DOCSLIB.ORG

Landmark Processing by Head Direction Cells

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Landmark Processing by Head Direction Cells LANDMARK PROCESSING BY HEAD DIRECTION CELLS Yave Roberto Lozano Navarro Thesis submitted to University College London for the degree of Doctor of Philosophy in Neuroscience September 2015 1 Contents DECLARATION ___________________________________________ 7 ACKNOWLEDGEMENTS ___________________________________ 8 ABBREVIATIONS _________________________________________ 9 ABSTRACT _____________________________________________ 11 I DESCRIPTION OF THE RESEARCH PROJECT ______________ 12 II REVIEW _____________________________________________ 17 Chapter 1 Behavioural and neural mechanisms of spatial navigation ___________________________________________ 17 1.1 Introduction ___________________________________ 17 1.2 Rodent navigation and memory ____________________ 18 1.2.1 Navigation strategies __________________________ 18 1.2.2 Sources of information for navigation ______________ 23 1.2.3 Reference frames _____________________________ 25 1.2.4 Role of landmarks in navigation __________________ 26 1.3 Spatially Modulated Cells ________________________ 30 1.3.1 Place cells __________________________________ 31 1.3.2 Head direction cells ___________________________ 33 1.3.3 Grid Cells ___________________________________ 35 1.3.4 Boundary vector cells __________________________ 37 1.4 Functional significance of spatially modulated cells _____ 38 Chapter 2 Neuroanatomy and functional properties of head direction cell circuits ___________________________________ 42 2.1 Introduction ______________________________________ 42 2.2 Neuroanatomy of the spatial navigation circuit ________ 43 2.3 Neuroanatomy of the head direction cell circuit ________ 45 2.4 Neuroanatomy of the landmark processing circuit ______ 50 2.5 Rodent visual system ___________________________ 55 2 2.6 Connectivity of the retrosplenial and postsubicular cortex 58 Chapter 3 Multisensory processing by head direction cells _____ 63 3.1 Introduction ___________________________________ 63 3.2 Properties of the head direction signal ______________ 64 3.3 Integration of sensory cues by head direction cells _____ 66 3.3.1 Influence of allothetic cues ______________________ 67 3.3.2 Influence of idiothetic cues ______________________ 71 3.4 Factors that influence landmark control ______________ 75 3.4.1 Learning of visual landmark cues _________________ 75 3.4.2 Learning of foreground and background cues _______ 77 3.4.3 Processing of geometric cues____________________ 79 3.5 Theoretical models of head direction cell activity_______ 80 3.6 Role of the RSC and the PoS in landmark processing __ 82 III EXPERIMENTAL CONTRIBUTIONS _______________________ 86 Chapter 4 General methods _____________________________ 86 4.1 Subjects ______________________________________ 86 4.2 Electrodes and microdrives _______________________ 86 4.3 Surgery ______________________________________ 87 4.3 Signal processing and tracking ____________________ 89 4.5 Screening procedure ____________________________ 90 4.6 Recording procedure ____________________________ 91 4.6.1 Recording arenas _____________________________ 91 4.6.2 Cue cards ___________________________________ 92 4.6.3 Cue control protocol ___________________________ 93 4.7 Data analysis __________________________________ 94 4.7.1 Spike sorting _________________________________ 95 4.7.2 Head direction cell rate map _____________________ 96 4.7.3 Head direction turning curve parameters ___________ 98 4.7.4 Head direction cell inclusion criteria _______________ 98 4.7.5 Head direction cell shift analysis __________________ 99 3 4.7.5.1 Head direction rate maps per session ____________ 99 4.7.5.2 Quantification of changes in the PFD ___________ 101 4.7.5.3 Kernel density estimates and population analysis __ 102 4.8 Histology ____________________________________ 102 Chapter 5 Population analysis of head direction cells ________ 103 5.1 Background and rationale _______________________ 103 5.2 Methods _____________________________________ 104 5.3 Head direction cell tuning curve parameters _________ 104 5.3.1 Estimation of tuning curve paramters _____________ 107 5.3.2 Statistical test for identifying head direction cells ____ 110 5.4 Standard methods for analysing a population of HD cells ___________________________________________ 113 5.5 Non-standard methods for analysing a population of HD cells ___________________________________________ 117 5.5.1 Kernel density estimates ______________________ 119 5.5.2 Statistical analysis of multimodal distributions ______ 123 5.6 Discussion and future directions __________________ 125 Chapter 6 Landmark feature processing by head direction cells 129 6.1 Background and rationale _______________________ 129 6.2 Methods and hypothesis ________________________ 131 6.2.1 Experimental procedure _______________________ 131 6.2.2 Hypothesis _________________________________ 133 6.3 Data analysis _________________________________ 136 6.3.1 Preferred firing direction shift analysis ____________ 137 6.3.2 Nonparametic density estimation ________________ 139 6.3.3 Circular summary statistics _____________________ 139 6.3.4 Inferential statistics ___________________________ 140 6.3.5 Cell response classification ____________________ 141 6.3.5.1 Bayesian analysis __________________________ 142 6.3.6 Co-rotation analysis __________________________ 143 6.3.7 Tuning curve characteristics ____________________ 144 4 6.4 Properties of PoS and RSC HD cell tuning curves ____ 145 6.5 Results of two cue card experiments _______________ 146 6.5.1 Subjects and cell numbers _____________________ 147 6.5.2 Are HD cells controlled by external room cues? _____ 148 6.5.3 Does brain area and cue type affect landmark control? _________________________________________ 149 6.5.4 Does the magnitude of cue rotation affect landmark control? _________________________________________ 150 6.5.5 Is there landmark control and discrimination for each cue type? ___________________________________________ 151 6.5.5.1 Bayesian estimates for cell response categories ___ 155 6.5.5.2 Vertical-horizontal __________________________ 159 6.5.5.3 Vertical-horizontal-polarity ____________________ 160 6.5.5.4 Top-bottom _______________________________ 161 6.5.5.5 Right-left _________________________________ 162 6.5.5.6 Black-black _______________________________ 163 6.5.5.7 Comparisons between cue types _______________ 164 6.6 Co-rotation activity in HD cell ensembles ___________ 167 6.7 Histology ____________________________________ 168 6.8 Discussion ___________________________________ 169 Chapter 7 Configural landmark processing by head direction cells ______________________________________________ 174 7.1 Background and rationale _______________________ 174 7.2 Methods _____________________________________ 177 7.2.1 Cue control protocol __________________________ 178 7.3 Data analysis _________________________________ 180 7.4 Results of the standard sessions __________________ 182 7.5 Results of the shuffle sessions ___________________ 184 7.5.1 Landmark processing of the standard cue configuration _____________________________________ 184 5 7.5.2 Landmark processing of the shuffled cue configuration _____________________________________ 186 7.6 Histology ____________________________________ 189 7.7 Discussion ___________________________________ 190 Chapter 8 General discussion and conclusion ______________ 195 References ____________________________________________ 201 6 DECLARATION I, Yave Roberto Lozano Navarro, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. 7 ACKNOWLEDGEMENTS Pursuing a doctoral degree in Neuroscience has been one of the great challenges in my life which would not have been possible without the encouragement of my parents Araceli and Roberto and my sister Heidi who have supported me unconditionally throughout my education. To my uncle Francisco, without whom I would not have been I able to cover the remaining tuition to enrol in UCL. To my supervisor, Kate Jeffery who has mentored, guided and supported me before and during the PhD, providing me with academic and personal advice, allowing me to persevere and succeed in the challenging field of behavioural electrophysiology. To my secondary supervisor, Frances Edwards for taking the time to review my upgrade report and guiding me on writing a thesis. To the scholarship from the Mexican National Council of Science and Technology, CONACYT (313254) which enabled me to study at a world’s leading research university in neuroscience. To the Medical Research Council grant G1100669, “A neuronal model of memory-integrative processing in the retrosplenial head direction system” which funded the work that I carried out. To all the former and past member of the Institute of Behavioural Neuroscience (IBN) who have been both colleagues and friends during the arduous years of graduate school. Special thanks to Robin and Liz who trained me in single-unit recording and my lab brothers Amir, Giulio, Jonathan, Laurenz, Shaz and Pierre- Yves who have been a source of both friendship and continuous help during the long days at the IBN. To Meghan, who recorded the rats that are described in Chapter 7. Special thanks to Miguel, whose statistical expertise and programming experience helped me to tackle the difficult problem of analysing circular data. To Josh for reviewing several chapters of this thesis and being a source of continuous discussion. To Caswell, for taking the time to discuss
Load more

Recommended publications
  • Representation of Spatial Orientation by the Intrinsic Dynamics of the Head-Direction Cell Ensemble: a Theory
    The Journal of Neuroscience, March 15, 1996, 16(6):2112-2126 Representation of Spatial Orientation by the Intrinsic Dynamics of the Head-Direction Cell Ensemble: A Theory Kechen Zhang Department of Cognitive Science, University of California at San Diego, La Jolla, California 92093-05 15 The head-direction (HD) cells found in the limbic system in disturbances to its shape, and the shift speed can be controlled freely moving rats represent the instantaneous head direction accurately by the strength of the odd-weight component. The of the animal in the horizontal plane regardless of the location generic formulation of the shift mechanism is determined of the animal. The internal direction represented by these cells uniquely within the current theoretical framework. The attractor uses both self-motion information for inet-tially based updating dynamics of the system ensures modality-independence of the and familiar visual landmarks for calibration. Here, a model of internal representation and facilitates the correction for cumu- the dynamics of the HD cell ensemble is presented. The sta- lative error by the putative local-view detectors. The model bility of a localized static activity profile in the network and a offers a specific one-dimensional example of a computational dynamic shift mechanism are explained naturally by synaptic mechanism in which a truly world-centered representation can weight distribution components with even and odd symmetry, be derived from observer-centered sensory inputs by integrat- respectively. Under symmetric weights or symmetric reciprocal ing self-motion information. connections, a stable activity profile close to the known direc- Key words: head-direction cell; spatial orientation; attractor tional tuning curves will emerge.
    [Show full text]
  • The Brain Compass: a Perspective on How Self-Motion Updates the Head Direction Cell Attractor
    bioRxiv preprint doi: https://doi.org/10.1101/189464; this version posted September 17, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. The brain compass: a perspective on how self-motion updates the head direction cell attractor Jean Laurens, Dora E. Angelaki Dept. of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA This study was supported by National Institutes of Health grants R21 NS098146 and R01- DC004260. Address for correspondence: Angelaki, Dora Department of Neuroscience Baylor College of Medicine One Baylor Plaza Houston, TX 77030 Office: (713) 798-1469 E-mail: [email protected] ABSTRACT Head Direction cells form an internal compass that signals head azimuth orientation even in the absence of visual landmarks. It is well accepted that head direction properties are generated through a ring attractor that is updated using rotation self-motion cues. The properties and origin of this self-motion velocity drive remain, however, unknown. We propose a unified, quantitative framework whereby the attractor velocity input represents a multisensory self-motion estimate computed through an internal model that uses sensory prediction error based on vestibular, visual, and somatosensory cues to improve on-line motor drive. We show how context- dependent strength of recurrent connections within the attractor itself, rather than the self- motion input, explain differences in head direction cell firing between free foraging and restrained movements. We also summarize recent findings on how head tilt relative to gravity influences the azimuth coding of head direction cells, and explain why and how these effects reflect an updating self-motion velocity drive that is not purely egocentric.
    [Show full text]
  • Head Direction Cells: Properties and Functional Significance Robert U Mullet-L, James B Ranck Jr* and Jeffrey S Taubea
    196 Head direction cells: properties and functional significance Robert U Mullet-l, James B Ranck Jr* and Jeffrey S Taubea The strong signal carried by head direction cells in the Under all known circumstances, postsubicular HD cells, postsubiculum complements the positional signal carried the first class to be discovered, discharge only as a by hippocampal place cells; together, the directional and function of the direction in which the rat’s head points positional signals provide the information necessary to permit in the horizontal plane, independent of head location. rats to generate and carry out intelligent, efficient solutions Postsubicular HD cell discharge is rapid only when the to spatial problems. Our opinion is that the hippocampal head points in an -90” sector of headings centered on a positional system acts as a cognitive map and that the role ‘preferred direction’. The relationship between direction of the directional system is to put the map into register with and discharge rate is steep; the function is triangular, the environment. In this way, paths found using the map can so that firing rate decreases linearly in both directions be properly executed. Head direction cells have recently been away from the preferred direction, to be nearly zero when discovered in parts of the thalamus reciprocally connected 45” away from the peak [2,3’]. In contrast to place cells, with the postsubiculum; such cells provide important clues to the reliability of postsubicular HD cell firing is very the organization of the directional system. high. (Some of the properties of HD cells are shown in Figure 2c.) Addresses tg2Department of Physiology, SUNY Health Science Center at In this review, we will first briefly recapitulate what is Brooklyn, 450 Clarkson Avenue, Brooklyn, New York 11203, USA known about HD cells (also called directional cells), t e-mail: [email protected] and then summarize what has been learned about them se-mail: [email protected] during the past two years.
    [Show full text]
  • May-Britt Moser Norwegian University of Science and Technology (NTNU), Trondheim, Norway
    Grid Cells, Place Cells and Memory Nobel Lecture, 7 December 2014 by May-Britt Moser Norwegian University of Science and Technology (NTNU), Trondheim, Norway. n 7 December 2014 I gave the most prestigious lecture I have given in O my life—the Nobel Prize Lecture in Medicine or Physiology. Afer lectures by my former mentor John O’Keefe and my close colleague of more than 30 years, Edvard Moser, the audience was still completely engaged, wonderful and responsive. I was so excited to walk out on the stage, and proud to present new and exciting data from our lab. Te title of my talk was: “Grid cells, place cells and memory.” Te long-term vision of my lab is to understand how higher cognitive func- tions are generated by neural activity. At frst glance, this seems like an over- ambitious goal. President Barack Obama expressed our current lack of knowl- edge about the workings of the brain when he announced the Brain Initiative last year. He said: “As humans, we can identify galaxies light years away; we can study particles smaller than an atom. But we still haven’t unlocked the mystery of the three pounds of matter that sits between our ears.” Will these mysteries remain secrets forever, or can we unlock them? What did Obama say when he was elected President? “Yes, we can!” To illustrate that the impossible is possible, I started my lecture by showing a movie with a cute mouse that struggled to bring a biscuit over an edge and home to its nest. Te biscuit was almost bigger than the mouse itself.
    [Show full text]
  • Neuronal Properties and Synaptic Connectivity in Rodent Presubiculum Jean Simonnet
    Neuronal properties and synaptic connectivity in rodent presubiculum Jean Simonnet To cite this version: Jean Simonnet. Neuronal properties and synaptic connectivity in rodent presubiculum. Neurons and Cognition [q-bio.NC]. Université Pierre et Marie Curie - Paris VI, 2014. English. NNT : 2014PA066435. tel-02295014 HAL Id: tel-02295014 https://tel.archives-ouvertes.fr/tel-02295014 Submitted on 24 Sep 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. THÈSE DE DOCTORAT DE L’UNIVERSITÉ PIERRE ET MARIE CURIE Spécialité Neurosciences École doctorale Cerveau – Cognition – Comportement Présentée par : Jean Simonnet Pour obtenir le grade de DOCTEUR DE L’UNIVERSITÉ PIERRE ET MARIE CURIE Sujet de la thèse : Neuronal properties and synaptic connectivity in rodent presubiculum Soutenue le 23.09.2014 devant le jury composé de : Dr Jean-Christophe Poncer Président Dr Dominique Debanne Rapporteur Dr Maria Cecilia Angulo Rapportrice Pr Hannah Monyer Examinatrice Dr Bruno Cauli Examinateur Dr Desdemona Fricker Directrice de thèse Université Pierre & Marie Curie - Paris 6 Tél. Secrétariat : 01 42 34 68 35 Bureau d’accueil, inscription des doctorants Fax : 01 42 34 68 40 et base de données Tél. pour les étudiants de A à EL : 01 42 34 68 41 Esc.
    [Show full text]
  • Encoding of 3D Head Direction Information in the Human Brain
    Received: 31 May 2018 Revised: 30 October 2018 Accepted: 26 November 2018 DOI: 10.1002/hipo.23060 RESEARCH ARTICLE Encoding of 3D head direction information in the human brain Misun Kim | Eleanor A. Maguire Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, Abstract University College London, London, United Head direction cells are critical for navigation because they convey information about which Kingdom direction an animal is facing within an environment. To date, most studies on head direction Correspondence encoding have been conducted on a horizontal two-dimensional (2D) plane, and little is known Eleanor Maguire, Wellcome Centre for Human Neuroimaging, Queen Square Institute of about how three-dimensional (3D) direction information is encoded in the brain despite humans Neurology, University College London, and other animals living in a 3D world. Here, we investigated head direction encoding in the 12 Queen Square, London WC1N 3AR, United human brain while participants moved within a virtual 3D “spaceship” environment. Movement Kingdom. was not constrained to planes and instead participants could move along all three axes in volu- Email: [email protected] metric space as if in zero gravity. Using functional magnetic resonance imaging (fMRI) multivoxel Funding information Wellcome, Grant/Award Numbers: 101759/ pattern similarity analysis, we found evidence that the thalamus, particularly the anterior por- Z/13/Z, 102263/Z/13/Z, 203147/Z/16/Z; tion, and the subiculum encoded the horizontal component of 3D head direction (azimuth). In Samsung Scholarship contrast, the retrosplenial cortex was significantly more sensitive to the vertical direction (pitch) than to the azimuth.
    [Show full text]
  • Sharp Tuning of Head Direction by Somatosensory Fast-Spiking
    bioRxiv preprint doi: https://doi.org/10.1101/2020.02.03.933143; this version posted February 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Sharp tuning of head direction 2 by somatosensory fast-spiking interneurons 1 2 1, 3 Xiaoyang Long , Calvin K. Young and Sheng-Jia Zhang * 4 1Department of Neurosurgery, Xinqiao Hospital, Army Medical University, 5 Chongqing, China 6 2Department of Psychology, Brain Health Research Centre, University of 7 Otago, Dunedin, New Zealand 8 *To whom correspondence should be addressed. 9 Correspondence and requests for materials should be addressed to: 10 [email protected] or [email protected] 11 Abstract 12 Head direction (HD) information is intricately linked to spatial navigation and cognition. 13 We recently reported the co-existence of all currently recognized spatial cell types can 14 be found in the hindlimb primary somatosensory cortex (S1HL). In this study, we 15 carried out an in-depth characterization of HD cells in S1HL. We show fast-spiking 16 (FS), putative inhibitory neurons are over-represented in and sharply tuned to HD 17 compared to regular-spiking (RS), putative excitatory neurons. These FS HD cells are 18 non-conjunctive, rarely theta modulated, not locally connected and are enriched in 19 layer 4/5a. Their co-existence with RS HD cells and angular head velocity (AHV) cells 20 in a layer-specific fashion through the S1HL presents a previously unreported 21 organization of spatial circuits.
    [Show full text]
  • Cortical Connectivity Maps Reveal Anatomically Distinct Areas in the Parietal Cortex of the Rat
    UC Irvine UC Irvine Previously Published Works Title Cortical connectivity maps reveal anatomically distinct areas in the parietal cortex of the rat. Permalink https://escholarship.org/uc/item/01d2v835 Journal Frontiers in neural circuits, 8(JAN) ISSN 1662-5110 Authors Wilber, Aaron A Clark, Benjamin J Demecha, Alexis J et al. Publication Date 2014 DOI 10.3389/fncir.2014.00146 License https://creativecommons.org/licenses/by/4.0/ 4.0 Peer reviewed eScholarship.org Powered by the California Digital Library University of California ORIGINAL RESEARCH ARTICLE published: 05 January 2015 NEURAL CIRCUITS doi: 10.3389/fncir.2014.00146 Cortical connectivity maps reveal anatomically distinct areas in the parietal cortex of the rat Aaron A. Wilber 1,2*†, Benjamin J. Clark 1,3*†, Alexis J. Demecha 1, Lilia Mesina 1, Jessica M. Vos 1 and Bruce L. McNaughton 1,2 1 Canadian Centre for Behavioural Neuroscience, The University of Lethbridge, Lethbridge, AB, Canada 2 Department of Neurobiology and Behavior, University of California, Irvine, CA, USA 3 Department of Psychology, The University of New Mexico, Albuquerque, NM, USA Edited by: A central feature of theories of spatial navigation involves the representation of spatial Charles F.Stevens, The Salk relationships between objects in complex environments. The parietal cortex has long Institute for Biological Studies, USA been linked to the processing of spatial visual information and recent evidence from Reviewed by: single unit recording in rodents suggests a role for this region in encoding egocentric Richard Hahnloser, ETH University Zurich, Switzerland and world-centered frames. The rat parietal cortex can be subdivided into four distinct Ya-tang Li, California Institute of rostral-caudal and medial-lateral regions, which includes a zone previously characterized as Technology, USA secondary visual cortex.
    [Show full text]
  • Why Isn't the Head-Direction System
    PERSPECTIVE published: 13 September 2019 doi: 10.3389/fncir.2019.00060 Why Isn’t the Head-Direction System Necessary for Direction? Lessons From the Lateral Mammillary Nuclei Christopher M. Dillingham* and Seralynne D. Vann School of Psychology, Cardiff University, Cardiff, United Kingdom Complex spatial representations in the hippocampal formation and related cortical areas require input from the head direction system. However, a recurrent finding is that behavior apparently supported by these spatial representations does not appear to require input from generative head direction regions, i.e., lateral mammillary nuclei (LMN). Spatial tasks that tax direction discrimination should be particularly sensitive to the loss of head direction information, however, this has been repeatedly shown not to be the case. A further dissociation between electrophysiological properties of the head direction system and behavior comes in the form of geometric-based navigation which is impaired following lesions to the head direction system, yet head direction cells are not normally Edited by: Kate J. Jeffery, guided by geometric cues. We explore this apparent mismatch between behavioral and University College London, electrophysiological studies and highlight future experiments that are needed to generate United Kingdom models that encompass both neurophysiological and behavioral findings. Reviewed by: Paul A. Dudchenko, Keywords: spatial memory, rodent, head-direction cells, dosral tegmental nucleus of Gudden, anterodorsal University of Stirling, thalamic nucleus United Kingdom Benjamin J. Clark, University of New Mexico, United States INTRODUCTION Jeffrey S. Taube, Dartmouth College, The ability to navigate through environments, and remember locations within those environments, United States is key to survival. Navigation requires a cognitive representation of both the environment and *Correspondence: current position within the environment.
    [Show full text]
  • Representation of Visual Landmarks in Retrosplenial Cortex Lukas F Fischer, Raul Mojica Soto-Albors, Friederike Buck, Mark T Harnett*
    RESEARCH ARTICLE Representation of visual landmarks in retrosplenial cortex Lukas F Fischer, Raul Mojica Soto-Albors, Friederike Buck, Mark T Harnett* Department of Brain and Cognitive Sciences, MGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States Abstract The process by which visual information is incorporated into the brain’s spatial framework to represent landmarks is poorly understood. Studies in humans and rodents suggest that retrosplenial cortex (RSC) plays a key role in these computations. We developed an RSC- dependent behavioral task in which head-fixed mice learned the spatial relationship between visual landmark cues and hidden reward locations. Two-photon imaging revealed that these cues served as dominant reference points for most task-active neurons and anchored the spatial code in RSC. This encoding was more robust after task acquisition. Decoupling the virtual environment from mouse behavior degraded spatial representations and provided evidence that supralinear integration of visual and motor inputs contributes to landmark encoding. V1 axons recorded in RSC were less modulated by task engagement but showed surprisingly similar spatial tuning. Our data indicate that landmark representations in RSC are the result of local integration of visual, motor, and spatial information. Introduction Spatial navigation requires the constant integration of sensory information, motor feedback, and prior knowledge of the environment (Hardcastle et al., 2015; McNaughton et al., 2006; Taube, 2007; Valerio and Taube, 2012). Visual landmarks are particularly advantageous for efficient navigation, representing information-rich reference points for self-location and route planning *For correspondence: (Etienne et al., 1996; Gothard et al., 1996b; Jeffery, 1998; Knierim et al., 1995; [email protected] McNaughton et al., 1991).
    [Show full text]
  • Head Direction Cell Representations Maintain Internal Coherence During Conflicting Proximal and Distal Cue Rotations: Comparison with Hippocampal Place Cells
    622 • The Journal of Neuroscience, January 11, 2006 • 26(2):622–631 Behavioral/Systems/Cognitive Head Direction Cell Representations Maintain Internal Coherence during Conflicting Proximal and Distal Cue Rotations: Comparison with Hippocampal Place Cells D. Yoganarasimha, Xintian Yu, and James J. Knierim Department of Neurobiology and Anatomy, W. M. Keck Center for the Neurobiology of Learning and Memory, The University of Texas Medical School at Houston, Houston, Texas 77225 Place cells of the hippocampal formation encode a spatial representation of the environment, and the orientation of this representation is apparently governed by the head direction cell system. The representation of a well explored environment by CA1 place cells can be split when there is conflicting information from salient proximal and distal cues, because some place fields rotate to follow the distal cues, whereas others rotate to follow the proximal cues (Knierim, 2002a). In contrast, the CA3 representation is more coherent than CA1, becausetheplacefieldsinCA3tendtorotateinthesamedirection(Leeetal.,2004).Thepresentstudytestswhethertheheaddirectioncell network produces a split representation or remains coherent under these conditions by simultaneously recording both CA1 place cells and head direction cells from the thalamus. In agreement with previous studies, split representations of the environment were observed in ensembles of CA1 place cells in ϳ75% of the mismatch sessions, in which some fields followed the counterclockwise rotation of proximal cues and other fields followed the clockwise rotation of distal cues. However, of 225 recording sessions, there was not a single instance of the head direction cell ensembles revealing a split representation of head direction. Instead, in most of the mismatch sessions, the head direction cell tuning curves rotated as an ensemble clockwise (94%) and in a few sessions rotated counterclockwise (6%).
    [Show full text]
  • The Neural Basis of Head Direction and Spatial Context in the Insect Central Complex
    THE NEURAL BASIS OF HEAD DIRECTION AND SPATIAL CONTEXT IN THE INSECT CENTRAL COMPLEX by ADRIENN G. VARGA Submitted in partial fulfillment of requirements For the degree of Doctor of Philosophy Advisor: Dr. Roy E. Ritzmann Department of Biology CASE WESTERN RESERVE UNIVERSITY May 2017 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of Adrienn G. Varga Candidate for the Doctor of Philosophy degree*. Committee Chair: Hillel J. Chiel Committee Member: Roy E. Ritzmann Committee Member: Mark A. Willis Committee Member: Jessica L. Fox Committee Member: David Friel Date of Defense: November 18th, 2016 *We also certify that written approval has been obtained for any proprietary material contained therein. Copyright © by Adrienn G. Varga All rights reserved Dedication For my Family Table of Contents Thesis Summary ................................................................................................................ 1 Chapter 1: Introduction ................................................................................................... 3 Mammalian navigation circuits ................................................................................... 6 Adaptive navigation .................................................................................................... 6 Head direction cells .................................................................................................. 10 Sensory cues underlying the head direction signal ................................................
    [Show full text]