Behavioral and Neural Correlates to Multisensory Detection of Sick Humans
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Toward a Common Terminology for the Gyri and Sulci of the Human Cerebral Cortex Hans Ten Donkelaar, Nathalie Tzourio-Mazoyer, Jürgen Mai
Toward a Common Terminology for the Gyri and Sulci of the Human Cerebral Cortex Hans ten Donkelaar, Nathalie Tzourio-Mazoyer, Jürgen Mai To cite this version: Hans ten Donkelaar, Nathalie Tzourio-Mazoyer, Jürgen Mai. Toward a Common Terminology for the Gyri and Sulci of the Human Cerebral Cortex. Frontiers in Neuroanatomy, Frontiers, 2018, 12, pp.93. 10.3389/fnana.2018.00093. hal-01929541 HAL Id: hal-01929541 https://hal.archives-ouvertes.fr/hal-01929541 Submitted on 21 Nov 2018 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. REVIEW published: 19 November 2018 doi: 10.3389/fnana.2018.00093 Toward a Common Terminology for the Gyri and Sulci of the Human Cerebral Cortex Hans J. ten Donkelaar 1*†, Nathalie Tzourio-Mazoyer 2† and Jürgen K. Mai 3† 1 Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Medical Center, Nijmegen, Netherlands, 2 IMN Institut des Maladies Neurodégénératives UMR 5293, Université de Bordeaux, Bordeaux, France, 3 Institute for Anatomy, Heinrich Heine University, Düsseldorf, Germany The gyri and sulci of the human brain were defined by pioneers such as Louis-Pierre Gratiolet and Alexander Ecker, and extensified by, among others, Dejerine (1895) and von Economo and Koskinas (1925). -
Quantity Determination and the Distance Effect with Letters, Numbers, and Shapes: a Functional MR Imaging Study of Number Processing
AJNR Am J Neuroradiol 23:193–200, February 2003 Quantity Determination and the Distance Effect with Letters, Numbers, and Shapes: A Functional MR Imaging Study of Number Processing Robert K. Fulbright, Stephanie C. Manson, Pawel Skudlarski, Cheryl M. Lacadie, and John C. Gore BACKGROUND AND PURPOSE: The ability to quantify, or to determine magnitude, is an important part of number processing, and the extent to which language and other cognitive abilities are involved with number processing is an area of interest. We compared activation patterns, reaction times, and accuracy as subjects determined stimulus magnitude by ordering letters, numbers, and shapes. A second goal was to define the brain regions involved in the distance effect (the farther apart numbers are, the faster subjects are at judging which number is larger) and whether this effect depended on stimulus type. METHODS: Functional MR images were acquired in 19 healthy subjects. The order task required the subjects to judge whether three stimuli were in order according to their position in the alphabet (letters), position in the number line (numbers), or size (shapes). In the control (identify task), subjects judged whether one of the three stimuli was a particular letter, number, or shape. Each stimulus type was divided into near trials (quantity difference of three or less) and far trials (quantity difference of at least five) to assess the distance effect. RESULTS: Subjects were less accurate and slower with letters than with numbers and shapes. A distance effect was present with shapes and numbers, as subjects ordered the near trials slower than far trials. No distance effect was detected with letters. -
01 05 Lateral Surface of the Brain-NOTES.Pdf
Lateral Surface of the Brain Medical Neuroscience | Tutorial Notes Lateral Surface of the Brain 1 MAP TO NEUROSCIENCE CORE CONCEPTS NCC1. The brain is the body's most complex organ. LEARNING OBJECTIVES After study of the assigned learning materials, the student will: 1. Demonstrate the four paired lobes of the cerebral cortex and describe the boundaries of each. 2. Sketch the major features of each cerebral lobe, as seen from the lateral view, identifying major gyri and sulci that characterize each lobe. NARRATIVE by Leonard E. WHITE and Nell B. CANT Duke Institute for Brain Sciences Department of Neurobiology Duke University School of Medicine Overview When you view the lateral aspect of a human brain specimen (see Figures A3A and A102), three structures are usually visible: the cerebral hemispheres, the cerebellum, and part of the brainstem (although the brainstem is not visible in the specimen photographed in lateral view for Fig. 1 below). The spinal cord has usually been severed (but we’ll consider the spinal cord later), and the rest of the subdivisions are hidden from lateral view by the hemispheres. The diencephalon and the rest of the brainstem are visible on the medial surface of a brain that has been cut in the midsagittal plane. Parts of all of the subdivisions are also visible from the ventral surface of the whole brain. Over the next several tutorials, you will find video demonstrations (from the brain anatomy lab) and photographs (in the tutorial notes) of these brain surfaces, and sufficient detail in the narrative to appreciate the overall organization of the parts of the brain that are visible from each perspective. -
A Core Speech Circuit Between Primary Motor, Somatosensory, and Auditory Cortex
bioRxiv preprint doi: https://doi.org/10.1101/139550; this version posted May 18, 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. Speech core 1 A core speech circuit between primary motor, somatosensory, and auditory cortex: Evidence from connectivity and genetic descriptions * ^ Jeremy I Skipper and Uri Hasson * Experimental Psychology, University College London, UK ^ Center for Mind/Brain Sciences (CIMeC), University of Trento, Italy, and Center for Practical Wisdom, Dept. of Psychology, The University of Chicago Running title: Speech core Words count: 20,362 Address correspondence to: Jeremy I Skipper University College London Experimental Psychology 26 Bedford Way London WC1H OAP United Kingdom E-mail: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/139550; this version posted May 18, 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. Speech core 2 Abstract What adaptations allow humans to produce and perceive speech so effortlessly? We show that speech is supported by a largely undocumented core of structural and functional connectivity between the central sulcus (CS or primary motor and somatosensory cortex) and the transverse temporal gyrus (TTG or primary auditory cortex). Anatomically, we show that CS and TTG cortical thickness covary across individuals and that they are connected by white matter tracts. -
Acetylcholinesterase Staining in Human Auditory and Language
Acetylcholinesterase Staining in Human Jeffrey J. Hutsler and Michael S. Gazzaniga Auditory and Language Cortices: Center for Neuroscience, University of California, Davis Regional Variation of Structural Features California 95616 Cholinergic innovation of the cerebral neocortex arises from the basal 1974; Greenfield, 1984, 1991; Robertson, 1987; Taylor et al., forebrain and projects to all cortical regions. Acetylcholinesterase 1987; Krisst, 1989; Small, 1989, 1990). AChE-containing axons (AChE), the enzyme responsible for deactivating acetylcholine, is found of the cerebral cortex are also immunoreactive for choline within both cholinergic axons arising from the basal forebrain and a acetyltransferase (ChAT) and are therefore known to be cho- Downloaded from subgroup of pyramidal cells in layers III and V of the cerebral cortex. linergic (Mesulam and Geula, 1992). This pattern of staining varies with cortical location and may contrib- AChE-containing pyramidal cells of layers III and V are not ute uniquely to cortical microcircuhry within functionally distinct cholinergic (Mesulam and Geula, 1991), but it has been sug- regions. To explore this issue further, we examined the pattern of AChE gested that they are cholinoceptive (Krnjevic and Silver, 1965; staining within auditory, auditory association, and putative language Levey et al., 1984; Mesulam et al., 1984b). In support of this regions of whole, postmortem human brains. notion, layer in and V pyramidal cell excitability can be mod- http://cercor.oxfordjournals.org/ The density and distribution of acetylcholine-containing axons and ulated by the application of acetylcholine in the slice prepa- pyramidal cells vary systematically as a function of auditory process- ration (McCormick and Williamson, 1989). Additionally, mus- ing level. -
Common and Distinct Functional Brain Networks for Intuitive and Deliberate Decision Making
brain sciences Article Common and Distinct Functional Brain Networks for Intuitive and Deliberate Decision Making Burak Erdeniz 1,* and John Done 2 1 Department of Psychology, Izmir˙ University of Economics, 35330 Izmir, Turkey 2 Department of Psychology and Sports Sciences, School of Life and Medical Sciences, University of Hertfordshire, Hatfield AL 10 9AB, UK * Correspondence: [email protected]; Tel.: +902-324-888-379 Received: 5 June 2019; Accepted: 19 July 2019; Published: 20 July 2019 Abstract: Reinforcement learning studies in rodents and primates demonstrate that goal-directed and habitual choice behaviors are mediated through different fronto-striatal systems, but the evidence is less clear in humans. In this study, functional magnetic resonance imaging (fMRI) data were collected whilst participants (n = 20) performed a conditional associative learning task in which blocks of novel conditional stimuli (CS) required a deliberate choice, and blocks of familiar CS required an intuitive choice. Using standard subtraction analysis for fMRI event-related designs, activation shifted from the dorso-fronto-parietal network, which involves dorsolateral prefrontal cortex (DLPFC) for deliberate choice of novel CS, to ventro-medial frontal (VMPFC) and anterior cingulate cortex for intuitive choice of familiar CS. Supporting this finding, psycho-physiological interaction (PPI) analysis, using the peak active areas within the PFC for novel and familiar CS as seed regions, showed functional coupling between caudate and DLPFC when processing novel CS and VMPFC when processing familiar CS. These findings demonstrate separable systems for deliberate and intuitive processing, which is in keeping with rodent and primate reinforcement learning studies, although in humans they operate in a dynamic, possibly synergistic, manner particularly at the level of the striatum. -
Online Tables (PDF)
On-line Table 1: Description of cortical and sulcation abnormalities in 40 patients Patient Description 1 Bilateral schizencephaly, extensive fcd, abnormal Sylvian fissures 2 Abnormal R intraparietal-occipital sulcus and open sylvian fissures, sylvian cortex and R occipital cortex 3 Unusual sulcation R postcingulate and transmantle bands to Sylvian fissures 4 Bilateral peri-Sylvian pmg, abnormal Sylvian fissures, thick and blurred cortex 5 Dysplastic L cingulate adjacent to transmantle dysplasia 6 Transmantle band left frontal and above right caudate 7 L frontal transmantle band 8 Abnormal Sylvian fissures, L Ͼ R 9 R posterior quadrantic dysplasia, abnormal posterior sulcation and R Sylvian fissure, linear band 10 Abnormal L Sylvian fissure 11 Linear bands from posterior atrium to occipital white matter, unusual stellate sulcal configuration joining R intraparietal sulcus 12 Short Sylvian fissures, absent L intra-parieto-occipital fissure and simplified gyral pattern, areas of increased cortical thickness 13 Unusual sulcation R postcentral–thick but only 3 years of age terminal zones 14 Abnormal L Sylvian fissure, abnormal sulcus from L frontal lobe joins it with stellate shape 15 Dysplastic cingulate gyrus R abnormal L calcarine with branching, N thickness, still young 16 Abnormal Sylvian fissures bilaterally, elongated with terminal branches; difficult to assess thickness because not myelinated yet 17 Abnormal L Sylvian fissure 18 Thick gray linear transmantle bands from nodules to adjacent Sylvian cortex, thickened but no pmg 19 Unusual sulcation -
(OCD) Using Treatment-Induced Neuroimaging Changes
Neurosurgery J Neurol Neurosurg Psychiatry: first published as 10.1136/jnnp-2020-324478 on 27 April 2021. Downloaded from Review Defining functional brain networks underlying obsessive–compulsive disorder (OCD) using treatment- induced neuroimaging changes: a systematic review of the literature Kelly R. Bijanki ,1 Yagna J. Pathak,2 Ricardo A. Najera,1 Eric A. Storch,3 Wayne K Goodman,3 H. Blair Simpson,4 Sameer A. Sheth1 ► Additional material is ABSTRACT Aberrant signalling in cortico- striato- thalamo- published online only. To view Approximately 2%–3% of the population suffers from cortical (CSTC) circuits is considered to be an please visit the journal online obsessive–compulsive disorder (OCD). Several brain important pathological mechanism underlying (http:// dx. doi. org/ 10. 1136/ [S1- S3] jnnp- 2020- 324478). regions have been implicated in the pathophysiology OCD. These circuits are composed of glutama- of OCD, but their various contributions remain unclear. tergic and GABAergic projections that connect fron- 1 Department of Neurosurgery, We examined changes in structural and functional tocortical and subcortical brain areas.[S4- S9] Within Baylor College of Medicine, the CSTC loop, the direct pathway from striatum Houston, Texas, USA neuroimaging before and after a variety of therapeutic 2Department of Neurological interventions as an index into identifying the underlying to internal pallidum to thalamus and back to cortex Surgery, Columbia University networks involved. We identified 64 studies from 1990 exerts a net excitatory effect, and the indirect Medical Center, New York, New to 2020 comparing pretreatment and post-treatment pathway, which additionally includes the external York, USA 3 imaging of patients with OCD, including metabolic pallidum and subthalamic nucleus, produces a Menninger Department of net inhibitory effect.[S4] A lack of balance in these Psychiatry and Behavioral and perfusion, neurochemical, structural, functional Sciences, Baylor College of and connectivity-based modalities. -
Supplementary Tables
Supplementary Tables: ROI Atlas Significant table grey matter Test ROI # Brainetome area beta volume EG pre vs post IT 8 'superior frontal gyrus, part 4 (dorsolateral area 6), right', 0.773 17388 11 'superior frontal gyrus, part 6 (medial area 9), left', 0.793 18630 12 'superior frontal gyrus, part 6 (medial area 9), right', 0.806 24543 17 'middle frontal gyrus, part 2 (inferior frontal junction), left', 0.819 22140 35 'inferior frontal gyrus, part 4 (rostral area 45), left', 1.3 10665 67 'paracentral lobule, part 2 (area 4 lower limb), left', 0.86 13662 EG pre vs post ET 20 'middle frontal gyrus, part 3 (area 46), right', 0.934 28188 21 'middle frontal gyrus, part 4 (ventral area 9/46 ), left' 0.812 27864 31 'inferior frontal gyrus, part 2 (inferior frontal sulcus), left', 0.864 11124 35 'inferior frontal gyrus, part 4 (rostral area 45), left', 1 10665 50 'orbital gyrus, part 5 (area 13), right', -1.7 22626 67 'paracentral lobule, part 2 (area 4 lower limb), left', 1.1 13662 180 'cingulate gyrus, part 3 (pregenual area 32), right', 0.9 10665 261 'Cerebellar lobule VIIb, vermis', -1.5 729 IG pre vs post IT 16 middle frontal gyrus, part 1 (dorsal area 9/46), right', -0.8 27567 24 'middle frontal gyrus, part 5 (ventrolateral area 8), right', -0.8 22437 40 'inferior frontal gyrus, part 6 (ventral area 44), right', -0.9 8262 54 'precentral gyrus, part 1 (area 4 head and face), right', -0.9 14175 64 'precentral gyrus, part 2 (caudal dorsolateral area 6), left', -1.3 18819 81 'middle temporal gyrus, part 1 (caudal area 21), left', -1.4 14472 -
Brain Networks for Confidence Weighting and Hierarchical
Brain networks for confidence weighting and PNAS PLUS hierarchical inference during probabilistic learning Florent Meyniela,1 and Stanislas Dehaenea,b,1 aCognitive Neuroimaging Unit, NeuroSpin Center, Institute of Life Sciences Frédéric Joliot, Fundemental Research Division, Commissariat à l’Énergie Atomique et aux Énergies Alternatives, INSERM, Université Paris–Sud, Université Paris–Saclay, 91191 Gif/Yvette, France; and bChair of Experimental Cognitive Psychology, Collège de France, 75005 Paris, France Contributed by Stanislas Dehaene, March 20, 2017 (sent for review September 23, 2016; reviewed by Stephen M. Fleming and Charles R. Gallistel) Learning is difficult when the world fluctuates randomly and and normative solution to this problem requires weighting each ceaselessly. Classical learning algorithms, such as the delta rule with source of information according to its reliability (3–12). According constant learning rate, are not optimal. Mathematically, the optimal to this Bayes-optimal solution, any discrepancy between a new ob- learning rule requires weighting prior knowledge and incoming servation and a learned estimate should lead to an update of this evidence according to their respective reliabilities. This “confidence internal estimate, but the size of this update should decrease as the weighting” implies the maintenance of an accurate estimate of the prior confidence in this internal estimate increases. Furthermore, reliability of what has been learned. Here, using fMRI and an ideal- this prior confidence should depend on two factors: the precision of observer analysis, we demonstrate that the brain’s learning algorithm the current internal estimate and a discounting factor that takes into relies on confidence weighting. While in the fMRI scanner, human account the possibility that a change occurred. -
Neural Arbitration Between Social and Individual Learning Systems
RESEARCH ARTICLE Neural arbitration between social and individual learning systems Andreea Oliviana Diaconescu1,2,3,4†*, Madeline Stecy1,2,5†, Lars Kasper1,2,6, Christopher J Burke2, Zoltan Nagy2, Christoph Mathys1,7,8, Philippe N Tobler2 1Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich & ETH Zurich, Zurich, Switzerland; 2Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, Zurich, Switzerland; 3University of Basel, Department of Psychiatry (UPK), Basel, Switzerland; 4Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), University of Toronto, Toronto, Canada; 5Rutgers Robert Wood Johnson Medical School, New Brunswick, United States; 6Institute for Biomedical Engineering, MRI Technology Group, ETH Zu¨ rich & University of Zurich, Zurich, Switzerland; 7Interacting Minds Centre, Aarhus University, Aarhus, Denmark; 8Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy Abstract Decision making requires integrating knowledge gathered from personal experiences with advice from others. The neural underpinnings of the process of arbitrating between information sources has not been fully elucidated. In this study, we formalized arbitration as the relative precision of predictions, afforded by each learning system, using hierarchical Bayesian modeling. In a probabilistic learning task, participants predicted the outcome of a lottery using recommendations from a more informed advisor and/or self-sampled outcomes. -
Parietal Dysgraphia: Characterization of Abnormal Writing Stroke Sequences, Character Formation and Character Recall
Behavioural Neurology 18 (2007) 99–114 99 IOS Press Parietal dysgraphia: Characterization of abnormal writing stroke sequences, character formation and character recall Yasuhisa Sakuraia,b,∗, Yoshinobu Onumaa, Gaku Nakazawaa, Yoshikazu Ugawab, Toshimitsu Momosec, Shoji Tsujib and Toru Mannena aDepartment of Neurology, Mitsui Memorial Hospital, Tokyo, Japan bDepartment of Neurology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan cDepartment of Radiology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan Abstract. Objective: To characterize various dysgraphic symptoms in parietal agraphia. Method: We examined the writing impairments of four dysgraphia patients from parietal lobe lesions using a special writing test with 100 character kanji (Japanese morphograms) and their kana (Japanese phonetic writing) transcriptions, and related the test performance to a lesion site. Results: Patients 1 and 2 had postcentral gyrus lesions and showed character distortion and tactile agnosia, with patient 1 also having limb apraxia. Patients 3 and 4 had superior parietal lobule lesions and features characteristic of apraxic agraphia (grapheme deformity and a writing stroke sequence disorder) and character imagery deficits (impaired character recall). Agraphia with impaired character recall and abnormal grapheme formation were more pronounced in patient 4, in whom the lesion extended to the inferior parietal, superior occipital and precuneus gyri. Conclusion: The present findings and a review of the literature suggest that: (i) a postcentral gyrus lesion can yield graphemic distortion (somesthetic dysgraphia), (ii) abnormal grapheme formation and impaired character recall are associated with lesions surrounding the intraparietal sulcus, the symptom being more severe with the involvement of the inferior parietal, superior occipital and precuneus gyri, (iii) disordered writing stroke sequences are caused by a damaged anterior intraparietal area.