (DeYoe et al., 1996; Tootell et al., 1997; Hadjikhani et al., 1998).

2.6 References Ad-Dab’bagh, Y., Lyttelton, O., Muehlboeck, J.-S., Lepage, C., Einarson, D., Mok, K., Ivanov, O., Vincent, R.D., Lerch, J., Fombonne, E. & Evans, A.C. (2006) The CIVET image-processing environment: a fully automated comprehensive pipeline for anatomical neuroimaging research. In Corbetta, M. (Ed.). Proceedings of the 12th Annual Meeting of the Organization for Human Brain Mapping, NeuroImage, Florence.

Amaral, D.G., Insausti, R. & Cowan, W.M. (1987) The entorhinal cortex of the monkey: I. Cytoarchitectonic organization. J. Comp. Neurol., 264, 326–355.

Amiez, C., Kostopoulos, P., Champod, A.-S. & Petrides, M. (2006) Local morphology predicts functional organization of the dorsal premotor region in the human brain. J. Neurosci., 26, 2724–2731.

Bajic, D., Moreira, N.C., Wikstro¨m, J. & Raininko, R. (2012) Asymmetric development of the hippocampal region is common: a fetal MR imaging study. Am. J. Neuroradiol, 33, 513–518.

Brodmann, K. (1925) Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbauses. Barth, Leipzig.

Chi, J.G., Dooling, E.C. & Gilles, F.H. (1977) Gyral development of the human brain. Ann. Neurol., 1, 86–93.

Collins, D.L., Neelin, P., Peters, T.M. & Evans, A.C. (1994) Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J. Comput. Assist. Tomo., 18, 192–205.

DeYoe, E.A., Carman, G.J., Bandettini, P., Glickman, S., Wieser, J., Cox, R., Miller, D. & Neitz, J. (1996) Mapping striate and extrastriate visual areas in human cerebral cortex. Proc. Natl. Acad. Sci. USA, 93, 2382–2386.

Dubois, J., Benders, M., Cachia, A., Lazeyras, F., Ha-Vinh Leuchter, R., Sizonenko, S.V., Borradori-Tolsa, C., Mangin, J.F. & Hu¨ppi, P.S. (2008) Mapping the early cortical folding process in the preterm neuwborn brain. Cereb. Cortex, 18, 1444–1454.

Duvernoy, H. (1999) The Human Brain: Surface, Three-Dimensional Sectional Anatomy and MRI, 2nd Edn. Springer-Verlag, Wien.

Duvernoy, H.M. (2005) The Human Hippocampus: Functional Anatomy, Vascularization and Serial Sections with MRI, 3rd Edn. Springer-Verlag, Berlin.

Eberstaller, O. (1890) Das Stirnhirn. Urban and Schwarzenberg, Wien.

Economo, C. & Koskinas, G.N. (1925) Die Cytoarchitektur der Hirnrinde des erwachsenen Menschen. Springer, Wien.

Epstein, R. & Kanwisher, N. (1998) A cortical representation of the local visual environment. Nature, 392, 598–601.

Epstein, R., Harris, A., Stanley, D. & Kanwisher, N. (1999) The parahippocampal place area: recognition, navigation, or encoding? Neuron, 23, 115–125.

Fox, P.T., Miezin, F.M., Allman, J.M., Van Essen, D.C. & Raichle, M.E. (1987) Retinotopic organization of human visual cortex mapped with positron-emission tomography. J. Neurosci., 7, 913–922.

Garel, C., Chantrel, E., Brisse, H., Elmaleh, M., Luton, D., Oury, J.F., Sebag, G. & Hassan, M. (2001) Fetal cerebral cortex: normal gestational landmarks identified using prenatal MR imaging. Am. J. Neuroradiol., 22, 184–189.

Gloor, P. (1997) The Temporal Lobe and Limbic System. Oxford University Press, New York.

Grabner, G., Janke, A.L., Budge, M.M., Smith, D., Pruessner, J. & Collins, D.L. (2006) Symmetric atlasing and model based segmentation: an application to the hippocampus in older adults. MICCAI, 9, 58–66.

Hadjikhani, N., Liu, A.K., Dale, A.M., Cavanagh, P. & Tootell, R.B.H. (1998) Retinotopy and color sensitivity in human visual cortical area V8. Nat. Neurosci., 1, 235–241.

Hanke, J. (1997) Sulcal pattern of the anterior parahippocampal gyrus in the human adult. Ann. Anat., 179, 335–339.

Haxby, J.V., Grady, C.L., Horwitz, B., Ungerleider, L.G., Mishkin, M., Carson, R.E., Herscovitch, P., Schapiro, M.B. & Rapoport, S.I. (1991) Dissociation of object and spatial visual processing pathways in human extrastriate cortex. Proc. Natl. Acad. Sci. USA, 88, 1621–1625.

Heckers, S., Heinsen, H., Heinsen, Y. & Beckmann, H. (1990) Morphometry of the parahippocampal gyrus in schizophrenics and controls. Some anatomical considerations. J. Neural Transm., 80, 151–155.

Henson, R.N.A., Cansino, S., Herro, J.E., Robb, W.G.K. & Rugg, M.D. (2003) A familiarity signal in human anterior medial temporal cortex? Hippocampus, 13, 301–304.

Iaria, G. & Petrides, M. (2007) Occipital sulci of the human brain: variability and probability maps. J. Comp. Neurol., 501, 243–259.

Insausti, R. & Amaral, D.G. (2004) Hippocampal formation. In Paxinos, G. & Mai, J.K. (Eds), The Human Nervous System, 2nd Edn. Elsevier Academic Press, San Diego, pp. 871–913.

Insausti, R. (1993) Comparative anatomy of the entorhinal cortex and hippocampus in mammals. Hippocampus, 3, 19–26.

Insausti, R., Tunon, T., Sobreviela, T., Insausti, A.M. & Gonzalo, L.M. (1995) The human entorhinal cortex: a cytoarchitectonic analysis. J. Comp. Neurol., 355, 171–198.

Insausti, R., Juottonen, K., Soininen, H., Insausti, A.M., Partanen, K., Vainio, P., Laakso, M.P. & Pitka¨nen, A. (1998) MR volumetric analysis of the human entorhinal, perirhinal, and temporopolar cortices. Am. J. Neuroradiol., 19, 659– 671.

Kim, H., Bernasconi, N., Bernhardt, B., Colliot, O. & Bernasconi, A. (2008) Basal temporal sulcal morphology in healthy controls and patients with temporal lobe epilepsy. Neurology, 70, 2159–2165.

Köhler, S., Crane, J. & Milner, B. (2002) Differential contributions of the parahippocampal place area and the anterior hippocampus to human memory for scenes. Hippocampus, 12, 718–723.

Krimer, L.S., Hyde, T.M., Herman, M.M. & Saunders, R.C. (1997) The entorhinal cortex: an examination of cyto- and myeloarchitectonic organization in humans. Cereb. Cortex, 7, 722–731.

MacDonald, D. (1996) Program for Display and Segmentation of Surfaces and Volumes. McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Quebec, Canada, Available from http://www.bic.mni.mcgill.ca.

Mazziotta, J.C., Toga, A.W., Evans, A., Fox, P.T. & Lancaster, J.L. (1995a) A probabilistic atlas of the human brain: theory and rationale for its development. NeuroImage, 2, 89–101.

Mazziotta, J.C., Toga, A.W., Evans, A., Fox, P.T. & Lancaster, J.L. (1995b) Digital brain atlases. Trends Neurosci., 18, 210–211.

Mishkin, M. (1978) Memory in the monkeys severely impaired by combined but not by separate removal of amygdala and hippocampus. Nature, 273, 297–298.

Novak, K., Czech, T., Prayer, D., Dietrich, W., Seres, W., Lehr, S. & Baumgartner, C. (2002) Individual variations in the sulcal anatomy of the basal temporal lobe and its relevance for epilepsy surgery: an anatomical study performed using magnetic resonance imaging. J. Neurosurg., 96, 464– 473.

Ono, M., Kubik, S. & Abernathey, C.D. (1990) Atlas of the Cerebral Sulci. Thieme, Stuttgart.

Paquette, V., Levesque, J., Mensour, B., Leroux, J.-M., Beaudoin, G., Bourgouin, P. & Beauregard, M. (2003) Change the mind and you change the brain: effects of cognitive-behavioral therapy on the neural correlates of spider phobia. NeuroImage, 18, 401–409.

Petrides, M. (2012) The Human Cerebral Cortex: An MRI Atlas of the Sulci and Gyri in MNI Stereotaxic Space. Academic Press, New York.

Retzius, G. (1896) Das Menschenhirn; Studien in der makroskopischen Morphologie. Norstedt and Soener, Stockholm.

Sarkissov, S.A., Filimonoff, I.N., Kononowa, E.P., Preobraschenskaja, I.S. & Kukuew, L.A. (1955) Atlas of the Cytoarchitectonics of the Human Cerebral Cortex. Meggiz, Moskau.

Scoville, W.B. & Milner, B. (1957) Loss of recent memory after bilateral hippocampal lesions. J. Neurol., Neurosur. Ps., 20, 11–21.

Sereno, M.I., Dale, A.M., Reppas, J.B., Kwong, K.K., Belliveau, J.W., Brady, T.J., Rosen, B.R. & Tootell, R.B. (1995) Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science, 268, 889– 893.

Sled, J.G., Zijdenbos, A.P. & Evans, A.C. (1998) A non-parametric method for automatic correction of intensity non-uniformity in MRI data. IEEE T. Med. Imaging, 17, 87–97.

Smith, E.G. (1904) Studies in the morphology of the human brain. In Egyptians - No.1: The occipital region. (Ed.). Records of the Egyptian Government School of Medicine, 2, 124–173.

Smith, S.M. (2002) Fast robust automated brain extraction. Hum. Brain Mapp., 17, 143–155.

Squire, L.R. & Zola-Morgan, S. (1991) The medial temporal lobe memory system. Science, 253, 1380–1386.

Staresina, B.P., Duncan, K.D. & Davachi, L. (2011) Perirhinal and parahippocampal cortices differentially contribute to later recollection of object- and scene-related event details. J. Neurosci., 31, 8739–8747.

Talairach, J. & Tournoux, P. (1988) Co-Planar Stereotaxic Atlas of the Human Brain. Thieme, New York.

Tootell, R.B.H., Mendola, J.D., Hadjikhani, N.K., Ledden, P.J., Liu, A.K., Reppas, J.B., Sereno, M.I. & Dale, A.M. (1997) Functional analysis of V3A and related areas in human visual cortex. J. Neurosci., 17, 7060-7078.

Van Hoesen, G.W. (1995) Anatomy of the medial temporal lobe. Magn. Reson. Imaging, 13, 1047–1055.

Witter, M.P. & Amaral, D.G. (1991) Entorhinal cortex of the monkey: V. Projections to the dentate gyrus, hippocampus, and subicular complex. J. Comp. Neurol., 307, 437–459.

Yue, X., Vessel, E.A. & Biederman, I. (2007) The neural basis of scene preferences. NeuroReport, 18, 525–529.

2.7 Acknowledgements We thank Asher Mendelson for help with cortex segmentation, Emily Segal for helpful discussions, Callah Boomhauer and Dr. Veronika Zlatkina for help with illustrations, and Dr Christine Tardif for help with the acquisition and processing of the magnetic resonance images on post-mortem data. We also thank Dr. Lana Vasung for her comments on the fetal development of the human brain. The research was supported by the Canadian Institutes of Health Research (CIHR) grant MOP-14620 to M.P. The authors declare that they have no competing financial interests.

2.8 Abbreviations MRI, magnetic resonance imaging.

2.9 Tables

Table 2.9.1 The terms used by different authors to refer to A) the shallow incisure at the rostral tip of the uncus, separating temporopolar from uncal cortex; B) the deep sulcus lateral to the uncus, delineating entorhinal cortex; C) the deep sulcus forming the lateral border of the posterior parahippocampal gyrus (see color- coded lines and letters in Fig. 2.10.1).

Table 2.9.2 Average stereotaxic Y-coordinates and standard deviations (SD), in millimeters in MNI standard space, for the rostral and caudal origins of the rhinal

sulcus and collateral sulcus proper (cos), the surrounding landmarks, the three relationships between the rhinal sulcus and cos (separated into Types I, IIa + b, III), and the 8 patterns describing the occipital extent of the collateral sulcus (see text for details). Cos coordinates are subdivided into: Cos-all, average of rostral origin across all cos’s, including the 16% that show a more anterior origin; Cos- early, referring to only those cos’s (16%) showing a more rostral origin; Cos-late, referring to cos excluding those that show a distinctively more rostral origin. Cos- 1 refers to the first, Cos-2 to the second of the two cos segments (when present). For all other abbreviations, see Abbreviations.

Table 2.9.3 Incidence of collateral sulcal complex characteristics in the left (LH) and right (RH) hemispheres of 40 MR brain volumes: A) the three types of relationship observed between the rhinal sulcus and collateral sulcus proper (cos). Type I: the rhinal sulcus and the cos are separate; Type II: the rhinal sulcus and the cos share a sulcal bed, but are clearly distinguishable; Type IIa, the cos originates out of the lateral bank of the rhinal sulcus, Type IIb, the cos originates out of the medial bank of the rhinal sulcus; Type III: the rhinal sulcus and the cos blend to form a single continuous sulcus. B) The eight relationships between the

cos and occipital extent of the collateral sulcus (cos-o). Pattern 1: only one cos-o is present, separable in-depth from the cos; Pattern 2 through 8: a medial and a lateral cos-o branch exist, which subdivide the cos-o into seven patterns (see text for details). C) The occasional presence of an ‘anterior sulcus’ medial to the rhinal sulcus, and D) the presence of the parahippocampal extension of the collateral sulcus (cos-ph). E) Communication occurrences between the rhinal sulcus (rhs), occipitotemporal sulcus (lots), and cos.

2.10 Figures

Figure 2.10.1 (A) Schematic representation of the medial surface of the brain by Economo & Koskinas (1925) illustrating the dimple, called the temporal incisure (label ‘A’ in red), the rhinal fissure (label ‘B’ in yellow⁄orange), and the

occipitotemporal fissure (collateral fissure) (label ‘C’ in blue). Abbreviations of interest: C, Fissura calcarina; Fus (T4), gyrus fusiformis; g.lg.i., gyrus lingualis inferior; g.lg.s., gyrus lingualis superior; g.rl., gyrus retrolimbicus; g.tl.a., gyrus temporolimbicus anterior; g.tl.p., gyrus temporolimbicus posterior; Hi, gyrus hippocampi; it, incisura temporalis; Is, isthmus; Lg, lingula; ot, fissura occipitotemporalis (f. collateralis); PT, gyrus (temporo-) polaris; rh, fissura rhinalis; Tr, truncus fissurae parietooccipitalis et calcarinae; U, uncus. (B) Schematic representation of the inferomedial surface of the brain by Duvernoy (1999) (reprinted with permission) illustrating the dimple that is referred to as the rhinal sulcus (label ‘A’ in red), the anterior part of the collateral sulcus (label ‘B’ in yellow⁄orange), and the posterior part of the collateral sulcus (label ‘C’ in blue). All colored lines and letters, labels ‘A’ – ‘C’, were added by the present authors for illustration purposes and did not form part of the original figures. Table 2.9.1 lists the various terms used for labels ‘A’, ‘B’, and ‘C’ by different investigators. Abbreviations of interest: 4, anterior calcarine sulcus; 5, collateral sulcus (medial occipitotemporal sulcus); 5`, anterior transverse collateral sulcus; 5``, posterior transverse collateral sulcus; 6, rhinal sulcus; 11, isthmus; 13, piriform lobe; 22, lateral occipitotemporal sulcus; 23, lingual sulcus, when present, it divides the lingual gyrus into a superior and inferior part; 24, calcarine sulcus; T4, fusiform gyrus; T5, parahippocampal gyrus; O4, fourth occipital gyrus, which forms together with the fourth temporal gyrus (T4) the fusiform gyrus, or lateral occipitotemporal gyrus; O5, lingual gyrus, which forms together with the parahippocampal gyrus the medial occipitotemporal gyrus; O3`, O4`, O5`, on the inferior aspect of the occipital pole, the caudal parts of these three occipital gyri merge into a common occipital cortex.

Figure 2.10.2 Schematic representation of the three relationships between the rhinal (label ‘B’ in yellow⁄orange) and collateral sulcus proper (label ‘C’ in blue). In (A), the rhinal and collateral sulcus proper could be separated on the surface and in-depth (Type I); in (B and C), the rhinal and collateral sulcus proper share a

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sulcal bed, but are clearly distinguishable in-depth (Type II), with the cos originating either laterally (B, Type IIa) or medially (C, Type IIb) to the rhinal sulcus, and in (D), the rhinal and collateral sulcus proper are continuous (Type III). Dotted lines between labels ‘B’ and ‘C’ represent the in-depth course of the sulcus [black dotted lines posterior to labels ‘C’ refer to the occipital extension of the collateral sulcal complex (see text)]. Figures 2.10.3–2.10.6 illustrate the in- depth origin of the collateral sulcus proper. Table 2.9.1 lists the nomenclature used for labels ‘B’ and ‘C’ by different authors.

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Figure 2.10.3 Sections of the left hemisphere illustrating Type I of the present study. Coronal sections are shown in (A) (a–d), sagittal sections in (B) (a–c), and horizontal sections in (C) (a–d). (D) is a three-dimensional reconstruction indicating the levels of sections presented in (A–C). A, amygdala; aCalS, anterior calcarine sulcus; cos, collateral sulcus proper; cos-o, occipital extension of the collateral sulcus; cos-o (lateral), cos-o (medial), lateral or medial branch,

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respectively, in the case of two cos-o’s; H, hippocampus; LGN, lateral geniculate nucleus; Limen insulae, frontotemporal junction; lots, occipitotemporal sulcus; LV, lateral ventricle; rhs, rhinal sulcus; sts, superior temporal sulcus; U, uncus.

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Figure 2.10.4 Sections of the right hemisphere illustrating Type IIa of the present study. Coronal sections are shown in (A) (a–d), sagittal sections in (B) (a–c), and horizontal sections in (C) (a–c). (D) is a three-dimensional reconstruction indicating the levels of sections presented in (A–C). A, amygdala; aCalS, anterior calcarine sulcus; bCalS, body of calcarine sulcus; cos, collateral sulcus proper; cos-o, occipital extension of the collateral sulcus; cos-o (lateral), cos-o (medial), lateral or medial branch, respectively, in the case of two cos-o’s; cos-ph,

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parahippocampal extension of the collateral sulcus; H, hippocampus; LGN, lateral geniculate nucleus; lgs, lingual sulcus; Limen insulae, frontotemporal junction; lots, occipitotemporal sulcus; LV, lateral ventricle; rhs, rhinal sulcus; sts, superior temporal sulcus; U, uncus.

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Figure 2.10.5 Sections of the left hemisphere illustrating Type IIb of the present study. Coronal sections are shown in (A) (a–d), sagittal sections in (B) (a–c), and horizontal sections in (C) (a–c). (D) is a three-dimensional reconstruction indicating the levels of sections presented in (A–C). A, amygdala; aCalS, anterior calcarine sulcus; bCalS, body of calcarine sulcus; cos, collateral sulcus proper; cos-1, first (anterior) of two cos segments (if present); cos-2, second (posterior) of two cos segments (if present); cos-o, occipital extension of the collateral sulcus;

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cos-o (lateral), cos-o (medial), lateral or medial branch, respectively, in the case of two cos-o’s; H, hippocampus; LGN, lateral geniculate nucleus; lgs, lingual sulcus; lots, occipitotemporal sulcus; LV, lateral ventricle; rhs, rhinal sulcus; sts, superior temporal sulcus; U, uncus.

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Figure 2.10.6 Sections of the right hemisphere illustrating Type III of the present study. Coronal sections are shown in (A) (a–d), sagittal sections in (B) (a–c), and horizontal sections in (C) (a–c). (D) is a three-dimensional reconstruction indicating the levels of sections presented in (A–C). A, amygdala; aCalS, anterior calcarine sulcus; bCalS, body of calcarine sulcus; cos, collateral sulcus proper; cos-o, occipital extension of the collateral sulcus; cos-o (lateral), cos-o (medial),

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lateral or medial branch, respectively, in the case of two cos-o’s; cos-ph, parahippocampal extension of the collateral sulcus; H, hippocampus; lots, occipitotemporal sulcus; LV, lateral ventricle; sts, superior temporal sulcus.

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Figure 2.10.7 (a–c) Posterior course of the occipital extent of the collateral sulcal complex illustrated in the coronal plane. Panels 1–4 refer to Patterns 1–4, respectively. aCalS, anterior calcarine sulcus; cos, collateral sulcus proper; cos-o, occipital extension of the collateral sulcus; cos-o (lateral), cos-o (medial), lateral or medial branch, respectively, in the case of two cos-o’s; H, hippocampus; lots, occipitotemporal sulcus.

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Figure 2.10.8 (a-c) Posterior course of the occipital extent of the collateral sulcal complex illustrated in the coronal plane. Panels 5–8 refer to Patterns 5–8, respectively. aCalS, anterior calcarine sulcus; cos, collateral sulcus proper; cos-o, occipital extension of the collateral sulcus; cos-o (lateral), cos-o (medial), lateral or medial branch, respectively, in the case of two cos-o’s; H, hippocampus; lots, occipitotemporal sulcus.

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Figure 2.10.9 Photographs of post-mortem brains illustrating the relationship between the rhinal and collateral sulcus proper as viewed from the surface. The upper left panel (A) illustrates the rhinal and collateral sulcus proper as separate on the surface and in-depth (Type I). Surface photographs (B and C) illustrate the rhinal and collateral sulcus proper sharing a sulcal bed, while being clearly distinguishable in-depth (Type II), with the cos originating laterally (B, Type IIa) or medially (C, Type IIb) to the rhinal sulcus. Figures 2.10.3–2.10.5 illustrate the in-depth nature of these relationships as observed in magnetic resonance images.

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Coronal sections (a–c) illustrate the in-depth course of the sulci within the post- mortem brains shown in A–C. The levels of the sections are indicated by the corresponding letters in the opaque boxes. A, amygdala; cos, collateral sulcus proper; cos-1, first (anterior) of two cos segments (if present); cos-2, second (posterior) of two cos segments (if present); ERC, entorhinal cortex; FG, fusiform gyrus; H, hippocampus; it, temporal incisure; lots, occipitotemporal sulcus; PHG, parahippocampal gyrus; rhs, rhinal sulcus.

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Chapter Three 3. Three-dimensional probability maps of the rhinal and the collateral sulci in the human brain

Huntgeburth S.C. and Petrides M. (2015). Three-Dimensional Probability Maps of the Rhinal and the Collateral Sulci in the Human Brain. The manuscript has been submitted and is currently under review (at the “revision submission” stage).

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3.1 Prelude The first anatomical study (Chapter 2), the morphology of the collateral sulcal complex, investigated systematically the morphological patterns of the sulcal complex that laterally delimits the parahippocampal gyrus. The results demonstrated that the collateral sulcal complex is not one long, continuous sulcus, but is composed of several segments. The anterior segment which runs lateral to the location of the entorhinal cortex is referred to as the rhinal sulcus and can be distinguished reliably from the sulcal segment that lies posterior to it and is referred to as the collateral sulcus proper. The collateral sulcus proper can posteriorly be differentiated from another sulcal segment, the occipital extension of the collateral sulcus. The level at which these two posterior sulcal segments are separated appears to correspond with the level of the caudal end of the parahippocampal gyrus and the anterior border of the lingual gyrus, thereby being a potential candidate for a morphological landmark distinguishing between cortex of the medial temporal lobe, involved in mnemonic information processing, and cortex of the occipital lobe, involved in visual information processing. The first study (Chapter 2) is a qualitative and quantitative description of the morphology of the sulci that make up the collateral sulcal complex. The aim of the second anatomical study (Chapter 3) is to evaluate quantitatively the variability of these sulci in the Montreal Neurological Institute standard stereotaxic space in the form of probability maps which may be used by the neuroscientific community as a reference frame for accurately identifying activation peaks from functional neuroimaging studies along the parahippocampal gyrus.

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3.2 Abstract The sulcal segments of the collateral sulcal complex on the medial part of the temporal lobe delineate the parahippocampal gyrus involved in memory processing from the laterally adjacent fusiform gyrus. The rhinal sulcus delineates the entorhinal cortex on the anterior portion of the parahippocampal gyrus. Posterior to the rhinal sulcus lies the collateral sulcus proper which delineates the parahippocampal cortex that occupies the posterior part of the parahippocampal gyrus. A small sulcus, the parahippocampal extension of the collateral sulcus, runs transversely within the parahippocampal gyrus. The rhinal sulcus, the collateral sulcus proper, and the parahippocampal extension of the collateral sulcus were identified on magnetic resonance images of 40 healthy human brains and probability maps were created to provide quantification of the location variability within standard stereotaxic space. These probability maps can act as a reference frame for the accurate identification of key components of the parahippocampal region and aid the interpretation of structural and functional changes obtained in neuroimaging studies.

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3.3 Introduction The cortical areas of the parahippocampal gyrus on the medial part of the temporal lobe are critical for memory (Milner, 1968; Milner et al., 1997; Scoville and Milner, 1957; Zola-Morgan et al., 1989). The entorhinal cortex, which is surrounded by the perirhinal cortex, lies on the anterior part of the parahippocampal gyrus. It continues into the medial bank of the rhinal sulcus and area 35 of the perirhinal cortex occupies the fundus and lateral bank of the rhinal sulcus (Amaral et al., 1987; Insausti and Amaral, 2004; Insausti et al., 1995). The entorhinal cortex receives input from various cortical areas, including the perirhinal and parahippocampal cortex, and then provides critical input to the hippocampus for memory processing (Insausti et al., 1987; Van Hoesen, 1982; Van Hoesen et al., 1972). Thus, it is a critical gateway of information transfer to the hippocampal system, but it also plays its own role in memory processing (Canto et al., 2008; Insausti et al., 1987; Mishkin et al., 1997; Squire and Zola- Morgan, 1988; Squire and Zola-Morgan, 1991). In the modern literature, the term “parahippocampal cortex” is used to refer to the cortex that lines the parahippocampal gyrus posterior to the entorhinal cortex. It receives major inputs from several association cortical areas in the frontal, parietal, and temporal lobes (Squire and Zola-Morgan, 1988; Squire and Zola-Morgan, 1991; Suzuki and Amaral, 1994; Van Hoesen, 1982; Van Hoesen et al., 1972) and is involved in certain aspects of mnemonic information processing (Suzuki et al., 1993; Zola- Morgan et al., 1989; Zola-Morgan et al., 1994), such as the processing of spatial information (Epstein and Kanwisher, 1998; Malkova and Mishkin, 2003). Morphologically, the collateral sulcal complex, a collection of deep sulci, separates the parahippocampal gyrus from adjacent temporal structures. It includes the rhinal sulcus, the collateral sulcus proper, and the parahippocampal extension of the collateral sulcus, which are important anatomical landmarks for the entorhinal, perirhinal, and parahippocampal cortex (Huntgeburth and Petrides, 2012). Functional neuroimaging studies record brain activity related to cognitive processing and attempt to relate such activity to specific brain regions (Aminoff et al., 2007; Epstein and Kanwisher, 1998; Köhler et al., 2002; Staresina et al.,

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2011). Correct interpretation of the location of functional activation relies on accurate description of the local morphology and its variability quantified in standard stereotaxic space in the form of probability maps. Such maps have been established for various sulci and parts of gyri, including the pars opercularis (Tomaiuolo et al., 1999), the precentral sulcal complex (Germann et al., 2005), the orbitofrontal sulci (Chiavaras et al., 2001), the three caudal branches of the superior temporal sulcus (Segal and Petrides, 2012), the cingulate and paracingulate sulci (Paus et al., 1996), and the occipital sulci (Iaria et al., 2008). The aim of the present investigation was to provide quantification of the spatial variability of the rhinal sulcus, the collateral sulcus proper, and the parahippocampal extension of the collateral sulcus, three sulci that are critical for the correct identification of functional activations related to memory in the medial temporal region. The variability was quantified in the form of probability maps in the standard stereotaxic space of the Montreal Neurological Institute (MNI) which is the space most widely used in structural and functional neuroimaging studies. The probabilistic quantification provided here should aid accurate identification of the locus of structural and functional changes observed in the medial temporal region in neuroimaging studies.

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3.4 Materials and methods Subjects We examined the sulcal patterns of the collateral sulcal complex using the magnetic resonance images (MRIs) of both hemispheres of 40 human brains that were acquired as part of the International Consortium for Brain Mapping project (ICBM) (Mazziotta et al., 2001; Mazziotta et al., 1995a; Mazziotta et al., 1995b) available at the Laboratory of Neuro Imaging at the University of Southern California (http://www.loni.usc.edu/ICBM). The 40 brains comprised 17 females, 23 males and the mean age was 25.0 ± 5.0 years. All participants were healthy, right handed, and had no history of neurological and⁄or psychiatric disorders, and gave written informed consent. The study conformed to the Code of Ethics of the World Medical Association (Declaration of Helsinki) as printed in the British Medical Journal (18 July 1964). Approval was given by the Research Ethics Board of the Montreal Neurological Institute (MNI) and Hospital.

Magnetic resonance imaging The MRI scans were acquired using a 1.5 Tesla Philips Gyroscan scanner [repetition time (Tr), 18 ms; echo delay time (Te), 10 ms; flip angle, 30] with a fast-field echo three-dimensional sequence in the sagittal plane. A total of 160 contiguous high-resolution T1-weighted magnetic resonance images (1 mm3) were acquired. All images were registered with a 12-parameter affine transformation (Collins et al., 1994; Grabner et al., 2006) to the ICBM 152 non- linear sixth generation symmetric target (Grabner et al., 2006) using the MNI CIVET pipeline (Ad-Dab'bagh et al., 2006). The ICBM 152 target is the Montreal Neurological Institute (MNI) standard stereotaxic space which evolved from the Talairach space (Talairach and Tournoux, 1988) and is the stereotaxic space widely used by the structural and functional neuroimaging community. Prior to this normalization, the brains of all images were extracted using a mask (Smith, 2002) and were corrected for radiofrequency non-uniformities (Sled et al., 1998).

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Probabilistic mapping The boundaries of the rhinal sulcus, the collateral sulcus proper, and the parahippocampal extension of the collateral sulcus were identified according to the criteria established in a previous study on the morphology of the sulci of the collateral sulcal complex (Huntgeburth and Petrides, 2012). The sulcal midline (i.e. the space between the two banks) was color coded on consecutive images within the individual brain using a virtual pen of 1 millimeter per voxel size. All the above sulci were marked, from the level of the limen insulae anteriorly to the level of the body of the calcarine sulcus, posteriorly, where the occipital extent of the collateral sulcus commences. These sulcal markings were then used to create probabilistic maps that express the spatial variability of the sulci in the MNI stereotaxic space. The sulcal midline markings were resampled to the ICBM 152 symmetrical non-linear average brain of the MNI stereotaxic space (Grabner et al., 2006). A full-width at half maximum filter blurring kernel of 3 millimeters was applied to increase the overlap between markings, and an average of the sulcal color coded markings was subsequently established to create the probability maps separately for each hemisphere. Note that, although the course of the sulcus starts, rostrally, from the level of the limen insulae in each individual brain, the blurring kernel applied in order to create the probability maps tends to show the origin of this sulcus a few millimeters anterior to the limen insulae. The probability maps quantify the amount of overlap of the voxels of the sulcal midline markings across all subjects, ranging from 0 to 100%. In each figure, the color scales indicate the proportion of brains contributing to the probability map at each voxel in MNI space. All probabilistic measures are superimposed onto the intensity-averaged target image (ICBM 152; Grabner et al., 2006) and are illustrated by providing the x, y, and z coordinates in MNI space. The x coordinate refers to the mediolateral axis (i.e. sagittal plane), the y coordinate represents the rostrocaudal axis (i.e. coronal plane), and the z coordinate reflects the dorsoventral axis (i.e. horizontal/axial plane). The skull has been extracted from each image displayed in Figures 3.10.1 to 3.10.6 to enhance the illustrations. The graphics program Adobe Illustrator CS5.1 was used to create the artwork.

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Furthermore, we combined the sulcal probability maps of the location of the rhinal sulcus and the collateral sulcus proper as established in the present study with the probabilistic cytoarchitectonic map of the entorhinal cortex (ERC) by Amunts et al. (2005) as distributed within the software package 'SPM Anatomy Toolbox' (version 2.1, release date June 29, 2015; http://www.fz- juelich.de/inm/inm-1/EN/Forschung/_docs/SPMAnatomyToolbox; Eickhoff et al., 2005; 2006; 2007). The probabilistic cytoarchitectonic map of the entorhinal cortex, which is based on 10 post-mortem human brains, is registered to a version of the MNI space with additional transformations to align the reference space with the AC-PC line, where AC refers to the anterior commissure and PC to the posterior commissure. It was therefore transformed to the ICBM 152 non-linear sixth generation symmetric target for MNI space to allow direct comparison with our sulcal probability maps. Figures 3.10.7 and 3.10.8 illustrate the probability maps of the rhinal sulcus (across rhs-cos relationship types), the collateral sulcus proper (excluding the 16.67% of cases with a more anterior origin; across rhs-cos relationship types, referred to as ‘cos-late’), and the cytoarchitectonic map of the entorhinal cortex by Amunts et al. (2005) in the same stereotaxic space.

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3.5 Results The three sulci examined were the rhinal sulcus (rhs) and the collateral sulcus proper (cos), which mark the lateral border of the parahippocampal gyrus, and the parahippocampal extension of the collateral sulcus (cos-ph) (Huntgeburth and Petrides, 2012). All 80 hemispheres were included in the generation of the probability map for the parahippocampal extension of the collateral sulcus. For the computation of the probability maps of the rhinal and collateral sulci, two right hemispheres were excluded as they expressed continuity between the rhinal and collateral sulci on the surface of the brain as well as in the sulcal depth. This relationship between the rhinal sulcus and the collateral sulcus proper (i.e. rhs-cos relationship) is referred to as Type III rhs-cos relationship pattern and has been observed to occur only occasionally, on average in 2.5 percent of cases (Huntgeburth and Petrides, 2012). In all other 78 hemispheres, the end of the rhinal sulcus and the beginning of the collateral sulcus proper could be clearly established. The rhinal sulcus and the collateral sulcus proper could be separated clearly from both the surface and the depth (i.e. Type I rhs-cos relationship pattern) or only in the depth of the sulci (i.e. Type II rhs-cos relationship pattern), with the collateral sulcus proper originating either from the lateral bank (i.e. Type IIa rhs-cos relationship pattern) or the medial bank (i.e. Type IIb rhs-cos relationship pattern) of the rhinal sulcus (see Huntgeburth and Petrides, 2012). The probability maps for the rhinal sulcus, the collateral sulcus proper, and the parahippocampal extension of the collateral sulcus are illustrated in Figures 3.10.1 to 3.10.6. Coronal sections show the progression of the sulci with coordinates on the sides of the images referring to the horizontal/axial (z) and sagittal (x) planes. The probability maps shown in Figure 3.10.1 do not separate the sulcus of interest according to the different relationship types (Type I, IIa, and IIb) that have been observed between the rhinal and collateral sulci. Figures 3.10.2 and 3.10.3 show the probability maps for the different relationships between the rhinal sulcus and the collateral sulcus proper, i.e. Types I, IIa, and IIb. This was necessary because the rostral and caudal origins of the collateral sulcus proper may vary in their location depending on whether they originate

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from the medial or the lateral banks of the rhinal sulcus. In a small proportion of hemispheres, the collateral sulcus proper originates early at the level of the amygdala. Such ‘early’ occurrences of the collateral sulcus proper (cos-early) were present in 16.67% of the cases (13 of 78 hemispheres), i.e. in 10% of left (4 of 40) and 23.68% of right (9 of 38) hemispheres (Huntgeburth and Petrides, 2012). The probability map for the collateral sulcus proper with such an anterior origin is presented in Figure 3.10.4. Figure 3.10.5 illustrates the variability in location of the anterior and posterior segments of the collateral sulcus proper, when such separation is present. Finally, Figure 3.10.6 shows the probability map for the parahippocampal extension of the collateral sulcus. The color markings that represent the probability values in all of the maps (Figs. 3.10.1 to 3.10.6) are on a continuum ranging from 0 to 100%. Figures 3.10.7 and 3.10.8 illustrate the probability maps of the rhinal sulcus and collateral sulcus proper in comparison with the cytoarchitectonic probability map of the entorhinal cortex by Amunts and colleagues (2005). All figures show the probabilistic maps of the location variability of the different sulci in a series of coronal sections (y coordinate), with the x and z coordinates of the sections indicated on the sides of the images. All images are superimposed on the average brain of the Montreal Neurological Institute (ICBM 152) and coordinates are within the MNI standard stereotaxic space.

Rhinal sulcus The probability maps of the rhinal sulcus (Figs. 3.10.1A and 3.10.2) were based on 40 left and 38 right hemispheres. Figure 3.10.1A presents the probability map of the rhinal sulcus across the Type I, IIa, and IIb rhs-cos relationships. The first panel (panel a) in Figure 3.10.1A illustrates approximately a 10-20% margin of overlap between the voxel markings of the rhinal sulcus at a y coordinate of +7 for the right and left hemispheres (panel a, Fig. 3.10.1A), followed by a 25-30% overlap commencing at a y coordinate of +5 in the left and right hemispheres (panel b, Fig. 3.10.1A). A 40-65% overlap can be seen at a y = +2 (panel c, Fig. 3.10.1A) and an overlap in the location of the rhinal sulcus in both hemispheres

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between 65 and 100% (panels d-f, Fig. 3.10.1A) is present between y = 0 all the way to y = -17. A subsequent reduction in the overlap to 40-65% is illustrated between the coordinates y = -18 and y = -20 (panel g, Fig. 3.10.1A), followed by a further decrease to approximately 25-30% overlap at y = -21 (panel h, Fig. 3.10.1A), and a drop to 0% in the right, and 0-20% in the left, hemisphere at y = - 26, marking the caudal limit of the rhinal sulcus (panel i, Fig. 3.10.1A). Figure 3.10.2 (A-C) provides the probability maps for the rhinal sulcus separated according to the rhs-cos relationships identified in our previous study (Huntgeburth and Petrides, 2012), i.e. according to Type I (Fig. 3.10.2A), Type IIa (Fig. 3.10.2B), and Type IIb (Fig. 3.10.2C). The Type I relationship between the rhinal and collateral sulcus proper was observed in 24 out of 40 (60%) left and 27 out of 40 (67.5%) right hemispheres (Fig. 3.10.2A). The probability for Type I (Fig. 3.10.2A) demonstrates similar rostral and caudal origins of the rhinal sulcus and similar overlap as seen in the more general probability map of the rhinal sulcus in Figure 3.10.1A. The Type IIa rhs-cos relationship was observed in 2 out of 40 right hemispheres (5%) only (Fig. 3.10.2B). The Type IIb rhs-cos relationship was seen in 16 of 40 (40%) of left and 9 of 40 (22.5%) right hemispheres (Fig. 3.10.2C). The probability map of the Type IIa pattern commences at y = +9 (panel a, Fig. 3.10.2B), that is approximately at the same level as the Type I pattern (y = +10, panel a, Fig. 3.10.2A), whereas the Type IIb pattern (panel a, Fig. 3.10.2C) presents a rostral limit further anterior at y = + 16. Furthermore, the caudal limit of the probability map of the rhinal sulcus Type IIa lies more anterior (y = -16, panel l, Fig. 3.10.2B), compared to the caudal limits observed in Type I (y = -25, panel l, Fig. 3.10.2A) and Type IIb (y = -30, panel l, Fig. 3.10.2C).

Collateral sulcus proper The probability maps of the collateral sulcus proper were based on 40 left and 38 right hemispheres. Figure 3.10.1B presents the probability map for the collateral sulcus proper across Types I, IIa, and IIb rhs-cos relationships. Panel a of Figure 3.10.1B shows the rostral limit of the collateral sulcus proper represented by a

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small degree of overlap (approximately a 0-15%) in the sulcal labels between hemispheres at y = -10 for the right and left hemispheres (panel a, Fig. 3.10.1B), followed by a 20-35% overlap commencing at y = -18 in the left and right hemispheres (panel b, Fig. 3.10.1B). A 55-65% overlap starts at y = -24 (panel c, Fig. 3.10.1B) and an overlap in sulcal labels in both hemispheres of 100% (panels d-g, Fig. 3.10.1B) is present between y = -28 and y = -38, with a reduction to approximately 65% in the right hemisphere at y = -41 (panel h, Fig. 3.10.1B). A reduction to 65-70% overlap is seen at y = -43 in the left hemisphere, and to 20- 30% in the right hemisphere (panel i, Fig. 3.10.1B). At y = -45 (panel j, Fig. 3.10.1B) an overlap can be observed of 20-35% in the left, and of 0-20% in the right hemisphere, with the caudal end of the collateral sulcus proper marked at around y = -49 (panel k, Fig. 3.10.1B). The probabilistic maps of the variability in location of the collateral sulcus proper are shown separately in Figure 3.10.3 for the Type I (Fig. 3.10.3A) and Type IIb (Fig. 3.10.3B) rhs-cos relationship patterns. Images here are generated across collateral sulcus proper markings excluding those collateral sulci that form part of the 16.67% of observations in which the collateral sulcus proper originates at the level of the amygdala (see ‘cos-early’ below) (Huntgeburth and Petrides, 2012). The probability map of the collateral sulcus proper, for Type I rhs-cos relationship, is based on 21 left and 22 right hemispheres. The collateral sulcus proper has a probability of equal or greater than 45% overlap in the right hemisphere starting at y = -19 (panel c, Fig. 3.10.3A) and ending at y= -44 (panel l, Fig. 3.10.3A), whereas in the left hemisphere such a probability of equal or greater than 45% in overlap is observed starting at y = -25 (panel e, Fig. 3.10.3A) and ending around between y = -45 and y = -46. The probability map for the collateral sulcus proper, illustrating the Type IIb rhs-cos relationship, is computed over 15 left and 7 right hemispheres (Fig. 3.10.3B). The collateral sulcus proper exhibits a probability of equal or greater than 45% overlap in the right hemisphere starting at y = -28 (panel f, Fig. 3.10.3B) and ending at y = -42 (panel l, Fig. 3.10.3B), whereas in the left hemisphere, such a probability in overlap is observed between y = -21 (panel c, Fig. 3.10.3B) and y = -45.

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In the 16.67% of cases in which the collateral sulcus proper was observed to originate early at the level of the amygdala (‘cos-early’, Huntgeburth and Petrides, 2012), the collateral sulcus proper has a probability of equal or greater than 65% overlap in the left hemisphere between y = -8 (panel e, 3.10.Fig. 4) and y = -39 (panel n, 3.10.Fig. 4) and in the right hemisphere between y = -13 (panel h, Fig. 3.10.4) and y = -40 (panel o, Fig. 3.10.4).

Segments of the collateral sulcus proper The collateral sulcus proper appears either as one continuous sulcus or as two segments (i.e. an anterior and a posterior segment). In 20 out of 40 left (i.e. 50% of cases), and in 19 out of 38 (i.e. 50% of cases) right hemispheres, the collateral sulcus proper was subdivided into two such segments (Huntgeburth and Petrides, 2012). All 20 left and 19 right hemispheres were included in the generation of the probability maps (Fig. 3.10.5). The generation of the probability maps excluded one right hemisphere as the rhinal and collateral sulcus proper were not separable from the surface and in depth (i.e. illustration of a Type III rhs-cos relationship). When the collateral sulcus proper can be subdivided into two sulcal segments, the anterior segment is referred to as cos-1 and the posterior segment is referred to as cos-2. Figure 3.10.5 shows the probabilistic maps of the anterior (cos-1; Fig. 3.10.5A) and posterior (cos-2; Fig. 3.10.5B) segments of the collateral sulcus proper. For the anterior segment of the collateral sulcus proper (cos-1), a probability of equal or greater than 65% can be observed between y = -17 and y = -33 for the right hemisphere (panels d-j, Fig. 3.10.5A) and between y = -19 and y = -35 for the left hemisphere (panels e-l, Fig. 3.10.5A). For the posterior segment of the collateral sulcus proper (cos-2), this level of probability (i.e. 65%) occurs between y = -35 and y = -41 for the right hemisphere (panels d-h, Fig. 3.10.5B) and between y = -35 and y = -44 (panels d-k, Fig. 3.10.5B).

Parahippocampal extension of the collateral sulcus The parahippocampal extension of the collateral sulcus (cos-ph) was observed in 75% of cases in the left (30 of 40 hemispheres) and 65% of cases in the right

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hemisphere (26 of 40 hemispheres). These hemispheres form the basis of the probabilistic map of the variability for this sulcus (Fig. 3.10.6). In the right hemisphere, the parahippocampal extension of the collateral sulcus shows a probability of equal or greater than 65% between y = -33 and y = -41 (panels d-k, Fig. 3.10.6) and in the left hemisphere, this probability is between y = -36 and y = -43 (panels g-l, Fig. 3.10.6).

Sulcal probability in relation to cytoarchitectonic probability Figures 3.10.7 and 3.10.8 illustrate the relation of the probability maps of the rhinal sulcus and the collateral sulcus proper and the probability map of the location of the entorhinal cortex (as defined by Amunts et al., 2005). Inspection of the figures demonstrates that the entorhinal cortex lies medial to the rhinal sulcus. Figures 3.10.7 and 3.10.8 show that the entorhinal cortex is bound by the entire rostrocaudal length of the rhinal sulcus (panels a-f, Fig. 3.10.7, and Fig. 3.10.8). Figure 3.10.8 shows the sagittal plane that allows an appreciation of the fact that the entorhinal cortex lies next to the entire rostrocaudal extent of the rhinal sulcus and continues, on average, for a short distance next to the most anterior part of the collateral sulcus proper (also observed in panels g-h of Fig. 3.10.7). This overlap may partly reflect the fact that the caudal end of the rhinal sulcus and the rostral end of the collateral sulcus proper overlap in a number of cases (e.g. Type II rhs- cos relationship patterns, Huntgeburth and Petrides, 2012) and also variance in the cytoarchitectonic probability map due to the relatively low number of cases (i.e. 10 post-mortem brains), as well as some variance due to the transformation necessary to place the sulcal and cytoarchitectonic probability maps into the same stereotaxic space for comparison.

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3.6 Discussion The parahippocampal gyrus comprises distinct regions, each making its own contribution to memory processing (Aminoff et al., 2007; Bachevalier and Nemanic, 2008; Bohbot and Corkin, 2007; Köhler et al., 2002; Meunier et al., 1993; Staresina et al., 2011). The lateral border of the parahippocampal gyrus consists of a series of sulci that constitute the collateral sulcal complex. An anterior sulcus, the rhinal sulcus, delineates laterally the entorhinal cortex (Gloor, 1997; Huntgeburth and Petrides, 2012; Petrides, unpublished observations) and, further posteriorly, the collateral sulcus proper, defines the lateral border of the parahippocampal gyrus from the level of the body of the hippocampus to the lingual gyrus of the occipital lobe (Brodmann, 1909; Economo and Koskinas, 1925; Gloor, 1997; Hanke, 1997; Huntgeburth and Petrides, 2012; Kim et al., 2008; Novak et al., 2002; Ono et al., 1990; Petrides, 2012; Retzius, 1896; Smith, 1904). The collateral sulcus has been divided, based on its morphology, into the collateral sulcus proper and the occipital extension of the collateral sulcus, with the collateral sulcus proper terminating at the level of the splenium when viewed in the coronal plane, and the occipital extent of the collateral sulcus running within the lingual gyrus, parallel to the calcarine sulcus (Huntgeburth and Petrides, 2012). We had previously identified consistent patterns of the various sulci that constitute the collateral sulcal complex and which delimit the lateral border of the parahippocampal gyrus (see Fig. 2.10.2 in Huntgeburth and Petrides, 2012). The present study provides a quantitative measure of the variability of these sulci, i.e. the rhinal sulcus, the collateral sulcus proper, and the parahippocampal extension of the collateral sulcus, in the form of probability maps in the MNI standard stereotaxic space.

Rhinal sulcus In all mammals, including primates, the rhinal sulcus is an important landmark of the location of the entorhinal cortex (Brodmann, 1909). For instance, in the macaque monkey, the rhinal sulcus has been shown to form the lateral border of

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the entorhinal cortex (Amaral et al., 1987; Brodmann, 1909; Insausti, 1993; Van Hoesen and Pandya, 1975; Van Hoesen et al., 1972). In the human brain, the terminology for the sulcus that lies lateral to the entorhinal cortex has led to confusion. One group of investigators has referred to the entire sulcus that lies lateral to the entorhinal cortex, as the rhinal sulcus (Brodmann, 1909; Economo and Koskinas, 1925; Gloor, 1997; Hanke, 1997; Huntgeburth and Petrides, 2012; Kim et al., 2008; Novak et al., 2002; Ono et al., 1990; Petrides, 2012; Retzius, 1896), but another group has restricted the term rhinal sulcus to a small sulcus in the most anterior part of the parahippocampal gyrus that, in this case, only delineates the most anterior part of the entorhinal cortex (Duvernoy, 1999; Insausti and Amaral, 2004; Insausti et al., 1998; Insausti et al., 1995; Augustinack et al., 2013; Fischl et al., 2009). The latter group of investigators has considered the sulcus that runs along the lateral border of the entorhinal cortex as an anterior extension of the collateral sulcus. Regardless of whether one refers to the sulcus that defines the lateral border of the entorhinal cortex as the rhinal sulcus or an anterior part of the collateral sulcus, we have shown that this sulcus is distinct from the collateral sulcus proper which lies posterior to the entorhinal cortex and provides the lateral boundary of the posterior parahippocampal gyrus (Huntgeburth and Petrides, 2012). We were able to separate this anterior sulcus that runs along the anterior part of the parahippocampal gyrus and borders the entorhinal cortex from the one that runs along the posterior part of the parahippocampal gyrus in 97.5% of the cases (Huntgeburth and Petrides, 2012). In agreement with the suggestion by Gloor (1997) and many other classical and recent investigators (Brodmann, 1909; Economo and Koskinas, 1925; Gloor, 1997; Hanke, 1997; Huntgeburth and Petrides, 2012; Kim et al., 2008; Novak et al., 2002; Ono et al., 1990; Petrides, 2012; Retzius, 1896), we refer to this sulcus that runs along the anterior part of the parahippocampal gyrus and defines the lateral border of the entorhinal cortex as the rhinal sulcus to be consistent with the data available in all other primates. We label the sulcus that marks the lateral border of the posterior part of the parahippocampal gyrus (i.e. the parahippocampal cortex) as the collateral sulcus proper.

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In the majority of cases (63.75%), the rhinal sulcus and collateral sulcus proper form separate sulcal entities visible on the cortical surface and in the sulcal depth (i.e. Type I rhs-cos relationship), but in about a third of the cases (33.75%) the collateral sulcus proper develops in the sulcal depth out of the lateral or medial bank of the rhinal sulcus (i.e. Type IIa and Type IIb rhs-cos relationship; see Figs. 2.10.4, 2.10.5, 2.10.9B and 2.10.9C in Huntgeburth and Petrides, 2012). In the latter cases (i.e. Type II), inspection from the surface of the brain gives the false impression that these two distinct sulci are continuous and easily leads to the labelling of the rhinal sulcus as an anterior part of the collateral sulcus. It is thus imperative to examine carefully the in-depth anterior origin of the collateral sulcus proper and the end of the rhinal sulcus in order to relate the entorhinal cortex to the appropriate one of these two distinct sulci. In conclusion, regardless of whether the sulcus that runs along the antero-posterior extent of the entorhinal cortex is labeled as the rhinal sulcus (for consistency with all other primate species as argued by Gloor (1997, p. 329)) or as an “anterior collateral sulcus”, the important fact is that this sulcus is distinct from the collateral sulcus proper which marks the extensive border of the posterior parahippocampal gyrus, posterior to the entorhinal cortex. As can be seen in Figures 3.10.7 and 3.10.8, the entorhinal cortex lies consistently medial to the entire antero-posterior extent of the rhinal sulcus as defined here (panels a-f, Fig. 3.10.7) and continues in the probability space for a short distance posterior to the most anterior end of the collateral sulcus proper (panels g-h, Fig. 3.10.7 and Fig. 3.10.8). It is important to note here that, in about one third of the brains, the anterior end of the collateral sulcus proper and the posterior end of the rhinal sulcus overlap (Type II rhs-cos relationship). The distinction between the rhinal sulcus (“anterior collateral sulcus”) and the collateral sulcus proper is not a mere matter of nomenclature. It is an important distinction because the anterior sulcus marks the entorhinal cortex (as in all other mammals) and the posterior sulcus marks the posterior extent of the parahippocampal gyrus where the parahippocampal cortex lies. Given that the entorhinal cortex and the parahippocampal cortex are distinct parts of the

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parahippocampal gyrus in terms of their cytoarchitectonic organization (Economo and Koskinas, 1925) and function (Aminoff et al., 2007; Köhler et al., 2002; Litman et al., 2009), the ability to identify these two distinct sulci is of immense importance. The probability maps presented here provide the variability of the various segments that mark the boundary of the parahippocampal gyrus and may be used to identify with greater accuracy the locus of activation peaks along the parahippocampal gyrus. As such, it is assumed that activation peaks falling medial to the rhinal sulcus (as defined here) are located in the entorhinal cortex, whereas peaks falling lateral to the rhinal sulcus may reflect activation of the temporal pole or the adjacent fusiform gyrus. Similarly, activation peaks medial to the collateral sulcus proper reflect activation of the parahippocampal cortex and activation lateral to the collateral sulcus proper fall in the fusiform gyrus. The present probability map of the rhinal sulcus (which one could refer to as the “anterior collateral sulcus” but, importantly, not as an anterior part of the collateral sulcus proper; see Fig. 3.10.1A and Fig. 3.10.2A-C) provides quantitative information on the inter-subject variability of this sulcus in standard stereotaxic space to aid accurate identification of the location of functional activation peaks in the entorhinal cortex. Table 3.9.1 provides a list of functional activation peaks related to object stimuli that have been reported along the anterior part of the parahippocampal gyrus of the human brain (i.e. entorhinal and perirhinal cortex) in functional magnetic resonance imaging (fMRI) studies, together with the location of these activation peaks as defined by using the present probability maps. These activations can be shown to fall within one of two adjacent regions (e.g. entorhinal and perirhinal cortex, or entorhinal and parahippocampal cortex). Note that in cases where the activity lies at a y coordinate of approximately -20, it may be difficult to dissociate entorhinal/perirhinal cortex from parahippocampal cortex activation, as the caudal limit of the rhinal sulcus has been identified at an average y coordinate of -21.4 (standard deviation 4.63; Huntgeburth and Petrides, 2012), a few millimeters anterior to the posterior boundary of the entorhinal cortex (Insausti et al., 1995).

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In such cases, examination of activity in individual brains may lead to clearer identification of the location of the activity. Furthermore, the present probability maps can be used to segment the parahippocampal gyrus to examine differential functional contributions of its various parts. For instance, the present findings might have been useful to investigations such as the one by Staresina and colleagues (2011) that attempted to examine the functional contribution of the various parts of the parahippocampal gyrus. In that study, the parahippocampal gyrus was divided into three parts of equal distance, with no reference to local morphology, but the subdivisions could have been made on the basis of morphological information that defines reasonably well the entorhinal cortex, the parahippocampal cortex, and the occipital lingual cortex further posteriorly. The present probability maps can aid future investigations of the parahippocampal region in identifying sulcal segments, such as the rhinal sulcus and the collateral sulcus proper, which could provide anatomically reasonable subdivisions of this region (Insausti et al., 1998; Insausti et al., 1995; Krimer et al., 1997; Vogt et al., 2001).

Collateral sulcus proper Although the parahippocampal cortex has often been referred to as a single functional region caudal to the entorhinal and perirhinal cortex (Reber et al., 2002), it can, functionally, be further subdivided (Aminoff et al., 2007; Pihlajamaki et al., 2004; Staresina et al., 2011). One reason for the idea that the parahippocampal cortex may consist of various functional subregions is the presence of neurons that differ in their receptive field sizes along the rostrocaudal axis of the parahippocampal cortex in the non-human primate, suggesting that this region may not be functionally homogeneous (Sato and Nakamura, 2003). Morphologically, the parahippocampal cortex is delimited laterally by the collateral sulcus proper (Economo and Koskinas, 1925), which can be separated on the surface and in-depth from the rostrally located rhinal sulcus (Huntgeburth and Petrides, 2012). A more detailed discussion of this issue will be presented below in the section on ‘Segments of the collateral sulcus proper’.

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The present probability maps provide information on the variability in location of the sulci of the collateral complex that can be used to identify accurately the local morphology and correctly relate it to functional activation patterns in neuroimaging studies. For instance, in a study by Paquette and colleagues (2003), subjects underwent functional magnetic resonance imaging to examine the effect of cognitive-behavior therapy for specific phobia. In the visual display of their findings (see Figure 2 pre-treatment, p. 405), the authors reported an activation peak that falls lateral to a deep rostrocaudally oriented sulcus which in turn lies lateral to the hippocampal fissure. The probability maps of the present study would have provided the authors with an aid to identify accurately the collateral sulcus proper, and thus provide an accurate attribution of their activation peak to the fusiform gyrus since the activation falls lateral to the collateral sulcus proper.

Segments of the collateral sulcus proper According to our previous study, there are two segments of the collateral sulcus proper in 50 percent of the cases examined: an anterior segment (cos-1) and a posterior segment (cos-2) (Huntgeburth and Petrides, 2012). The probability maps of the variability in location of both segments are presented in Figure 3.10.5. Such a distinction of two segments of the collateral sulcus proper had not been made prior to our study (Huntgeburth and Petrides, 2012). The probability maps of these two segments of the collateral sulcus proper provide valuable information when examining activation along the parahippocampal cortex. Tables 3.9.2 and 3.9.3 provide a list of activation peaks from various functional neuroimaging studies and present the interpretation of the location by the authors as well as the interpretation when using the present probability maps. Table 3.9.2 presents activation peaks along the anterior part of the parahippocampal cortex. Note that all activation peaks listed in Table 3.9.2 fall caudal to the posterior limit of the entorhinal cortex as defined by Amunts et al. (2005) and illustrated in Figures 3.10.7 and 3.10.8. Table 3.9.3 focuses explicitly on studies that have reported activation peaks showing greater activation for place/scene stimuli than for other

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stimuli, such as objects, faces, houses, and/or scrambled images. Such studies were either said to represent the parahippocampal place area (PPA) and were defined by functional localizer scans or interpreted by the authors to correspond to the parahippocampal place area, although the study did not explicitly apply functional localizer scans to identify this region of interest (therefore denoted as PPA-like activation in Table 3.9.3). The information presented in Tables 3.9.2 and 3.9.3 demonstrates that a more precise description of the anatomical location of activation peaks in the parahippocampal region can be achieved by use of the present probability maps. For example, a study by Köhler and colleagues (2002) investigated the functional involvement of the hippocampus and parahippocampal cortex in recognition-memory for scenes and objects. Greater activation for scenes compared with objects was observed in the parahippocampal cortex, close to where the parahippocampal place area is often reported. On the basis of the present probability maps, the locus of the activation cluster can be further specified using the variability information for the anterior and posterior segments of the collateral sulcus proper (Fig. 3.10.5): the left activation cluster of Köhler and colleagues (2002) clearly falls along the posterior segment of the collateral sulcus proper, thereby within the posterior parahippocampal cortex, whereas the right activation cluster of Köhler and colleagues (2002) lies along the transition between the anterior and posterior segments of the collateral sulcus proper. If the parahippocampal cortex is indeed a heterogeneous region, it is of importance to determine precisely the parts of the parahippocampal cortex that are involved in particular aspects of cognitive processing. An examination of the activation peaks on a subject-by-subject basis in the original data set may provide more precise location of this activation cluster. Such more detailed description may help future studies to examine whether a difference exists in the contribution made by the region occupying the length of the anterior segment versus that occupying the posterior segment of the collateral sulcus proper. In reviewing the literature on studies examining the parahippocampal place area, the activation peak coordinates are often reported to fall along what has here been referred to as the posterior segment of the collateral sulcus proper. For

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instance, a study by Pihlajamäki et al. (2004) reported activation along the parahippocampal cortex and interpreted the activation clusters as falling within what the investigators termed the anterior and the posterior parahippocampal cortex (see Tables 3.9.2 and 3.9.3). Besides this rudimentary delineation into anterior and posterior regions, the authors did not provide anatomical criteria for their parahippocampal cortex subdivision. The present study may offer improved anatomical criteria. According to the probability maps (Figs. 3.10.3-3.10.6; Tables 3.9.2 and 3.9.3), the activation peaks for the anterior or posterior parahippocampal cortex fall along the anterior or posterior segments of the collateral sulcus proper. Functional activation peaks observed at specific points along the parahippocampal cortex may therefore be more precisely located according to the likelihood with which they fall along these two segments of the collateral sulcus proper (see Tables 3.9.2-3.9.4). In the previously mentioned study by Staresina and colleagues (2011), the parahippocampal gyrus was segregated into three segments of equal distance: anterior, middle, and posterior parts. An activation peak was observed within the part that the authors defined as the middle part of the parahippocampal gyrus (see Table 3.9.2 for details) and the peak was interpreted as representing domain- general activation because this region responded equally to the presentation of object and scene stimuli (Staresina et al., 2011). Using the present probability maps, we were able to identify four regions of the parahippocampal gyrus based on the local morphology: the entorhinal/perirhinal cortex, delimited by the rhinal sulcus, an anterior part of the parahippocampal cortex, bound by the anterior segment of the collateral sulcus proper (posterior to the small portion of overlap of the entorhinal cortex with the anterior tip of the collateral sulcus proper, as observed in Figs. 3.10.7 and 3.10.8), a middle part of the parahippocampal cortex, i.e. the region of overlap between the anterior and posterior segments of the collateral sulcus proper, and a posterior part of the parahippocampal cortex bound by the posterior segment of the collateral sulcus proper. Note that given that the entorhinal cortex may extend a short distance along the anterior segment of the collateral sulcus proper (Figs. 3.10.7 and 3.10.8), activation along the most

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anterior tip of the collateral sulcus proper may be difficult to interpret. We inserted the activation peak coordinates, identified by Staresina and colleagues (2011) as located in the middle part of the parahippocampal gyrus, see Table 3.9.2 for the peak coordinates, into the probabilistic maps provided here and we show that the peak has a high probability (100%) of falling along the anterior, rather than the posterior segment (30%) of the collateral sulcus proper (Table 3.9.2; Figs. 3.10.3-3.10.5). Another peak of functional activation reported by Staresina and colleagues (2011) represents a preference for scene stimuli rather than objects and was identified in the right parahippocampal cortex (Table 3.9.3). According to the present probability maps, this activation peak may be better described as falling along the caudal part of the transition between the anterior and posterior segments of the collateral sulcus proper and may more precisely be defined as mid-parahippocampal cortex activation (see Table 3.9.3). Similarly, Aminoff and colleagues (2007) observed differential involvement of the anterior part of the parahippocampal cortex in non-spatial contextual associations and involvement of the posterior part of the parahippocampal cortex for spatial contextual associations. In conclusion, reference to anatomical landmarks or specific criteria regarding the point of separation of the parahippocampal cortex in many functional neuroimaging studies can lead to more precise definition of the locus of activation and thus to better understanding of functional differences along the parahippocampal gyrus. Further support for the usefulness of sulcal probability maps to help identify functional subdivisions along the antero-posterior axis of the parahippocampal cortex comes from Litman et al. (2009). In their fMRI study, Litman and colleagues (2009) examined the responses of the parahippocampal gyrus to various stimulus categories, such as objects and scenes, and demonstrated a double dissociation between scene processing by the posterior part of the parahippocampal cortex and object processing by the perirhinal cortex. These investigators subsequently divided the parahippocampal gyrus into seven regions of interest (ROI) of equal size (see Table 3.9.4) in order to take a closer look at the location along the parahippocampal gyrus of the activation patterns. The two

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most posterior segments, ranging in y coordinates from -41 to -53 (average of - 48), were said to correspond to the parahippocampal place area (PPA; Epstein and Kanwisher, 1998) because this region showed preferential response to novel scene stimuli in comparison with novel objects. Although the response to scenes decreased significantly when moving anteriorly along the subdivisions of the parahippocampal gyrus, the response to objects remained consistent. In Figure 3 of Litman et al. (2009), one observes that the region where the preferential response to scenes decreased spanned two ROIs (y coordinates -22 to -38). Table 3.9.4 presents the parahippocampal subdivisions by Litman and colleagues (2009), in addition to corresponding specifications of the localization that can be provided by the present probability maps.

Parahippocampal extension of the collateral sulcus A part of the parahippocampal cortex has received considerable attention in part because it is a region that has been shown to respond selectively to place information compared to other stimuli, such as faces, houses, and objects. This region has been termed the parahippocampal place area (PPA; Epstein and Kanwisher, 1998). The coordinates reported for the parahippocampal place area have been quite variable (Table 3.9.3), ranging from the mid-parahippocampal cortex into the anterior lingual gyrus (Aguirre and D’Esposito, 1997; Epstein and Kanwisher, 1998; Epstein et al., 1999; Epstein et al., 2003; Köhler et al., 2002; Bar and Aminoff, 2003; Pihlajamaki et al., 2004; Henderson et al., 2008; Litman et al., 2009; Andrews et al., 2010; Staresina et al., 2011; Sulpizio et al., 2013; Arcaro et al., 2009). Examination of the reported activation peaks using our probability maps (e.g. Figs. 3.10.3, 3.10.5, and 3.10.6) demonstrates that a great proportion of the activation peaks with a response preference for scene stimuli fall along the posterior segment of the collateral sulcus proper, anterior to the junction with the parahippocampal extension of the collateral sulcus. This places them within the posterior part of the parahippocampal cortex. A recent fMRI study by Sulpizio et al. (2013) examined the neural correlates of viewpoint variations (i.e. judgements of viewpoint reference frame

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changes between the observer, the room, and the objects in the room) and reported a region of bilateral activation in “the anterior lingual gyrus where it meets the posterior parahippocampal gyrus…” (p. 68). Examination of the coordinates provided by Sulpizio et al. (2013) and others (e.g. Andrews et al. 2010; see our Table 3.9.3) on the basis of the probabilistic maps provided here shows that these activations fall posterior to the parahippocampal gyrus, i.e. within the lingual gyrus. The lingual gyrus, of course, is occupied by visual association cortex (Iaria and Petrides, 2007). Using the probabilistic information provided here may lead to a clearer picture in the attempt to unravel the contributions of different cortical regions within and near the parahippocampal region. Finally, the present probability maps provide the variability of the posterior limits of the parahippocampal cortex and hence the parahippocampal gyrus. To date the caudal border has been rather arbitrarily chosen as “the first coronal slice on which the calcarine sulcus is visible” (p. 366, Reber et al., 2002). Similar boundaries have been adopted by other researchers (Aminoff et al., 2007; Staresina et al., 2011). The posterior boundary of the parahippocampal cortex within the present framework is based on local anatomical landmarks, namely the junction between the collateral sulcus proper and the parahippocampal extension of the collateral sulcus. The parahippocampal extension of the collateral sulcus (cos-ph) may be found at the caudal end of the collateral sulcus proper, at the level of the rostral most tip of the anterior calcarine sulcus. It has been identified in 70% of cases (Huntgeburth and Petrides, 2012). This relatively ‘short’ sulcus first runs parallel to the collateral sulcus proper and subsequently merges with it in-depth. The point where the parahippocampal extension and the collateral sulcus proper merge provides the point of origin of the occipital extension of the collateral sulcus which continues into the lingual gyrus, thereby forming the posterior limit of the parahippocampal cortex.

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3.7 References Ad-Dab'bagh, Y., Lyttelton, O., Muehlboeck, J.-S., Lepage, C., Einarson, D., Mok, K., Ivanov, O., Vincent, R.D., Lerch, J., Fombonne, E. & Evans, A.C. (2006) The CIVET image-processing environment: a fully automated comprehensive pipeline for anatomical neuroimaging research In: Corbetta M (ed) Proceedings of the 12th Annual Meeting of the Organization for Human Brain Mapping, Florence, Italy

Aguirre, G.K. & D'Esposito, M. (1997) Environmental knowledge is subserved by separable dorsal/ventral neural areas. The Journal of neuroscience, 17, 2512-2518.

Amaral, D.G., Insausti, R. & Cowan, W.M. (1987) The entorhinal cortex of the monkey: I. Cytoarchitectonic organization. The Journal of comparative neurology, 264, 326-355.

Aminoff, E., Gronau, N. & Bar, M. (2007) The parahippocampal cortex mediates spatial and nonspatial associations. Cerebral cortex, 17, 1493-1503.

Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N.J., Habel, U., Schneider, F. & Zilles, K. (2005) Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and embryology, 210, 343-352.

Andrews, T.J., Clarke, A., Pell, P. & Hartley, T. (2010) Selectivity for low-level features of objects in the human ventral stream. NeuroImage, 49, 703-711.

Arcaro, M.J., McMains, S.A., Singer, B.D. & Kastner, S. (2009) Retinotopic organization of human ventral visual cortex. The Journal of neuroscience, 29, 10638-10652.

139

Augustinack, J.C., van der Kouwe, A.J. & Fischl, B. (2013) Medial temporal cortices in ex vivo magnetic resonance imaging. The Journal of comparative neurology, 521, 4177-4188.

Bachevalier, J. & Nemanic, S. (2008) Memory for spatial location and object- place associations are differently processed by the hippocampal formation, parahippocampal areas TH/TF and perirhinal cortex. Hippocampus, 18, 64-80.

Bar, M. & Aminoff, E. (2003) Cortical analysis of visual context. Neuron, 38, 347-358.

Bohbot, V.D. & Corkin, S. (2007) Posterior parahippocampal place learning in H.M. Hippocampus, 17, 863-872.

Brodmann, K. (1909) Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Barth, Leipzig.

Canto, C.B., Wouterlood, F.G. & Witter, M.P. (2008) What does the anatomical organization of the entorhinal cortex tell us? Neural plasticity 2008:1-18

Chiavaras, M.M., LeGoualher, G., Evans, A. & Petrides, M. (2001) Three- dimensional probabilistic atlas of the human orbitofrontal sulci in standardized stereotaxic space. NeuroImage, 13, 479-496.

Collins, D.L., Neelin, P., Peters, T.M. & Evans, A.C. (1994) Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. Journal of computer assisted tomography, 18, 192-205.

Duvernoy, H. (1999) The Human Brain: Surface, Three-Dimensional Sectional Anatomy and MRI. 2nd Edition edn. Springer-Verlag, Wien.

140

Economo, C. & Koskinas, G.N. (1925) Die Cytoarchitektur der Hirnrinde des erwachsenen Menschen. Springer, Wien.

Eickhoff, S.B., Heim, S., Zilles, K. & Amunts K (2006) Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps. NeuroImage, 32, 570-582.

Eickhoff, S.B., Stephan, K.E., Mohlberg, H., Grefkes, C., Fink, G.R., Amunts, K. & Zilles, K. (2005) A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. NeuroImage, 25, 1325-1335.

Eickhoff, S.B., Paus, T., Caspers, S., Grosbras, M.H., Evans, A.C., Zilles, K. & Amunts, K. (2007) Assignment of functional activations to probabilistic cytoarchitectonic areas revisited. NeuroImage, 36, 511-521.

Epstein, R., Graham, K.S. & Downing, P.E. (2003) Viewpoint-Specific Scene Representations in Human Parahippocampal Cortex. Neuron, 37, 865-876.

Epstein, R., Harris, A., Stanley, D. & Kanwisher, N. (1999) The Parahippocampal Place Area: Recognition, Navigation, or Encoding? Neuron, 23, 115-125.

Epstein, R. & Kanwisher, N. (1998) A cortical representation of the local visual environment. Nature, 392, 598-601.

Fischl, B., Stevens, A.A., Rajendran, N., Yeo, B.T., Greve, D.N., Van Leemput, K., Polimeni, J.R., Kakunoori, S., Buckner, R.L., Pacheco, J., Salat, D.H., Melcher, J., Frosch, M.P., Hyman, B.T., Grant, P.E., Rosen, B.R., van der Kouwe, A.J., Wiggins, G.C., Wald, L.L. & Augustinack, J.C. (2009) Predicting the location of entorhinal cortex from MRI. NeuroImage, 47, 8-17.

141

Germann, J., Robbins, S., Halsband, U. & Petrides M (2005) Precentral sulcal complex of the human brain: morphology and statistical probability maps. The Journal of comparative neurology, 493, 334-356.

Gloor, P. (1997) The Temporal Lobe and Limbic System. Oxford University Press, New York.

Grabner, G., Janke, A.L., Budge, M.M., Smith, D., Pruessner, J. & Collins DL (2006) Symmetric atlasing and model based segmentation: an application to the hippocampus in older adults. Medical image computing and computer-assisted intervention, 9, 58-66.

Hanke, J. (1997) Sulcal pattern of the anterior parahippocampal gyrus in the human adult. Ann Anat, 179, 335-339.

Henderson, J.M., Larson, C.L. & Zhu, D.C. (2008) Full scenes produce more activation than close-up scenes and scene-diagnostic objects in parahippocampal and retrosplenial cortex: an fMRI study. Brain and cognition, 66, 40-49.

Huntgeburth, S.C. & Petrides, M. (2012) Morphological patterns of the collateral sulcus in the human brain. The European journal of neuroscience, 35, 1295-1311.

Iaria, G. & Petrides, M. (2007) Occipital sulci of the human brain: Variability and probability maps. The Journal of comparative neurology, 501, 243-259.

Iaria, G., Robbins, S. & Petrides, M. (2008) Three-dimensional probabilistic maps of the occipital sulci of the human brain in standardized stereotaxic space. Neuroscience, 151, 174-185.

Insausti, R. (1993) Comparative anatomy of the entorhinal cortex and hippocampus in mammals. Hippocampus, 3, Spec No:19-26.

142

Insausti, R. & Amaral, D.G. (2004) Hippocampal formation In: Paxinos G, Mai JK (eds) The Human Nervous System. 2nd Edition edn. Elsevier Academic Press, San Diego, pp 871-913.

Insausti, R., Amaral, D.G. & Cowan, W.M. (1987) The entorhinal cortex of the monkey: II. Cortical afferents. The Journal of comparative neurology, 264, 356- 395.

Insausti, R., Juottonen, K., Soininen, H., Insausti, A.M., Partanen, K., Vainio, P., Laakso, M.P. & Pitkänen, A. (1998) MR volumetric analysis of the human entorhinal, perirhinal, and temporopolar cortices. American Journal of Neuroradiology, 19, 659-671.

Insausti, R., Tunon, T., Sobreviela, T., Insausti, A.M. & Gonzalo, L.M. (1995) The human entorhinal cortex: a cytoarchitectonic analysis. The Journal of comparative neurology, 355, 171-198.

Janzen, G. & van Turennout, M. (2004) Selective neural representation of objects relevant for navigation. Nature neuroscience, 7, 673-677.

Kim, H., Bernasconi, N., Bernhardt, B., Colliot, O. & Bernasconi, A. (2008) Basal temporal sulcal morphology in healthy controls and patients with temporal lobe epilepsy. Neurology, 70, 2159-2165.

Köhler, S., Crane, J. & Milner, B. (2002) Differential contributions of the parahippocampal place area and the anterior hippocampus to human memory for scenes. Hippocampus, 12, 718-723.

143

Krimer, L.S., Hyde, T.M., Herman, M.M. & Saunders, R.C. (1997) The entorhinal cortex: an examination of cyto- and myeloarchitectonic organization in humans. Cerebral cortex, 7, 722-731.

Litman, L., Awipi, T. & Davachi, L. (2009) Category-specificity in the human medial temporal lobe cortex. Hippocampus, 19, 308-319.

Malkova, L. & Mishkin, M. (2003) One-trial memory for object-place associations after separate lesions of hippocampus and posterior parahippocampal region in the monkey. The Journal of neuroscience, 23, 1956-1965.

Mazziotta, J., Toga, A., Evans, A., Fox, P., Lancaster, J., Zilles, K., Woods, R., Paus, T., Simpson, G., Pike, B., Holmes, C., Collins, L., Thompson, P., MacDonald, D., Iacoboni, M., Schormann, T., Amunts, K., Palomero-Gallagher, N., Geyer, S., Parsons, L., Narr, K., Kabani, N., Le Goualher, G., Boomsma, D., Cannon, T., Kawashima, R. & Mazoyer, B. (2001) A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philosophical Transactions of the Royal Society of London Series B, 356, 1293-1322.

Mazziotta, J.C., Toga, A.W., Evans, A., Fox, P. & Lancaster, J. (1995a) A probabilistic atlas of the human brain: theory and rationale for its development the international consortium for brain mapping (ICBM). NeuroImage, 2, 89-101.

Mazziotta, J.C., Toga, A.W., Evans, A.C., Fox, P.T. & Lancaster, J.L. (1995b) Digital brain atlases. Trends in Neurosciences, 18, 210-211.

Meunier, M., Bachevalier, J., Mishkin, M. & Murray, E.A. (1993) Effects on visual recognition of combined and separate ablations of the entorhinal and perirhinal cortex in rhesus monkeys. The Journal of neuroscience, 13, 5418-5432.

144

Milner, B. (1968) Disorders of memory after brain lesion in man: preface: material-specific and generalized memory loss. Neuropsychologia, 6, 175-179.

Milner, B., Johnsrude, I. & Crane, J. (1997) Right medial temporal-lobe contribution to object-location memory. Philosophical transactions of the Royal Society of London Series B, Biological sciences, 352, 1469-1474.

Mishkin, M., Suzuki, W.A., Gadian, D.G. & Vargha-Khadem, F. (1997) Hierarchical organization of cognitive memory. Philosophical transactions of the Royal Society of London Series B, Biological sciences, 352, 1461-1467.

Novak, K., Czech, T., Prayer, D., Dietrich, W., Serles, W., Lehr, S. & Baumgartner, C. (2002) Individual variations in the sulcal anatomy of the basal temporal lobe and its relevance for epilepsy surgery: an anatomical study performed using magnetic resonance imaging. Journal of neurosurgery, 96, 464- 473.

Ono, M., Kubik, S. & Abernathey, C.D. (1990) Atlas of the Cerebral Sulci. Thieme, Stuttgart.

Paquette, V., Levesque, J., Mensour, B., Leroux, J.M., Beaudoin, G., Bourgouin, P. & Beauregard, M. (2003) "Change the mind and you change the brain": effects of cognitive-behavioral therapy on the neural correlates of spider phobia. NeuroImage, 18, 401-409.

Paus, T., Otaky, N., Caramanos, Z., MacDonald, D., Zijdenbos, A., D'Avirro, , D., Gutmans, D., Holmes, C., Tomaiuolo, F. & Evans, A. C. (1996) In vivo morphometry of the intrasulcal gray matter in the human cingulate, paracingulate, and superior-rostral sulci: hemispheric asymmetries, gender differences and probability maps. The Journal of comparative neurology, 376, 664-673.

145

Petrides, M. (2012) The Human Cerebral Cortex, An MRI Atlas of the Sulci and Gyri in MNI Stereotaxic Space. Academic Press, New York.

Pihlajamaki, M., Tanila, H., Kononen, M., Hanninen, T., Hamalainen, A., Soininen, H. & Aronen, H.J. (2004) Visual presentation of novel objects and new spatial arrangements of objects differentially activates the medial temporal lobe subareas in humans. The European journal of neuroscience, 19, 1939-1949.

Reber, P.J., Wong, E.C. & Buxton, R.B. (2002) Encoding activity in the medial temporal lobe examined with anatomically constrained fMRI analysis. Hippocampus, 12, 363-376.

Retzius, G. (1896) Das Menschenhirn: Studien der makroskopischen Morphologie. Norstedt and Soener, Stockholm.

Sato, N. & Nakamura, K. (2003) Visual response properties of neurons in the parahippocampal cortex of monkeys. Journal of neurophysiology, 90, 876-886.

Scoville, W.B. & Milner, B. (1957) Loss of recent memory after bilateral hippocampal lesions. Journal of neurology, neurosurgery, and psychiatry, 20, 11- 21.

Segal, E. & Petrides, M. (2012) The morphology and variability of the caudal rami of the superior temporal sulcus. The European journal of neuroscience, 36, 2035-2053.

Sled, J.G., Zijdenbos, A.P. & Evans, A.C. (1998) A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE transactions on medical imaging, 17, 87-97.

146

Smith, E.G. (1904) Studies in the morphology of the human brain. Records of the Egyption Government School of Medicine Egyptians - No.1. The occipital Region, 2, 124-173.

Smith, S.M. (2002) Fast robust automated brain extraction. Human brain mapping, 17, 143-155.

Squire, L.R. & Zola-Morgan, S. (1988) Memory: brain systems and behavior. Trends Neurosci, 11, 170-175.

Squire, L.R. & Zola-Morgan, S. (1991) The medial temporal lobe memory system. Science, 253, 1380-1386.

Sulpizio, V., Committeri, G., Lambrey, S., Berthoz, A. & Galati, G. (2013) Selective role of lingual/parahippocampal gyrus and retrosplenial complex in spatial memory across viewpoint changes relative to the environmental reference frame. Behavioural brain research, 242, 62-75.

Suzuki, W.A. & Amaral, D.G. (1994) Perirhinal and parahippocampal cortices of the macaque monkey: cortical afferents. The Journal of comparative neurology, 350, 497-533.

Suzuki, W.A. & Amaral, D.G. (2003) Perirhinal and parahippocampal cortices of the macaque monkey: cytoarchitectonic and chemoarchitectonic organization. The Journal of comparative neurology, 463, 67-91.

147

Suzuki, W.A., Zola-Morgan, S., Squire, L.R. & Amaral, D.G. (1993) Lesions of the perirhinal and parahippocampal cortices in the monkey produce long-lasting memory impairment in the visual and tactual modalities. The Journal of neuroscience, 13, 2430-2451.

Talairach, J. & Tournoux, P. (1988) Co-Planar Stereotaxic Atlas of the Human Brain. Thieme, New York.

Tomaiuolo, F., MacDonald, J.D., Caramanos, Z., Posner, G., Chiavaras, M., Evans, A.C. & Petrides, M. (1999) Morphology, morphometry and probability mapping of the pars opercularis of the inferior frontal gyrus: an in vivo MRI analysis. The European journal of neuroscience, 11, 3033-3046.

Van Hoesen, G.W. (1982) The parahippocampal gyrus: New observations regarding its cortical connections in the monkey. Trends in Neurosciences, 5, 345- 350.

Van Hoesen, G.W. & Pandya, D.N. (1975) Some connections of the entorhinal (area 28) and perirhinal (area 35) cortices of the rhesus monkey. I. Temporal lobe afferents. Brain Research, 95, 1-24.

Van Hoesen, G.W., Pandya, D.N. & Butters, N. (1972) Cortical afferents to the entorhinal cortex of the Rhesus monkey. Science, 175, 1471-1473.

Vogt, B.A., Vogt, L.J., Perl, D.P. & Hof, P.R. (2001) Cytology of human caudomedial cingulate, retrosplenial, and caudal parahippocampal cortices. The Journal of comparative neurology, 438, 353-376.

Von Bonin, G. & Bailey, P. (1947) The Neocortex of Macaca Mulatta. University of Illinois Press, Urbana.

148

Zola-Morgan, S., Squire, L.R., Amaral, D.G. & Suzuki, W.A. (1989) Lesions of perirhinal and parahippocampal cortex that spare the amygdala and hippocampal formation produce severe memory impairment. The Journal of neuroscience, 9, 4355-4370.

Zola-Morgan, S., Squire, L.R. & Ramus, S.J. (1994) Severity of memory impairment in monkeys as a function of locus and extent of damage within the medial temporal lobe memory system. Hippocampus, 4, 483-495.

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3.8 Acknowledgements We thank the National Institute of Biomedical Imaging and BioEngineering (principal investigator: John Mazziotta, MD, Ph.D.) for funding for the International Consortium for Brain Mapping (ICBM) brains that were used in the present study. Furthermore, we thank Dr. Claude Lepage for technical help in image-processing necessary to register the entorhinal cortex probability map into the stereotaxic space used in the present study to allow comparison with the probability maps of the rhinal sulcus and the collateral sulcus proper. We also thank Dr. Veronika Zlatkina for helpful discussions.

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3.9 Tables

Table 3.9.1 Location of functional activation peaks along the anterior part of the parahippocampal gyrus (i.e. the entorhinal and perirhinal cortex) of the human brain that have been reported in functional magnetic resonance imaging studies to represent greater activation for object stimuli than whole scenes/places. The location of these peaks is also interpreted using the present probability maps. Abbreviations: cos, collateral sulcus proper; ERC, entorhinal cortex; PHC, parahippocampal cortex; PHG, parahippocampal gyrus; rhs, rhinal sulcus; PRC, perirhinal cortex. Asterisk (*) indicates when the location of activation peak may fall within two adjacent regions; individual subject examination is indicated in such cases for accurate interpretation of activation peaks.

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Table 3.9.2 Location of functional activation peaks along the parahippocampal cortex of the human brain, reported in functional magnetic resonance imaging studies to represent greater activation for object stimuli compared with scenes/places. The location of these peaks is also interpreted using the present probability maps. Abbreviations: cos, collateral sulcus proper; cos-1, cos-2, anterior, posterior cos segment (respectively); cos-ph, parahippocampal extension of the collateral sulcus; n/p, information not provided; PHC, parahippocampal cortex; PHG, parahippocampal gyrus; rhs, rhinal sulcus; PPA, parahippocampal place area (defined using functional localizer scan; see Epstein and Kanwisher, 1998); PPA-like, scene-preferential region (defined without functional localizer scan). Positive, negative x coordinates refer to the right, left hemispheres, respectively.

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Table 3.9.3 Location of functional activation peaks along the parahippocampal cortex of the human brain reported in functional magnetic resonance imaging studies to represent greater activation for scenes/places compared with other visual stimuli (e.g., objects, houses, faces, scrambled images). The location of these peaks is also interpreted using the present probability maps. The table

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indicates the location of activation peaks identified by the authors as parahippocampal place area (PPA; Epstein and Kanwisher, 1998) when a functional localizer scan was used to identify this region. ‘PPA-like’ refers to peaks interpreted by the authors as corresponding to the PPA, but the peaks were not confirmed with a localizer scan. Location of activation peaks are also defined using the present probability maps. Abbreviations: cos, collateral sulcus proper; cos-1, cos-2, anterior, posterior cos segment (respectively); cos-ph, parahippocampal extension of the collateral sulcus; FG, fusiform gyrus; LG, lingual gyrus; LPHG, “lingual/parahippocampal gyri”; PHC, parahippocampal cortex; PHG, parahippocampal gyrus; PPA, parahippocampal place area (defined using functional localizer scan; see Epstein and Kanwisher, 1998); PPA-like, scene-preferential region (defined without functional localizer scan); rhs, rhinal sulcus. Positive, negative x coordinates refer to the right, left hemispheres, respectively.

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Table 3.9.4 Region of interest (ROI) subdivisions of the parahippocampal gyrus by Litman and colleagues (2009). The ranges of the ROI regions are indicated with the rostral and caudal y coordinates, together with the interpretation of the location by Litman and colleagues (2009). The location is also identified using the present probability maps. Abbreviations: cos, collateral sulcus proper; cos-1, cos- 2, anterior, posterior cos segment (respectively); cos-ph, parahippocampal extension of the collateral sulcus; ERC, entorhinal cortex; LG, lingual gyrus; n/p, information not provided; PHC, parahippocampal cortex; PHG, parahippocampal gyrus; PPA, parahippocampal place area (defined using functional localizer scan; see Epstein and Kanwisher, 1998); PPA-like, scene-preferential region (defined without functional localizer scan); PRC, perirhinal cortex; rhs, rhinal sulcus. Positive, negative x coordinates refer to the right, left hemispheres, respectively. Asterisk (*) indicates that the location of activation peak may fall within two adjacent regions; individual subject examination is indicated in such cases for accurate interpretation of activation peaks.

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3.10 Figures

Figure 3.10.1 A-B: Probabilistic maps of the location of (A) the rhinal sulcus (rhs) and (B) the collateral sulcus proper displayed on a series of coronal sections (y coordinates). The x and z coordinates of the sections are provided on the sides of the images. The probability maps are superimposed on the average brain of the Montreal Neurological Institute (MNI) and thus the coordinates are in the MNI standard stereotaxic space. The color scale indicates the proportion of brains contributing to the probability map at each voxel in MNI space.

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Figure 3.10.2 A-C: Probabilistic map of the location of the rhinal sulcus (rhs) displayed on a series of coronal sections (y coordinates), illustrated separately for the different relationship patterns, i.e. according to (A) Type I (i.e. the rhinal sulcus and collateral sulcus proper are separated clearly on the surface and in depth), (B) Type IIa (i.e. the rhinal sulcus and collateral sulcus proper are separated clearly in the depth of the sulci; the collateral sulcus proper develops out of the lateral bank of the rhinal sulcus), and (C) Type IIb (i.e. the rhinal sulcus and collateral sulcus proper are separated clearly in the depth of the sulci; the

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collateral sulcus proper develops out of the medial bank of the rhinal sulcus). The x and z coordinates of the sections are provided on the sides of the images.

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Figure 3.10.3 A-B: Probabilistic map of the location of the collateral sulcus proper (cos) displayed on a series of coronal sections (y coordinates), illustrated separately for the different relationship patterns: (A) Type I (i.e. the rhinal sulcus and collateral sulcus proper are separated clearly on the surface and in depth) and (B) Type IIb (i.e. the rhinal sulcus and collateral sulcus proper are separated clearly in the depth of the sulci; the collateral sulcus proper develops out of the medial bank of the rhinal sulcus). The collateral sulci with a more rostral origin (i.e. cos-early), making up 16.67% of the cases, are not included. The x and z coordinates of the sections are provided on the sides of the images.

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Figure 3.10.4 Probabilistic map of the location of the collateral sulcus proper with a more anterior origin (originating at the height of the amygdala; ‘cos- early’), occurring in 16.67% of cases, displayed on a series of coronal sections (y coordinates). The x and z coordinates of the sections are provided on the sides of the images.

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Figure 3.10.5 A-B: Probabilistic maps of coronal sections of the (A) anterior (cos-1) and (B) posterior (cos-2) segments of the collateral sulcus proper, displayed on a series of coronal sections (y coordinates). The x and z coordinates of the sections are provided on the sides of the images.

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Figure 3.10.6 Probabilistic map of coronal of the parahippocampal extension of the collateral sulcus (cos-ph), displayed on a series of coronal sections (y coordinates). The x and z coordinates of the sections are provided on the sides of the images.

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Figure 3.10.7 Illustration of the probabilistic maps of the rhinal sulcus (in blue) and the collateral sulcus proper (in red) as established in the present article, together with the cytoarchitectonic probability map of the entorhinal cortex (in green) by Amunts et al. (2005) as published in the SPM toolbox (Eickhoff et al., 2005; 2006; 2007), in coronal sections in the MNI standard stereotaxic space.

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Figure 3.10.8 Illustration of the probabilistic maps of the rhinal sulcus (in blue) and the collateral sulcus proper (in red) as established in the present article, together with the cytoarchitectonic probability map of the entorhinal cortex (in green) by Amunts et al. (2005) as published in the SPM toolbox (Eickhoff et al., 2005; 2006; 2007), in sagittal sections in the MNI standard stereotaxic space.

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Chapter Four 4. Local morphology informs location of activation during navigation within the parahippocampal region of the human brain

Huntgeburth S.C., Chen J.-K., Ptito A., and Petrides M. (2015). Local Morphology Informs Location of Activation during Navigation within the Parahippocampal Region of the Human Brain. The manuscript has been submitted and is currently under review (at the “initial submission” stage).

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4.1 Prelude The anatomical study presented in Chapter 3 complements the first study in that the study in Chapter 3 quantifies the variability of the rhinal sulcus, collateral sulcus proper, and parahippocampal extension of the collateral sulcus, as well as provides a reference frame for accurate identification of activation peaks obtained by functional neuroimaging by the neuroscience community. The provision of the probabilistic maps demonstrated a close link between the antero-posterior extent of the rhinal sulcus and the entorhinal cortex by relating these maps to the cytoarchitectonic probability map of the entorhinal cortex, strengthening the argument made in the first study (Chapter 2) of the definition of the rhinal sulcus. Thus, it can be shown that the rhinal sulcus in the human brain, if defined appropriately, forms a reliable landmark of the entorhinal cortex as it does in all other mammals. This informs the debate on the terminology used to refer to the sulci along the rostro-caudal axis of the parahippocampal cortex and suggests that nomenclature used for the sulcus that delimits the entorhinal cortex in the human brain should be comparable to that used for the same sulcus in all other mammals. Furthermore, the study in Chapter 3 builds on the provision of the two segments of the collateral sulcus proper (i.e. the anterior and the posterior segments of the collateral sulcus proper) which lie posterior to the rhinal sulcus and mark the lateral border of the parahippocampal cortex, by offering their location variability as probability maps. Both anatomical studies (Chapters 2 and 3) offer the framework for the investigation presented in the third and fourth studies (Chapters 4 and 5). The identification of the location of the three different clusters of activation peaks described in the third study (Chapter 4) was made possible by studies 1 and 2 (Chapters 2 and 3). Specifically, first, the morphological examination of the collateral sulcus proper (Chapters 2 and 3) allowed for an accurate differentiation based on the local morphology of the parahippocampal cortex into an anterior part (i.e. the entorhinal cortex) and a posterior part (i.e. parahippocampal cortex) of the parahippocampal gyrus. Second, the observation that the collateral sulcus proper is composed of two sulcal segments was described in Chapter 2 and built upon by quantifying the location variability in the

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form of probability maps in Chapter 3, allowed for a linking of the location of the clusters of functional activation that was found in Chapter 4, to the local morphology of the segments of the collateral sulcus proper, which lead to support the idea of functional subdivisions along the parahippocampal cortex within the standard space of the Montreal Neurological Institute.

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4.2 Abstract The relationship between the local morphological features that define the entorhinal and parahippocampal cortex in the human brain and activation as measured during a navigation task with functional magnetic resonance imaging was examined individually in 14 healthy participants. Two functional activation clusters were identified posteriorly in the parahippocampal cortex, one within the caudal end of the collateral sulcus proper and the other in the parahippocampal extension of the collateral sulcus. A third activation cluster, rostral to the peaks of the posterior parahippocampal cortex was identified where the anterior segment of the collateral sulcus proper gives way to the posterior segment thereby positioning itself within the middle parahippocampal cortex. The location of these peaks could be clearly differentiated from adjacent cortex of the entorhinal and perirhinal cortex on the anterior parahippocampal gyrus and the cortex of the fusiform and lingual gyri further posteriorly. These activation foci along the rostro-caudal axis of the parahippocampal cortex may represent functional subregions involved in processing spatial information and demonstrate that the segments of the collateral sulcal complex represent important anatomical landmarks that can provide an accurate localization of activation foci along the parahippocampal cortex and allow identification of subdivisions involved in the processing of spatial information.

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4.3 Introduction The parahippocampal gyrus, known to be critically involved in memory (Scoville & Milner, 1957; Squire & Zola-Morgan, 1991), is a long elongated structure that extends along the medial surface of the temporal lobe, from the temporo-polar cortex, anteriorly, to the medial occipital lobe and the retrosplenial region, posteriorly. It comprises several distinct areas that include the entorhinal and parahippocampal cortex on its surface and the hippocampal formation folded medially under the hippocampal fissure (Van Hoesen, 1995). Although the involvement of the hippocampal formation in memory is generally accepted, the specific roles of the cortical areas on the surface of the parahippocampal gyrus require clarification. In particular, the cortex on the posterior part of the parahippocampal gyrus, referred to as the parahippocampal cortex, has received considerable attention as a critical region for spatial processing from lesion research in the macaque monkey (Bachevalier & Nemanic, 2008; Malkova & Mishkin, 2003) and functional neuroimaging in the human brain (Köhler et al., 2002; Litman et al., 2009). For instance, in the monkey, ablations restricted to the parahippocampal cortex impaired memory for object-place associations even after a single trial (Malkova & Mishkin, 2003). In the human, temporal damage that includes the parahippocampal cortex impairs performance on object-location memory (Ploner et al., 2000; Smith & Milner, 1981) and the use of visual environmental information to navigate to a target (Bohbot et al., 1998; Habib & Sirigu, 1987). Functional neuroimaging in the human brain has demonstrated increased activation in the posterior part of the parahippocampal gyrus, the locus of which was interpreted to involve the parahippocampal cortex (Epstein and Kanwisher, 1998; Köhler et al., 2002; Litman et al., 2009). For instance, a category-selective region has been identified along the parahippocampal cortex, named the ‘parahippocampal place area’, which preferentially responds to place and scene-stimuli compared to faces, objects, and houses (Epstein & Kanwisher, 1998). The coordinates reported for the activation peaks of scene-selectivity have varied along the medial temporal lobe (Epstein & Kanwisher, 1998; Köhler et al., 2002; Pihlajamaki et al., 2004; Staresina et al., 2011), often extending into the

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nearby lingual gyrus (Andrews et al., 2010; Sulpizio et al., 2013). It is imperative to use well-defined anatomical landmarks in individual subjects to demarcate the cortical sub-regions in the medial temporal lobe when examining their association with functional activation. Unfortunately, the sulcal anatomy delineating the parahippocampal gyrus had in the past generated considerable confusion with divergent terminology used across studies that prevented the establishment of clear morphological criteria for the location of the entorhinal and parahippocampal cortex and their borders with the adjacent cortical regions, such as the lingual and fusiform gyri. A recent examination of the variability of the sulci that demarcate the parahippocampal gyrus has resolved these issues and established clear criteria to differentiate entorhinal cortex from parahippocampal cortex and the cortex of the lingual and fusiform gyri, criteria that could be used to examine activation patterns in individual subject brains (Huntgeburth & Petrides, 2012). Using these criteria, the present functional neuroimaging study set to examine the relationship between the local morphology and the locus of activation in a navigation task, on a subject-by-subject basis. The aim was to provide an accurate definition of the location of activation peaks related to spatial processing on the parahippocampal cortex of the human brain. Examination of activation in individual brains is critical because group studies often obscure a clear assignment of activation within particular regions. Indeed, the examination of activation patterns in individual subjects following detailed anatomical study of the sulcal patterns has resolved many controversies, such as the differentiation of the frontal eye fields from the hand premotor region (Amiez et al., 2006), the demonstrations of three cingulate motor areas in the human brain (Amiez & Petrides, 2014), the location of the hand region in the primary motor cortex (Yousry et al., 1997) and the precise location of reading activity in the angular gyrus (Segal & Petrides, 2013).

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4.4 Materials and methods Participants Fourteen healthy male university athletes (ice-hockey, football, and soccer) participated in the present study (mean age 21.1 ± 2.14 years). They formed part of a control group of a larger study, which examined mild traumatic brain injury (mTBI) and its association with post-concussion and depressive symptoms. Post- concussive symptoms (PCS) were evaluated for each participant using a 21-item symptom checklist adapted from the Post-Concussion Symptom Scale-Revised (Lovell & Collins, 1998) and depressive symptoms were measured with the Beck’s Depression Inventory (BDI-II). All participants were asked to rate their symptoms within the three days prior to the study. None of the subjects included in the present investigation had sustained an mTBI during the season (mean number of concussions 0.2 ± 0.43) and none suffered from post-concussion and/or depressive symptoms (mean PCS score 1.5 ± 1.74; mean BDI-II scores 1.4 ± 1.86). All subjects were right handed, with no history of neurological and/or psychiatric disorders, or use of medication, and they all gave written informed consent. The study conformed to the Code of Ethics of the World Medical Association (Declaration of Helsinki) as printed in the British Medical Journal (18 July 1964). Approval was given by the Research Ethics Board of the Montreal Neurological Institute (MNI) and Hospital.

Task and procedure Subjects participated in a virtual reality navigation task that resembled a small city with buildings made up of brick walls. The walls varied in size and shape but remained constant in texture and color. A blue sky and grey flooring consistently lined the neighbourhood. The task was based on the experimental paradigm of a previous study by Iaria and colleagues (2007). The virtual environment was created using game editor software 3D GameStudio A6 (Conitec Datasystems, Inc. La Mesa, CA, USA). Six landmarks were located at fixed positions within the neighbourhood (i.e. a bank, church, clinic, police station, post office, and a supermarket). All landmarks were easily distinguishable from one another and

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navigation within the neighbourhood occurred from the perspective of the individual subject as she/he navigated in the environment. All subjects participated in a training session prior to scanning. During training, participants were instructed to orient themselves freely within the virtual neighbourhood and to familiarize themselves with the location of the six landmark locations. During this learning phase, subjects were required to note the spatial relationships between the landmarks and to form a mental representation (i.e. cognitive map) of the virtual city. During the scanning session, in the experimental task, a recall of the learned landmarks from memory was required. Participants were asked to navigate to these locations using the most direct route (i.e. shortest distance), thereby using the mental representation of the city acquired during training. The start position within the virtual city varied randomly between the six landmarks on each functional neuroimaging trial. Participants commenced facing a sign that informed them of the target landmark that was to be reached. Start and target locations varied across trials to ensure the use of the cognitive map for efficient performance. The control condition consisted of instructions to follow a set of arrow signs within a virtual city that was similar to the one used in the experimental condition, but without embedded landmarks. The difference between the two conditions was therefore the spatial organization of the brick wall. This was done to remove any potential confounds (e.g. incidental topographical encoding) that may have influenced the experimental condition, all the while keeping the visual and motor demands of the task constant between conditions. Each control trial differed from the other in the route that was to be followed. The ratio of control to experimental trials was one for every six. For an example of the virtual environment, see Figure 4.10.1.

Image acquisition Magnetic resonance imaging was done on a 1.5 Tesla Siemens Sonata scanner (Siemens AG, Erlangen, Germany) using a 32-channel head coil. A high-

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resolution (1 mm3) T1-weighted 3D Gradient Echo structural image was acquired for each functional session (TE = 9.2 ms, TR = 22 ms, FOV = 256 mm, image matrix = 256 x 256, flip angle = 30 degrees, interleaved excitation). Functional images, using T2* weighted gradient echo (GE) echo planar imaging (EPI) sequence images were acquired for the blood oxygenation level dependent (BOLD) functional MRI measurements (TE = 50 ms, TR = 4500 ms, FOV = 256 mm, image matrix = 64 x 64, flip angle = 90 degrees, interleaved excitation). All 200 volumes consisted of 32 oblique slices (4 mm) and were positioned parallel to the hippocampus so as to cover the entire cerebrum and most of the cerebellum. The functional scan lasted 15 minutes. During this time participants performed the experimental (i.e. recall and navigate to target location) and control conditions (i.e. follow the arrow signs) in a block-design paradigm. The virtual environment was presented to participants through a mirror system attached to the head-coil that allowed viewing of a back-projected screen. Participants received a 4-button MRI compatible fiber-optic response pad in order to navigate at a constant speed within the environment. All participants completed a total of 18 experimental and 3 control trials during the functional scan. fMRI data processing and analysis Functional imaging data were processed using the in-house software package fMRIstat (Worsley et al., 2002; available at www.math.mcgill.ca/keith/fmristat). In order to increase the signal-to-noise ratio and the tolerance of the subsequent analysis steps to residual motion in the scans, and to minimize resampling artefacts, all images were motion-corrected by realigning all functional volumes to the third volume of that run and spatially smoothed with a 6-mm full-width at half-maximum Gaussian filter. Subsequently, a voxel-wise statistical analysis was performed. This was done by converting the BOLD data to percentage of the whole volume and by determining significant percent BOLD changes between the experimental and the control conditions at each voxel based on a linear model with correlated errors. A design matrix of the linear model containing the onset time and duration of each task condition was convolved with a hemodynamic

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response function modeled as a difference of two gamma functions, and corrected for slice-timing to coincide with the acquisition of each slice (Friston et al., 1998). Temporal and spatial drifts were removed by modeling them as an autoregressive process of degree 1. At each voxel, the autocorrelation parameter was estimated from the least squares residuals using the Yule-Walker equations, after a bias correction for correlations had been induced by the linear model. The autocorrelation parameter was first regularized by spatial smoothing, and then used to whiten the data and the design matrix. Then, the linear model was re- estimated using least squares on the whitened data to produce estimates of effects and their standard errors. A statistical map was calculated for each participant’s experimental condition (i.e. recall of route to and from target location) against the control condition (i.e. follow the arrow signs). The data were then normalized in the first- level individual analysis through linear registration to the Montreal Neurological Institute template (ICBM152) using an in-house algorithm (Collins et al., 1994), resulting in a t-statistical image for each subject. A cut-off t-value of 2.5 for a cluster size equal or greater to 25 voxels were applied to each subject’s contrast of interest obtained from the functional magnetic resonance imaging data, due to this forming the statistical threshold for significant activation clusters. For identification of the location of the functional imaging results, images were superimposed onto an average normalized (ICBM152) anatomical scan.

Local morphology and analysis of functional activation peaks The locations of the functional activation peaks in the parahippocampal cortex as observed in the navigational task were identified on a subject-by-subject basis and their location interpreted by reference to the morphology of the sulci of the collateral sulcal complex as described by Huntgeburth and Petrides (2012). According to this study, the collateral sulcal complex comprises the rhinal sulcus, the collateral sulcus proper, the parahippocampal extension of the collateral sulcus, and the occipital extent of the collateral sulcus. The rhinal sulcus forms the lateral limit of the entorhinal cortex that is located on the anterior portion of the

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parahippocampal gyrus, with the caudal end of the rhinal sulcus marking the posterior border of the entorhinal cortex. The parahippocampal cortex extends posterior to the entorhinal cortex and, therefore, the rostral origin of the anterior segment of the collateral sulcus proper provides an anatomical marker of the anterior limit of the parahippocampal cortex, differentiating it form the adjacent entorhinal cortex. Laterally, the collateral sulcus proper delineates the parahippocampal cortex from the adjacent fusiform gyrus. In 50% of cases, two segments of the collateral sulcus proper can be identified, an anterior and a posterior one, abbreviated as cos-1 and cos-2, respectively (Huntgeburth & Petrides, 2012). When the collateral sulcus proper can be divided into these two sulcal segments, the transition between the anterior and posterior segments occurs approximately around a y-coordinate of -33 in the right hemisphere, and around a y-coordinate of -35 in the left hemisphere. The two segments of the collateral sulcus proper thus form anatomical landmarks that may be used to differentiate between activation located in the anterior versus the posterior parahippocampal cortex: the anterior parahippocampal cortex lying medially along the anterior segment of the collateral sulcus proper, caudal to the entorhinal cortex, and the posterior portion of the parahippocampal cortex along the posterior segment of the collateral sulcus proper, rostral to the lingual gyrus. The area around the transition between the anterior and posterior segments of the collateral sulcus proper, where the two sulcal segments overlap, may be considered the separate, middle, portion of the parahippocampal cortex. The caudal end of the parahippocampal cortex is marked by the end of the collateral sulcus proper. The parahippocampal extension of the collateral sulcus first runs parallel and then transversely to, and finally joins the collateral sulcus proper, thereby forming the posterior boundary of the parahippocampal cortex and separating it from the adjacent lingual gyrus (Figure 4.10.2B). The posterior limit of the parahippocampal cortex coincides when viewed in the coronal plane with the rostral origin of the anterior calcarine sulcus and the caudal end of the splenium. This is also the level of the caudal end of the collateral sulcus proper and its junction with the parahippocampal extension of the collateral sulcus, separating the posterior part of the parahippocampal cortex from

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the medially located retrosplenial cortex of the posterior cingulate gyrus and the caudally situated cortex of the lingual gyrus. It is at this junction that the occipital extent of the collateral sulcus commences, often, in 91.25% expressed as a sulcal bifurcation within the sulcal depth (Huntgeburth & Petrides, 2012). Figure 4.10.2 illustrates the morphological landmarks of the collateral sulcal complex used as boundaries to differentiate the anterior versus posterior parahippocampal activation from the nearby lingual and fusiform gyrus. The t-statistical maps from the contrast experimental (navigation) condition versus control condition were examined. The voxel with the highest peak value of each of the observed activation clusters were identified. A spread of the activation cluster was taken into consideration when determining the location of the activation peak. The location coordinates of all the activation peaks observed along the parahippocampal cortex and the adjacent hippocampus, entorhinal and perirhinal cortex, as well as the fusiform and lingual gyri are presented in Tables 4.9.1 through 4.9.4. All coordinates are reported in MNI space: the medio-lateral dimension, x-coordinate, is shown in the sagittal plane, the rostro-caudal dimension, y-coordinate, in the coronal plane, and the dorsoventral dimension, z-coordinate, in the axial/horizontal plane.

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4.5 Results Comparison of the functional activity in the experimental condition in which subjects attempted to find the most direct way to a target location to activity in the control condition in which a path indicated by arrows was to be followed resulted in three clusters of activation peaks along the parahippocampal region. Two were identified in the posterior parahippocampal cortex and the other in its middle part. One of the two clusters in the posterior parahippocampal cortex was observed along the collateral sulcus proper, at its most caudal part. This cluster was observed in the left hemisphere in the majority (57 percent) of individuals (8/14 subjects; mean y = -41.7, SD ±2.71) while in the right hemisphere, it was observed in 29 percent (4/14) of subjects; mean y = -40.2, SD ±2.87). On a coronal plane, this posterior parahippocampal peak lies at the junction between the collateral sulcus proper and the parahippocampal extension of the collateral sulcus, just anterior to the rostral origin of the occipital extent of the collateral sulcus and the rostral origin of the anterior calcarine sulcus (Figure 4.10.2 and 4.10.3; Table 4.9.1). The second cluster of activation peaks lay in the sulcus of the parahippocampal extension of the collateral sulcus where it joins the collateral sulcus proper. This cluster was observed in the left hemisphere in 57 percent of individuals (8/14 subjects; mean y = -40, SD ±1.51) while in the right hemisphere, the posterior parahippocampal peak was observed in 36 percent of subjects (5/14; mean y = -39.8, SD ±1.48). This cluster of peaks also lay at the caudal ending of the collateral sulcus proper, just anterior to the rostral origins of the occipital extension of the collateral sulcus and the anterior calcarine sulcus (Figure 4.10.2 and 4.10.4; Table 4.9.2). Tables 4.9.1 and 4.9.2 provide an overview of the x, y, and z coordinates of the activation peaks observed in the posterior part of the parahippocampal cortex within the MNI standard space for individual subjects. The third cluster of activation peaks was identified within the middle portion of the parahippocampal cortex. This peak was observed in the right hemisphere of 36 percent of subjects (5/14 subjects; mean y = -34.8, SD ±1.79) and in the left hemisphere of 29 percent of subjects (4/14; mean y = -34.5, SD

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±3.0). When viewed on a coronal plane, this cluster of activation peaks lay along the collateral sulcus proper, just anterior to or at the height of the rostral origin of the parahippocampal extension of the collateral sulcus, in the area of transition of the first and second segments of the collateral sulcus proper, when these were present. When viewed in the sagittal plane, this activation cluster may be observed at the height of the body of the hippocampus. The first and second segments of the collateral sulcus proper may be formed by a shift of the course of the collateral sulcus proper in the anterior-posterior direction from a location on the basal surface to a location more medially. Figures 4.10.2 and 4.10.5 illustrate this cluster of activation peaks that falls along the transition part of the two segments of the collateral sulcus proper. Table 4.9.3 provides an overview of the x, y, and z coordinates of the activation peaks within the MNI standard space. Additional activation peaks observed in regions adjacent to the posterior and middle region of the parahippocampal cortex are listed in Table 4.9.4. Activation in the anterior part of the parahippocampal cortex, along the anterior collateral sulcus proper segment (cos-1), was observed in only 7% percent of subjects (2/14), in one in the right hemisphere and one in the left (subject 7 and 12, respectively). In addition, activation more rostral in the parahippocampal gyrus, that is where the entorhinal and perirhinal cortex lies, was observed in only two subjects; subject 7 had one activation peak in the right entorhinal cortex and subject 12 one in the right perirhinal cortex. These peaks were rostral to the collateral sulcus proper, medial to and along the rhinal sulcus which demarcates the entorhinal cortex. No other participants showed activation peaks in the entorhinal/perirhinal cortex or in the most anterior part of the parahippocampal cortex. In addition, subject 12 presented a single activation peak in the right amygdala and subject 7 had bilateral activation of the posterior hippocampus, caudal to the posterior end of the uncal notch. Two participants (subjects 4 and 7) showed an activation peak in the posterior hippocampus of the left hemisphere. No other participants showed hippocampal activation peaks. Furthermore, fifty percent of subjects exhibited activation peaks in the right fusiform gyrus and 21 percent in the left. Activation peaks were identified as fusiform gyrus activation

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when the locus of the activation peak fell laterally to the collateral sulcus proper. Twenty-one percent of participants showed activation peaks in the right lingual gyrus and 29 percent in the left. The activation peak was located in the cortex of the lingual gyrus when the locus of the activation peak fell clearly posterior to the caudal end of the collateral sulcus proper. In some cases the activation peak fell within the depth of the cortex, where it was clearly identified as falling along the portion of the cortex within the sulcal depth that belonged to the lingual gyrus (e.g. at the caudal end of the collateral sulcus proper, where the bifurcation of the occipital extend of the collateral sulcus proper occurs in the depth of the cortex, while not yet being visible on the surface of the brain). Table 4.9.4 provides more details on the additional activation that was observed in this study.

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4.6 Discussion This study examined in detail, on a subject-by-subject basis, the functional activation patterns along the parahippocampal gyrus (PHG) obtained during the performance of a navigation task in a virtual environment. The use of criteria established in a recent anatomical study of the sulcal landmarks delimiting the various parts of the PHG and its limits from the nearby lingual and fusiform gyri (Huntgeburth & Petrides, 2012) resulted in an accurate definition of the location of activation peaks related to spatial processing. The activation peaks fell within the posterior part of the PHG (Figure 4.10.2-4.10.5; Tables 4.9.1-4.9.3). No activation was observed medial to the rhinal sulcus anterior to the collateral sulcus proper, i.e. the region occupied by the entorhinal cortex. The absence of entorhinal cortex activation, which had been reported in a few earlier studies during navigation (Iaria et al, 2010), is most probably the result of the control task used that required guided navigation in the same environment, thus removing activity related to basic input into the medial temporal region. The experimental task required the mnemonic retrieval and use of spatial information from a previously learned environment during navigation and clearly activated selectively the posterior PHG where the parahippocampal cortex (PHC) lies. The first cluster of activation peaks (Figure 4.10.2-4.10.3; Table 4.9.1) was located in the caudal part of the collateral sulcus proper, rostral to the origin of the occipital extent of the collateral sulcus (Huntgeburth & Petrides, 2012), positioning it in the posterior portion of the PHC, just rostral to the lingual gyrus. A similar peak (x, y, z-coordinates: 32,-44,-4) observed by Arnold and colleagues (2014) was interpreted to reflect the recognition of landmarks or decoding of allocentric information. The second cluster (Figure 4.10.2 and 4.10.4; Table 4.9.2) fell medial to the first, along the parahippocampal extension of the collateral sulcus, at or only a few millimeters anterior to its junction with the collateral sulcus proper (Table 4.9.4), which marks the border with the lingual gyrus that has been related to the processing of visually presented stimuli such as buildings (Aguirre et al., 1996; 1998). The third activation cluster (Figure 4.10.2 and 4.10.5; Table 4.9.3) was consistently observed along the transition between the anterior

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and posterior segments of the collateral sulcus proper, a region here referred to as the middle PHC. This middle PHC is a new notion and is defined as the region medial to the overlap of the anterior and posterior segments of the collateral sulcus proper as established in the morphological investigation by Huntgeburth and Petrides (2012). The posterior PHC lies along the posterior segment, and the anterior PHC is marked by the anterior segment of the collateral sulcus proper. Hence the sulci of the collateral sulcal complex offer clear landmarks for defining an anterior, middle, and posterior PHC.

The posterior parahippocampal cortex The collateral sulcus proper and parahippocampal extension of the collateral sulcus (Figure 4.10.2B) provide important anatomical boundaries for the identification of the locus of activation clusters, attributing them to the PHC and separating them from the nearby cortex of the lingual gyrus. Arcaro and colleagues (2009) reported two visual field maps (PHC-1, PHC-2) in an anterior- to-posterior arrangement along what the authors considered the human PHC and reported an overlap with the parahippocampal place area (PPA). However, with respect to the local morphology (Huntgeburth & Petrides, 2012), the posterior map PHC-1 (x, y, z-coordinates: -27,-54,-5; +31,-52,-5) appears to lie caudal to the posterior limit of the collateral sulcus proper and may thus fall on the visual cortex of the lingual gyrus, whereas the rostral map PHC-2 (x, y, z-coordinates: - 28,-46,-5; +32,-44,-5) appears to fall along the posterior limit of the collateral sulcus proper occupying the caudalmost PHC. Functional neuroimaging studies have implicated the posterior PHC in the processing of scene and place information (Aminoff et al., 2007; Epstein & Kanwisher, 1998; Litman et al., 2009; Staresina et al., 2011). Specifically, the PPA, defined using functional localizer scans and a scene-selective region identified without localizer scans, have been located on the posterior PHC (Aguirre & D'Esposito, 1997; Epstein & Kanwisher, 1998; Köhler et al., 2002; Pihlajamaki et al., 2004; Staresina et al., 2011; Sulpizio et al., 2013). However, no clear anatomical definitions have been provided regarding what constitutes the

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posterior PHC (Aguirre & D'Esposito, 1997; Epstein & Kanwisher, 1998; Köhler et al., 2002; Pihlajamaki et al., 2004; Staresina et al., 2011; Sulpizio et al., 2013). Our results offer a precise anatomical definition of the location of spatial activity in the posterior PHC, providing a framework to investigate the hypothesis of functional subdivisions along the PHC (Litman et al., 2009; Sato & Nakamura, 2003) and a hypothesis by Epstein (2008) suggesting the existence of sub-regions within the PPA itself. Support for the latter was provided by a study by Baldassano and colleagues (2013) which showed stronger connectivity of the anterior PPA with the retrosplenial cortex and caudal inferior parietal lobule, and stronger connectivity of the posterior PPA with the lateral occipital complex and transverse occipital sulcus. However, the functionally defined PPA served as seed region to investigate connectivity, without reference to coordinates and/or anatomical boundaries. The illustrations provided (Figure 3, p.233) suggest that the seed region was within the posterior PHC and adjacent fusiform and lingual gyrus, which may explain the connectivity results and similar response-preference for scenes and objects of the posterior part, and greater response-sensitivity to scenes only of the anterior part of the PPA (Baldassano et al., 2013). Litman and colleagues (2009) examined response-sensitivity along the PHC by dividing it into four regions-of-interest of equal distance (y-coordinate: -22 to -53), with the anterior PHC border coinciding with the caudal part of the uncus. Their results showed the posteriormost PHC (y-coordinate: -47 to -53) responding strongest to scenes. Further anterior along the PHC, scene-preference decreased, while the response to objects was maintained (Litman et al., 2009). Buffalo and colleagues (2006) observed a similar response to scenes and objects in the posterior PHC, although the rostral limit of their ‘posterior PHC’ was not defined. The three segregated clusters of activation observed in this study suggest subdivisions along the anterior-to-posterior extent of the PHC, and within the posterior PHC, and provide valuable information about the location and extent of such subdivisions. Therefore, they may serve as regions-of-interest for further studies to disentangle the differential functional contribution to spatial memory of specific parts of the PHC.

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The middle parahippocampal cortex Support for a subdivision on the middle PHC, as observed here, comes from other functional neuroimaging. For instance, Staresina and colleagues (2011) observed a stronger responsiveness to scenes in what they termed the posterior PHC (x, y, z-coordinates: 27,-36,-9), and similar sensitivity to scenes and objects in what they referred to as mid-PHG (x, y-coordinates: 33,-30). However, their subdivisions were not based on anatomical landmarks and the mid-PHG comprised parts of the posterior perirhinal/entorhinal and parahippocampal cortex (Staresina et al., 2011). According to the present classification, the location of the activation peaks in what Staresina and colleagues termed posterior PHC is along the middle PHC at the transition between the anterior and posterior segments of the collateral sulcus proper, and their mid-PHG peak falls along the anterior segment of the collateral sulcus proper, and thus on the anterior PHC of the present study. Pihlajamaki and colleagues (2004) differentiated between anterior PHC involvement in the processing of novel objects (x, y, z-coordinates: 27,-28,- 15; -26,-30,-14) and posterior PHC response to spatial arrangements (x, y, z- coordinates: 20,-36,-8; -22,-40,-8). Their anterior PHC peak corresponds to that observed by Staresina and colleagues (2011), whereas the posterior peaks spread along what we called middle and posterior PHC. A detailed subject-by-subject examination of the activation peaks in relation to the segments of the collateral sulcus proper would be necessary to establish whether the pattern supports functional subdivisions along the PHC, as observed here. A navigation study by Xu and colleagues (2010) suggested involvement of the anterior PHC during the initial phase versus the posterior PHC throughout the navigational period. However, this study referred to all activation peaks solely as ‘parahippocampal cortex’ (y-coordinates: -23 to -41), with one reference to the anterior PHC corresponding to y-coordinates ranging from -24 to -35. Findings by Buffalo and colleagues (2006) support anterior PHC involvement, caudal to the entorhinal cortex, in spatial task performance, although the caudal limit of their anterior PHC lacked precise definition. The brief review above shows that a more accurate identification of the location of activation peaks is imperative for a better

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understanding of the structure-to-function organization of the PHC. The present study offers support for specific functional subdivisions, when engaged in a navigation task, and their relationship to local anatomical landmarks. In conclusion, the present study showed that the middle and posterior parts of the PHC, but not the anterior PHC and entorhinal cortex, were involved when scene-selective information necessary for navigation is processed, providing explicit landmarks for possible PHC subdivisions in future studies and hoping to establish a clear nomenclature based on morphological landmarks to refer to the different parts of the PHC.

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4.7 References Aguirre, G.K. & D'Esposito, M. (1997) Environmental knowledge is subserved by separable dorsal/ventral neural areas. The Journal of neuroscience, 17, 2512-2518

Aguirre, G.K., Detre, J.A., Alsop, D.C. & D'Esposito, M. (1996) The parahippocampus subserves topographical learning in man. Cerebral cortex, 6, 823-829.

Aguirre, G.K., Zarahn, E. & D'Esposito, M. (1998) An area within human ventral cortex sensitive to "building" stimuli: evidence and implications. Neuron, 21, 373- 383.

Amiez, C., Kostopoulos, P., Champod, A.S. & Petrides, M. (2006) Local morphology predicts functional organization of the dorsal premotor region in the human brain. The Journal of neuroscience, 26, 2724-2731.

Amiez, C. & Petrides, M. (2014) Neuroimaging evidence of the anatomo- functional organization of the human cingulate motor areas. Cerebral cortex, 24, 563-578.

Aminoff, E., Gronau, N. & Bar, M. (2007) The parahippocampal cortex mediates spatial and nonspatial associations. Cerebral cortex, 17, 1493-1503.

Andrews, T.J., Clarke, A., Pell, P. & Hartley, T. (2010) Selectivity for low-level features of objects in the human ventral stream. NeuroImage, 49,:703-711.

Arcaro, M.J., McMains, S.A., Singer, B.D. & Kastner, S. (2009) Retinotopic organization of human ventral visual cortex. The Journal of neuroscience, 29, 10638-10652.

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Arnold, A.E., Protzner, A.B., Bray, S., Levy, R.M. & Iaria, G. (2014) Neural network configuration and efficiency underlies individual differences in spatial orientation ability. J Cogn Neurosci, 26, 380-394.

Baldassano, C., Beck, D.M. & Fei-Fei, L. (2013) Differential connectivity within the Parahippocampal Place Area. NeuroImage, 75, 228-237.

Bohbot, V.D., Kalina, M., Stepankova, K., Spackova, N., Petrides, M. & Nadel, L. (1998) Spatial memory deficits in patients with lesions to the right hippocampus and to the right parahippocampal cortex. Neuropsychologia, 36, 1217-1238.

Buffalo, E.A., Bellgowan, P.S. & Martin, A. (2006) Distinct roles for medial temporal lobe structures in memory for objects and their locations. Learning & memory, 13, 638-643.

Epstein, R. & Kanwisher, N. (1998) A cortical representation of the local visual environment. Nature, 392, 598-601.

Epstein, R.A. (2008) Parahippocampal and retrosplenial contributions to human spatial navigation. Trends in cognitive sciences, 12, 388-396.

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Friston, K.J., Fletcher, P., Josephs, O., Holmes, A., Rugg, M.D. & Turner, R. (1998) Event-related fMRI: characterizing differential responses. NeuroImage, 7, 30-40.

Habib, M. & Sirigu, A. (1987) Pure topographical disorientation: a definition and anatomical basis. Cortex, 23, 73-85.

Huntgeburth, S.C. & Petrides, M. (2012) Morphological patterns of the collateral sulcus in the human brain. The European journal of neuroscience, 35, 1295-1311.

Iaria, G., Chen, J.K., Guariglia, C., Ptito, A. & Petrides, M. (2007) Retrosplenial and hippocampal brain regions in human navigation: complementary functional contributions to the formation and use of cognitive maps. The European journal of neuroscience, 25, 890-899.

Iaria, G., Fox, C.J., Chen, J.-K., Petrides, M. & Barton, J.J.S. (2008) Detection of unexpected events during spatial navigation in humans: bottom-up attentional system and neural mechanisms. European Journal of Neuroscience, 27, 1017- 1025.

Köhler, S., Crane, J. & Milner, B. (2002) Differential contributions of the parahippocampal place area and the anterior hippocampus to human memory for scenes. Hippocampus, 12, 718-723.

Litman, L., Awipi, T. & Davachi, L. (2009) Category-specificity in the human medial temporal lobe cortex. Hippocampus, 19, 308-319.

Lovell, M.R. & Collins, M.W. (1998) Neuropsychological assessment of the college football player. The Journal of head trauma rehabilitation 13:9-26

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Ploner, C.J., Gaymard, B.M., Rivaud-Pechoux, S., Baulac, M., Clemenceau, S., Samson, S. & Pierrot-Deseilligny, C. (2000) Lesions affecting the parahippocampal cortex yield spatial memory deficits in humans. Cerebral cortex, 10, 1211-1216.

Sato, N. & Nakamura, K. (2003) Visual response properties of neurons in the parahippocampal cortex of monkeys. Journal of neurophysiology, 90, 876-886.

Scoville, W.B. & Milner, B. (1957) Loss of recent memory after bilateral hippocampal lesions. Journal of neurology, neurosurgery, and psychiatry, 20, 11- 21.

Segal, E. & Petrides, M. (2013) Functional activation during reading in relation to the sulci of the angular gyrus region. The European journal of neuroscience, 38, 2793-2801.

Smith, M.L. & Milner, B. (1981) The role of the right hippocampus in the recall of spatial location. Neuropsychologia, 19, 781-793.

Squire, L.R. & Zola-Morgan, S. (1991) The medial temporal lobe memory system. Science, 253, 1380-1386.

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Van Hoesen, G.W. (1995) Anatomy of the medial temporal lobe. Magnetic resonance imaging, 13, 1047-1055.

Worsley, K.J., Liao, C., Aston, J., Petre, V., Duncan, G.H., Morales, F. & Evans, A.C. (2002) A general statistical analysis for fMRI data. NeuroImage, 15, 1-15.

Xu, J., Evensmoen, H.R., Lehn, H., Pintzka, C.W. & Haberg, A.K. (2010) Persistent posterior and transient anterior medial temporal lobe activity during navigation. NeuroImage, 52, 1654-1666.

Yousry, T.A., Schmid, U.D., Alkadhi, H., Schmidt, D., Peraud, A., Buettner, A. & Winkler, P. (1997) Localization of the motor hand area to a knob on the precentral gyrus, a new landmark. Brain, 120, 141-157.

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4.8 Acknowledgements The authors thank Dr. Rhonda Amsel and Dr. Veronika Zlatkina for helpful discussions on the project.

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4.9 Tables

Table 4.9.1 Activation peaks of individual subjects in stereotaxic coordinates of the Montreal Neurological Institute (MNI) space observed at the posterior origin of the collateral sulcus proper in the posterior parahippocampal cortex in the left and right hemispheres. Data are the maxima of BOLD signal activation peaks. Only activation peaks with t-values above 2.5 and a cluster size equal or greater to 25 voxels were included, i.e. statistically significant peaks.

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Table 4.9.2 Activation peaks of individual subjects in stereotaxic coordinates of the Montreal Neurological Institute (MNI) space observed in the parahippocampal extension of the collateral sulcus proper in the posterior parahippocampal cortex in the left and right hemispheres. Data are the maxima of BOLD signal activation peaks. Only activation peaks with t-values above 2.5 and a cluster size equal or greater to 25 voxels were included, i.e. statistically significant peaks.

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Table 4.9.3 Activation peaks of individual subjects in stereotaxic coordinates of the Montreal Neurological Institute (MNI) space observed along the transition between the anterior (cos-1) and posterior (cos-2) segments of the collateral sulcus in the middle parahippocampal cortex in the left and right hemispheres. Data are the maxima of BOLD signal activation peaks. Only activation peaks with t-values above 2.5 and a cluster size equal or greater to 25 voxels were included, i.e. statistically significant peaks.

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Table 4.9.4 Activation peaks of individual subjects adjacent to peaks in the middle and posterior parahippocampal cortex (reported in Tables 4.9.1-4.9.3), in stereotaxic coordinates of the Montreal Neurological Institute (MNI) space observed in the in the left and right hemispheres. Data are the maxima of BOLD signal activation peaks. Only activation peaks with t-values above 2.5 and a cluster size equal or greater to 25 voxels were included, i.e. statistically significant peaks.

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4.10 Figures

Figure 4.10.1 Experimental and control tasks. Illustration of the virtual environment used in the present study. A, shows a schematic outline of the virtual environment (top-down view). B, presents the starting position of one of the six landmark targets that participants were asked to navigate towards from the first- person perspective. C, shows the control condition in which the subjects simply followed a series of arrow signs.

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Figure 4.10.2 Activation peaks along the parahippocampal cortex. A, Illustration of the mean coordinates (and standard deviations) in MNI space for the three clusters of activation peaks, across subjects and hemispheres, in the coronal (y-coordinates) and axial/horizontal plane (z-coordinates). Solid and stippled lines in brown and green along the top and bottom of the grid indicate the average position, across hemispheres, of the rhinal sulcus, collateral sulcus proper (including its anterior and posterior segments), the parahippocampal extension 197

and occipital extent of the collateral sulcus, and the anterior calcarine sulcus. See also Tables 1-3 for the individual and average peak coordinates. B, Schematic representation of the three clusters of activation peaks along a schematic drawing of the parahippocampal cortical region, including the sulcal segments of the collateral sulcal complex used to differentiate between anterior, middle, and posterior parahippocampal cortical activation. Illustration is not drawn to scale. In both sections A and B, the three clusters of activation peaks are indicated: within the parahippocampal extension of the collateral sulcus (cos-ph; RED), the posterior part of the collateral sulcus proper (cos; BLUE), and halfway along the collateral sulcus proper (ORANGE), in the middle part of the parahippocampal cortex, i.e. at the point of transition between the anterior and posterior segments of the collateral sulcus proper (cos-1 and cos-2, respectively). Abbreviations of interest: aCalS, anterior calcarine sulcus; cos, collateral sulcus proper, cos-1, anterior segment of the collateral sulcus proper; cos-2, posterior segment of the collateral sulcus proper, cos-o, occipital extent of the collateral sulcus; cos-ph, parahippocampal extension of the collateral sulcus; rhs, rhinal sulcus.

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Figure 4.10.3 Activation peaks along the posterior parahippocampal cortex. Illustration of the functional activation peaks along the posterior part of the collateral sulcus proper (see yellow arrows; also see Figure 4.10.2, blue marking) in the left and right hemisphere in the coronal (y-coordinates) and the axial/horizontal plane (z-coordinates) in individual participants within MNI space.

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Figure 4.10.4 Activation peaks along the posterior parahippocampal cortex. Illustration of the functional activation peaks along the parahippocampal extension of the collateral sulcus (see yellow arrows; also see Figure 4.10.2, red marking) in the left and right hemisphere in the coronal (y-coordinates) and the axial/horizontal plane (z-coordinates) in individual participants within MNI space.

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Figure 4.10.5 Activation peaks along the middle parahippocampal cortex. Illustration of the functional activation peaks halfway along the collateral sulcus proper (see yellow arrows; also see Figure 4.10.2, orange marking) in the left and right hemisphere in the coronal (y-coordinates) and the axial/horizontal plane (z- coordinates) in individual participants within MNI space.

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Chapter Five 5. Consequences of mild traumatic brain injury on functional activation patterns during navigation in a virtual-reality environment: an fMRI study

Huntgeburth S.C., Chen J.-K., Petrides M.*, and Ptito A* (2015). Consequences of mild traumatic brain injury on functional activation patterns during navigation in a virtual-reality environment: an fMRI study. The manuscript has been submitted for publication.

*Senior authors

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5.1 Prelude The principal focus of the functional magnetic resonance imaging (fMRI) study of Chapter 4 was to examine the relation of activation during navigation and the sulcal patterns. This study found that there are three clusters of peaks along the parahippocampal cortex during navigation, two in the posterior parahippocampal cortex and one along the middle parahippocampal cortex. These results provide support for the notion that there are subdivisions along the parahippocampal cortex. No activation peaks were observed in the anterior parahippocampal cortex or in the entorhinal cortex. This differentiation in location of the clusters was made possible by the morphological studies presented in Chapters 2 and 3. Furthermore, the study in Chapter 4 informed the study in Chapter 5 of the presence of, and precise location of the middle cluster of activation peaks observed in healthy subjects during navigation. The study in Chapter 5 examined the consequence of having sustained a mild traumatic brain injury on brain activation patterns. As the parahippocampal cortex has been implicated to play an important role in the processing of scene-relevant information, and as the medial temporal lobes, of which the parahippocampal gyrus forms a great part are vulnerable to head trauma, it was of great interest to see if information processing (as measured by presence of activation peaks obtained through functional neuroimaging) is the same in participants who have and who have not sustained a mild head trauma.

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5.2 Abstract Little is known about the consequences of mild traumatic brain injury (mTBI) on functional cerebral activation patterns during navigation. The present functional magnetic resonance imaging study examined functional activation patterns during navigation within a virtual-reality environment in healthy individuals and subjects having sustained mTBI. Both groups performed the tasks at comparable speeds and recruited similar brain regions. However, the percent blood-oxygen level dependent signal changes were significantly reduced in the mTBI group. The brain regions that showed a significant reduction in activation in the mTBI group, relative to the control group, included the right parahippocampal and retrosplenial cortex, right caudate nucleus, right dorsolateral prefrontal cortex, and left middle parahippocampal cortex. The results also revealed significantly greater activation in the mTBI group, not observed in the control group, in visual association areas in the right lingual gyrus and the fusiform gyrus, bilaterally. In conclusion, although comparable brain activation patterns were largely observed in the mTBI group, activation was decreased in several brain regions that are known to be key for navigation and additional increased activation was observed in certain visual association areas that may reflect compensatory mechanisms to carry out the task and achieve the normal behavioral performance observed in this group.

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5.3 Introduction Mild traumatic brain injury (mTBI) is a serious health concern, accounting for the majority (i.e. 70-90 percent) of all treated brain injuries in the world, and 100-300 people per 100,000 are treated for mTBI in hospital settings (Holm et al., 2005), although this incidence rate is thought to be low due to under-reporting (Gosselin et al., 2006; Holm et al., 2005). The majority of individuals who sustain mTBI are adolescent and young adult males (Holm et al., 2005). Generally, no structural abnormalities are observable on conventional neuroimaging scans, and individuals show recovery within the initial 3-12 month post-injury period (Holm et al., 2005). However, a small proportion (i.e. approximately 15 percent) of individuals continue experiencing persistent cognitive problems (Bernstein, 1999; Carroll et al., 2004). In addition, cumulative mTBI’s have been shown to lead to more severe, long-lasting cognitive impairments (Gaetz et al., 2000; Rabadi & Jordan, 2001). Therefore, a better understanding of the influence that mTBI has on the brain is of great importance, especially at the early post-injury stage. This would allow best-practice treatments to be established particularly in subjects likely to sustain multiple injuries (e.g., professional as well as amateur athletes). The inferior and posterior parts of the frontal lobe and anterior and medial regions of the temporal lobe are especially vulnerable to damage after head injury because of the edge created by the sphenoid bone (Bigler, 2000). Enlargement of the temporal horn of the lateral ventricle and atrophy in the volume of the hippocampus have been reported in individuals who have sustained traumatic brain injury (TBI) compared to healthy control individuals (Bigler et al., 1997). That study by Bigler and colleagues (1997) included participants who scored from the mild to the severe range on the Glasgow Coma Scale (GCS), a measure used to gauge the severity of a TBI (i.e. GCS range: 3-15; mild: 13-15; moderate: 9-12; severe: 3-8). They divided their participants into two groups; participants in the ‘early’ group (i.e. within 100 days of having sustained a TBI) presented with an average GCS score of 7.1, and in the ‘late’ group (i.e. after 100 days of sustaining a TBI) exhibited an average score of 8. While enlargements of the temporal horn were found in the ‘early’ and ‘late’ groups, hippocampal damage was observed

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only in the late group (Bigler et al., 1997), suggesting that the effect of a TBI may be progressive. The medial part of the temporal lobe plays a key role in memory (Bohbot & Corkin, 2007; Scoville & Milner, 1957, 2000). Damage to the right medial temporal lobe that includes the hippocampus, the entorhinal cortex and parahippocampal cortex impairs performance on object-location memory (Ploner et al., 2000; Smith et al., 2011, 1995; Smith & Milner, 1981, 1989), and undermines navigational abilities (Bohbot et al., 2000; Bohbot & Corkin, 2007; Bohbot et al., 1998; Habib & Sirigu, 1987; Maguire et al., 1996). Given the vulnerability of the medial temporal lobe region to damage following trauma, and the key role that it plays in spatial memory processing, it is of great interest to examine the influence of TBI on the functional activation patterns observed during navigation. Little is known to date about the consequences of mTBI on functional brain activity patterns related to navigation in the environment. To date, the two functional neuroimaging studies that have compared performance speed and functional activation patterns in mTBI and control participants in a navigation paradigm have observed somewhat different results (Saluja et al., 2015; Slobounov et al., 2010). Both studies showed that mTBI, in the absence of differences in performance speed (i.e. time to complete the navigation task), leads to the recruitment of additional, compensatory cortical regions compared to control subjects (Saluja et al., 2015; Slobounov et al., 2010). Slobounov and colleagues (2010) examined an adult population during a navigation task where participants were asked to encode and subsequently recall a set of paths to reach a target landmark. They observed additional activation only during encoding, and not retrieval of the learned routes in the parietal cortex, right dorsolateral prefrontal cortex, and right hippocampus (Slobounov et al., 2010). In contrast, Saluja and colleagues (2015) investigated adolescents during the performance of a navigation task, which required the retrieval of information from a previously formed cognitive map. Their results found less intense activation in adolescent mTBI than control subjects in the retrosplenial cortex, thalamus and posterior parahippocampal cortex, bilaterally, and in the right dorsolateral prefrontal cortex

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and left precuneus, while increased activation was observed in the left hippocampus and right middle temporal gyrus. The present study therefore set out to investigate the consequences of mTBI on brain activity of an adult population during navigation in a virtual- reality environment to see whether activation changes are evident between the control and mTBI individuals at an early stage of trauma. It is hypothesized that mTBI will lead to alterations in the intensity of task-related activation measured with functional magnetic resonance imaging. Of particular interest were changes in the parahippocampal gyrus and other key regions involved in navigation, such as the retrosplenial cortex, the prefrontal cortex, and the caudate nucleus (Boccia et al., 2014; Iaria et al., 2003, 2007; Maguire et al., 1998, 2006). As the effects of mTBI can be subtle, early identification of possible changes in activation patterns is necessary for clinicians and researchers alike to improve treatment and develop individualized rehabilitation plans.

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5.4 Materials and methods Participants A total of twenty eight male university athletes, fourteen with a diagnosis of mTBI and fourteen control participants matched for sex and age, were included in this study. All participants were athletes recruited from ice-hockey, football, or soccer teams. The fourteen mTBI participants had sustained a sport-related mTBI and the injury was identified first by a team therapist on the field, and subsequently a diagnosis was given by trained medical personnel. All mTBI athletes were recruited for the study within 72 hours post-injury and only participants not taking any medication at the time of the study were included. The control participants had not sustained an mTBI at least during the present season. The severity of post-concussive symptoms was assessed for each participant using a 21-item symptom checklist adapted from the Post-Concussion Symptom (PCS) Scale-Revised (Lovell & Collins, 1998) before the functional magnetic resonance imaging (fMRI) session. Participants were asked to rate their symptoms on the PCS scale (severity ranging from one to six) for the three days prior to the study. To assess depressive mood, the Beck Depression Inventory-II (BDI-II; Beck et al., 1996) was completed by all participants. All participants were right handed, had no history of neurological and/or psychiatric disorders and did not use any medication. Table 5.9.1 provides the demographics and clinical characteristics as well as performances (i.e. reaction time) for the two groups. Approval for the study was provided by the Research Ethics Board of the Montreal Neurological Institute and Hospital and all subjects gave written informed consent. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Task and procedure Participants engaged in a navigation task within a virtual-reality environment which was created using game editor software 3D GameStudio A6 (Conitec

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Datasystems, Inc. La Mesa, CA, USA). It represented a small virtual city formed by blocks of brick walls of different sizes and shapes but of the same texture and color, a blue sky, and a grey floor. Six easily distinguishable landmarks (i.e. a church, clinic, bank, post office, supermarket, police station) were embedded in the brick walls and distributed across the virtual city. Participants navigated within this environment in the first-person view. Figure 5.10.1 provides an example of the virtual environment and the landmarks. Prior to scanning, all participants engaged in a training session in which they could familiarize themselves with the virtual environment. The instructions were to locate and learn the spatial relationship between the embedded landmarks by navigating freely in the virtual environment. All participants started from the same position, at the center of the city facing the same direction. The training phase was intended to allow the subjects to become accustomed to moving around and to orient themselves within the virtual environment, in the process of which they formed a cognitive map of the virtual city. During the experimental task, participants were asked to recall from memory the location of the learned landmarks and to navigate to these locations using the most direct route (i.e. the most efficient path / the shortest distance). In order to achieve this, they had to use the mental representation of the virtual city, which they had formed during the training session. Participants started randomly on each recall trial during the fMRI session at one of the six landmarks facing a sign that indicated the target landmark they needed to reach (see Fig. 5.10.1). Both the starting and the target locations varied across trials to ensure that the use of the cognitive map would be the only efficient way to perform the task. In the control condition, participants were asked to follow directions as indicated by a set of arrow signs (Fig. 5.10.1). The appearance of the virtual city (i.e. color and texture of the wall, sky, and floor) was the same as in the experimental condition, the only difference being the spatial organization of the wall blocks, which had no embedded landmarks. This was done to ensure that any incidental topographical encoding of this environment would not contribute to the formation and use of the cognitive map explicitly required during the

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experimental condition, while controlling for visual and motor information. During the functional scanning, one trial of the control condition was introduced for every six trials of the experimental condition. Each control trial differed from the others in terms of the route the participants were asked to follow.

Image acquisition Images were acquired using a 1.5 Tesla Siemens Sonata scanner (Siemens AG, Erlangen, Germany) and a 32-channel head coil. For anatomical localization of the functional data, high-resolution (voxel size = 1 x 1 x 1 mm) T1-weighted 3D Gradient Echo structural images were acquired for each session (TE = 9.2 ms, TR = 22 ms, FOV = 256 mm, image matrix = 256 x 256, flip angle = 30 degrees, interleaved excitation). Functional data related to the cognitive map task was acquired using blood oxygenation level dependent (BOLD) functional MRI by means of a T2* weighted gradient echo (GE) echo planar imaging (EPI) sequence (TE = 50 ms, TR = 4500 ms, FOV = 256 mm, image matrix = 64 x 64, flip angle = 90 degrees, interleaved excitation). A total of 200 volumes were acquired, each volume consisting of 32 oblique slices (4 x 4 x 4 mm) positioned parallel to the hippocampus, covering the entire cerebrum and most of the cerebellum. During the 15 minute functional scan participants performed a total of 18 experimental trials (i.e. recall of location) and four control trials (i.e. follow-the-arrow) in a block-design paradigm. Each trial consisted of one recall task (i.e. navigate from one location to another). Six experimental trials were performed in succession followed by one control trial. While in the scanner, participants viewed the virtual environment back projected onto a screen through a mirror system that was attached to the head coil. Navigation occurred at a constant speed using a 4- buttom MRI compatible fiber-optic response pad (Current Designs, Philadelphia, USA). Furthermore, all participants were subjected to a routine MRI examination that was evaluated by a clinical neuroradiologist for obvious signs of axonal injury and/or abnormal signal intensity in the brain. This examination included dual axial T2-weighted turbo spin echo (TSE) sequence (TE[1] = 13 ms, TE[2] =

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81ms, TR = 3910 ms, FOV = 256 mm, image matrix = 256 x 256, flip angle = 150 degrees), axial fluid attenuated inversion recovery (FLAIR) sequence (TE = 66ms, TR = 9000 ms, FOV = 256 mm, image matrix = 256 x 256, flip angle = 150 degrees), and the T1-weighted 3D gradient echo images acquired as part of the functional scans.

Processing and analysis of fMRI data All functional data were processed using the in-house software package fMRIstat (Worsley et al., 2002). The data was corrected for motion by realigning all functional volumes to the third volume of that run. Images were then spatially smoothed using a 6-mm full-width at half-maximum Gaussian filter to increase the signal-to-noise ratio of the data, increase the tolerance of the subsequent analysis steps to residual motion in the scans, and to minimize resampling artefacts. Subsequently, a voxel-wise statistical analysis was performed, by first converting the blood- oxygen level dependent (BOLD) data to percentage of the whole volume. Significant percent BOLD changes between experimental and control conditions were determined at each voxel based on a linear model with correlated errors. A design matrix of the linear model containing the onset time and duration of each task condition was convolved with a hemodynamic response function modeled as a difference of two gamma functions and corrected for slice- timing to coincide with the acquisition of each slice (Friston et al., 1998). Temporal and spatial drifts were removed by modeling them as an autoregressive process of degree 1. At each voxel, the autocorrelation parameter was estimated from the least squares residuals using the Yule-Walker equations, after a bias correction for correlations had been induced by the linear model. The autocorrelation parameter was first regularized by spatial smoothing, and then used to whiten the data and the design matrix. Then, the linear model was re- estimated using least squares on the whitened data to produce estimates of effects and their standard errors. For each participant, a statistical map of the experimental condition (i.e. location recall) against the control condition (i.e. follow-the-arrow) was constructed. To obtain the average group t map, data from

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the first-level individual analysis were first normalized through linear registration to the Montreal Neurological Institute template (ICBM152) using an in-house algorithm (Collins et al., 1994). For the group effects, the normalized data of each participant was combined in a second-level analysis using a mixed effects linear model with fixed effects standard deviations taken from the previous analysis. A random effects analysis was performed by first estimating the ratio of the random effects variance to the fixed effects variance and subsequently regularizing this ratio by spatial smoothing with a Gaussian filter. The variance of the effect was estimated by the smoothed ratio multiplied by the fixed effects variance. The amount of smoothing was chosen to achieve 100 effective degrees of freedom. The threshold for the resulting t statistic images was determined by using the minimum given by a Bonferroni correction and random field theory to correct for multiple comparisons, taking into account the non-isotropic spatial correlation of the errors (Worsley, 2005). Functional imaging results were superimposed onto the average normalized (ICBM152) anatomical scan for their group (mTBI and/or healthy control group). The threshold for a single peak of activation was a t-value ≥ 4.98 (p < 0.001 uncorrected, which corresponds to a corrected p < 0.05). The threshold for clusters of sizes equal to or greater than 80 voxels (638 mm3) to reach significance of a p < 0.001 uncorrected (corresponding approximately to a corrected p < 0.05) was set at a t-value of ≥ 3.17 for the voxels. In this case the coordinate representing the highest value within the cluster is reported. Region of interest analyses were conducted and the BOLD signal intensity was extracted from the activation peaks obtained from the t-statistical maps for the comparison between the experimental and control task for each group and an independent samples t-test was conducted using the statistical software program SPSS for Windows (version 21) to explore whether differences exist between the healthy control and the mTBI group.

Analysis of anatomical location of fMRI activation peaks The morphological structures of the cortex within which activity was observed were interpreted by reference to the recent MRI atlas of the sulci and gyri of the

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human brain in MRI standard stereotaxic space (Petrides, 2012), as well as by using prior studies of the sulci of the orbitofrontal cortex (Chiavaras et al., 2001), the precentral sulcal complex (Germann et al., 2005), the parietal and occipital lobes (Segal & Petrides, 2012; Zlatkina & Petrides, 2010), the cingulate region (Amiez et al., 2013; Amiez & Petrides, 2014), and the sulci of the collateral sulcal complex (Huntgeburth and Petrides, 2012).

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5.5 Results Behavioral Results Comparison of the mTBI group of athletes with the group of non-brain injured control participants did not differ significantly in age (mTBI group: mean age = 21.1 years, standard deviation (SD) = 1.77; Control group: mean age = 21.1 years,

SD = 2.14; t(26) = 0.096, p = 0.92). The mTBI group had experienced a significantly greater number of concussions than the control group (mTBI group: mean number of concussions = 1.9, SD = 1.86; Control group: mean number of concussions = 0.2; SD = 0.43; t(26) = -3.363, p = 0.002) and presented with significantly higher scores as measured by the post-concussion symptoms (PCS) scale (mTBI group: mean = 25.0, SD = 15.18; Control group: mean = 1.5, SD =

1.74; t(26) = -5.756, p = 0.000). While brain injured athletes obtained higher scores on the Beck Depression Inventory-II (mTBI group: mean = 5.9, SD = 5.50;

Control group: mean = 1.4, SD = 1.86; t(1,26) = -2.989, p = 0.008), this difference was considered not clinically significant since the scores of both groups fell within what is defined as the ‘normal’ range (Beck et al., 1996). No difference was observed between the groups with regard to performance measures, i.e. the time taken by the subjects to complete all 18 trials measured as reaction time (mTBI group: mean = 418.1 milliseconds, SD =

118.02; Control group: mean = 362.8 milliseconds, SD = 66.35; t(26) = -1.530, p = 0.137). A Pearson’s correlation analysis demonstrated a positive correlation between both symptom score measures, i.e. PCS and BDI-II (r28 = 0.74, p < 0.001), with higher BDI-II scores linked to higher PCS scores. No correlation was observed between PCS scores and RT (r28 = 0.25, p = 0.20) and between BDI-II scores and RT (r28 = -0.01, p = 0.97). Table 5.9.1 provides a list of these results.

Structural Magnetic Resonance Imaging Results The evaluation of the structural scans (T1, T2, and FLAIR) by a clinical neuroradiologist yielded normal results for all participants with regard to signal intensity and diffuse axonal injury.

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Functional Magnetic Resonance Imaging Results Group analyses Table 5.9.2 presents a list of the functional activation peaks. Peaks reaching the statistical significance threshold for a single peak of activation of t ≥ 4.98 for a p < 0.001 uncorrected (corresponding approximately to a corrected p < 0.05) are presented. An asterisk beside the t-value in Table 5.9.2 indicates significance reached at the cluster threshold; the peak coordinate representing the highest value within a cluster size equal to or greater than 80 voxels (638 mm3) reaching a threshold of t ≥ 3.17 for a p < 0.001 uncorrected (corresponding approximately to a corrected p < 0.05). In addition, to show that the mTBI and control groups both showed activation in corresponding regions, albeit to a less intense degree, the superscript letter ‘a’ indicates that upon lowering the threshold, activation was observed. These activation peaks did not reach statistical significance at neither the single peak nor the cluster threshold level (Table 5.9.2). A t-statistical analysis was conducted comparing the percent BOLD signal change obtained with fMRI by the control group for the contrasts experimental versus control conditions. Significant activation peaks were observed in both hemispheres within the angular gyrus in the inferior parietal lobule, posterior cingulate cortex (area 23), region of the posterior cingulate cortex/parieto- occipital cortex, retrosplenial cortex (BA29/30), middle and posterior parts of the parahippocampal cortex, premotor cortex (area 6), region of the mid-dorsolateral prefrontal cortex (mid-DLPFC) and area 8, anterior insular cortex/caudalmost ventrolateral prefrontal cortex (VLPFC), frontopolar cortex, and the body of the caudate nucleus (see Table 2). Unilateral activation was found in the left mid- cingulate cortex, right precuneus (area 7) on the medial surface of the parietal lobe, as well as right anterior mid-cingulate cortex (Table 5.9.2). A t-statistical analysis comparing the percent BOLD signal change obtained with fMRI by the mTBI group for the contrasts experimental versus control conditions showed significant activation peaks in both hemispheres within the angular gyrus in the inferior parietal lobule, region of the posterior cingulate cortex/parieto-occipital cortex, retrosplenial cortex (BA29/30), posterior part of

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the parahippocampal cortex, lingual gyrus, fusiform gyrus, anterior insular cortex/caudalmost ventrolateral prefrontal cortex (VLPFC), frontopolar cortex, and cerebellum. Unilateral activation was found in the left mid-cingulate cortex, left caudal DLPFC above the inferior frontal sulcus, and the right precuneus (area 7) on the medial surface of the parietal lobe, right posterior cingulate cortex (area 23), and right anterior mid-cingulate cortex.

Region of interest analyses Two region-of-interest (ROI) analyses were carried out. The first was conducted for the areas known to be important for navigation (Boccia et al., 2014; Iaria et al., 2003, 2007; Maguire et al., 1998; Rauchs et al., 2008; Spiers & Maguire, 2006), namely the retrosplenial cortex, parahippocampal cortex, mid-dorsolateral prefrontal cortex, and caudate nucleus in order to see whether, within these regions, percent BOLD signal change differences exist between the control and the mTBI groups. These regions had shown significant t-statistical activation peaks in the control group (see Table 5.9.2). Significant differences in the percent BOLD activation signal were in fact observed between the control and mTBI group. A greater percent BOLD signal change in the control compared to the mTBI group was observed in the right retrosplenial cortex (control group: 8, -52,

8; mTBI group: 10, -48, 6; t(26) = 2.177, p = 0.039), right posterior parahippocampal cortex (control group: 22, -40, -8; mTBI group: 34, -38, -10; t(26) = 2.573, p = 0.016), right dorsolateral prefrontal cortex (area 9/46 and area 8)

(control group: 46, 22, 40; mTBI group: subthreshold activation 44, 24, 36; t(26) = 2.477, p = 0.02), left middle parahippocampal cortex (control group: -32, -34, -14; mTBI group: not observed; t(26) = 4.615, p = 0.000) and right caudate nucleus (control group: 16, -10, 22; mTBI group: subthreshold activation at 14, -10, 16; t(26) = 2.130, p = 0.043). Figures 5.10.2 and 5.10.3 illustrate these findings and Table 5.9.2 lists the functional activation peaks within the standard stereotaxic space of the Montreal Neurological Institute. For the left middle parahippocampal peak, no peak coordinate could be determined despite lowering the threshold. In

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this case, the peak coordinate from the control group was used to derive the percentage BOLD signal change (see Fig. 5.10.3a). The t-statistic examining the significant activation patterns in the mTBI group showed several activation peaks which did not reach significance in the control group (see Table 5.9.2). In order to see the difference in the percent BOLD activation signal between the groups, a second ROI analysis was carried out for the peaks in the fusiform and lingual gyri. Significant differences in the strength of the percentage BOLD signal change were seen between the groups, with the mTBI group showing increased BOLD signal changes compared to the control group. These included the left fusiform gyrus (mTBI group: -28, -52, -10; control group: subthreshold activation at -34, -52, -12; t(26) = -2.261, p = 0.032), right fusiform gyrus (mTBI group: 24, -58, -10; control group: not observed; t(26) = -2.508, p = 0.019), and right lingual gyrus (mTBI group: 14, -82, -4; control group: subthreshold activation at 21, -80, 0; t(26) = -2.380, p = 0.025). Figure 5.10.4 illustrates the main findings and Table 5.9.2 lists the functional activation peaks within the standard stereotaxic space of the Montreal Neurological Institute. For the right fusiform gyrus, no peak coordinate could be determined despite lowering of the threshold. In this case, the peak coordinates from the control group was used to derive the percentage BOLD signal change (see Fig. 5.10.4a).

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5.6 Discussion The present fMRI study used a virtual-reality environment to assess, within the adult population and at an early stage of trauma, the presence of altered cerebral activation as a consequence of mTBI. In the healthy brain, previous studies had shown that, during navigation, there are brain activation increases in the parahippocampal region and related retrosplenial cortex, the dorsolateral prefrontal cortex, and the caudate nucleus (Boccia et al., 2014; Iaria et al., 2003, 2007; Maguire et al., 1998; Rauchs et al., 2008; Spiers & Maguire, 2006). In the present study, as expected, the control group showed a robust activation signal in these task-related brain regions, but the mTBI group showed reduced activation compared to the control group in several regions: the posterior parahippocampal and retrosplenial cortex, the dorsolateral prefrontal cortex, and caudate nucleus in the right hemisphere, as well as in the middle parahippocampal cortex in the left hemisphere (Figs. 5.10.2 and 3, Table 5.9.2). Furthermore, increased activation was observed in the mTBI compared to the control participants in the posterior visual association cortical regions of the fusiform gyrus, bilaterally, and in the right lingual gyrus (Fig. 5.10.4, Table 5.9.2). Note that these changes in functional activation signal intensity were observed in the absence of differences between control participants and mTBI subjects in the time to navigate to particular landmarks within the virtual environment. In the parahippocampal region, the present detailed analysis aided by the sulcal patterns of this region located the activation decrease in the mTBI group in the right posterior and, to an even greater extent, in the left middle parahippocampal cortex (Figs. 5.10.2 and 3, Table 5.9.2). Note that a particular type of cortex, the parahippocampal cortex, occupies the posterior part of the parahippocampal gyrus (and not the entorhinal cortex which is observed in its anterior part). Thus, the present findings suggest particular dysfunction of the parahippocampal cortex in the mTBI subjects. Changes in this region may be reflective of difficulties in spatial memory processing, as the posterior parahippocampal region has been shown to be crucial for object-location memory (Ploner et al., 2000; Smith et al., 2011; Smith & Milner, 1981, 1989) and

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navigational abilities (Bohbot et al., 2000; Bohbot & Corkin, 2007; Bohbot et al., 1998; Habib & Sirigu, 1987; Maguire et al., 1996). A recent study in our laboratory (Huntgeburth et al., in preparation), which examined the structure- function relationship along the parahippocampal gyrus in healthy individual subjects during navigation found activation clusters that related to specific morphological parts of the collateral sulcus proper: along the middle and the posterior parahippocampal cortex. This finding supported the notion of at least two potential subdivisions along the parahippocampal cortex important for spatial processing and navigation. The posterior parahippocampal cortex is thought to be preferentially responsive to scene-relevant information (Epstein & Kanwisher, 1998; Litman et al., 2009), while a gradual decrease in scene-preference is observed the further anterior along the parahippocampal cortex the signal is measured, while the response to objects per se is maintained (Litman et al., 2009). The finding of the present study that the middle and the posterior parahippocampal cortex were significantly recruited, bilaterally, by the control group suggests that at least two functional parahippocampal subregions are necessary for processing information (e.g. related to scenes/places and objects) relevant for successful navigation in the healthy brain and that these regions are under-responsive as a consequence of mTBI. In normal subjects, it has been shown that navigation depends on two distinct but complementary strategies: a spatial strategy based on declarative memory and supported by the hippocampal and parahippocampal regions of the medial temporal lobe that make possible the creation and recalling of a cognitive map of the environment (Iaria et al., 2003; O'Keefe & Nadel, 1978) and a strategy based on habitual responses (e.g., turn right at first alley, then take the second passage to the left; O'Keefe & Nadel, 1978). The latter type of procedural learning relies on stimulus-response behavior supported by the basal ganglia (i.e. caudate nucleus and putamen; Iaria et al., 2003; O'Keefe & Nadel, 1978). In the healthy brain, information during navigation is processed by the visual cortex and subsequently in the retrosplenial cortex and the parahippocampal cortex (i.e. its posterior and middle subdivisions; Iaria et al., 2007; Maguire, 2001; Wolbers &

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Büchel, 2005). Furthermore, Iaria and colleagues (2003) found that several participants who started out using a spatial strategy subsequently changed to a habitual one as the environment became more familiar. In the mTBI group, we observed increased activity in the posterior visual association regions in the lingual and fusiform gyrus during navigation (Fig. 5.10.4, Table 5.9.2) relative to the control group. This increase in activity may reflect the recruitment of compensatory mechanisms. Although task-performance did not differ between the control and the mTBI group, it can be hypothesized that the individuals with mTBI may be allocating more attentional processing to the visual environment as they were navigating. It is interesting that this increased activity was observed in the posterior fusiform cortex, a region that has been associated with the processing of stable visual features of the environment (Johnsrude et al., 1999). Note that damage that includes the fusiform and lingual cortex has resulted in landmark agnosia, i.e. an inability to identify familiar buildings and landscapes (Takahashi & Kawamura, 2002). Finally, the present results showed significant activation in DLPFC in the control group, an observation which is in line with other studies of navigation in healthy participants (Iaria et al., 2003, 2007; Maguire et al., 1998; Rauchs et al., 2008; Spiers & Maguire, 2006). The mTBI group, in contrast, exhibited a significant decrease in signal intensity in this region (Fig. 5.10.2, Table 5.9.2). The DLPFC has been shown to play a major role in the monitoring of response choices (Petrides, 1991, 2013; Petrides et al., 1993) and the regulation of attention (Petrides, 2005) and, naturally, such cognitive control processing would be expected and, indeed, has been shown in previous studies to be engaged during complex navigation tasks (Iaria et al., 2003, 2007). The reduction in DLPFC signal strength that was clearly demonstrated in the adult mTBI group suggests reduced cognitive control of various aspects of information processing, a finding that confirms previous reports that the DLPFC is vulnerable to the effects of mTBI (Chen et al., 2004, 2008). The results of the present study are similar to those of a previous navigation fMRI study in a pediatric mTBI population who showed comparable

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activation patterns between an mTBI and control group in the absence of differences in the time taken to complete the task (Saluja et al., 2015). That study showed less intense activation in the retrosplenial cortex, posterior parahippocampal cortex, and the thalamus, bilaterally, as well as in the right dorsolateral prefrontal cortex and left precuneus, as a consequence of mTBI during a navigation task that required the retrieval of information from a previously formed cognitive map. In addition, the study by Saluja and colleagues (2015) found increased activation in the mTBI, compared to control participants, in the left hippocampus and right middle temporal gyrus. Together, the results indicate that although the consequences of mTBI appear subtle in terms of overall performance, changes in brain activation can be clearly demonstrated and these effects of mTBI should be taken in consideration, clinically, because of the potentially severe consequences of cumulative effects of TBI (Gaetz et al., 2000; Rabadi & Jordan, 2001) and deferred onset of brain changes (Bigler et al., 1997).

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5.7 References Amiez, C. & Petrides, M. (2014) Neuroimaging evidence of the anatomo- functional organization of the human cingulate motor areas. Cerebral cortex, 24, 563-578.

Amiez, C., Neveu, R., Warrot, D., Petrides, M., Knoblauch, K. & Procyk, E. (2013) The location of feedback-related activity in the midcingulate cortex is predicted by local morphology. The Journal of neuroscience, 33, 2217-2228.

Beck, A.T., Steer, R.A. & Brown, G.K. (1996) Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation.

Bernstein, D.M. (1999) Subject Review: Recovery from mild head injury. Brain injury, 13, 151-172.

Bigler, E. (2000) The Lesion(s) in Traumatic Brain Injury: Implications for Clinical Neuropsychology. http://web.archive.org/web/20041205062946/ http://psych.byu.edu/work/tbi.pdf (In Internet Archive)

Bigler, E.D., Blatter, D.D., Anderson, C.V., Johnson, S.C., Gale, S.D., Hopkins, R.O. & Burnett, B. (1997) Hippocampal volume in normal aging and traumatic brain injury. American Journal of Neuroradiology, 18, 11-23.

Boccia, M., Nemmi, F. & Guariglia, C. (2014) Neuropsychology of environmental navigation in humans: review and meta-analysis of FMRI studies in healthy participants. Neuropsychology review, 24, 236-251.

Bohbot, V.D. & Corkin, S. (2007) Posterior parahippocampal place learning in H.M. Hippocampus, 17, 863-872.

222

Bohbot, V.D., Allen, J.J. & Nadel, L. (2000) Memory deficits characterized by patterns of lesions to the hippocampus and parahippocampal cortex. Annals of the New York Academy of Sciences, 911, 355-368.

Carroll, L., Cassidy, J.D., Peloso, P., Borg, J., Von Holst, H., Holm, L., Paniak, C. & Pépin, M. (2004) Prognosis for mild traumatic brain injury: results of the WHO Collaborating Centre Task Force on Mild Traumatic Brain Injury. Journal of Rehabilitation Medicine, 36, 84-105.

Chen, J.K., Johnston, K.M., Petrides, M. & Ptito, A. (2008) Neural substrates of symptoms of depression following concussion in male athletes with persisting postconcussion symptoms. Archives of general psychiatry, 65, 81-89.

Chen, J.K., Johnston, K.M., Frey, S., Petrides, M., Worsley, K. & Ptito, A. (2004) Functional abnormalities in symptomatic concussed athletes: an fMRI study. NeuroImage, 22, 68-82.

Chiavaras, M.M., LeGoualher, G., Evans, A. & Petrides, M. (2001) Three- dimensional probabilistic atlas of the human orbitofrontal sulci in standardized stereotaxic space. NeuroImage, 13, 479-496.

223

Epstein, R. & Kanwisher, N. (1998) A cortical representation of the local visual environment. Nature, 392, 598-601.

Friston, K.J., Fletcher, P., Josephs, O., Holmes, A., Rugg, M.D. & Turner, R. (1998) Event-related fMRI: characterizing differential responses. NeuroImage, 7, 30-40.

Gaetz, M., Goodman, D. & Weinberg, H. (2000) Electrophysiological evidence for the cumulative effects of concussion. Brain injury, 14, 1077-1088.

Germann, J., Robbins, S., Halsband, U. & Petrides, M. (2005) Precentral sulcal complex of the human brain: morphology and statistical probability maps. The Journal of comparative neurology, 493, 334-356.

Gosselin, N., Theriault, M., Leclerc, S., Montplaisir, J. & Lassonde, M. (2006) Neurophysiological anomalies in symptomatic and asymptomatic concussed athletes. Neurosurgery, 58, 1151-1161.

Habib, M. & Sirigu, A. (1987) Pure topographical disorientation: a definition and anatomical basis. Cortex; a journal devoted to the study of the nervous system and behavior, 23, 73-85.

Holm, L., Cassidy, J.D., Carroll, L.J. & Borg, J. (2005) Summary of the WHO Collaborating Centre for Neurotrauma Task Force on Mild Traumatic Brain Injury. Journal of rehabilitation medicine : official journal of the UEMS European Board of Physical and Rehabilitation Medicine, 37, 137-141.

Huntgeburth, S.C., Chen, J.-K., Ptito, A. & Petrides, M. (in preparation) Local Morphology Informs Location of Activation during Navigation within the Parahippocampal Region of the Human Brain.

224

Iaria, G., Petrides, M., Dagher, A., Pike, B. & Bohbot, V.D. (2003) Cognitive strategies dependent on the hippocampus and caudate nucleus in human navigation: variability and change with practice. The Journal of neuroscience : the official journal of the Society for Neuroscience, 23, 5945-5952.

Johnsrude, I.S., Owen, A.M., Crane, J., Milner, B. & Evans, A.C. (1999) A cognitive activation study of memory for spatialrelationships. Neuropsychologia, 37, 829-841.

Litman, L., Awipi, T. & Davachi, L. (2009) Category-specificity in the human medial temporal lobe cortex. Hippocampus, 19, 308-319.

Lovell, M.R. & Collins, M.W. (1998) Neuropsychological assessment of the college football player. The Journal of head trauma rehabilitation, 13, 9-26.

Maguire, E. (2001) The retrosplenial contribution to human navigation: a review of lesion and neuroimaging findings. Scandinavian journal of psychology, 42, 225-238.

Maguire, E.A., Nannery, R. & Spiers, H.J. (2006) Navigation around London by a taxi driver with bilateral hippocampal lesions. Brain, 129, 2894-2907.

Maguire, E.A., Burke, T., Phillips, J. & Staunton, H. (1996) Topographical disorientation following unilateral temporal lobe lesions in humans. Neuropsychologia, 34, 993-1001.

225

Maguire, E.A., Frith, C.D., Burgess, N., Donnett, J.G. & O'Keefe, J. (1998) Knowing where things are parahippocampal involvement in encoding object locations in virtual large-scale space. J Cogn Neurosci, 10, 61-76.

O'Keefe, J. & Nadel, L. (1978) The hippocampus as a cognitive map. Oxford University Press.

Petrides, M. (1991) Monitoring of selections of visual stimuli and the primate frontal cortex. Proceedings Biological sciences / The Royal Society, 246, 293- 298.

Petrides, M. (2012) The Human Cerebral Cortex: An MRI Atlas of the Sulci and Gyri in MNI Sereotaxic Space. New York: Academic Press.

Petrides, M. (2013) The mid-dorsolateral prefronto-parietal network and the epoptic process. In: Principles of Frontal Lobe Function, 2nd Edition (Stuss DT, Knight RT, eds), pp 79-89. New York: Oxford University Press.

Petrides, M., Alivisatos, B., Evans, A.C. & Meyer, E. (1993) Dissociation of human mid-dorsolateral from posterior dorsolateral frontal cortex in memory processing. Proceedings of the National Academy of Sciences of the United States of America, 90, 873-877.

Rabadi, M.H. & Jordan, B.D. (2001) The cumulative effect of repetitive concussion in sports. Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine, 11, 194-198.

226

Rauchs, G., Orban, P., Balteau, E., Schmidt, C., Degueldre, C., Luxen, A., Maquet, P. & Peigneux, P. (2008) Partially segregated neural networks for spatial and contextual memory in virtual navigation. Hippocampus, 18, 503-518.

Saluja, R.S., Chen, J.K., Gagnon, I.J., Keightley, M. & Ptito, A. (2015) Navigational memory functional magnetic resonance imaging: a test for concussion in children. Journal of neurotrauma, 32, 712-722.

Scoville, W.B. & Milner, B. (1957) Loss of recent memory after bilateral hippocampal lesions. Journal of neurology, neurosurgery, and psychiatry, 20, 11- 21.

Scoville, W.B. & Milner, B. (2000) Loss of recent memory after bilateral hippocampal lesions. 1957. The Journal of neuropsychiatry and clinical neurosciences, 12, 103-113.

Segal, E. & Petrides, M. (2012) The morphology and variability of the caudal rami of the superior temporal sulcus. The European journal of neuroscience, 36, 2035-2053.

Slobounov, S., Zhang, K., Pennell, D., Ray, W., Johnson, B. & Sebastianelli, W. (2010) Functional abnormalities in normally appearing athletes following mild traumatic brain injury: a functional MRI study. Experimental Brain Research, 202, 341-354.

Smith, M.L. & Milner, B. (1981) The role of the right hippocampus in the recall of spatial location. Neuropsychologia, 19, 781-793.

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Smith, M.L. & Milner, B. (1989) Right hippocampal impairment in the recall of spatial location: Encoding deficit or rapid forgetting? Neuropsychologia, 27, 71- 81.

Smith, M.L., Bigel, M. & Miller, L.A. (2011) Visual paired-associate learning: in search of material-specific effects in adult patients who have undergone temporal lobectomy. Epilepsy & Behavior, 20, 326-330.

Smith, M.L., Leonard, G., Crane, J. & Milner, B. (1995) The effects of frontal-or temporal-lobe lesions on susceptibility to interference in spatial memory. Neuropsychologia, 33, 275-285.

Spiers, H.J. & Maguire, E.A. (2006) Thoughts, behaviour, and brain dynamics during navigation in the real world. NeuroImage, 31, 1826-1840.

Takahashi, N. & Kawamura, M. (2002) Pure Topographical Disorientation —The Anatomical Basis of Landmark Agnosia. Cortex; a journal devoted to the study of the nervous system and behavior, 38, 717-725.

Wolbers, T. & Büchel, C. (2005) Dissociable retrosplenial and hippocampal contributions to successful formation of survey representations. The Journal of neuroscience, 25, 3333-3340.

Worsley, K.J. (2005) Spatial smoothing of autocorrelations to control the degrees of freedom in fMRI analysis. NeuroImage, 26, 635-641.

Worsley, K.J., Liao, C., Aston, J., Petre, V., Duncan, G.H., Morales, F. & Evans, A.C. (2002) A general statistical analysis for fMRI data. NeuroImage, 15, 1-15.

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Zlatkina, V. & Petrides, M. (2010) Morphological patterns of the postcentral sulcus in the human brain. The Journal of comparative neurology, 518, 3701- 3724.

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5.8 Acknowledgements The authors thank Dr. Veronika Zlatkina and Dr. Emily Segal for helpful discussions on the project. The research was supported by the Canadian Institute of Health Research (CIHR) grant MOP-64271 to AP and MP, and MOP-130361 to MP.

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5.9 Tables

Figure 5.9.1 Demographics and clinical characteristics of the mild traumatic brain injury (mTBI) group and the healthy control group. Abbreviations: SD, standard deviation; N, number of participants; n/a, not applicable.

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Figure 5.9.2 Task-related activation peaks from the comparison experimental minus control task for the mild traumatic brain injury (mTBI) group and the healthy control group. Abbreviations: AG, angular gyrus; BA, Brodmann area; DLPFC, dorsolateral prefrontal cortex; VLPFC, ventrolateral prefrontal cortex. Special symbols: Asterisk, indicates significance at cluster threshold (the highest peak of the cluster is reported here); Superscript ‘a’, refers to subthreshold

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activation (activation peak did not reach significance, yet subthreshold activation could be observed); Superscript ‘b’, denotes that the activation peak is part of a larger peak cluster that spreads across the cerebral midline; the peak coordinate with the highest value fell within one hemisphere and is reported only one time in the table (i.e. either for the right or the left); Superscript ‘c’, indicates that despite a lowering of the threshold, no clear peak could be identified. All coordinates are presented in the standard stereotaxic space of the Montreal Neurological Institute (MNI).

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5.10 Figures

Figure 5.10.1 Experimental and control tasks. (A) In the experimental task, participants were asked to navigate towards one of six landmarks embedded within the virtual environment: the bank in this example. (B) In the control condition, the participants were instructed to navigate a defined route by following a series of arrow signs along a path through the virtual environment, which was similar to that of the experimental task except that no landmarks were imbedded in the environment. (C) An aerial perspective of the virtual environment with a yellow arrow indicating an example path from the church to the bank (the church is the starting position illustrated in panel A).

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Figure 5.10.2 Reduced activation within the right retrosplenial (a), right posterior parahippocampal (b), and right dorsolateral prefrontal cortex (c) in the mild traumatic brain injury (mTBI) group in comparison with the healthy control group. Horizontal (a) and coronal (b, c) MRI sections with the region exhibiting reduced activation in the mTBI group outlined in red. The histograms illustrate the percent BOLD signal change within the outlined region for the mTBI and control groups. The coordinate below each image indicates the level of the section in the standard stereotaxic space of the Montreal Neurological Institute. All peak coordinates are reported in Table 5.9.2.

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Figure 5.10.3 Reduced activation within the left and right middle parahippocampal cortex (a) and left and right caudate nucleus (b) in the mild traumatic brain injury (mTBI) group in comparison with the healthy control group. Coronal (a, b) MRI sections with the region exhibiting reduced activation in the mTBI group outlined in red. The histograms illustrate the percent BOLD signal change within the outlined region for the mTBI and control groups. The coordinate below each image indicates the level of the section in the standard stereotaxic space of the Montreal Neurological Institute. All peak coordinates are reported in Table 5.9.2.

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Figure 5.10.4 Increased activation within the left and right fusiform gyrus (a) and right lingual gyrus (b) in the mild traumatic brain injury (mTBI) group in comparison with the healthy control group. Coronal (a, b) MRI sections with the region exhibiting reduced activation in the mTBI group outlined in red. The histograms illustrate the percent BOLD signal change within the outlined region for the mTBI and control groups. The coordinate below each image indicates the level of the section in the standard stereotaxic space of the Montreal Neurological Institute. All peak coordinates are reported in Table 5.9.2.

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Chapter Six 6. General Discussion Careful examination of the sulci in the depth, and not solely from the surface of the brain, has offered the scientific community a better understanding of cortical folding patterns in various regions of the brain. In this thesis, this approach was applied to the sulci that make up the collateral sulcal complex in order to provide qualitative and quantitative measures of inter-subject sulcal variance along the parahippocampal region of the brain. The anatomical studies of this thesis are the first to demonstrate in detail the different sulcal segments of the collateral sulcal complex, and how these relate to the medially adjacent entorhinal and parahippocampal cortex on the parahippocampal gyrus. In addition, the subsequent fMRI study links task-specific functional activations to specific sulcal landmarks based on the morphological findings, providing additional evidence that a thorough understanding of the sulcal-gyral morphology is imperative as it offers important information about the relationship between brain structure and function, taking into account inter-subject variability. This approach has been shown to have great predictive value of the functional organization of adjacent regions (Amiez et al., 2006; Amiez et al., 2013; Amiez & Petrides, 2009; Segal & Petrides, 2013; Yousry et al., 1997; Zlatkina et al., 2015). The parahippocampal gyrus is a heterogeneous region that comprises the entorhinal cortex on its anterior surface and the parahippocampal cortex on its posterior extent. The entorhinal and parahippocampal cortex are distinct in terms of their cytoarchitectonic organization (Economo & Koskinas, 1925) and their function (Aminoff et al., 2007; Köhler et al., 2002; Litman et al., 2009). The anatomical studies of this thesis identified the sulci that laterally delimit the parahippocampal gyrus, and further showed that the extent of the rhinal sulcus relates to the anterior-posterior extent of the entorhinal cortex, thereby delineating it from the posterior parahippocampal cortex and the lateral fusiform gyrus. Furthermore, these studies also showed that the collateral sulcus proper laterally delineates the parahippocampal cortex, thereby functioning as a morphological landmark separating it from the entorhinal cortex rostrally, as well as from the

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laterally adjacent fusiform gyrus and caudally bordering lingual gyrus. These quantitative and qualitative descriptions of the relationship between the rhinal sulcus and the collateral sulcus proper clarify the question of nomenclature thereby aiding cytoarchitectonic investigations. For instance, when examining the cytoarchitectonic organization of the entorhinal cortex in post-mortem human brains, investigators may now also identify appropriately the rhinal sulcus. In addition, the anatomical descriptions of the collateral sulcus proper and its distinction from the rhinal sulcus rostrally and the occipital extent of the collateral sulcus caudally allow for a more detailed investigation of the parahippocampal cortex, distinct from the adjacent cortex of the entorhinal cortex (rostrally), the fusiform gyrus (laterally), and the lingual gyrus (caudally). The studies of this thesis demonstrated that a relationship exists in the parahippocampal gyrus between the local morphology and functional properties subserved by the cortex that lies adjacent to it (Chapter 3). Previous studies had simply referred to the activation peaks as falling in the parahippocampal gyrus failing to define precisely their location along the parahippocampal gyrus and the likelihood that they may be in the entorhinal and/or parahippocampal cortex. In light of the anatomical studies, investigators can now localize and more precisely identify where an activation peak falls along the parahippocampal cortex, for instance, by examining whether the peak falls anterior to or posterior to the rhinal sulcus and/or collateral sulcus proper. In the study in Chapter 3, task-specific activation peaks on the parahippocampal gyrus were dissociated from the peaks of the adjacent fusiform and lingual gyrus. The results of this study demonstrated that in the individual brain the functional activation peaks on the parahippocampal gyrus during a navigation paradigm were related to the cortical folding pattern of the sulcal segments of the collateral sulcal complex. More precisely, they related to specific segments of the collateral sulcus proper, thereby falling in specific regions along the parahippocampal cortex, not along the entorhinal cortex, and not in the fusiform or lingual gyrus. This thesis contributes directly to recent developments in functional neuroimaging studies that have set out to assess and identify different functional

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subdivisions along the parahippocampal gyrus. However, studies that have attempted to subdivide the parahippocampal gyrus to date, have not based their subdivisions on local morphological landmarks. For instance, such investigations have divided the parahippocampal gyrus into regions-of-interest of equal distance (Aminoff et al., 2007; Litman et al., 2009; Staresina et al., 2011). The fMRI study in Chapter 4 of this thesis has illustrated that functional subdivisions along the parahippocampal gyrus may be identified based on the local anatomy. Furthermore, clinical studies on patients with lesions may use the landmarks of the collateral sulcal complex to describe more accurately the extent of their patients’ lesions. One objective of basic research in neuroscience is to understand and describe the brain functions in the healthy population. Another aim is to apply subsequently this knowledge to the clinical population in order to understand better how the structural and functional changes occur and progress as a function of disease. The key finding of the final study of the present thesis is that the anatomo-function relationship as established in the healthy brain can identify subtle changes in functional activation patterns in individuals with mild traumatic brain injury. These results demonstrate the value that the morphological studies (Chapter 2 and Chapter 3) bring to establishing a structure-function relationship in the human brain on a subject-by-subject basis (Chapter 4), which can then be applied to identify subtle consequences of brain trauma in the clinical population.

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6.1 The morphology of the collateral sulcal complex The results of the examination of the morphology of the sulci of the collateral sulcal complex in Chapter 2, and the establishment of the location variability in the form of probabilistic maps in Chapter 3 provide important and novel information to the field of neuroscience. First, these studies provide essential information of the variability of the morphology and the patterns of the sulci that make up the collateral sulcal complex. This is based on a detailed and systematic investigation of the entire extent of the collateral sulcal complex in a series of continuous magnetic resonance images in the coronal, horizontal, and sagittal plane, in-vivo in a large sample of neurologically healthy human subjects (Chapter 2). Previous studies examined the sulcal patterns of the ventromedial surface of the human brain by outlining the surface anatomy of the sulci on successive coronal images using different colored lines on translucent paper (Novak et al., 2002), or by tracing sulcal patterns on photographs of post-mortem human brains (Hanke, 1997). The collateral sulcal complex often appears as one continuous sulcal entity when viewed from the surface of the brain, thereby giving the erroneous impression that it is a sole segment. For this reason, an in-depth examination of this complex sulcus in continuous series of images is especially important. The studies in Chapters 2 and 3 addressed this issue by studying the sulcal depth and the surface impressions of the collateral sulcal complex. The findings offer a detailed description of the prominent relationship patterns formed by the sulcal segments that make up this complex and provide quantitative and qualitative information about the inter-subject variability of the location of the sulcal segments. Second, the findings of Chapters 2 and 3 are presented in the standard stereotaxic space of the MNI, which is the space most commonly used in the neuroscience community, thereby allowing for direct applicability of our findings by other researchers. An important finding of the morphological investigation (Chapter 2) was that the so-called ‘collateral sulcus’, the prominent landmark on the ventromedial aspect of the temporal and occipital lobe, is a complex of three sulci. The anterior segment was referred to as the rhinal sulcus in order to help clarify the current

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ambiguous use of this name in the literature (i.e. referring to the sulcus that laterally delimits the entorhinal cortex (Brodmann, 1909; Economo & Koskinas, 1925; Gloor, 1997; Retzius, 1896), or applying the term to a small sulcal dimple at the most anterior part of the parahippocampal gyrus (Duvernoy, 1999; Insausti & Amaral, 2004; Insausti et al., 1998; Insausti et al., 1995)). The middle segment was termed the collateral sulcus proper, as this is in line with how most researchers have referred to this sulcal entity (Duvernoy, 1999; Economo & Koskinas, 1925; Insausti & Amaral, 2004; Insausti et al., 1998; Insausti et al., 1995; Retzius, 1896). The posterior segment was called the occipital extent of the collateral sulcus. This subdivision of the collateral sulcal complex into three main segments demonstrates that the sulcus that laterally delimits the parahippocampal gyrus is not a single, morphologically continuous furrow (Duvernoy, 1999). Despite inter-individual variability in cortical folding patterns, the rhinal sulcus was reliably identified in the majority of cases (97.5 percent) as separate from the collateral sulcus proper. This finding highlights the importance of a careful in- depth examination and the fact that the impression of a sulcus that is observable on the surface of the brain may not correspond to the submerged sulcal structure. In this specific case, our investigation helped clarify the independence between these two sulci by identifying and describing the morphological pattern of the posterior end of the rhinal sulcus and the anterior origin of the collateral sulcus proper. Furthermore, the results of this study (Chapter 2) demonstrated that the rhinal sulcus and collateral sulcus proper form separate sulcal entities visible on the cortical surface and in the sulcal depth in 63.75 percent of cases. In approximately one third of observations (33.75 percent), the surface inspection of the brain offers an erroneous impression of continuation between the two sulci that may lead to misidentification and mislabeling of the rhinal sulcus as an anterior part of the collateral sulcus. In these cases it was only an in-depth examination that illustrated that the collateral sulcus proper developed in the sulcal depth out of either the lateral or the medial bank of the rhinal sulcus. The image of the collateral sulcus proper as a single continuous furrow that spans the entire parahippocampal gyrus as provided by Duvernoy (1999) (Fig. 2.10.1 in

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Chapter 2) was determined by our examinations to depict the exception rather than the rule, as a continuous relationship between the rhinal sulcus and the collateral sulcus proper occurred only occasionally (in 2.5 percent). The identification of the anterior segment of the collateral sulcal complex as a separate sulcus from the middle segment is of importance, as the term ‘rhinal sulcus’ was explicitly used to refer to this anterior segment. The findings in Chapter 2 showed that the sulcus that in Chapter 2 is referred to as the ‘rhinal sulcus’ marks the entire length of the anterior part of the parahippocampal gyrus that contains the entorhinal cortex. This sulcus originates rostrally around the anteroposterior level of the limen insulae and forms the first prominent sulcal indentation lateral to the amygdala and hippocampus. Posteriorly, it continues just slightly caudal to the anteroposterior level of the lateral geniculate nucleus, which is also the caudalmost limit of the uncus. This extent of this sulcus relates to the histologically defined entorhinal cortex (Insausti et al., 1995). Furthermore, in Chapter 3, the probability map of the rhinal sulcus was superimposed with the cytoarchitectonic probability maps of the entorhinal cortex of Amunts and colleagues (2005) and it has shown that the posterior limit of the sulcus that in the present investigation (and the study in Chapter 3) is called rhinal sulcus coincides approximately with the caudal border of the entorhinal cortex. Therefore, if this sulcus in the human brain marks the rostro-caudal extent of the entorhinal cortex, and if in the non-human primate brain the sulcus which laterally delimits the entorhinal cortex is referred to as the rhinal sulcus, then it supports the proposition that these two sulci may be homologues of one another (see Gloor (1997), p. 329; Petrides (unpublished observations)). Therefore, in the human brain, the term rhinal sulcus should be used to refer to the sulcus that laterally binds the entorhinal cortex (Aguirre & D'Esposito, 1999; Brodmann, 1909; Economo & Koskinas, 1925; Kim et al., 2008; Retzius, 1896), and not to denote a small dimple (Duvernoy, 1999; Heckers et al., 1990; Insausti & Amaral, 2004; Insausti et al., 1998; Insausti et al., 1995; Van Hoesen & Pandya, 1975) that bears no great relationship in the human brain to the extent of the entorhinal cortex. It should be noted that, in the older neuroanatomical literature, this sulcus was indeed referred

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to as the ‘fissura rhinica’ (Retzius, 1896), ‘sulcus rhinalis posterior’ (Brodmann, 1925), and ‘fissura rhinalis’ (Economo & Koskinas, 1925; Smith, 1904). Additionally, this usage has continued with some modern investigators (Kim et al., 2008; Novak et al., 2002; Ono et al., 1990). This distinction, which may appear as a mere debate of nomenclature, has important implications for research. Given that the entorhinal cortex and the parahippocampal cortex are distinct parts of the parahippocampal gyrus in terms of their cytoarchitectonic organization (Economo & Koskinas, 1925) and function (Aminoff et al., 2007; Köhler et al., 2002; Litman et al., 2009), the ability to identify these two distinct regions is of immense importance. Chapter 3 builds on the morphological analysis of Chapter 2 and offers probability maps that provide a measure of the location variability in the standard stereotaxic space of the MNI of the segments that mark the parahippocampal gyrus, i.e. the rhinal sulcus, collateral sulcus proper, and parahippocampal extent of the collateral sulcus, which help to identify more accurately the locus of activation peaks obtained with functional neuroimaging techniques along the parahippocampal gyrus (e.g. peaks falling medial to the rhinal sulcus are located in the entorhinal cortex, whereas peaks medial to the collateral sulcus proper reflect activation peaks in the parahippocampal cortex). In Chapter 3, the findings demonstrated how future research will benefit from combining information from various sources, such as morphological descriptions, cytoarchitectonic investigations, and probabilistic quantifications. The information from the probability maps of the rhinal sulcus and the collateral sulcus proper was combined with the cytoarchitectonic probability map of the location of the entorhinal cortex provided by Amunts et al. (2005). This investigation demonstrated that the entorhinal cortex lies medial to the rhinal sulcus and is bound by its entire rostrocaudal length (Figs. 3.10.7 and 3.10.8 in Chapter 3). The observation that the entorhinal cortex continues caudally for a short distance next to the most anterior part of the collateral sulcus proper may in part reflect the fact that the caudal end of the rhinal sulcus and the rostral end of the collateral sulcus proper overlap in a number of cases (e.g. Type II rhs-cos

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relationship patterns, see Chapter 2). Another reason may be the greater variance in the cytoarchitectonic probability map than in the sulcal probability maps due to the relatively low number of cases in the cytoarchitectonic probability map (i.e. 10 post-mortem brains by Amunts et al., 2005) versus 40 in-vivo magnetic resonance imaging volumes in Chapter 3), as well as that the transformation necessary to place the sulcal and cytoarchitectonic probability maps into the same stereotaxic space for comparison has added variability. Nevertheless, this approach illustrates how these different investigations may be combined to offer a greater insight into the relationship between morphology and cytoarchitecture. In conclusion, the provision of the probabilistic maps (Chapter 3) demonstrated a close link between the antero-posterior extent of the rhinal sulcus and the entorhinal cortex by relating these maps to the cytoarchitectonic probability map of the entorhinal cortex by Amunts and colleagues (2005), strengthening our argument for our definition of the rhinal sulcus (Chapter 2). Thus, it can be shown that the rhinal sulcus in the human brain, if defined appropriately, forms a reliable landmark of the entorhinal cortex as it does in other mammals. This informs the debate on the terminology used to refer to the sulci along the rostro-caudal axis of the parahippocampal cortex and suggests that nomenclature used for the sulcus that delimits the entorhinal cortex in the human brain should be comparable to that used for the same sulcus in other mammals. Furthermore, another key finding of the morphological investigations of the present thesis (Chapter 2) was the differentiation of the collateral sulcus proper in its posterior end from another sulcal segment, called the occipital extent of the collateral sulcus. These two posterior sulcal segments are separated at the level of the caudal limit of the splenium and the posterior limit of the hippocampus when viewed in the coronal plane, a few millimeters posterior to the most rostral origin of the anterior calcarine sulcus. The anterior point of the in- depth development of the occipital extent of the collateral sulcus marks the caudal limit of the collateral sulcus proper. Differences in cytoarchitectonic organization between the parahippocampal cortex and the cortex of the lingual gyrus have been reported (Brodmann, 1909). However, more work is needed in order to see

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whether the junction between the posterior limit of the collateral sulcus proper and the occipital extent of the collateral sulcus may provide a morphological landmark indicating the caudal end of the parahippocampal cortex and the anterior limit of the lingual gyrus. Nevertheless, functionally, these two cortical regions have been shown to differ. The cortex of the parahippocampal gyrus of the medial temporal lobe is involved in mnemonic information processing and the cortex of the lingual gyrus in the occipital lobe is associated with processing visual information. Damage to the parahippocampal cortex has been demonstrated to cause mnemonic impairments related to the environment, called topographical amnesia (Habib & Sirigu, 1987), while lesions of the lingual gyrus have been reported to cause a visual perceptual deficit, referred to as landmark agnosia (Aguirre & D'Esposito, 1999; Aguirre et al., 1998). In order to examine whether such a posterior morphological landmark (i.e. the posterior limit of the collateral sulcus proper, at the junction with the occipital extent of the collateral sulcus) may have importance in discriminating activation of the parahippocampal cortex from that of the lingual gyrus, the findings of the location variability of the posterior limit of the collateral sulcus proper and the parahippocampal extension of the collateral sulcus (Chapter 3) were applied to identify more precisely the location of the coordinates reported for the parahippocampal place area (Aguirre & D'Esposito, 1997; Andrews et al., 2010; Arcaro et al., 2009; Bar & Aminoff, 2003; Epstein et al., 2003; Epstein et al., 1999; Epstein & Kanwisher, 1998; Henderson et al., 2008; Köhler et al., 2002; Litman et al., 2009; Pihlajamaki et al., 2004; Staresina et al., 2011; Sulpizio et al., 2013). The findings of the investigation in Chapter 3 demonstrated that the activation peaks reported as being selectively responsive to scene and place information fell along the posterior segment of the collateral sulcus proper, anterior to the junction with the parahippocampal extension of the collateral sulcus. This places them within the posterior part of the parahippocampal cortex (Chapter 3). The posterior limit of the parahippocampal cortex has until now been chosen rather arbitrarily (e.g. at “the first coronal slice on which the calcarine sulcus is visible”, p. 366, Reber et al. (2002), or defined as the “last slide in ACPC [i.e. anterior-posterior

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commissure] orientation where the hippocampus can be identified inferomedial to the trigone of the lateral ventricle”, p.1344 in Pruessner et al.(2002)). In addition, such arbitrary boundaries have been adopted by other researchers (Aminoff et al., 2007; Staresina et al., 2011). The information from the present investigation is valuable as it provides clear anatomical landmarks for the posterior limit of the parahippocampal cortex, i.e. the junction between the posterior limit of the collateral sulcus proper, the anterior origin of the occipital extent of the collateral sulcus proper, and the parahippocampal extension of the collateral sulcus. Future studies should take into account these landmarks for the posterior limit of the parahippocampal gyrus and combine them with the morphological description of the sulci of the lingual gyrus (Iaria and Petrides, 2007). Functional neuroimaging studies may use these criteria to differentiate within these regions (i.e. of the posterior parahippocampal and anterior lingual gyri) the areas involved in the processing of mnemonic aspects of scene-relevant information and the processing of visual stimulus qualities (e.g. of scene information). Activation related to the former region is expected to recruit the parahippocampal cortex, and therefore fall rostral to where the posterior limit of the collateral sulcus proper joins the posterior limit of the parahippocampal extension of the collateral sulcus proper and the anterior origin of the occipital extent of the collateral sulcus proper. Activation of the region related scene information may be expected to engage the anterior lingual gyrus, i.e. the activation peaks are expected to lie caudal to the anterior origin of the occipital extent of the collateral sulcus, posterior to the caudal end of the collateral sulcus proper and the parahippocampal extension of the collateral sulcus. Such functional neuroimaging studies based on examining the relationship between anatomy and function will provide a more detailed definition of the posterior boundary of the parahippocampal cortex and gyrus. Another important and novel finding of our morphological investigation of the sulci of the collateral sulcal complex in Chapter 2 was that this study was the first to observe that in 50 percent of all cases, the collateral sulcus proper was not one continuous entity along the lateral limit of the parahippocampal cortex, but it could be reliably separated into two sulcal segments. Chapter 2 provided a

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definition of the two segments of the collateral sulcus proper (i.e. the anterior and the posterior segments of the collateral sulcus proper) which both lie posterior to the rhinal sulcus and thereby mark the lateral border of the parahippocampal cortex. The findings in Chapter 3 offer a quantitative measure of the variability of these two sulcal segments within the standard stereotaxic space of the MNI (Fig. 3.10.5 in Chapter 3). The importance of this finding becomes clear when one considers that the parahippocampal cortex is not a single homogeneous region. In the non-human primate, the presence of neurons that differ in their receptive field sizes along the rostrocaudal axis of the parahippocampal cortex have suggested that functional subregions exist along the parahippocampal cortex (Sato & Nakamura, 2003). Several studies have examined whether the parahippocampal cortex in the human brain can be further subdivided functionally (Aminoff et al., 2007; Pihlajamaki et al., 2004; Staresina et al., 2011). In Chapter 3 of this thesis, quantification of the location variability of the two segments of the collateral sulcus proper is provided in the form of probability maps and it demonstrates how the probabilistic approach may have aided previous neuroimaging research in determining more accurately the location of the activation peaks along the parahippocampal cortex that are related to scene-relevant information processing (see especially Table 3.9.3 in Chapter 3). This study offers anatomical criteria to support the notion of functional subdivisions along the parahippocampal cortex. In particular, the focus of the study was on determining which parts of the parahippocampal cortex are involved in processing scene-relevant information (e.g. the PPA and PPA-like areas, see Table 3.9.3 in Chapter 3). The location and extent of the parahippocampal place area on the parahippocampal cortex has not been accurately described previously and the location of activation peaks varies considerable across studies (see Table 3.9.3 in Chapter 3). The finding of the anterior and the posterior segment of the collateral sulcus proper therefore offer clear morphological criteria for a more accurate identification of the location of activation peaks along the parahippocampal cortex. As such, activation peaks may fall medially to the anterior segment of the collateral sulcus proper, medially along the posterior segment of the collateral sulcus proper, or along the transition

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of the anterior and posterior segments, that is the area of overlap of both sulcal segments. This allows for a parcellation of the parahippocampal cortex into an anterior, middle, and a posterior part. The next paragraph illustrates how this understanding of the subdivisions of the parahippocampal cortex (from Chapters 2 and 3) was applied to discriminate between the locations of activation peaks obtained from a functional neuroimaging study (Chapter 4).

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6.2 Linking anatomy and function in the parahippocampal gyrus The studies presented in Chapters 2 and 3 provided the framework for the investigation presented in Chapter 4. The objective of the study in Chapter 4 was to use the acquired knowledge of the sulcal anatomy of the collateral sulcal complex in order to identify more accurately on a subject-by-subject basis the location of activation peaks along the parahippocampal gyrus obtained from a functional magnetic resonance imaging study using a navigation paradigm. A navigation paradigm was employed as previous studies have demonstrated functional activity increases in the parahippocampal region during navigation tasks (Boccia et al., 2014; Iaria et al., 2007; Iaria et al., 2003; Maguire et al., 1998; Rauchs et al., 2008; Spiers & Maguire, 2006). The parahippocampal cortex is a critical structure for spatial memory during navigation when the use of a cognitive map, i.e. a mental representation of the environment and information of the location of landmarks within it and their relationship to each other, is required (Iaria et al., 2003; O'Keefe & Nadel, 1978). Unilateral damage to the right medial temporal lobes that includes the parahippocampal cortex impairs spatial memory abilities (Bohbot et al., 2000; Bohbot & Corkin, 2007; Bohbot et al., 1998; Habib & Sirigu, 1987), and performance on object-location memory tasks (Ploner et al., 2000; Smith & Milner, 1981, 1989; Smith et al., 2011). The aim of this study was to provide an accurate definition of the location of activation peaks related to spatial processing on the parahippocampal cortex of the human brain on a subject- by-subject basis. Examination of functional activity in individual brains is critical because group studies often obscure a clear assignment of activation within particular regions. The advantage of subject-per-subject analysis has already been demonstrated for various regions of the brain, including the differentiation of the frontal eye field region from the hand premotor region (Amiez et al., 2006), the identification of three cingulate motor areas in the human brain (Amiez & Petrides, 2014), the location of the hand region in the primary motor cortex (Yousry et al., 1997) and the accurate identification of the locus of reading activity in the angular gyrus (Segal & Petrides, 2013).

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In the fMRI study presented in Chapter 4, the morphological descriptions of the rhinal sulcus, the collateral sulcus proper, and the parahippocampal extension of the collateral sulcus that were established in Chapter 2, together with the measures of location variability of these three sulci in the form of probabilistic maps offered in Chapter 3, were applied to identify more accurately and thereby discriminate between the location of activation peaks. The results showed that this approach allowed for a distinction between three functional activation clusters along the parahippocampal gyrus, during navigation, two in the posterior parahippocampal cortex and one along the middle parahippocampal cortex. More specifically, the findings showed that the middle and posterior parts of the parahippocampal cortex, but neither the anterior parahippocampal cortex nor the entorhinal cortex, were involved when scene-selective information necessary for navigation was processed. This functional neuroimaging study is important, as it is the first to provide explicit landmarks for possible functional subdivisions of the parahippocampal cortex. The identification of the location of the three different clusters of activation peaks (Chapter 4) was made possible only because of the anatomical studies of Chapters 2 and 3. Specifically, first, the morphological examination of the collateral sulcus proper of the first study (Chapter 2) allowed for an accurate differentiation based on the local morphology of the parahippocampal gyrus into an anterior part (i.e. the entorhinal cortex) and a posterior part (i.e. parahippocampal cortex). Second, the observation that the collateral sulcus proper is composed of two sulcal segments allowed for a linking of the functional activation peaks to the distinct morphological parts of the anterior, or posterior collateral sulcus proper, or to the region of overlap between the two segments. The probabilistic maps of the anterior and posterior segments of the collateral sulcus proper (Chapter 3) provided quantitative data in the form of coordinates within the standard space of the Montreal Neurological Institute that greatly aided in the more accurate identification of the location of the clusters observed in the fMRI study in Chapter 4. Together, these results provide support for the notion that there are subdivisions along the parahippocampal cortex.

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Subsequently this information may be crucial for future studies when examining such the location and functional specialization of such subdivisions. In addition, the results from our third study (Chapter 4) may have aided previous investigations in a number of ways. Several studies to date have set out to examine functional subdivisions along the parahippocampal gyrus (Aminoff et al., 2007; Köhler et al., 2002; Litman et al., 2009; Pihlajamaki et al., 2004; Staresina et al., 2011; Sulpizio et al., 2013). Some studies divided the parahippocampal gyrus into an anterior part, which most often corresponded to the entorhinal cortex, and a posterior part, which corresponded to the parahippocampal cortex (Köhler et al., 2002; Staresina et al., 2011). Staresina and colleagues (2011) added a ‘transition’ zone, by separating the parahippocampal gyrus into three segments of equal distance. This way, the transition zone contained portions of the posterior region of the entorhinal cortex and of the anterior part of the parahippocampal cortex (Staresina et al., 2011). A study by Litman and colleagues (2009) examined several subdivisions of the parahippocampal cortex. Their results provided some insight into the functional subdivisions of the parahippocampal gyrus in general and of the parahippocampal cortex specifically. The study by Litman and colleagues (2009) divided the parahippocampal gyrus into two major subdivisions based on anatomical criteria (i.e. an anterior parahippocampal gyrus, corresponding to the extent of the entorhinal cortex, and a posterior parahippocampal gyrus, corresponding to the parahippocampal cortex). However, the posterior limit of the posterior subdivision was arbitrarily chosen and located rather caudally, thereby including parts of the anterior lingual gyrus. In addition, the investigators created further partitions of the anterior and posterior parahippocampal subdivisions. The anterior part, which corresponded to the extent of the entorhinal cortex, was divided into three sections of equal distance, while the posterior part, corresponding approximately to the parahippocampal cortex, was divided into four sections of equal distance. The results of this study found that the posterior parahippocampal cortex showed the greatest response-sensitivity to scene stimuli, with a gradual decrease in scene- preference, as measured using BOLD signal strength, the further anterior along

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the parahippocampal cortex that the signal was measured, while the response to object stimuli was maintained to the same degree across the parahippocampal cortex (Litman et al., 2009). In light of the findings presented in Chapter 4 of the present thesis (e.g. discrimination of activation peaks along the parahippocampal cortex, that relate to the local morphology of the segments of the collateral sulcus proper (as established in Chapters 2 and 3)), future studies may test more accurately the differential contribution of parahippocampal subdivisions to the processing of spatial memory. Furthermore, another application of the findings of the three studies presented in Chapters 2, 3, and 4, is to the functional subdivision along the parahippocampal cortex that is known as the parahippocampal place area (Epstein & Kanwisher, 1998). This region has been implicated specifically in the processing of scene and place information (Aminoff et al., 2007; Epstein & Kanwisher, 1998; Litman et al., 2009; Staresina et al., 2011). The parahippocampal place area has been reported to lie on the posterior parahippocampal cortex. However, the parahippocampal place area is not an anatomically defined region. Rather it is defined using functional localizer scans, which take little account of the anatomy of the brain. Other studies that have identified a scene-selective region in the absence of localizer scans have located it in the posterior parahippocampal cortex (Aguirre & D'Esposito, 1997; Epstein & Kanwisher, 1998; Köhler et al., 2002; Pihlajamaki et al., 2004; Staresina et al., 2011; Sulpizio et al., 2013). However, no clear anatomical definitions have been provided regarding what constitutes the posterior parahippocampal cortex (Aguirre & D'Esposito, 1997; Epstein & Kanwisher, 1998; Köhler et al., 2002; Pihlajamaki et al., 2004; Staresina et al., 2011; Sulpizio et al., 2013) and the coordinates reported by functional neuroimaging studies have shown great variability in terms of the location of the activation peaks (see Table 3.9.3 in Chapter 3). The present study offers specific anatomical criteria for a more accurate localization of activation peaks on the posterior part of the parahippocampal cortex, which likely corresponds to what has been referred to as the parahippocampal place area. Future research may examine in greater detail the

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functional contributions of regions-of-interest in the anterior, middle, and the posterior parts of the parahippocampal cortex (as presented in Chapter 4), which are based on anatomical definitions (Chapters 2 and 3), rather than arbitrary delineations.

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6.3 Anatomo-functional relationships from the healthy brain to the study of a clinical population The key findings of the study presented in Chapter 4 showed that there are three clusters of peaks along the parahippocampal cortex observed during navigation in healthy subjects, two in the posterior parahippocampal cortex and one along the middle parahippocampal cortex. This differentiation in location of the activation clusters was made possible by the findings of the anatomical studies that are presented in Chapters 2 and 3. The fourth study of this thesis, presented in Chapter 5, examined the influence of having sustained a mild traumatic brain injury on the functional activation patterns obtained during the same navigation experiment as employed in Chapter 4. This was done by comparing the percentage BOLD signal change between the mild traumatic brain injured and the healthy control participants (e.g. the control participants who formed the basis of Study 3 in Chapter 4 of this thesis). As the parahippocampal cortex has been implicated in the processing of scene-relevant information, it was of great interest to see if information processing (as measured by presence of activation peaks obtained through functional neuroimaging) is the same in participants who had and who had not sustained a mild head trauma. The main findings of the study presented in Chapter 5 were a lack of performance differences (i.e. in the time to navigate to a target landmark) between the healthy control group and mild traumatic brain injury group, and the presence of differences in the functional activation patterns between the two groups. The finding showed that while specific key regions involved in navigation (i.e. the parahippocampal cortex, retrosplenial cortex, caudate nucleus, and the dorsolateral prefrontal cortex) were recruited by both groups, the mild traumatic brain injured group showed a significant reduction in the percentage BOLD signal change, compared to healthy control participants, in the right parahippocampal cortex, right retrosplenial cortex, right caudate nucleus, right dorsolateral prefrontal cortex, and left middle parahippocampal cortex. A significantly greater BOLD activation signal change for the mild traumatic brain injured compared to the healthy control group was observed in visual association areas in the right lingual gyrus and the fusiform

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gyrus bilaterally. The identification of differences between the healthy and the mild traumatic brain injured groups in the activation peaks observed in the middle and posterior parahippocampal cortex clearly demonstrates the value and necessity of the morphological studies presented in Chapters 2 and 3 in the examination of activation patterns in clinical groups (i.e. subjects who have sustained brain injury). Without these morphological investigations, the identification of the location of the activation peaks, and their separation into different parahippocampal subdivisions, would not have been possible. The precise understanding and definition of the sulcal-gyral morphology permits a detailed examination of functional activations along the parahippocampal gyrus, such as the differences in functional activation patterns following a mild traumatic brain injury. Even though the studies presented in Chapters 3 and 4 of the present thesis did not set out to test the difference in the stimulus qualities processed by the parahippocampal subdivisions, it is of great importance to note that these studies are based on a thorough investigation of the local morphology. Thereby, the findings in Chapters 3 and 4 provide ample evidence that supports a differential functional contribution of the middle and the posterior parahippocampal cortex during navigation. Furthermore, these findings may offer the foundation for the identification of functional and anatomical biomarkers for the differences seen as a result of mild head trauma. Future studies may examine whether rehabilitation has an effect on the signal strength in the regions-of- interest identified in the study of Chapter 5. In addition, it is of great value to see whether repeated mild head trauma causes an even greater reduction in the signal strength in the regions of the middle and posterior parahippocampal cortex. Furthermore, the results of the study presented in Chapter 5 suggest that during navigation, the healthy control participants employ a combination of navigation strategies that recruit the caudate nucleus (procedural approach to navigation) and the cortex of the parahippocampal gyrus (landmark-based approach to navigation). While the participants with mild traumatic brain injury use these strategies as well, as seen by subthreshold activation in these regions, they do so to a less optimal degree. It is therefore hypothesized that in order to compensate

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for this sub-optimal processing in the regions of the parahippocampal cortex, the caudate nucleus, and the dorsolateral prefrontal cortex, visual association areas of the fusiform and lingual gyri are recruited to a greater amount than needed by the healthy control participants. It is of importance for clinicians and researchers alike, to identify and quantify subtle (i.e. small) changes that result from the mild traumatic brain injury in order to achieve a better understanding and develop improved treatment and/or intervention plans. This is particularly important because mild traumatic brain injury often shows an absence of structural abnormalities on neuroimaging scans, and because approximately 15 percent of individuals continue reporting persistent cognitive problems (Bernstein, 1999; Carroll et al., 2004) even though the majority recovers within one year of injury (Holm et al., 2005). In addition, a study by Bigler and colleagues (1997) showed that the structural changes in the hippocampus only became apparent after 100 days post-injury, while they were not present within the initial 100 days, suggesting that the effects of a traumatic brain injury may be progressive even in the absence of repeated trauma. It must be noted that this study included various degrees of severity of traumatic brain injury (from mild to severe; Bigler et al., 1997). Furthermore, cumulative mild traumatic brain injury has been found to cause more severe and long-lasting cognitive impairments (Gaetz et al., 2000; Rabadi & Jordan, 2001). Together, the results of our fourth study presented in Chapter 5 are imperative to create a better understanding of the consequence that the mild traumatic brain injury has on the brain, and especially in light of the study of Bigler and colleagues (1997), identification of subtle changes is of immense importance.

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6.4 Conclusion The studies reported in this thesis advanced the knowledge in the field of neuroscience in several ways. First, they clarified the relation between the rhinal sulcus and the collateral sulcus proper. Second, they showed that the collateral sulcus proper could be divided into two segments. Third, they illustrated that a structure-function relationship exists in the parahippocampal gyrus in the healthy population. Finally, the insights into the anatomy of the collateral sulcal complex and the structure-functional relationship were shown to apply to a clinical population to identify subtle changes in functional activation patterns as a consequence of mild traumatic brain injury.

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List of References for Introduction and Discussion

Introduction

Aguirre, G. K. & D'Esposito, M. (1997). Environmental knowledge is subserved by separable dorsal/ventral neural areas. J Neurosci, 17, 2512-2518.

Aguirre, G. K., Detre, J. A., Alsop, D. C. & D'Esposito, M. (1996). The parahippocampus subserves topographical learning in man. Cerebral Cortex, 6, 823-829.

Aguirre, G. K., Zarahn, E. & D'Esposito, M. (1998). An area within human ventral cortex sensitive to "building" stimuli: evidence and implications. Neuron, 21, 373-383.

Amaral, D. & Insausti, R. (1990). The human nervous system. Academic, San Diego, CA, 711-755.

Amaral, D. G., Insausti, R. & Cowan, W. M. (1987). The entorhinal cortex of the monkey: I. Cytoarchitectonic organization. The Journal of Comparative Neurology, 264, 326-355.

Amiez, C., Kostopoulos, P., Champod, A. S. & Petrides, M. (2006). Local morphology predicts functional organization of the dorsal premotor region in the human brain. J Neurosci, 26, 2724-2731.

Amiez, C. & Petrides, M. (2014). Neuroimaging evidence of the anatomo- functional organization of the human cingulate motor areas. Cereb Cortex, 24, 563-578.

Aminoff, E., Gronau, N. & Bar, M. (2007). The parahippocampal cortex mediates spatial and nonspatial associations. Cereb Cortex, 17, 1493-1503.

Andrews, T. J., Clarke, A., Pell, P. & Hartley, T. (2010). Selectivity for low-level features of objects in the human ventral stream. Neuroimage, 49, 703-711.

259

Aoki, K., Hiroki, M., Bando, M., Miyamoto, K. & Hirai, S. (2003). [A case of agnosia for streets without visual memory disturbance]. Rinsho Shinkeigaku, 43, 335-340.

Arcaro, M. J., McMains, S. A., Singer, B. D. & Kastner, S. (2009). Retinotopic organization of human ventral visual cortex. J Neurosci, 29, 10638-10652.

Arnold, A. E., Burles, F., Krivoruchko, T., Liu, I., Rey, C. D., Levy, R. M. & Iaria, G. (2013). Cognitive mapping in humans and its relationship to other orientation skills. Exp Brain Res, 224, 359-372.

Bachevalier, J. & Nemanic, S. (2008). Memory for spatial location and object- place associations are differently processed by the hippocampal formation, parahippocampal areas TH/TF and perirhinal cortex. Hippocampus, 18, 64-80.

Baldassano, C., Beck, D. M. & Fei-Fei, L. (2013). Differential connectivity within the Parahippocampal Place Area. NeuroImage, 75, 228-237.

Barry, C., Ginzberg, L. L., O’Keefe, J. & Burgess, N. (2012). Grid cell firing patterns signal environmental novelty by expansion. Proceedings of the National Academy of Sciences, 109, 17687-17692.

Beall, M. J. & Lewis, D. A. (1992). Heterogeneity of layer II neurons in human entorhinal cortex. The Journal of Comparative Neurology, 321, 241-266.

Bigler, E. (2000). The Lesion(s) in Traumatic Brain Injury: Implications for Clinical Neuropsychology. Retrieved September 24, 2015, http://web.archive.org/web/20041205062946/http://psych.byu.edu/ work/tbi.pdf

Bigler, E. D., Blatter, D. D., Anderson, C. V., Johnson, S. C., Gale, S. D., Hopkins, R. O. & Burnett, B. (1997). Hippocampal volume in normal aging and traumatic brain injury. American Journal of Neuroradiology, 18, 11-23.

260

Boccara, C. N., Sargolini, F., Thoresen, V. H., Solstad, T., Witter, M. P., Moser, E. I. & Moser, M.-B. (2010). Grid cells in pre- and parasubiculum. Nat Neurosci, 13, 987-994.

Boccia, M., Nemmi, F. & Guariglia, C. (2014). Neuropsychology of environmental navigation in humans: review and meta-analysis of FMRI studies in healthy participants. Neuropsychol Rev, 24, 236-251.

Bogacz, R., Brown, M. & Giraud-Carrier, C. (2001). Model of Familiarity Discrimination in the Perirhinal Cortex. Journal of Computational Neuroscience, 10, 5-23.

Bohbot, V. D., Allen, J. J. & Nadel, L. (2000). Memory deficits characterized by patterns of lesions to the hippocampus and parahippocampal cortex. Ann N Y Acad Sci, 911, 355-368.

Bohbot, V. D. & Corkin, S. (2007). Posterior parahippocampal place learning in H.M. Hippocampus, 17, 863-872.

Bohbot, V. D., Kalina, M., Stepankova, K., Spackova, N., Petrides, M. & Nadel, L. (1998). Spatial memory deficits in patients with lesions to the right hippocampus and to the right parahippocampal cortex. Neuropsychologia, 36, 1217-1238.

Brewer, J. B., Zhao, Z., Desmond, J. E., Glover, G. H. & Gabrieli, J. D. E. (1998). Making Memories: Brain Activity that Predicts How Well Visual Experience Will Be Remembered. Science, 281, 1185-1187.

Brodmann, K. (1909). Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Leipzig: Barth.

Buffalo, E. A., Bellgowan, P. S. & Martin, A. (2006). Distinct roles for medial temporal lobe structures in memory for objects and their locations. Learn Mem, 13, 638-643.

261

Buffalo, E. A., Ramus, S. J., Clark, R. E., Teng, E., Squire, L. R. & Zola, S. M. (1999). Dissociation between the effects of damage to perirhinal cortex and area TE. Learn Mem, 6, 572-599.

Buffalo, E. A., Reber, P. J. & Squire, L. R. (1998). The human perirhinal cortex and recognition memory. Hippocampus, 8, 330-339.

Burwell, R. D., Witter, M. P. & Amaral, D. G. (1995). Perirhinal and postrhinal cortices of the rat: a review of the neuroanatomical literature and comparison with findings from the monkey brain. Hippocampus, 5, 390-408.

Chiavaras, M. M., LeGoualher, G., Evans, A. & Petrides, M. (2001). Three- dimensional probabilistic atlas of the human orbitofrontal sulci in standardized stereotaxic space. Neuroimage, 13, 479-496.

Collins, D. L., Neelin, P., Peters, T. M. & Evans, A. C. (1994). Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr, 18, 192-205.

Collins, L. (2012). Montreal Neurological Institute (MNI) stereotaxic space. In M. Petrides (Ed.), The human cerebral cortex: An MRI atlas of the sulci and gyri in MNI stereotaxic space (pp. 11-17). New York: Academic Press.

Corkin, S. (1965). Tactually-guided maze learning in man: Effects of unilateral cortical excisions and bilateral hippocampal lesions. Neuropsychologia, 3, 339- 351.

Corkin, S. (2002). What's new with the amnesic patient H.M.? Nat Rev Neurosci, 3, 153-160.

Corkin, S., Amaral, D. G., González, R. G., Johnson, K. A. & Hyman, B. T. (1997). H. M.’s Medial Temporal Lobe Lesion: Findings from Magnetic Resonance Imaging. The Journal of Neuroscience, 17, 3964-3979.

262

Duvernoy, H. (1999). The Human Brain: Surface, Three-Dimensional Sectional Anatomy and MRI (2nd Edition ed.). Wien: Springer-Verlag.

Eacott, M. J. & Gaffan, E. A. (2005). The roles of perirhinal cortex, postrhinal cortex, and the fornix in memory for objects, contexts, and events in the rat. Quarterly Journal of Experimental Psychology: Section B, 58, 202-217.

Economo, C. & Koskinas, G. N. (1925). Die Cytoarchitektur der Hirnrinde des erwachsenen Menschen. Wien: Springer.

Ekstrom, A. D., Kahana, M. J., Caplan, J. B., Fields, T. A., Isham, E. A., Newman, E. L. & Fried, I. (2003). Cellular networks underlying human spatial navigation. Nature, 425, 184-188.

Epstein, R., Graham, K. S. & Downing, P. E. (2003). Viewpoint-Specific Scene Representations in Human Parahippocampal Cortex. Neuron, 37, 865-876.

Epstein, R., Harris, A., Stanley, D. & Kanwisher, N. (1999). The Parahippocampal Place Area: Recognition, Navigation, or Encoding? Neuron, 23, 115-125.

Epstein, R. & Kanwisher, N. (1998). A cortical representation of the local visual environment. Nature, 392, 598-601.

Epstein, R. A. (2008). Parahippocampal and retrosplenial contributions to human spatial navigation. Trends Cogn Sci, 12, 388-396.

Evans, A. C., Marrett, S. & Peters, T. M. (1989). Anatomical-functional correlative analysis of the human brain using three-dimensional imaging systems. Proceedings of the International Society of Optical Engineering (SPIE): Medical Imaging III, 264–274.

Fox, P. T., Miezin, F. M., Allman, J. M., Van Essen, D. C. & Raichle, M. E. (1987). Retinotopic organization of human visual cortex mapped with positron- emission tomography. J Neurosci, 7, 913-922.

263

Friston, K. J. & Henson, R. N. (2006). Commentary on: Divide and conquer; a defence of functional localisers. NeuroImage, 30, 1097-1099.

Friston, K. J., Rotshtein, P., Geng, J. J., Sterzer, P. & Henson, R. N. (2006). A critique of functional localisers. NeuroImage, 30, 1077-1087.

Fyhn, M., Molden, S., Witter, M. P., Moser, E. I. & Moser, M.-B. (2004). Spatial Representation in the Entorhinal Cortex. Science, 305, 1258-1264.

Gaffan, E. A., Healey, A. N. & Eacott, M. J. (2004). Objects and positions in visual scenes: effects of perirhinal and postrhinal cortex lesions in the rat. Behav Neurosci, 118, 992-1010.

Georges-François, P., Rolls, E. T. & Robertson, R. G. (1999). Spatial View Cells in the Primate Hippocampus: Allocentric View not Head Direction or Eye Position or Place. Cerebral Cortex, 9, 197-212.

Germann, J., Robbins, S., Halsband, U. & Petrides, M. (2005). Precentral sulcal complex of the human brain: morphology and statistical probability maps. J Comp Neurol, 493, 334-356.

Gloor, P. (1997). The Temporal Lobe and Limbic System. New York: Oxford University Press.

Goldman-Rakic, P. S., Selemon, L. D. & Schwartz, M. L. (1984). Dual pathways connecting the dorsolateral prefrontal cortex with the hippocampal formation and parahippocampal cortex in the rhesus monkey. Neuroscience, 12, 719-743.

Gratiolet, L. P. (1854). Mémoire sur les plis cérébraux de l'homme et des primates. In Mit einem Atlas (4 pp. XIV pl.) in fol. 33i: A. Bertrand.

Habib, M. & Sirigu, A. (1987). Pure topographical disorientation: a definition and anatomical basis. Cortex, 23, 73-85.

264

Hafting, T., Fyhn, M., Molden, S., Moser, M.-B. & Moser, E. I. (2005). Microstructure of a spatial map in the entorhinal cortex. Nature, 436, 801-806.

Hanke, J. (1997). Sulcal pattern of the anterior parahippocampal gyrus in the human adult. Ann Anat, 179, 335-339.

Hartley, T., Maguire, E. A., Spiers, H. J. & Burgess, N. (2003). The well-worn route and the path less traveled: distinct neural bases of route following and wayfinding in humans. Neuron, 37, 877-888.

Haskins, A. L., Yonelinas, A. P., Quamme, J. R. & Ranganath, C. (2008). Perirhinal Cortex Supports Encoding and Familiarity-Based Recognition of Novel Associations. Neuron, 59, 554-560.

Haxby, J. V., Grady, C. L., Horwitz, B., Ungerleider, L. G., Mishkin, M., Carson, R. E., Herscovitch, P., Schapiro, M. B. & Rapoport, S. I. (1991). Dissociation of object and spatial visual processing pathways in human extrastriate cortex. Proc Natl Acad Sci U S A, 88, 1621-1625.

Heckers, S., Heinsen, H., Heinsen, Y. & Beckmann, H. (1990). Morphometry of the parahippocampal gyrus in schizophrenics and controls. Some anatomical considerations. J Neural Transm Gen Sect, 80, 151-155.

Henderson, J. M., Larson, C. L. & Zhu, D. C. (2008). Full scenes produce more activation than close-up scenes and scene-diagnostic objects in parahippocampal and retrosplenial cortex: an fMRI study. Brain Cogn, 66, 40-49.

Hirshhorn, M., Grady, C., Rosenbaum, R. S., Winocur, G. & Moscovitch, M. (2012). The hippocampus is involved in mental navigation for a recently learned, but not a highly familiar environment: A longitudinal fMRI study. Hippocampus, 22, 842-852.

Iaria, G., Chen, J. K., Guariglia, C., Ptito, A. & Petrides, M. (2007). Retrosplenial and hippocampal brain regions in human navigation: complementary functional

265

contributions to the formation and use of cognitive maps. Eur J Neurosci, 25, 890- 899.

Iaria, G., Fox, C. J., Chen, J.-K., Petrides, M. & Barton, J. J. S. (2008). Detection of unexpected events during spatial navigation in humans: bottom-up attentional system and neural mechanisms. European Journal of Neuroscience, 27, 1017- 1025.

Iaria, G. & Petrides, M. (2007). Occipital sulci of the human brain: Variability and probability maps. The Journal of Comparative Neurology, 501, 243-259.

Iaria, G., Petrides, M., Dagher, A., Pike, B. & Bohbot, V. D. (2003). Cognitive strategies dependent on the hippocampus and caudate nucleus in human navigation: variability and change with practice. J Neurosci, 23, 5945-5952.

Iaria, G., Robbins, S. & Petrides, M. (2008). Three-dimensional probabilistic maps of the occipital sulci of the human brain in standardized stereotaxic space. Neuroscience, 151, 174-185.

Insausti, R. (1993). Comparative anatomy of the entorhinal cortex and hippocampus in mammals. Hippocampus, 3 Spec No, 19-26.

Insausti, R. & Amaral, D. G. (2004). Hippocampal formation. In G. Paxinos & J. K. Mai (Eds.), The Human Nervous System (2nd Edition ed., pp. 871-913). San Diego: Elsevier Academic Press.

Insausti, R., Amaral, D. G. & Cowan, W. M. (1987a). The entorhinal cortex of the monkey: II. Cortical afferents. The Journal of Comparative Neurology, 264, 356- 395.

Insausti, R., Amaral, D. G. & Cowan, W. M. (1987b). The entorhinal cortex of the monkey: III. Subcortical afferents. The Journal of Comparative Neurology, 264, 396-408.

266

Insausti, R., Juottonen, K., Soininen, H., Insausti, A. M., Partanen, K., Vainio, P., Laakso, M. P. & Pitkänen, A. (1998). MR volumetric analysis of the human entorhinal, perirhinal, and temporopolar cortices. American Journal of Neuroradiology, 19, 659-671.

Insausti, R., Tunon, T., Sobreviela, T., Insausti, A. M. & Gonzalo, L. M. (1995). The human entorhinal cortex: a cytoarchitectonic analysis. J Comp Neurol, 355, 171-198.

Jacobs, J., Kahana, M. J., Ekstrom, A. D., Mollison, M. V. & Fried, I. (2010). A sense of direction in human entorhinal cortex. Proceedings of the National Academy of Sciences, 107, 6487-6492.

Jacobs, J., Weidemann, C. T., Miller, J. F., Solway, A., Burke, J. F., Wei, X.-X., Suthana, N., Sperling, M. R., Sharan, A. D., Fried, I. & Kahana, M. J. (2013). Direct recordings of grid-like neuronal activity in human spatial navigation. Nat Neurosci, 16, 1188-1190.

Janzen, G. & van Turennout, M. (2004). Selective neural representation of objects relevant for navigation. Nat Neurosci, 7, 673-677.

Jenkinson, M., Beckmann, C. F., Behrens, T. E., Woolrich, M. W. & Smith, S. M. (2012). FSL. Neuroimage, 62, 782-790.

Kanwisher, N., McDermott, J. & Chun, M. M. (1997). The fusiform face area: a module in human extrastriate cortex specialized for face perception. J Neurosci, 17, 4302-4311.

Killian, N. J., Jutras, M. J. & Buffalo, E. A. (2012). A map of visual space in the primate entorhinal cortex. Nature, 491, 761-764.

Köhler, S., Crane, J. & Milner, B. (2002). Differential contributions of the parahippocampal place area and the anterior hippocampus to human memory for scenes. Hippocampus, 12, 718-723.

267

Krimer, L. S., Hyde, T. M., Herman, M. M. & Saunders, R. C. (1997). The entorhinal cortex: an examination of cyto- and myeloarchitectonic organization in humans. Cereb Cortex, 7, 722-731.

Lavenex, P., Suzuki, W. A. & Amaral, D. G. (2002). Perirhinal and parahippocampal cortices of the macaque monkey: projections to the neocortex. J Comp Neurol, 447, 394-420.

Lavenex, P., Suzuki, W. A. & Amaral, D. G. (2004). Perirhinal and parahippocampal cortices of the macaque monkey: Intrinsic projections and interconnections. The Journal of Comparative Neurology, 472, 371-394.

Litman, L., Awipi, T. & Davachi, L. (2009). Category-specificity in the human medial temporal lobe cortex. Hippocampus, 19, 308-319.

Maguire, E. A., Burgess, N., Donnett, J. G., Frackowiak, R. S. J., Frith, C. D. & O'Keefe, J. (1998). Knowing Where and Getting There: A Human Navigation Network. Science, 280, 921-924.

Maguire, E. A., Burke, T., Phillips, J. & Staunton, H. (1996). Topographical disorientation following unilateral temporal lobe lesions in humans. Neuropsychologia, 34, 993-1001.

Maguire, E. A., Frackowiak, R. S. J. & Frith, C. D. (1997). Recalling Routes around London: Activation of the Right Hippocampus in Taxi Drivers. The Journal of Neuroscience, 17, 7103-7110.

Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S. & Frith, C. D. (2000). Navigation-related structural change in the hippocampi of taxi drivers. Proc Natl Acad Sci U S A, 97, 4398-4403.

Malkova, L. & Mishkin, M. (2003). One-trial memory for object-place associations after separate lesions of hippocampus and posterior parahippocampal region in the monkey. J Neurosci, 23, 1956-1965.

268

Mazziotta, J., Toga, A., Evans, A., Fox, P., Lancaster, J., Zilles, K., Woods, R., Paus, T., Simpson, G., Pike, B., Holmes, C., Collins, L., Thompson, P., MacDonald, D., Iacoboni, M., et al. (2001). A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philosophical Transactions of the Royal Society of London. Series B, 356, 1293- 1322.

Mazziotta, J. C., Toga, A. W., Evans, A., Fox, P. & Lancaster, J. (1995). A probabilistic atlas of the human brain: theory and rationale for its development the international consortium for brain mapping (ICBM). Neuroimage, 2, 89-101.

Meunier, M., Bachevalier, J., Mishkin, M. & Murray, E. A. (1993). Effects on visual recognition of combined and separate ablations of the entorhinal and perirhinal cortex in rhesus monkeys. J Neurosci, 13, 5418-5432.

Miller, J. F., Neufang, M., Solway, A., Brandt, A., Trippel, M., Mader, I., Hefft, S., Merkow, M., Polyn, S. M., Jacobs, J., Kahana, M. J. & Schulze-Bonhage, A. (2013). Neural Activity in Human Hippocampal Formation Reveals the Spatial Context of Retrieved Memories. Science, 342, 1111-1114.

Milner, B. (1965). Visually-guided maze learning in man: Effects of bilateral hippocampal, bilateral frontal, and unilateral cerebral lesions. Neuropsychologia, 3, 317-338.

Mishkin, M. (1978). Memory in monkeys severely impaired by combined but not by separate removal of amygdala and hippocampus. Nature, 273, 297-298.

Morris, R., Pandya, D. N. & Petrides, M. (1999). Fiber system linking the mid- dorsolateral frontal cortex with the retrosplenial/presubicular region in the rhesus monkey. The Journal of Comparative Neurology, 407, 183-192.

Morris, R. G. M. (1981). Spatial localization does not require the presence of local cues. Learning and Motivation, 12, 239-260.

269

Murray, E. A. & Mishkin, M. (1986). Visual recognition in monkeys following rhinal cortical ablations combined with either amygdalectomy or hippocampectomy. J Neurosci, 6, 1991-2003.

O'Keefe, J. & Dostrovsky, J. (1971). The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Research, 34, 171-175.

O'Keefe, J. & Nadel, L. (1978). The hippocampus as a cognitive map. Oxford University Press.

Ono, M., Kubik, S. & Abernathey, C. D. (1990). Atlas of the Cerebral Sulci. Stuttgart: Thieme.

Parkinson, J., Murray, E. & Mishkin, M. (1988). A selective mnemonic role for the hippocampus in monkeys: memory for the location of objects. The Journal of Neuroscience, 8, 4159-4167.

Passingham, R. E., Stephan, K. E. & Kotter, R. (2002). The anatomical basis of functional localization in the cortex. Nat Rev Neurosci, 3, 606-616.

Paus, T., Otaky, N., Caramanos, Z., MacDonald, D., Zijdenbos, A., D'Avirro, D., Gutmans, D., Holmes, C., Tomaiuolo, F. & Evans, A. C. (1996). In vivo morphometry of the intrasulcal gray matter in the human cingulate, paracingulate, and superior-rostral sulci: hemispheric asymmetries, gender differences and probability maps. J Comp Neurol, 376, 664-673.

Penhune, V. B., Zatorre, R. J., MacDonald, J. D. & Evans, A. C. (1996). Interhemispheric anatomical differences in human primary auditory cortex: probabilistic mapping and volume measurement from magnetic resonance scans. Cereb Cortex, 6, 661-672.

Penny, W. D., Ashburner, J., Kiebel, S., Henson, R., Glaser, D. E., Phillips, C. & Friston, K. (2001). Statistical Parametric Mapping: An Annotated Bibliography. from http://www.fil.ion.ucl.ac.uk/spm/doc/spmbib.html 270

Petrides, M. (2005a). Lateral prefrontal cortex: architectonic and functional organization. Philosophical Transactions of the Royal Society B: Biological Sciences, 360, 781-795.

Petrides, M. (2005b). Lateral prefrontal cortex: architectonic and functional organization. Philos Trans R Soc Lond B Biol Sci, 360, 781-795.

Petrides, M. (2012). The Human Cerebral Cortex: An MRI Atlas of the Sulci and Gyri in MNI Sereotaxic Space. New York: Academic Press.

Petrides, M. (unpublished observations).

Petrides, M. & Pandya, D. N. (1999). Dorsolateral prefrontal cortex: comparative cytoarchitectonic analysis in the human and the macaque brain and corticocortical connection patterns. Eur J Neurosci, 11, 1011-1036.

Petrides, M. & Pandya, D. N. (2002a). Comparative cytoarchitectonic analysis of the human and the macaque ventrolateral prefrontal cortex and corticocortical connection patterns in the monkey. European Journal of Neuroscience, 16, 291- 310.

Petrides, M. & Pandya, D. N. (2002b). Comparative cytoarchitectonic analysis of the human and the macaque ventrolateral prefrontal cortex and corticocortical connection patterns in the monkey. Eur J Neurosci, 16, 291-310.

Pihlajamaki, M., Tanila, H., Kononen, M., Hanninen, T., Hamalainen, A., Soininen, H. & Aronen, H. J. (2004). Visual presentation of novel objects and new spatial arrangements of objects differentially activates the medial temporal lobe subareas in humans. Eur J Neurosci, 19, 1939-1949.

Ploner, C. J., Gaymard, B. M., Rivaud-Pechoux, S., Baulac, M., Clemenceau, S., Samson, S. & Pierrot-Deseilligny, C. (2000). Lesions affecting the parahippocampal cortex yield spatial memory deficits in humans. Cereb Cortex, 10, 1211-1216.

271

Pruessner, J. C., Kohler, S., Crane, J., Pruessner, M., Lord, C., Byrne, A., Kabani, N., Collins, D. L. & Evans, A. C. (2002). Volumetry of temporopolar, perirhinal, entorhinal and parahippocampal cortex from high-resolution MR images: considering the variability of the collateral sulcus. Cereb Cortex, 12, 1342-1353.

Reagh, Z. M. & Yassa, M. A. (2014). Object and spatial mnemonic interference differentially engage lateral and medial entorhinal cortex in humans. Proceedings of the National Academy of Sciences, 111, E4264-E4273.

Regis, J., Mangin, J. F., Ochiai, T., Frouin, V., Riviere, D., Cachia, A., Tamura, M. & Samson, Y. (2005). "Sulcal root" generic model: a hypothesis to overcome the variability of the human cortex folding patterns. Neurol Med Chir (Tokyo), 45, 1-17.

Retzius, G. (1896). Das Menschenhirn: Studien der makroskopischen Morphologie. Stockholm: Norstedt and Soener.

Robertson, R. G., Rolls, E. T., Georges-Francois, P. & Panzeri, S. (1999). Head direction cells in the primate pre-subiculum. Hippocampus, 9, 206-219.

Rolls, E. T. & O'Mara, S. M. (1995). View-responsive neurons in the primate hippocampal complex. Hippocampus, 5, 409-424.

Rolls, E. T., Robertson, R. G. & Georges-Francois, P. (1997). Spatial view cells in the primate hippocampus. Eur J Neurosci, 9, 1789-1794.

Rolls, E. T., Treves, A., Robertson, R. G., Georges-Francois, P. & Panzeri, S. (1998). Information about spatial view in an ensemble of primate hippocampal cells. J Neurophysiol, 79, 1797-1813.

Rosenbaum, R. S., Ziegler, M., Winocur, G., Grady, C. L. & Moscovitch, M. (2004). “I have often walked down this street before”: fMRI Studies on the hippocampus and other structures during mental navigation of an old environment. Hippocampus, 14, 826-835.

272

Saluja, R. S., Chen, J. K., Gagnon, I. J., Keightley, M. & Ptito, A. (2015). Navigational memory functional magnetic resonance imaging: a test for concussion in children. J Neurotrauma, 32, 712-722.

Sarkissov, S. A., Filimonoff, I. N., Kononowa, E. P., Preobraschenskaja, I. S. & Kukuew, L. A. (1955). Atlas of the Cytoarchitectonics of the Human Cerebral Cortex.: Meggiz, Moskau.

Sato, N. & Nakamura, K. (2003). Visual response properties of neurons in the parahippocampal cortex of monkeys. J Neurophysiol, 90, 876-886.

Saxe, R., Brett, M. & Kanwisher, N. (2006). Divide and conquer: A defense of functional localizers. NeuroImage, 30, 1088-1096.

Schacter, D. L. & Tulving, E. (1994). Memory systems 1994: Mit Press.

Schinazi, V. R. & Epstein, R. A. (2010). Neural correlates of real-world route learning. Neuroimage, 53, 725-735.

Scoville, W. B. & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions. J Neurol Neurosurg Psychiatry, 20, 11-21.

Scoville, W. B. & Milner, B. (2000). Loss of recent memory after bilateral hippocampal lesions. 1957. J Neuropsychiatry Clin Neurosci, 12, 103-113.

Segal, E. & Petrides, M. (2012). The morphology and variability of the caudal rami of the superior temporal sulcus. Eur J Neurosci, 36, 2035-2053.

Segal, E. & Petrides, M. (2013). Functional activation during reading in relation to the sulci of the angular gyrus region. Eur J Neurosci, 38, 2793-2801.

Shelton, A. L. & Gabrieli, J. D. E. (2002). Neural Correlates of Encoding Space from Route and Survey Perspectives. The Journal of Neuroscience, 22, 2711- 2717.

273

Slobounov, S., Zhang, K., Pennell, D., Ray, W., Johnson, B. & Sebastianelli, W. (2010). Functional abnormalities in normally appearing athletes following mild traumatic brain injury: a functional MRI study. Experimental Brain Research, 202, 341-354.

Smith, E. G. (1904). Studies in the morphology of the human brain, Records of the Egyption Government School of Medicine (Vol. 2, pp. 124-173).

Smith, M. L., Bigel, M. & Miller, L. A. (2011). Visual paired-associate learning: in search of material-specific effects in adult patients who have undergone temporal lobectomy. Epilepsy & Behavior, 20, 326-330.

Smith, M. L., Leonard, G., Crane, J. & Milner, B. (1995). The effects of frontal-or temporal-lobe lesions on susceptibility to interference in spatial memory. Neuropsychologia, 33, 275-285.

Smith, M. L. & Milner, B. (1981). The role of the right hippocampus in the recall of spatial location. Neuropsychologia, 19, 781-793.

Smith, M. L. & Milner, B. (1989). Right hippocampal impairment in the recall of spatial location: Encoding deficit or rapid forgetting? Neuropsychologia, 27, 71- 81.

Solstad, T., Boccara, C. N., Kropff, E., Moser, M.-B. & Moser, E. I. (2008). Representation of geometric borders in the entorhinal cortex. Science, 322, 1865- 1868.

Spiers, H. J. & Maguire, E. A. (2006). Thoughts, behaviour, and brain dynamics during navigation in the real world. Neuroimage, 31, 1826-1840.

Squire, L. R. & Zola-Morgan, S. (1988). Memory: brain systems and behavior. Trends Neurosci, 11, 170-175.

Squire, L. R. & Zola-Morgan, S. (1991). The medial temporal lobe memory system. Science, 253, 1380-1386.

274

Staresina, B. P., Duncan, K. D. & Davachi, L. (2011). Perirhinal and parahippocampal cortices differentially contribute to later recollection of object- and scene-related event details. J Neurosci, 31, 8739-8747.

Stefanacci, L., Suzuki, W. A. & Amaral, D. G. (1996). Organization of connections between the amygdaloid complex and the perirhinal and parahippocampal cortices in macaque monkeys. The Journal of Comparative Neurology, 375, 552-582.

Sulpizio, V., Committeri, G., Lambrey, S., Berthoz, A. & Galati, G. (2013). Selective role of lingual/parahippocampal gyrus and retrosplenial complex in spatial memory across viewpoint changes relative to the environmental reference frame. Behavioural Brain Research, 242, 62-75.

Suzuki, W. A. (1996). Neuroanatomy of the monkey entorhinal, perirhinal and parahippocampal cortices: Organization of cortical inputs and interconnections with amygdala and striatum. Seminars in Neuroscience, 8, 3-12.

Suzuki, W. A. & Amaral, D. G. (1994a). Perirhinal and parahippocampal cortices of the macaque monkey: cortical afferents. J Comp Neurol, 350, 497-533.

Suzuki, W. A. & Amaral, D. G. (1994b). Topographic organization of the reciprocal connections between the monkey entorhinal cortex and the perirhinal and parahippocampal cortices. J Neurosci, 14, 1856-1877.

Suzuki, W. A. & Amaral, D. G. (2003). Where are the perirhinal and parahippocampal cortices? a historical overview of the nomenclature and boundaries applied to the primate medial temporal lobe. Neuroscience, 120, 893- 906.

Suzuki, W. A., Zola-Morgan, S., Squire, L. R. & Amaral, D. G. (1993). Lesions of the perirhinal and parahippocampal cortices in the monkey produce long- lasting memory impairment in the visual and tactual modalities. J Neurosci, 13, 2430-2451.

275

Talairach, J. & Tournoux, P. (1988). Co-Planar Stereotaxic Atlas of the Human Brain. New York: Thieme.

Taube, J. S., Goodridge, J. P., Golob, E. J., Dudchenko, P. A. & Stackman, R. W. (1996). Processing the head direction cell signal: A review and commentary. Brain Research Bulletin, 40, 477-484.

Taube, J. S., Muller, R. U. & Ranck, J. B., Jr. (1990). Head-direction cells recorded from the postsubiculum in freely moving rats. II. Effects of environmental manipulations. J Neurosci, 10, 436-447.

Tomaiuolo, F., MacDonald, J. D., Caramanos, Z., Posner, G., Chiavaras, M., Evans, A. C. & Petrides, M. (1999). Morphology, morphometry and probability mapping of the pars opercularis of the inferior frontal gyrus: an in vivo MRI analysis. Eur J Neurosci, 11, 3033-3046.

Van Cauter, T., Camon, J., Alvernhe, A., Elduayen, C., Sargolini, F. & Save, E. (2013). Distinct roles of medial and lateral entorhinal cortex in spatial cognition. Cereb Cortex, 23, 451-459.

Van Hoesen, G. W. (1982). The parahippocampal gyrus: New observations regarding its cortical connections in the monkey. Trends in Neurosciences, 5, 345- 350.

Van Hoesen, G. W. (1995). Anatomy of the medial temporal lobe. Magn Reson Imaging, 13, 1047-1055.

Van Hoesen, G. W. & Pandya, D. N. (1975). Some connections of the entorhinal (area 28) and perirhinal (area 35) cortices of the rhesus monkey. I. Temporal lobe afferents. Brain Research, 95, 1-24.

Van Hoesen, G. W., Pandya, D. N. & Butters, N. (1972). Cortical afferents to the entorhinal cortex of the Rhesus monkey. Science, 175, 1471-1473.

276

Vogt, B. A., Vogt, L. J., Perl, D. P. & Hof, P. R. (2001). Cytology of human caudomedial cingulate, retrosplenial, and caudal parahippocampal cortices. The Journal of Comparative Neurology, 438, 353-376. von Bonin, G. & Bailey, P. (1947). The Neocortex of Macaca Mulatta: University of Illinois Press, Urbana IL.

Worsley, K. J., Liao, C., Aston, J., Petre, V., Duncan, G. H., Morales, F. & Evans, A. C. (2002). A general statistical analysis for fMRI data. NeuroImage, 15, 1-15.

Xu, J., Evensmoen, H. R., Lehn, H., Pintzka, C. W. & Haberg, A. K. (2010). Persistent posterior and transient anterior medial temporal lobe activity during navigation. Neuroimage, 52, 1654-1666.

Yousry, T. A., Schmid, U. D., Alkadhi, H., Schmidt, D., Peraud, A., Buettner, A. & Winkler, P. (1997). Localization of the motor hand area to a knob on the precentral gyrus. A new landmark. Brain, 120, 141-157.

Zlatkina, V., Amiez, C. & Petrides, M. (2015). The postcentral sulcal complex and the transverse postcentral sulcus and their relation to sensorimotor functional organization. European Journal of Neuroscience.

Zlatkina, V. & Petrides, M. (2010). Morphological patterns of the postcentral sulcus in the human brain. J Comp Neurol, 518, 3701-3724.

Zlatkina, V. & Petrides, M. (2014). Morphological patterns of the intraparietal sulcus and the anterior intermediate parietal sulcus of Jensen in the human brain (Vol. 281).

Zola-Morgan, S., Squire, L. & Amaral, D. (1986a). Human amnesia and the medial temporal region: enduring memory impairment following a bilateral lesion limited to field CA1 of the hippocampus. The Journal of Neuroscience, 6, 2950- 2967.

277

Zola-Morgan, S. & Squire, L. R. (1993). Neuroanatomy of memory. Annu Rev Neurosci, 16, 547-563.

Zola-Morgan, S., Squire, L. R. & Amaral, D. G. (1986b). Human amnesia and the medial temporal region: enduring memory impairment following a bilateral lesion limited to field CA1 of the hippocampus. J Neurosci, 6, 2950-2967.

Zola-Morgan, S., Squire, L. R., Amaral, D. G. & Suzuki, W. A. (1989). Lesions of perirhinal and parahippocampal cortex that spare the amygdala and hippocampal formation produce severe memory impairment. J Neurosci, 9, 4355- 4370.

Zola-Morgan, S., Squire, L. R. & Ramus, S. J. (1994). Severity of memory impairment in monkeys as a function of locus and extent of damage within the medial temporal lobe memory system. Hippocampus, 4, 483-495.

278

Discussion

Aguirre, G. K. & D'Esposito, M. (1997). Environmental knowledge is subserved by separable dorsal/ventral neural areas. J Neurosci, 17, 2512-2518.

Aguirre, G. K. & D'Esposito, M. (1999). Topographical disorientation: a synthesis and taxonomy. Brain, 122 ( Pt 9), 1613-1628.

Aguirre, G. K., Zarahn, E. & D'Esposito, M. (1998). An area within human ventral cortex sensitive to "building" stimuli: evidence and implications. Neuron, 21, 373-383.

Amiez, C., Kostopoulos, P., Champod, A. S. & Petrides, M. (2006). Local morphology predicts functional organization of the dorsal premotor region in the human brain. J Neurosci, 26, 2724-2731.

Amiez, C., Neveu, R., Warrot, D., Petrides, M., Knoblauch, K. & Procyk, E. (2013). The location of feedback-related activity in the midcingulate cortex is predicted by local morphology. J Neurosci, 33, 2217-2228.

Amiez, C. & Petrides, M. (2009). Anatomical organization of the eye fields in the human and non-human primate frontal cortex. Progress in neurobiology, 89, 220- 230.

Amiez, C. & Petrides, M. (2014). Neuroimaging evidence of the anatomo- functional organization of the human cingulate motor areas. Cereb Cortex, 24, 563-578.

Aminoff, E., Gronau, N. & Bar, M. (2007). The parahippocampal cortex mediates spatial and nonspatial associations. Cereb Cortex, 17, 1493-1503.

Amunts, K., Kedo, O., Kindler, M., Pieperhoff, P., Mohlberg, H., Shah, N., Habel, U., Schneider, F. & Zilles, K. (2005). Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and embryology, 210, 343-352.

279

Andrews, T. J., Clarke, A., Pell, P. & Hartley, T. (2010). Selectivity for low-level features of objects in the human ventral stream. Neuroimage, 49, 703-711.

Arcaro, M. J., McMains, S. A., Singer, B. D. & Kastner, S. (2009). Retinotopic organization of human ventral visual cortex. J Neurosci, 29, 10638-10652.

Bar, M. & Aminoff, E. (2003). Cortical analysis of visual context. Neuron, 38, 347-358.

Bernstein, D. M. (1999). Subject Review: Recovery from mild head injury. Brain injury, 13, 151-172.

Boccia, M., Nemmi, F. & Guariglia, C. (2014). Neuropsychology of environmental navigation in humans: review and meta-analysis of FMRI studies in healthy participants. Neuropsychol Rev, 24, 236-251.

Bohbot, V. D., Allen, J. J. & Nadel, L. (2000). Memory deficits characterized by patterns of lesions to the hippocampus and parahippocampal cortex. Ann N Y Acad Sci, 911, 355-368.

Bohbot, V. D. & Corkin, S. (2007). Posterior parahippocampal place learning in H.M. Hippocampus, 17, 863-872.

Brodmann, K. (1909). Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Leipzig: Barth.

280

Carroll, L., Cassidy, J. D., Peloso, P., Borg, J., Von Holst, H., Holm, L., Paniak, C. & Pépin, M. (2004). Prognosis for mild traumatic brain injury: results of the WHO Collaborating Centre Task Force on Mild Traumatic Brain Injury. Journal of Rehabilitation Medicine, 36, 84-105.

Duvernoy, H. (1999). The Human Brain: Surface, Three-Dimensional Sectional Anatomy and MRI (2nd Edition ed.). Wien: Springer-Verlag.

Economo, C. & Koskinas, G. N. (1925). Die Cytoarchitektur der Hirnrinde des erwachsenen Menschen. Wien: Springer.

Epstein, R., Graham, K. S. & Downing, P. E. (2003). Viewpoint-Specific Scene Representations in Human Parahippocampal Cortex. Neuron, 37, 865-876.

Epstein, R., Harris, A., Stanley, D. & Kanwisher, N. (1999). The Parahippocampal Place Area: Recognition, Navigation, or Encoding? Neuron, 23, 115-125.

Epstein, R. & Kanwisher, N. (1998). A cortical representation of the local visual environment. Nature, 392, 598-601.

Gaetz, M., Goodman, D. & Weinberg, H. (2000). Electrophysiological evidence for the cumulative effects of concussion. Brain Inj, 14, 1077-1088.

Gloor, P. (1997). The Temporal Lobe and Limbic System. New York: Oxford University Press.

Habib, M. & Sirigu, A. (1987). Pure topographical disorientation: a definition and anatomical basis. Cortex, 23, 73-85.

Hanke, J. (1997). Sulcal pattern of the anterior parahippocampal gyrus in the human adult. Ann Anat, 179, 335-339.

281

Holm, L., Cassidy, J. D., Carroll, L. J. & Borg, J. (2005). Summary of the WHO Collaborating Centre for Neurotrauma Task Force on Mild Traumatic Brain Injury. J Rehabil Med, 37, 137-141.

Iaria, G., Chen, J. K., Guariglia, C., Ptito, A. & Petrides, M. (2007). Retrosplenial and hippocampal brain regions in human navigation: complementary functional contributions to the formation and use of cognitive maps. Eur J Neurosci, 25, 890- 899.

Insausti, R. & Amaral, D. G. (2004). Hippocampal formation. In G. Paxinos & J. K. Mai (Eds.), The Human Nervous System (2nd Edition ed., pp. 871-913). San Diego: Elsevier Academic Press.

Insausti, R., Tunon, T., Sobreviela, T., Insausti, A. M. & Gonzalo, L. M. (1995). The human entorhinal cortex: a cytoarchitectonic analysis. J Comp Neurol, 355, 171-198.

282

Kim, H., Bernasconi, N., Bernhardt, B., Colliot, O. & Bernasconi, A. (2008). Basal temporal sulcal morphology in healthy controls and patients with temporal lobe epilepsy. Neurology, 70, 2159-2165.

Köhler, S., Crane, J. & Milner, B. (2002). Differential contributions of the parahippocampal place area and the anterior hippocampus to human memory for scenes. Hippocampus, 12, 718-723.

Litman, L., Awipi, T. & Davachi, L. (2009). Category-specificity in the human medial temporal lobe cortex. Hippocampus, 19, 308-319.

Maguire, E. A., Frith, C. D., Burgess, N., Donnett, J. G. & O'Keefe, J. (1998). Knowing where things are parahippocampal involvement in encoding object locations in virtual large-scale space. J Cogn Neurosci, 10, 61-76.

Novak, K., Czech, T., Prayer, D., Dietrich, W., Serles, W., Lehr, S. & Baumgartner, C. (2002). Individual variations in the sulcal anatomy of the basal temporal lobe and its relevance for epilepsy surgery: an anatomical study performed using magnetic resonance imaging. J Neurosurg, 96, 464-473.

O'Keefe, J. & Nadel, L. (1978). The hippocampus as a cognitive map. Oxford University Press.

Ono, M., Kubik, S. & Abernathey, C. D. (1990). Atlas of the Cerebral Sulci. Stuttgart: Thieme.

Petrides, M. (unpublished observations).

Ploner, C. J., Gaymard, B. M., Rivaud-Pechoux, S., Baulac, M., Clemenceau, S., Samson, S. & Pierrot-Deseilligny, C. (2000). Lesions affecting the

283

parahippocampal cortex yield spatial memory deficits in humans. Cereb Cortex, 10, 1211-1216.

Rabadi, M. H. & Jordan, B. D. (2001). The cumulative effect of repetitive concussion in sports. Clin J Sport Med, 11, 194-198.

Rauchs, G., Orban, P., Balteau, E., Schmidt, C., Degueldre, C., Luxen, A., Maquet, P. & Peigneux, P. (2008). Partially segregated neural networks for spatial and contextual memory in virtual navigation. Hippocampus, 18, 503-518.

Reber, P. J., Wong, E. C. & Buxton, R. B. (2002). Encoding activity in the medial temporal lobe examined with anatomically constrained fMRI analysis. Hippocampus, 12, 363-376.

Retzius, G. (1896). Das Menschenhirn: Studien der makroskopischen Morphologie. Stockholm: Norstedt and Soener.

Sato, N. & Nakamura, K. (2003). Visual response properties of neurons in the parahippocampal cortex of monkeys. J Neurophysiol, 90, 876-886.

Segal, E. & Petrides, M. (2013). Functional activation during reading in relation to the sulci of the angular gyrus region. Eur J Neurosci, 38, 2793-2801.

Smith, E. G. (1904). Studies in the morphology of the human brain, Records of the Egyption Government School of Medicine (Vol. 2, pp. 124-173).

Smith, M. L. & Milner, B. (1981). The role of the right hippocampus in the recall of spatial location. Neuropsychologia, 19, 781-793.

284

Smith, M. L. & Milner, B. (1989). Right hippocampal impairment in the recall of spatial location: Encoding deficit or rapid forgetting? Neuropsychologia, 27, 71- 81.

Spiers, H. J. & Maguire, E. A. (2006). Thoughts, behaviour, and brain dynamics during navigation in the real world. Neuroimage, 31, 1826-1840.

Van Hoesen, G. W. & Pandya, D. N. (1975). Some connections of the entorhinal (area 28) and perirhinal (area 35) cortices of the rhesus monkey. I. Temporal lobe afferents. Brain Research, 95, 1-24.

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Appendices Appendix A Permissions to reproduce Figures 1.6.2 and 1.6.3 Permission to reprint the article in Chapter Two Permission to reproduce Figure 2.10.1B Ethics approval certificate for studies in Chapters Four and Five

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