1
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Assimopoulos S, Warrington S, Bryant KL, Pszczolkowski S, Jbabdi S, Mars RB, Sotiropoulos SN. Generalising XTRACT tractography protocols across common macaque brain templates. Brain Struct Funct 2024; 229:1873-1888. [PMID: 38388696 PMCID: PMC11485040 DOI: 10.1007/s00429-024-02760-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/09/2024] [Indexed: 02/24/2024]
Abstract
Non-human primates are extensively used in neuroscience research as models of the human brain, with the rhesus macaque being a prominent example. We have previously introduced a set of tractography protocols (XTRACT) for reconstructing 42 corresponding white matter (WM) bundles in the human and the macaque brain and have shown cross-species comparisons using such bundles as WM landmarks. Our original XTRACT protocols were developed using the F99 macaque brain template. However, additional macaque template brains are becoming increasingly common. Here, we generalise the XTRACT tractography protocol definitions across five macaque brain templates, including the F99, D99, INIA, Yerkes and NMT. We demonstrate equivalence of such protocols in two ways: (a) Firstly by comparing the bodies of the tracts derived using protocols defined across the different templates considered, (b) Secondly by comparing the projection patterns of the reconstructed tracts across the different templates in two cross-species (human-macaque) comparison tasks. The results confirm similarity of all predictions regardless of the macaque brain template used, providing direct evidence for the generalisability of these tractography protocols across the five considered templates.
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Affiliation(s)
- Stephania Assimopoulos
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Shaun Warrington
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Katherine L Bryant
- Laboratoire de Psychologie Cognitive, Aix-Marseille Université, Marseille, France
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stefan Pszczolkowski
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.
- Wellcome Centre for Integrative Neuroimaging (WIN-FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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2
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Autio JA, Uematsu A, Ikeda T, Ose T, Hou Y, Magrou L, Kimura I, Ohno M, Murata K, Coalson T, Kennedy H, Glasser MF, Van Essen DC, Hayashi T. Charting Cortical-Layer Specific Area Boundaries Using Gibbs' Ringing Attenuated T1w/T2w-FLAIR Myelin MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.27.615294. [PMID: 39386722 PMCID: PMC11463467 DOI: 10.1101/2024.09.27.615294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/12/2024]
Abstract
Cortical areas have traditionally been defined by their distinctive layer cyto- and/or myelo- architecture using postmortem histology. Recent studies have delineated many areas by measuring overall cortical myelin content and its spatial gradients using the T1w/T2w ratio MRI in living primates, including humans. While T1w/T2w studies of areal transitions might benefit from using the layer profile of this myelin-related contrast, a significant confound is Gibbs' ringing artefact, which produces signal fluctuations resembling cortical layers. Here, we address these issues with a novel approach using cortical layer thickness-adjusted T1w/T2w-FLAIR imaging, which effectively cancels out Gibbs' ringing artefacts while enhancing intracortical myelin contrast. Whole-brain MRI measures were mapped onto twelve equivolumetric layers, and layer-specific sharp myeloarchitectonic transitions were identified using spatial gradients resulting in a putative 182 area/subarea partition of the macaque cerebral cortex. The myelin maps exhibit unexpectedly high homology with humans suggesting cortical myelin shares the same developmental program across the species. Comparison with histological Gallyas myelin stains explains over 80% of the variance in the laminar T1w/T2w-FLAIR profiles, substantiating the validity of the method. Altogether, our approach provides a novel, noninvasive means for precision mapping layer myeloarchitecture in the primate cerebral cortex, advancing the pioneering work of classical neuroanatomists.
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Affiliation(s)
- Joonas A. Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Akiko Uematsu
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Takuro Ikeda
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Takayuki Ose
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Yujie Hou
- Université Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Loïc Magrou
- Université Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
- Center for Neural Science, New York University, New York, NY, United States
| | - Ikko Kimura
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Masahiro Ohno
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | | | - Tim Coalson
- Department of Neuroscience, Washington University School of Medicine, St Louis, Missouri USA
| | - Henry Kennedy
- Université Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, Shanghai 200031, China
| | - Matthew F. Glasser
- Department of Neuroscience, Washington University School of Medicine, St Louis, Missouri USA
- Department of Radiology, Washington University School of Medicine, St Louis, Missouri, USA
| | - David C. Van Essen
- Department of Neuroscience, Washington University School of Medicine, St Louis, Missouri USA
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
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3
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Liu Z, Li A, Gong H, Yang X, Luo Q, Feng Z, Li X. The cytoarchitectonic landscape revealed by deep learning method facilitated precise positioning in mouse neocortex. Cereb Cortex 2024; 34:bhae229. [PMID: 38836835 DOI: 10.1093/cercor/bhae229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/13/2024] [Accepted: 05/23/2024] [Indexed: 06/06/2024] Open
Abstract
Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, we developed a cytoarchitectonic landmark identification pipeline. The fluorescence micro-optical sectioning tomography method was employed to image the whole mouse brain stained by general fluorescent nucleotide dye. A fast 3D convolution network was subsequently utilized to segment neuronal somas in entire neocortex. By approach, the cortical cytoarchitectonic profile and the neuronal morphology were analyzed in 3D, eliminating the influence of section angle. And the distribution maps were generated that visualized the number of neurons across diverse morphological types, revealing the cytoarchitectonic landscape which characterizes the landmarks of cortical regions, especially the typical signal pattern of barrel cortex. Furthermore, the cortical regions of various ages were aligned using the generated cytoarchitectonic landmarks suggesting the structural changes of barrel cortex during the aging process. Moreover, we observed the spatiotemporally gradient distributions of spindly neurons, concentrated in the deep layer of primary visual area, with their proportion decreased over time. These findings could improve structural understanding of neocortex, paving the way for further exploration with this method.
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Affiliation(s)
- Zhixiang Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, No. 1037 Luoyu Road, Wuhan 430070, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Xiaoquan Yang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Qingming Luo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
| | - Zhao Feng
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
| | - Xiangning Li
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, No. 58 Renmin Road, Haikou 570228, China
- HUST-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, No. 388 Ruoshui Road, Suzhou 215000, China
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4
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Liu Z, Feng Z, Liu G, Li A, Gong H, Yang X, Li X. A complementary approach for neocortical cytoarchitecture inspection with cellular resolution imaging at whole brain scale. Front Neuroanat 2024; 18:1388084. [PMID: 38846539 PMCID: PMC11153794 DOI: 10.3389/fnana.2024.1388084] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 04/26/2024] [Indexed: 06/09/2024] Open
Abstract
Cytoarchitecture, the organization of cells within organs and tissues, serves as a crucial anatomical foundation for the delineation of various regions. It enables the segmentation of the cortex into distinct areas with unique structural and functional characteristics. While traditional 2D atlases have focused on cytoarchitectonic mapping of cortical regions through individual sections, the intricate cortical gyri and sulci demands a 3D perspective for unambiguous interpretation. In this study, we employed fluorescent micro-optical sectioning tomography to acquire architectural datasets of the entire macaque brain at a resolution of 0.65 μm × 0.65 μm × 3 μm. With these volumetric data, the cortical laminar textures were remarkably presented in appropriate view planes. Additionally, we established a stereo coordinate system to represent the cytoarchitectonic information as surface-based tomograms. Utilizing these cytoarchitectonic features, we were able to three-dimensionally parcel the macaque cortex into multiple regions exhibiting contrasting architectural patterns. The whole-brain analysis was also conducted on mice that clearly revealed the presence of barrel cortex and reflected biological reasonability of this method. Leveraging these high-resolution continuous datasets, our method offers a robust tool for exploring the organizational logic and pathological mechanisms of the brain's 3D anatomical structure.
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Affiliation(s)
- Zhixiang Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
| | - Zhao Feng
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Guangcai Liu
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
| | - Anan Li
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Hui Gong
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Xiaoquan Yang
- Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, MoE Key Laboratory for Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
| | - Xiangning Li
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
- Research Unit of Multimodal Cross Scale Neural Signal Detection and Imaging, Chinese Academy of Medical Sciences, HUST-Suzhou Institute for Brainsmatics, JITRI, Suzhou, China
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5
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Zhang S, Zhang T, Cao G, Zhou J, He Z, Li X, Ren Y, Liu T, Jiang X, Guo L, Han J, Liu T. Species -shared and -unique gyral peaks on human and macaque brains. eLife 2024; 12:RP90182. [PMID: 38635322 PMCID: PMC11026093 DOI: 10.7554/elife.90182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2024] Open
Abstract
Cortical folding is an important feature of primate brains that plays a crucial role in various cognitive and behavioral processes. Extensive research has revealed both similarities and differences in folding morphology and brain function among primates including macaque and human. The folding morphology is the basis of brain function, making cross-species studies on folding morphology important for understanding brain function and species evolution. However, prior studies on cross-species folding morphology mainly focused on partial regions of the cortex instead of the entire brain. Previously, our research defined a whole-brain landmark based on folding morphology: the gyral peak. It was found to exist stably across individuals and ages in both human and macaque brains. Shared and unique gyral peaks in human and macaque are identified in this study, and their similarities and differences in spatial distribution, anatomical morphology, and functional connectivity were also dicussed.
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Affiliation(s)
- Songyao Zhang
- School of Automation, Northwestern Polytechnical UniversityXi’anChina
| | - Tuo Zhang
- School of Automation, Northwestern Polytechnical UniversityXi’anChina
| | - Guannan Cao
- School of Automation, Northwestern Polytechnical UniversityXi’anChina
| | - Jingchao Zhou
- School of Life Science and Technology, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of ChinaChengduChina
| | - Zhibin He
- School of Automation, Northwestern Polytechnical UniversityXi’anChina
| | - Xiao Li
- School of Information Technology, Northwest UniversityXi'anChina
| | - Yudan Ren
- School of Information Technology, Northwest UniversityXi'anChina
| | - Tao Liu
- College of Science, North China University of Science and TechnologyTangshanChina
| | - Xi Jiang
- School of Life Science and Technology, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of ChinaChengduChina
| | - Lei Guo
- School of Automation, Northwestern Polytechnical UniversityXi’anChina
| | - Junwei Han
- School of Automation, Northwestern Polytechnical UniversityXi’anChina
| | - Tianming Liu
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, University of GeorgiaAthensUnited States
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6
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Günther DM, Batiuk MY, Petukhov V, De Oliveira R, Wunderle T, Buchholz CJ, Fries P, Khodosevich K. Heterogeneity of layer 4 in visual areas of rhesus macaque cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.11.584345. [PMID: 38559123 PMCID: PMC10979896 DOI: 10.1101/2024.03.11.584345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Recently, single-cell RNA-sequencing (scRNA-seq) has enabled unprecedented insights to the cellular landscape of the brains of many different species, among them the rhesus macaque as a key animal model. Building on previous, broader surveys of the macaque brain, we closely examined five immediately neighboring areas within the visual cortex of the rhesus macaque: V1, V2, V4, MT and TEO. To facilitate this, we first devised a novel pipeline for brain spatial archive - the BrainSPACE - which enabled robust archiving and sampling from the whole unfixed brain. SnRNA-sequencing of ~100,000 nuclei from visual areas V1 and V4 revealed conservation within the GABAergic neuron subtypes, while seven and one distinct principle neuron subtypes were detected in V1 and V4, respectively, all most likely located in layer 4. Moreover, using small molecule fluorescence in situ hybridization, we identified cell type density gradients across V1, V2, V4, MT, and TEO appearing to reflect the visual hierarchy. These findings demonstrate an association between the clear areal specializations among neighboring areas with the hierarchical levels within the visual cortex of the rhesus macaque.
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Affiliation(s)
- Dorothee M. Günther
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, the Netherlands
- Molecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, 63225 Langen, Germany
| | - Mykhailo Y. Batiuk
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Viktor Petukhov
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Romain De Oliveira
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Thomas Wunderle
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Christian J. Buchholz
- Molecular Biotechnology and Gene Therapy, Paul-Ehrlich-Institut, 63225 Langen, Germany
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, the Netherlands
| | - Konstantin Khodosevich
- Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
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7
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Zhang S, Zhang T, Cao G, Zhou J, He Z, Li X, Ren Y, Liu T, Jiang X, Guo L, Han J, Liu T. Species -Shared and -Unique Gyral Peaks on Human and Macaque Brains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.26.550760. [PMID: 37546923 PMCID: PMC10402126 DOI: 10.1101/2023.07.26.550760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Cortical folding is an important feature of primate brains that plays a crucial role in various cognitive and behavioral processes. Extensive research has revealed both similarities and differences in folding morphology and brain function among primates including macaque and human. The folding morphology is the basis of brain function, making cross-species studies on folding morphology important for understanding brain function and species evolution. However, prior studies on cross-species folding morphology mainly focused on partial regions of the cortex instead of the entire brain. Previously, we defined a whole-brain landmark based on folding morphology: the gyral peak. It was found to exist stably across individuals and ages in both human and macaque brains. In this study, we identified shared and unique gyral peaks in human and macaque, and investigated the similarities and differences in the spatial distribution, anatomical morphology, and functional connectivity of them.
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Affiliation(s)
- Songyao Zhang
- School of Automation, Northwestern Polytechnical University, Xi’an, China
| | - Tuo Zhang
- School of Automation, Northwestern Polytechnical University, Xi’an, China
| | - Guannan Cao
- School of Automation, Northwestern Polytechnical University, Xi’an, China
| | - Jingchao Zhou
- College of Science, North China University of Science and Technology, Tangshan, China
| | - Zhibin He
- School of Automation, Northwestern Polytechnical University, Xi’an, China
| | - Xiao Li
- School of Information Technology, Northwest University, Xi’an, China
| | - Yudan Ren
- School of Information Technology, Northwest University, Xi’an, China
| | - Tao Liu
- College of Science, North China University of Science and Technology, Tangshan, China
| | - Xi Jiang
- School of Life Science and Technology, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi’an, China
| | - Junwei Han
- School of Automation, Northwestern Polytechnical University, Xi’an, China
| | - Tianming Liu
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, University of Georgia, Athens, GA, USA
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8
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Karadachka K, Assem M, Mitchell DJ, Duncan J, Medendorp WP, Mars RB. Structural connectivity of the multiple demand network in humans and comparison to the macaque brain. Cereb Cortex 2023; 33:10959-10971. [PMID: 37798142 PMCID: PMC10646692 DOI: 10.1093/cercor/bhad314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 10/07/2023] Open
Abstract
Fluid intelligence encompasses a wide range of abilities such as working memory, problem-solving, and relational reasoning. In the human brain, these abilities are associated with the Multiple Demand Network, traditionally thought to involve combined activity of specific regions predominantly in the prefrontal and parietal cortices. However, the structural basis of the interactions between areas in the Multiple Demand Network, as well as their evolutionary basis among primates, remains largely unexplored. Here, we exploit diffusion MRI to elucidate the major white matter pathways connecting areas of the human core and extended Multiple Demand Network. We then investigate whether similar pathways can be identified in the putative homologous areas of the Multiple Demand Network in the macaque monkey. Finally, we contrast human and monkey networks using a recently proposed approach to compare different species' brains within a common organizational space. Our results indicate that the core Multiple Demand Network relies mostly on dorsal longitudinal connections and, although present in the macaque, these connections are more pronounced in the human brain. The extended Multiple Demand Network relies on distinct pathways and communicates with the core Multiple Demand Network through connections that also appear enhanced in the human compared with the macaque.
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Affiliation(s)
- Katrin Karadachka
- Donders Institute for Brain, Cognition and Behaviour, Faculty of Social Sciences, Radboud University Nijmegen, 6525HR Nijmegen, The Netherlands
| | - Moataz Assem
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom
| | - Daniel J Mitchell
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom
| | - John Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom
| | - W Pieter Medendorp
- Donders Institute for Brain, Cognition and Behaviour, Faculty of Social Sciences, Radboud University Nijmegen, 6525HR Nijmegen, The Netherlands
| | - Rogier B Mars
- Donders Institute for Brain, Cognition and Behaviour, Faculty of Social Sciences, Radboud University Nijmegen, 6525HR Nijmegen, The Netherlands
- Wellcome Centre for Integrative Neuroimaging Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford OX3 9DU, United Kingdom
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9
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Rapan L, Froudist-Walsh S, Niu M, Xu T, Zhao L, Funck T, Wang XJ, Amunts K, Palomero-Gallagher N. Cytoarchitectonic, receptor distribution and functional connectivity analyses of the macaque frontal lobe. eLife 2023; 12:e82850. [PMID: 37578332 PMCID: PMC10425179 DOI: 10.7554/elife.82850] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 06/14/2023] [Indexed: 08/15/2023] Open
Abstract
Based on quantitative cyto- and receptor architectonic analyses, we identified 35 prefrontal areas, including novel subdivisions of Walker's areas 10, 9, 8B, and 46. Statistical analysis of receptor densities revealed regional differences in lateral and ventrolateral prefrontal cortex. Indeed, structural and functional organization of subdivisions encompassing areas 46 and 12 demonstrated significant differences in the interareal levels of α2 receptors. Furthermore, multivariate analysis included receptor fingerprints of previously identified 16 motor areas in the same macaque brains and revealed 5 clusters encompassing frontal lobe areas. We used the MRI datasets from the non-human primate data sharing consortium PRIME-DE to perform functional connectivity analyses using the resulting frontal maps as seed regions. In general, rostrally located frontal areas were characterized by bigger fingerprints, that is, higher receptor densities, and stronger regional interconnections. Whereas more caudal areas had smaller fingerprints, but showed a widespread connectivity pattern with distant cortical regions. Taken together, this study provides a comprehensive insight into the molecular structure underlying the functional organization of the cortex and, thus, reconcile the discrepancies between the structural and functional hierarchical organization of the primate frontal lobe. Finally, our data are publicly available via the EBRAINS and BALSA repositories for the entire scientific community.
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Affiliation(s)
- Lucija Rapan
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Sean Froudist-Walsh
- Center for Neural Science, New York UniversityNew YorkUnited States
- Bristol Computational Neuroscience Unit, Faculty of Engineering, University of BristolBristolUnited Kingdom
| | - Meiqi Niu
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Ting Xu
- Center for the Developing Brain, Child Mind InstituteNew YorkUnited States
| | - Ling Zhao
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Thomas Funck
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
| | - Xiao-Jing Wang
- Center for Neural Science, New York UniversityNew YorkUnited States
| | - Katrin Amunts
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- C. & O. Vogt Institute for Brain Research, Heinrich-Heine-UniversityDüsseldorfGermany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine INM-1, Research Centre JülichJülichGermany
- C. & O. Vogt Institute for Brain Research, Heinrich-Heine-UniversityDüsseldorfGermany
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10
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Reiner A. Could theropod dinosaurs have evolved to a human level of intelligence? J Comp Neurol 2023; 531:975-1006. [PMID: 37029483 PMCID: PMC10106414 DOI: 10.1002/cne.25458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 01/05/2023] [Accepted: 01/11/2023] [Indexed: 04/09/2023]
Abstract
Noting that some theropod dinosaurs had large brains, large grasping hands, and likely binocular vision, paleontologist Dale Russell suggested that a branch of these dinosaurs might have evolved to a human intelligence level, had dinosaurs not become extinct. I offer reasons why the likely pallial organization in dinosaurs would have made this improbable, based on four assumptions. First, it is assumed that achieving human intelligence requires evolving an equivalent of the about 200 functionally specialized cortical areas characteristic of humans. Second, it is assumed that dinosaurs had an avian nuclear type of pallial organization, in contrast to the mammalian cortical organization. Third, it is assumed that the interactions between the different neuron types making up an information processing unit within pallium are critical to its role in analyzing information. Finally, it is assumed that increasing axonal length between the neuron sets carrying out this operation impairs its efficacy. Based on these assumptions, I present two main reasons why dinosaur pallium might have been unable to add the equivalent of 200 efficiently functioning cortical areas. First, a nuclear pattern of pallial organization would require increasing distances between the neuron groups corresponding to the separate layers of any given mammalian cortical area, as more sets of nuclei equivalent to a cortical area are interposed between the existing sets, increasing axon length and thereby impairing processing efficiency. Second, because of its nuclear organization, dinosaur pallium could not reduce axon length by folding to bring adjacent areas closer together, as occurs in cerebral cortex.
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Affiliation(s)
- Anton Reiner
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, Tennessee, USA
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11
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Pelekanos V, Premereur E, Mitchell AS. Structural Connectivity Changes After Fornix Transection in Macaques Using Probabilistic Diffusion Tractography. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1423:11-20. [PMID: 37525029 DOI: 10.1007/978-3-031-31978-5_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2023]
Abstract
The fornix, the limbic system's white matter tract connecting the extended hippocampal system to subcortical structures of the medial diencephalon, is strongly associated with learning and memory in humans and nonhuman primates (NHPs). Here, we sought to investigate alterations in structural connectivity across key cortical and subcortical regions after fornix transection in NHPs. We collected diffusion-weighted MRI (dMRI) data from three macaque monkeys that underwent bilateral fornix transection during neurosurgery and from four age- and cohort-matched control macaques that underwent surgery to implant a head-post but remained neurologically intact. dMRI data were collected from both groups at two time points, before and after the surgeries, and scans took place at around the same time for the two groups. We used probabilistic tractography and employed the number of tracking streamlines to quantify connectivity across our regions of interest (ROIs), in all dMRI sessions. In the neurologically intact monkeys, we observed high connectivity across certain ROIs, including the CA3 hippocampal subfield with the retrosplenial cortex (RSC), the anterior thalamus with the RSC, and the RSC with the anterior cingulate cortex (ACC). However, we found that, compared to the control group, the fornix-transected monkeys showed marked, significant, connectivity changes including increases between the anterior thalamus and the ACC and between the CA3 and the ACC, as well as decreases between the CA3 and the RSC. Our results highlight cortical and subcortical network changes after fornix transection and identify candidate indirect connectivity routes that may support memory functions after damage and/or neurodegeneration.
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Affiliation(s)
| | - Elsie Premereur
- Laboratory for Neuro- and Psychophysiology, KU Leuven, Leuven, Belgium
| | - Anna S Mitchell
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Department of Psychology, Hearing and Speech, University of Canterbury, Christchurch, New Zealand
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12
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Cortical adaptation of the night monkey to a nocturnal niche environment: a comparative non-invasive T1w/T2w myelin study. Brain Struct Funct 2022:10.1007/s00429-022-02591-x. [PMID: 36399210 DOI: 10.1007/s00429-022-02591-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 10/25/2022] [Indexed: 11/21/2022]
Abstract
Night monkeys (Aotus) are the only genus of monkeys within the Simian lineage that successfully occupy a nocturnal environmental niche. Their behavior is supported by their sensory organs' distinctive morphological features; however, little is known about their evolutionary adaptations in sensory regions of the cerebral cortex. Here, we investigate this question by exploring the cortical organization of night monkeys using high-resolution in-vivo brain MRI and comparative cortical-surface T1w/T2w myeloarchitectonic mapping. Our results show that the night monkey cerebral cortex has a qualitatively similar but quantitatively different pattern of cortical myelin compared to the diurnal macaque and marmoset monkeys. T1w/T2w myelin and its gradient allowed us to parcellate high myelin areas, including the middle temporal complex (MT +) and auditory cortex, and a low-myelin area, Brodmann area 7 (BA7) in the three species, despite species differences in cortical convolutions. Relative to the total cortical-surface area, those of MT + and the auditory cortex are significantly larger in night monkeys than diurnal monkeys, whereas area BA7 occupies a similar fraction of the cortical sheet in all three species. We propose that the selective expansion of sensory areas dedicated to visual motion and auditory processing in night monkeys may reflect cortical adaptations to a nocturnal environment.
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13
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Warrington S, Thompson E, Bastiani M, Dubois J, Baxter L, Slater R, Jbabdi S, Mars RB, Sotiropoulos SN. Concurrent mapping of brain ontogeny and phylogeny within a common space: Standardized tractography and applications. SCIENCE ADVANCES 2022; 8:eabq2022. [PMID: 36260675 PMCID: PMC9581484 DOI: 10.1126/sciadv.abq2022] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/31/2022] [Indexed: 06/16/2023]
Abstract
Developmental and evolutionary effects on brain organization are complex, yet linked, as evidenced by the correspondence in cortical area expansion across these vastly different time scales. However, it is still not possible to study concurrently the ontogeny and phylogeny of cortical areal connections, which is arguably more relevant to brain function than allometric measurements. Here, we propose a novel framework that allows the integration of structural connectivity maps from humans (adults and neonates) and nonhuman primates (macaques) onto a common space. We use white matter bundles to anchor the common space and use the uniqueness of cortical connection patterns to these bundles to probe area specialization. This enabled us to quantitatively study divergences and similarities in connectivity over evolutionary and developmental scales, to reveal brain maturation trajectories, including the effect of premature birth, and to translate cortical atlases between diverse brains. Our findings open new avenues for an integrative approach to imaging neuroanatomy.
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Affiliation(s)
- Shaun Warrington
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Elinor Thompson
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Matteo Bastiani
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jessica Dubois
- Université Paris Cité, Inserm, NeuroDiderot Unit, Paris, France
- University Paris-Saclay, CEA, NeuroSpin, Gif-sur-Yvette, France
| | - Luke Baxter
- Department of Paediatrics, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Rogier B. Mars
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Stamatios N. Sotiropoulos
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, UK
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14
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Zhao J, Chen W, Liu C, Gao Y, Chen X, Chen G, Xia L, Dai Y, Zhang X. Automatic macaque brain segmentation based on 7T MRI. Magn Reson Imaging 2022; 92:232-242. [PMID: 35842194 DOI: 10.1016/j.mri.2022.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 07/02/2022] [Accepted: 07/07/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND In monkey neuroimaging, particularly magnetic resonance imaging (MRI) studies, quick and accurate automatic macaque brain segmentation is essential. However, there are few processing and analysis tools dedicated to automatic brain tissue segmentation and labeling of the macaque brain on a subject-specific basis. As a result, currently most adopted methods are through direct implementation of existing tools that have been designed for human brain. However, the operation steps combining different functional modules of a variety of processing and analysis tool software are inevitably complicated, cumbersome, time-consuming and labor-intensive. NEW METHOD In this study, we proposed a novel quick and accurate automatic macaque brain segmentation method based on multi-atlas registration and majority-vote algorithm. First, the single-atlas method based on S-HAMMER is used to register each template image of the reference atlas set (including brain tissue labeled images and brain anatomical structure labeled images) to the preprocessed image to be segmented. Thus, we obtain the corresponding deformation field and spatially transform the labeled image, and then get multiple segmentation results by local weighted voting method, which perform label fusion to obtain the final labeled images of brain structures segmentation result. RESULTS By collecting high SNR and high spatial resolution images of macaque brain images from our 7T human MRI scanner, we have constructed two brain templates for each individual macaque subject, and macaque brain tissues and brain anatomical structure by one-atlas method. However, segmentation result of single-atlas method is not much accurate in some brain tissue area. It takes about 2 h and need more manual correction for segmentation. Automatic segmentation of macaque brain structure based on multi-atlas method was reasonably successful, the accuracy of segmentation was greatly improved without manual correction. Also, the proposed method provided good tissue fitting to V1 with smooth and continuous boundary. The Dice similarity of multi-atlas method showing 3.24%, 4.24%, 2.55%, 2.85%, 3.05%, and 0.35% improvement in image slices of 63, 66, 70, 71, 99 and 100, respectively. The entire processing time for the construction of a single template map took ~40 min. CONCLUSIONS This study proposed a novel automatic segmentation method of individual macaque brain structure based on multi-atlas registration method, which is concise and reliable. It may offer a valuable tool to applications in the field of brain and neuroscience research using the macaque as an experimental animal model.
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Affiliation(s)
- Jie Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
| | - Weidao Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China; Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Infervision Institute of Research, Beijing, China
| | - Chunyi Liu
- School of Radiation Medicine and Protection, Soochow University, Suzhou, China
| | - Yang Gao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China; Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China
| | - Xiaodong Chen
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Gang Chen
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Ling Xia
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
| | - Yakang Dai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.
| | - Xiaotong Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China; Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China.
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15
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Thilakavathy P, Diwan B. An Adaboost Support Vector Machine Based Harris Hawks Optimization Algorithm for Intelligent Quotient Estimation from MRI Images. Neural Process Lett 2022. [DOI: 10.1007/s11063-022-10895-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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16
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Ainsworth M, Wu Z, Browncross H, Mitchell AS, Bell AH, Buckley MJ. Frontopolar cortex shapes brain network structure across prefrontal and posterior cingulate cortex. Prog Neurobiol 2022; 217:102314. [DOI: 10.1016/j.pneurobio.2022.102314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 04/08/2022] [Accepted: 07/01/2022] [Indexed: 11/16/2022]
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17
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Reward Value Enhances Sequence Monitoring Ramping Dynamics as Ending Rewards Approach in the Rostrolateral Prefrontal Cortex. eNeuro 2022; 9:ENEURO.0003-22.2022. [PMID: 35168953 PMCID: PMC8906790 DOI: 10.1523/eneuro.0003-22.2022] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 01/25/2022] [Indexed: 11/21/2022] Open
Abstract
Many fundamental human behaviors contain multiple sequences performed to reach a desired outcome, such as cooking. Reward is inherently associated with sequence completion and has been shown to generally enhance cognitive control. However, the impact of reward on cognitive sequence processing remains unexplored. To address this key question, we focused on the rostrolateral prefrontal cortex (RLPFC). This area is necessary and exhibits increasing (“ramping”) activation during sequences, a dynamic that may be related to reward processing in other brain regions. To separate these dynamics, we designed a task where reward was only provided after multiple four-item sequences (“iterations”), rather than each individual sequence. Using fMRI in humans, we investigated three possible interactions of reward and sequential control signals in RLPFC: (1) with the visibility of sequential cues, i.e., memory; (2) equally across individual sequence iterations; and (3) differently across individual sequence iterations (e.g., increasing as reward approaches). Evidence from previous, nonsequential cognitive control experiments suggested that reward would uniformly change RLPFC activity across iterations and may depend on the visibility of cues. However, we found the influence of reward on RLPFC ramping increased across sequence iterations and did not interact with memory. These results suggest an active, predictive, and distinctive role for RLPFC in sequence monitoring and integration of reward information, consistent with extant literature demonstrating similar accelerating reward-related dopamine dynamics in regions connected to RLPFC. These results have implications for understanding sequential behavior in daily life, and when they go awry in disorders such as addiction.
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18
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Folloni D, Fouragnan E, Wittmann MK, Roumazeilles L, Tankelevitch L, Verhagen L, Attali D, Aubry JF, Sallet J, Rushworth MFS. Ultrasound modulation of macaque prefrontal cortex selectively alters credit assignment-related activity and behavior. SCIENCE ADVANCES 2021; 7:eabg7700. [PMID: 34910510 PMCID: PMC8673758 DOI: 10.1126/sciadv.abg7700] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 10/28/2021] [Indexed: 05/30/2023]
Abstract
Credit assignment is the association of specific instances of reward to the specific events, such as a particular choice, that caused them. Without credit assignment, choice values reflect an approximate estimate of how good the environment was when the choice was made—the global reward state—rather than exactly which outcome the choice caused. Combined transcranial ultrasound stimulation (TUS) and functional magnetic resonance imaging in macaques demonstrate credit assignment–related activity in prefrontal area 47/12o, and when this signal was disrupted with TUS, choice value representations across the brain were impaired. As a consequence, behavior was no longer guided by choice value, and decision-making was poorer. By contrast, global reward state–related activity in the adjacent anterior insula remained intact and determined decision-making after prefrontal disruption.
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Affiliation(s)
- Davide Folloni
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, Tinsley Building, Mansfield Road, Oxford OX1 3TA, University of Oxford, Oxford, UK
| | - Elsa Fouragnan
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, Tinsley Building, Mansfield Road, Oxford OX1 3TA, University of Oxford, Oxford, UK
- School of Psychology, University of Plymouth, Plymouth, UK
| | - Marco K. Wittmann
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, Tinsley Building, Mansfield Road, Oxford OX1 3TA, University of Oxford, Oxford, UK
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, Tinsley Building, Mansfield Road, Oxford OX1 3TA, University of Oxford, Oxford, UK
| | - Lev Tankelevitch
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, Tinsley Building, Mansfield Road, Oxford OX1 3TA, University of Oxford, Oxford, UK
| | - Lennart Verhagen
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, Tinsley Building, Mansfield Road, Oxford OX1 3TA, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, 6525 HR, Netherlands
| | - David Attali
- Physics for Medicine Paris, ESPCI Paris, INSERM, CNRS, PSL Research University, Paris, France
- GHU PARIS Psychiatrie and Neurosciences, site Sainte-Anne, Service Hospitalo-Universitaire, Pôle Hospitalo-Universitaire, Paris 15, F-75014 Paris, France
- Université de Paris, F-75005 Paris, France
| | - Jean-François Aubry
- Physics for Medicine Paris, ESPCI Paris, INSERM, CNRS, PSL Research University, Paris, France
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, Tinsley Building, Mansfield Road, Oxford OX1 3TA, University of Oxford, Oxford, UK
- Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 18 Avenue Doyen Lepine, 69500 Bron, France
| | - Matthew F. S. Rushworth
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, Tinsley Building, Mansfield Road, Oxford OX1 3TA, University of Oxford, Oxford, UK
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19
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Xu F, Shen Y, Ding L, Yang CY, Tan H, Wang H, Zhu Q, Xu R, Wu F, Xiao Y, Xu C, Li Q, Su P, Zhang LI, Dong HW, Desimone R, Xu F, Hu X, Lau PM, Bi GQ. High-throughput mapping of a whole rhesus monkey brain at micrometer resolution. Nat Biotechnol 2021; 39:1521-1528. [PMID: 34312500 DOI: 10.1038/s41587-021-00986-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 06/14/2021] [Indexed: 02/06/2023]
Abstract
Whole-brain mesoscale mapping in primates has been hindered by large brain sizes and the relatively low throughput of available microscopy methods. Here, we present an approach that combines primate-optimized tissue sectioning and clearing with ultrahigh-speed fluorescence microscopy implementing improved volumetric imaging with synchronized on-the-fly-scan and readout technique, and is capable of completing whole-brain imaging of a rhesus monkey at 1 × 1 × 2.5 µm3 voxel resolution within 100 h. We also developed a highly efficient method for long-range tracing of sparse axonal fibers in datasets numbering hundreds of terabytes. This pipeline, which we call serial sectioning and clearing, three-dimensional microscopy with semiautomated reconstruction and tracing (SMART), enables effective connectome-scale mapping of large primate brains. With SMART, we were able to construct a cortical projection map of the mediodorsal nucleus of the thalamus and identify distinct turning and routing patterns of individual axons in the cortical folds while approaching their arborization destinations.
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Affiliation(s)
- Fang Xu
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, China.,CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Yan Shen
- CAS Key Laboratory of Brain Function and Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Lufeng Ding
- CAS Key Laboratory of Brain Function and Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Chao-Yu Yang
- CAS Key Laboratory of Brain Function and Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Heng Tan
- Key Laboratory of Animal Models and Human Disease Mechanism, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,Department of Pathology and Pathophysiology, Kunming Medical University, Kunming, China
| | - Hao Wang
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
| | - Qingyuan Zhu
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Rui Xu
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Fengyi Wu
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Yanyang Xiao
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Cheng Xu
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Qianwei Li
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, China
| | - Peng Su
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Key Laboratory of Magnetic Resonance in Biological Systems, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Li I Zhang
- Zilkha Neurogenetic Institute, Center for Neural Circuits & Sensory Processing Disorders, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Hong-Wei Dong
- UCLA Brain Research & Artificial Intelligence Nexus, Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Robert Desimone
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Fuqiang Xu
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China.,State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Key Laboratory of Magnetic Resonance in Biological Systems, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China
| | - Xintian Hu
- Key Laboratory of Animal Models and Human Disease Mechanism, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China
| | - Pak-Ming Lau
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, China. .,CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China. .,CAS Key Laboratory of Brain Function and Disease, and School of Life Sciences, University of Science and Technology of China, Hefei, China. .,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
| | - Guo-Qiang Bi
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, and School of Life Sciences, University of Science and Technology of China, Hefei, China. .,CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China. .,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China. .,CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, China.
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20
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Elam JS, Glasser MF, Harms MP, Sotiropoulos SN, Andersson JLR, Burgess GC, Curtiss SW, Oostenveld R, Larson-Prior LJ, Schoffelen JM, Hodge MR, Cler EA, Marcus DM, Barch DM, Yacoub E, Smith SM, Ugurbil K, Van Essen DC. The Human Connectome Project: A retrospective. Neuroimage 2021; 244:118543. [PMID: 34508893 PMCID: PMC9387634 DOI: 10.1016/j.neuroimage.2021.118543] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 08/13/2021] [Accepted: 08/30/2021] [Indexed: 01/21/2023] Open
Abstract
The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the "WU-Minn-Ox" HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The "HCP-style" neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium.
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Affiliation(s)
| | | | - Michael P Harms
- Washington University School of Medicine, St. Louis, MO, USA
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre & NIHR Nottingham Biomedical Research Centre, Queen's Medical Centre, School of Medicine, University of Nottingham, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | | | | | | | - Robert Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | | | - Jan-Mathijs Schoffelen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | - Michael R Hodge
- Washington University School of Medicine, St. Louis, MO, USA
| | - Eileen A Cler
- Washington University School of Medicine, St. Louis, MO, USA
| | - Daniel M Marcus
- Washington University School of Medicine, St. Louis, MO, USA
| | - Deanna M Barch
- Washington University School of Medicine, St. Louis, MO, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
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21
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Foster C, Sheng WA, Heed T, Ben Hamed S. The macaque ventral intraparietal area has expanded into three homologue human parietal areas. Prog Neurobiol 2021; 209:102185. [PMID: 34775040 DOI: 10.1016/j.pneurobio.2021.102185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 10/27/2021] [Accepted: 11/05/2021] [Indexed: 10/19/2022]
Abstract
The macaque ventral intraparietal area (VIP) in the fundus of the intraparietal sulcus has been implicated in a diverse range of sensorimotor and cognitive functions such as motion processing, multisensory integration, processing of head peripersonal space, defensive behavior, and numerosity coding. Here, we exhaustively review macaque VIP function, cytoarchitectonics, and anatomical connectivity and integrate it with human studies that have attempted to identify a potential human VIP homologue. We show that human VIP research has consistently identified three, rather than one, bilateral parietal areas that each appear to subsume some, but not all, of the macaque area's functionality. Available evidence suggests that this human "VIP complex" has evolved as an expansion of the macaque area, but that some precursory specialization within macaque VIP has been previously overlooked. The three human areas are dominated, roughly, by coding the head or self in the environment, visual heading direction, and the peripersonal environment around the head, respectively. A unifying functional principle may be best described as prediction in space and time, linking VIP to state estimation as a key parietal sensorimotor function. VIP's expansive differentiation of head and self-related processing may have been key in the emergence of human bodily self-consciousness.
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Affiliation(s)
- Celia Foster
- Biopsychology & Cognitive Neuroscience, Faculty of Psychology & Sports Science, Bielefeld University, Bielefeld, Germany; Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany
| | - Wei-An Sheng
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229, CNRS-University of Lyon 1, France
| | - Tobias Heed
- Biopsychology & Cognitive Neuroscience, Faculty of Psychology & Sports Science, Bielefeld University, Bielefeld, Germany; Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany; Department of Psychology, University of Salzburg, Salzburg, Austria; Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria.
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229, CNRS-University of Lyon 1, France.
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22
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Bryant KL, Ardesch DJ, Roumazeilles L, Scholtens LH, Khrapitchev AA, Tendler BC, Wu W, Miller KL, Sallet J, van den Heuvel MP, Mars RB. Diffusion MRI data, sulcal anatomy, and tractography for eight species from the Primate Brain Bank. Brain Struct Funct 2021; 226:2497-2509. [PMID: 34264391 PMCID: PMC8608778 DOI: 10.1007/s00429-021-02268-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 03/26/2021] [Indexed: 12/16/2022]
Abstract
Large-scale comparative neuroscience requires data from many species and, ideally, at multiple levels of description. Here, we contribute to this endeavor by presenting diffusion and structural MRI data from eight primate species that have not or rarely been described in the literature. The selected samples from the Primate Brain Bank cover a prosimian, New and Old World monkeys, and a great ape. We present preliminary labelling of the cortical sulci and tractography of the optic radiation, dorsal part of the cingulum bundle, and dorsal parietal-frontal and ventral temporal-frontal longitudinal white matter tracts. Both dorsal and ventral association fiber systems could be observed in all samples, with the dorsal tracts occupying much less relative volume in the prosimian than in other species. We discuss the results in the context of known primate specializations and present hypotheses for further research. All data and results presented here are available online as a resource for the scientific community.
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Affiliation(s)
- Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU, UK
| | - Dirk Jan Ardesch
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Lianne H Scholtens
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Alexandre A Khrapitchev
- Department of Oncology, University of Oxford, Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Oxford, UK
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU, UK
| | - Wenchuan Wu
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU, UK
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, UK
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500, Bron, France
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU, UK.
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.
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23
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Nam H, Pae C, Eo J, Oh MK, Park HJ. Inter-species cortical registration between macaques and humans using a functional network property under a spherical demons framework. PLoS One 2021; 16:e0258992. [PMID: 34673832 PMCID: PMC8530290 DOI: 10.1371/journal.pone.0258992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 10/08/2021] [Indexed: 11/26/2022] Open
Abstract
Systematic evaluation of cortical differences between humans and macaques calls for inter-species registration of the cortex that matches homologous regions across species. For establishing homology across brains, structural landmarks and biological features have been used without paying sufficient attention to functional homology. The present study aimed to determine functional homology between the human and macaque cortices, defined in terms of functional network properties, by proposing an iterative functional network-based registration scheme using surface-based spherical demons. The functional connectivity matrix of resting-state functional magnetic resonance imaging (rs-fMRI) among cortical parcellations was iteratively calculated for humans and macaques. From the functional connectivity matrix, the functional network properties such as principal network components were derived to estimate a deformation field between the human and macaque cortices. The iterative registration procedure updates the parcellation map of macaques, corresponding to the human connectome project’s multimodal parcellation atlas, which was used to derive the macaque’s functional connectivity matrix. To test the plausibility of the functional network-based registration, we compared cortical registration using structural versus functional features in terms of cortical regional areal change. We also evaluated the interhemispheric asymmetry of regional area and its inter-subject variability in humans and macaques as an indirect validation of the proposed method. Higher inter-subject variability and interhemispheric asymmetry were found in functional homology than in structural homology, and the assessed asymmetry and variations were higher in humans than in macaques. The results emphasize the significance of functional network-based cortical registration across individuals within a species and across species.
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Affiliation(s)
- Haewon Nam
- Department of Liberal Arts, Hongik University, Sejong, Republic of Korea
| | - Chongwon Pae
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Center for Systems and Translational Brain Sciences, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, Republic of Korea
| | - Jinseok Eo
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Center for Systems and Translational Brain Sciences, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, Republic of Korea
- Department of Nuclear Medicine, Department of Psychiatry, Yonsei University College of Medicine, Seoul, Republic of Korea
- Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Maeng-Keun Oh
- Department of Nuclear Medicine, Department of Psychiatry, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hae-Jeong Park
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
- Center for Systems and Translational Brain Sciences, Institute of Human Complexity and Systems Science, Yonsei University, Seoul, Republic of Korea
- Department of Nuclear Medicine, Department of Psychiatry, Yonsei University College of Medicine, Seoul, Republic of Korea
- Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Cognitive Science, Yonsei University, Seoul, Republic of Korea
- * E-mail:
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24
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Klink PC, Aubry JF, Ferrera VP, Fox AS, Froudist-Walsh S, Jarraya B, Konofagou EE, Krauzlis RJ, Messinger A, Mitchell AS, Ortiz-Rios M, Oya H, Roberts AC, Roe AW, Rushworth MFS, Sallet J, Schmid MC, Schroeder CE, Tasserie J, Tsao DY, Uhrig L, Vanduffel W, Wilke M, Kagan I, Petkov CI. Combining brain perturbation and neuroimaging in non-human primates. Neuroimage 2021; 235:118017. [PMID: 33794355 PMCID: PMC11178240 DOI: 10.1016/j.neuroimage.2021.118017] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 03/07/2021] [Accepted: 03/22/2021] [Indexed: 12/11/2022] Open
Abstract
Brain perturbation studies allow detailed causal inferences of behavioral and neural processes. Because the combination of brain perturbation methods and neural measurement techniques is inherently challenging, research in humans has predominantly focused on non-invasive, indirect brain perturbations, or neurological lesion studies. Non-human primates have been indispensable as a neurobiological system that is highly similar to humans while simultaneously being more experimentally tractable, allowing visualization of the functional and structural impact of systematic brain perturbation. This review considers the state of the art in non-human primate brain perturbation with a focus on approaches that can be combined with neuroimaging. We consider both non-reversible (lesions) and reversible or temporary perturbations such as electrical, pharmacological, optical, optogenetic, chemogenetic, pathway-selective, and ultrasound based interference methods. Method-specific considerations from the research and development community are offered to facilitate research in this field and support further innovations. We conclude by identifying novel avenues for further research and innovation and by highlighting the clinical translational potential of the methods.
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Affiliation(s)
- P Christiaan Klink
- Department of Vision & Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA Amsterdam, the Netherlands.
| | - Jean-François Aubry
- Physics for Medicine Paris, Inserm U1273, CNRS UMR 8063, ESPCI Paris, PSL University, Paris, France
| | - Vincent P Ferrera
- Department of Neuroscience & Department of Psychiatry, Columbia University Medical Center, New York, NY, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Andrew S Fox
- Department of Psychology & California National Primate Research Center, University of California, Davis, CA, USA
| | | | - Béchir Jarraya
- NeuroSpin, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), Institut National de la Santé et de la Recherche Médicale (INSERM), Cognitive Neuroimaging Unit, Université Paris-Saclay, France; Foch Hospital, UVSQ, Suresnes, France
| | - Elisa E Konofagou
- Ultrasound and Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New York, NY, USA; Department of Radiology, Columbia University, New York, NY, USA
| | - Richard J Krauzlis
- Laboratory of Sensorimotor Research, National Eye Institute, Bethesda, MD, USA
| | - Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD, USA
| | - Anna S Mitchell
- Department of Experimental Psychology, Oxford University, Oxford, United Kingdom
| | - Michael Ortiz-Rios
- Newcastle University Medical School, Newcastle upon Tyne NE1 7RU, United Kingdom; German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany
| | - Hiroyuki Oya
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Neurosurgery, University of Iowa, Iowa city, IA, USA
| | - Angela C Roberts
- Department of Physiology, Development and Neuroscience, Cambridge University, Cambridge, United Kingdom
| | - Anna Wang Roe
- Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou 310029, China
| | | | - Jérôme Sallet
- Department of Experimental Psychology, Oxford University, Oxford, United Kingdom; Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Michael Christoph Schmid
- Newcastle University Medical School, Newcastle upon Tyne NE1 7RU, United Kingdom; Faculty of Science and Medicine, University of Fribourg, Chemin du Musée 5, CH-1700 Fribourg, Switzerland
| | - Charles E Schroeder
- Nathan Kline Institute, Orangeburg, NY, USA; Columbia University, New York, NY, USA
| | - Jordy Tasserie
- NeuroSpin, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), Institut National de la Santé et de la Recherche Médicale (INSERM), Cognitive Neuroimaging Unit, Université Paris-Saclay, France
| | - Doris Y Tsao
- Division of Biology and Biological Engineering, Tianqiao and Chrissy Chen Institute for Neuroscience; Howard Hughes Medical Institute; Computation and Neural Systems, Caltech, Pasadena, CA, USA
| | - Lynn Uhrig
- NeuroSpin, Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), Institut National de la Santé et de la Recherche Médicale (INSERM), Cognitive Neuroimaging Unit, Université Paris-Saclay, France
| | - Wim Vanduffel
- Laboratory for Neuro- and Psychophysiology, Neurosciences Department, KU Leuven Medical School, Leuven, Belgium; Leuven Brain Institute, KU Leuven, Leuven Belgium; Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Melanie Wilke
- German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany; Department of Cognitive Neurology, University Medicine Göttingen, Göttingen, Germany
| | - Igor Kagan
- German Primate Center, Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany.
| | - Christopher I Petkov
- Newcastle University Medical School, Newcastle upon Tyne NE1 7RU, United Kingdom.
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25
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Ainsworth M, Sallet J, Joly O, Kyriazis D, Kriegeskorte N, Duncan J, Schüffelgen U, Rushworth MFS, Bell AH. Viewing Ambiguous Social Interactions Increases Functional Connectivity between Frontal and Temporal Nodes of the Social Brain. J Neurosci 2021; 41:6070-6086. [PMID: 34099508 PMCID: PMC8276745 DOI: 10.1523/jneurosci.0870-20.2021] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 04/19/2021] [Accepted: 04/28/2021] [Indexed: 11/25/2022] Open
Abstract
Social behavior is coordinated by a network of brain regions, including those involved in the perception of social stimuli and those involved in complex functions, such as inferring perceptual and mental states and controlling social interactions. The properties and function of many of these regions in isolation are relatively well understood, but less is known about how these regions interact while processing dynamic social interactions. To investigate whether the functional connectivity between brain regions is modulated by social context, we collected fMRI data from male monkeys (Macaca mulatta) viewing videos of social interactions labeled as "affiliative," "aggressive," or "ambiguous." We show activation related to the perception of social interactions along both banks of the superior temporal sulcus, parietal cortex, medial and lateral frontal cortex, and the caudate nucleus. Within this network, we show that fronto-temporal functional connectivity is significantly modulated by social context. Crucially, we link the observation of specific behaviors to changes in functional connectivity within our network. Viewing aggressive behavior was associated with a limited increase in temporo-temporal and a weak increase in cingulate-temporal connectivity. By contrast, viewing interactions where the outcome was uncertain was associated with a pronounced increase in temporo-temporal, and cingulate-temporal functional connectivity. We hypothesize that this widespread network synchronization occurs when cingulate and temporal areas coordinate their activity when more difficult social inferences are being made.SIGNIFICANCE STATEMENT Processing social information from our environment requires the activation of several brain regions, which are concentrated within the frontal and temporal lobes. However, little is known about how these areas interact to facilitate the processing of different social interactions. Here we show that functional connectivity within and between the frontal and temporal lobes is modulated by social context. Specifically, we demonstrate that viewing social interactions where the outcome was unclear is associated with increased synchrony within and between the cingulate cortex and temporal cortices. These findings suggest that the coordination between the cingulate and temporal cortices is enhanced when more difficult social inferences are being made.
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Affiliation(s)
- Matthew Ainsworth
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, CB2 7EF
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, OX2 6GG
| | - Jérôme Sallet
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, OX2 6GG
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, OX3 9DU
- Inserm, Stem Cell and Brain Research Institute U1208, Université Lyon 1, 69500 Bron, France
| | - Olivier Joly
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, CB2 7EF
| | - Diana Kyriazis
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, CB2 7EF
| | - Nikolaus Kriegeskorte
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, CB2 7EF
- Zuckerman Mind Brain Institute, Columbia University, New York, New York, NY 10027
| | - John Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, CB2 7EF
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, OX2 6GG
| | - Urs Schüffelgen
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, OX2 6GG
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, OX3 9DU
| | - Matthew F S Rushworth
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, OX2 6GG
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, OX3 9DU
| | - Andrew H Bell
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, CB2 7EF
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom, OX2 6GG
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, OX3 9DU
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26
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O'Neal CM, Ahsan SA, Dadario NB, Fonseka RD, Young IM, Parker A, Maxwell BD, Yeung JT, Briggs RG, Teo C, Sughrue ME. A connectivity model of the anatomic substrates underlying ideomotor apraxia: A meta-analysis of functional neuroimaging studies. Clin Neurol Neurosurg 2021; 207:106765. [PMID: 34237682 DOI: 10.1016/j.clineuro.2021.106765] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/10/2021] [Accepted: 06/15/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Patients with ideomotor apraxia (IMA) present with selective impairments in higher-order motor cognition and execution without damage to any motor or sensory pathways. Although extensive research has been conducted to determine the regions of interest (ROIs) underlying these unique impairments, previous models are heterogeneous and may be further clarified based on their structural connectivity, which has been far less described. OBJECTIVE The goal of this research is to propose an anatomically concise network model for the neurophysiologic basis of IMA, specific to the voluntary pantomime, imitation and tool execution, based on intrinsic white matter connectivity. METHODS We utilized meta-analytic software to identify relevant ROIs in ideomotor apraxia as reported in the literature based on functional neuroimaging data with healthy participants. After generating an activation likelihood estimation (ALE) of relevant ROIs, cortical parcellations overlapping the ALE were used to construct an anatomically precise model of anatomic substrates using the parcellation scheme outlined by the Human Connectome Project (HCP). Deterministic tractography was then performed on 25 randomly selected, healthy HCP subjects to determine the structural connectivity underlying the identified ROIs. RESULTS 10 task-based fMRI studies met our inclusion criteria and the ALE analysis demonstrated 6 ROIs to constitute the IMA network: SCEF, FOP4, MIP, AIP, 7AL, and 7PC. These parcellations represent a fronto-parietal network consisting mainly of intra-parietal, U-shaped association fibers (40%) and long-range inferior fronto-occipital fascicle (IFOF) fibers (50%). These findings support previous functional models based on dual-stream motor processing. CONCLUSION We constructed a preliminary model demonstrating the underlying structural interconnectedness of anatomic substrates involved in higher-order motor functioning which is seen impaired in IMA. Our model provides support for previous dual-stream processing frameworks discussed in the literature, but further clarification is necessary with voxel-based lesion studies of IMA to further refine these findings.
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Affiliation(s)
- Christen M O'Neal
- Department of Neurosurgery, University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA
| | - Syed A Ahsan
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | | | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | | | - Allan Parker
- Department of Neurosurgery, University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA
| | - B David Maxwell
- Department of Neurosurgery, University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA
| | - Jacky T Yeung
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia.
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27
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Rushmore RJ, Bouix S, Kubicki M, Rathi Y, Rosene DL, Yeterian EH, Makris N. MRI-based Parcellation and Morphometry of the Individual Rhesus Monkey Brain: the macaque Harvard-Oxford Atlas (mHOA), a translational system referencing a standardized ontology. Brain Imaging Behav 2021; 15:1589-1621. [PMID: 32960419 PMCID: PMC8608281 DOI: 10.1007/s11682-020-00357-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Investigations of the rhesus monkey (Macaca mulatta) brain have shed light on the function and organization of the primate brain at a scale and resolution not yet possible in humans. A cornerstone of the linkage between non-human primate and human studies of the brain is magnetic resonance imaging, which allows for an association to be made between the detailed structural and physiological analysis of the non-human primate and that of the human brain. To further this end, we present a novel parcellation method and system for the rhesus monkey brain, referred to as the macaque Harvard-Oxford Atlas (mHOA), which is based on the human Harvard-Oxford Atlas (HOA) and grounded in an ontological and taxonomic framework. Consistent anatomical features were used to delimit and parcellate brain regions in the macaque, which were then categorized according to functional systems. This system of parcellation will be expanded with advances in technology and, like the HOA, will provide a framework upon which the results from other experimental studies (e.g., functional magnetic resonance imaging (fMRI), physiology, connectivity, graph theory) can be interpreted.
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Affiliation(s)
- R Jarrett Rushmore
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA
| | - Sylvain Bouix
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA
| | - Douglas L Rosene
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Edward H Yeterian
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA
- Department of Psychology, Colby College, Waterville, ME, USA
| | - Nikos Makris
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA.
- Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA.
- Center for Morphometric Analysis, Massachusetts General Hospital, 149 Thirteenth Street, Charlestown, MA, 02129, USA.
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28
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Hayashi T, Hou Y, Glasser MF, Autio JA, Knoblauch K, Inoue-Murayama M, Coalson T, Yacoub E, Smith S, Kennedy H, Van Essen DC. The nonhuman primate neuroimaging and neuroanatomy project. Neuroimage 2021; 229:117726. [PMID: 33484849 PMCID: PMC8079967 DOI: 10.1016/j.neuroimage.2021.117726] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/13/2020] [Accepted: 01/02/2021] [Indexed: 11/29/2022] Open
Abstract
Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, 'ground truth' validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how "functional connectivity" from fMRI and "tractographic connectivity" from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.
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Affiliation(s)
- Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 MI R&D Center 3F, Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan; Department of Neurobiology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yujie Hou
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France
| | - Matthew F Glasser
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA; Department of Neuroscience and Radiology, Washington University Medical School, St Louis, MO USA
| | - Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 MI R&D Center 3F, Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Kenneth Knoblauch
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France
| | | | - Tim Coalson
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA
| | - Stephen Smith
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Henry Kennedy
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, CAS, Shanghai, China
| | - David C Van Essen
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA
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29
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Changeux JP, Goulas A, Hilgetag CC. A Connectomic Hypothesis for the Hominization of the Brain. Cereb Cortex 2021; 31:2425-2449. [PMID: 33367521 PMCID: PMC8023825 DOI: 10.1093/cercor/bhaa365] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 10/30/2020] [Accepted: 11/02/2020] [Indexed: 02/06/2023] Open
Abstract
Cognitive abilities of the human brain, including language, have expanded dramatically in the course of our recent evolution from nonhuman primates, despite only minor apparent changes at the gene level. The hypothesis we propose for this paradox relies upon fundamental features of human brain connectivity, which contribute to a characteristic anatomical, functional, and computational neural phenotype, offering a parsimonious framework for connectomic changes taking place upon the human-specific evolution of the genome. Many human connectomic features might be accounted for by substantially increased brain size within the global neural architecture of the primate brain, resulting in a larger number of neurons and areas and the sparsification, increased modularity, and laminar differentiation of cortical connections. The combination of these features with the developmental expansion of upper cortical layers, prolonged postnatal brain development, and multiplied nongenetic interactions with the physical, social, and cultural environment gives rise to categorically human-specific cognitive abilities including the recursivity of language. Thus, a small set of genetic regulatory events affecting quantitative gene expression may plausibly account for the origins of human brain connectivity and cognition.
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Affiliation(s)
- Jean-Pierre Changeux
- CNRS UMR 3571, Institut Pasteur, 75724 Paris, France
- Communications Cellulaires, Collège de France, 75005 Paris, France
| | - Alexandros Goulas
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, 20246 Hamburg, Germany
| | - Claus C Hilgetag
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, 20246 Hamburg, Germany
- Department of Health Sciences, Boston University, Boston, MA 02115, USA
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30
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Wild B, Treue S. Primate extrastriate cortical area MST: a gateway between sensation and cognition. J Neurophysiol 2021; 125:1851-1882. [PMID: 33656951 DOI: 10.1152/jn.00384.2020] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Primate visual cortex consists of dozens of distinct brain areas, each providing a highly specialized component to the sophisticated task of encoding the incoming sensory information and creating a representation of our visual environment that underlies our perception and action. One such area is the medial superior temporal cortex (MST), a motion-sensitive, direction-selective part of the primate visual cortex. It receives most of its input from the middle temporal (MT) area, but MST cells have larger receptive fields and respond to more complex motion patterns. The finding that MST cells are tuned for optic flow patterns has led to the suggestion that the area plays an important role in the perception of self-motion. This hypothesis has received further support from studies showing that some MST cells also respond selectively to vestibular cues. Furthermore, the area is part of a network that controls the planning and execution of smooth pursuit eye movements and its activity is modulated by cognitive factors, such as attention and working memory. This review of more than 90 studies focuses on providing clarity of the heterogeneous findings on MST in the macaque cortex and its putative homolog in the human cortex. From this analysis of the unique anatomical and functional position in the hierarchy of areas and processing steps in primate visual cortex, MST emerges as a gateway between perception, cognition, and action planning. Given this pivotal role, this area represents an ideal model system for the transition from sensation to cognition.
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Affiliation(s)
- Benedict Wild
- Cognitive Neuroscience Laboratory, German Primate Center, Leibniz Institute for Primate Research, Goettingen, Germany.,Goettingen Graduate Center for Neurosciences, Biophysics, and Molecular Biosciences (GGNB), University of Goettingen, Goettingen, Germany
| | - Stefan Treue
- Cognitive Neuroscience Laboratory, German Primate Center, Leibniz Institute for Primate Research, Goettingen, Germany.,Faculty of Biology and Psychology, University of Goettingen, Goettingen, Germany.,Leibniz-ScienceCampus Primate Cognition, Goettingen, Germany.,Bernstein Center for Computational Neuroscience, Goettingen, Germany
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31
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Kaas JH. Comparative Functional Anatomy of Marmoset Brains. ILAR J 2021; 61:260-273. [PMID: 33550381 PMCID: PMC9214571 DOI: 10.1093/ilar/ilaa026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 10/09/2020] [Accepted: 10/23/2020] [Indexed: 12/23/2022] Open
Abstract
Marmosets and closely related tamarins have become popular models for understanding aspects of human brain organization and function because they are small, reproduce and mature rapidly, and have few cortical fissures so that more cortex is visible and accessible on the surface. They are well suited for studies of development and aging. Because marmosets are highly social primates with extensive vocal communication, marmoset studies can inform theories of the evolution of language in humans. Most importantly, marmosets share basic features of major sensory and motor systems with other primates, including those of macaque monkeys and humans with larger and more complex brains. The early stages of sensory processing, including subcortical nuclei and several cortical levels for the visual, auditory, somatosensory, and motor systems, are highly similar across primates, and thus results from marmosets are relevant for making inferences about how these systems are organized and function in humans. Nevertheless, the structures in these systems are not identical across primate species, and homologous structures are much bigger and therefore function somewhat differently in human brains. In particular, the large human brain has more cortical areas that add to the complexity of information processing and storage, as well as decision-making, while making new abilities possible, such as language. Thus, inferences about human brains based on studies on marmoset brains alone should be made with a bit of caution.
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Affiliation(s)
- Jon H Kaas
- Corresponding Author: Jon H. Kaas, PhD, Department of Psychology, Vanderbilt University, 301 Wilson Hall, 111 21st Ave. S., Nashville, TN 37203, USA. E-mail:
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32
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Overlooked Tertiary Sulci Serve as a Meso-Scale Link between Microstructural and Functional Properties of Human Lateral Prefrontal Cortex. J Neurosci 2021; 41:2229-2244. [PMID: 33478989 DOI: 10.1523/jneurosci.2362-20.2021] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 12/22/2020] [Accepted: 01/05/2021] [Indexed: 11/21/2022] Open
Abstract
Understanding the relationship between neuroanatomy and function in portions of cortex that perform functions largely specific to humans such as lateral prefrontal cortex (LPFC) is of major interest in systems and cognitive neuroscience. When considering neuroanatomical-functional relationships in LPFC, shallow indentations in cortex known as tertiary sulci have been largely unexplored. Here, by implementing a multimodal approach and manually defining 936 neuroanatomical structures in 72 hemispheres (in both males and females), we show that a subset of these overlooked tertiary sulci serve as a meso-scale link between microstructural (myelin content) and functional (network connectivity) properties of human LPFC in individual participants. For example, the posterior middle frontal sulcus (pmfs) is a tertiary sulcus with three components that differ in their myelin content, resting-state connectivity profiles, and engagement across meta-analyses of 83 cognitive tasks. Further, generating microstructural profiles of myelin content across cortical depths for each pmfs component and the surrounding middle frontal gyrus (MFG) shows that both gyral and sulcal components of the MFG have greater myelin content in deeper compared with superficial layers and that the myelin content in superficial layers of the gyral components is greater than sulcal components. These findings support a classic, yet largely unconsidered theory that tertiary sulci may serve as landmarks in association cortices, as well as a modern cognitive neuroscience theory proposing a functional hierarchy in LPFC. As there is a growing need for computational tools that automatically define tertiary sulci throughout cortex, we share pmfs probabilistic sulcal maps with the field.SIGNIFICANCE STATEMENT Lateral prefrontal cortex (LPFC) is critical for functions that are thought to be specific to humans compared with other mammals. However, relationships between fine-scale neuroanatomical structures largely specific to hominoid cortex and functional properties of LPFC remain elusive. Here, we show that these structures, which have been largely unexplored throughout history, surprisingly serve as markers for anatomical and functional organization in human LPFC. These findings have theoretical, methodological, developmental, and evolutionary implications for improved understanding of neuroanatomical-functional relationships not only in LPFC, but also in association cortices more broadly. Finally, these findings ignite new questions regarding how morphological features of these neglected neuroanatomical structures contribute to functions of association cortices that are critical for human-specific aspects of cognition.
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33
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Thomas J, Sharma D, Mohanta S, Jain N. Resting-State functional networks of different topographic representations in the somatosensory cortex of macaque monkeys and humans. Neuroimage 2020; 228:117694. [PMID: 33385552 DOI: 10.1016/j.neuroimage.2020.117694] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 12/15/2020] [Accepted: 12/21/2020] [Indexed: 11/16/2022] Open
Abstract
Information processing in the brain is mediated through a complex functional network architecture whose comprising nodes integrate and segregate themselves on different timescales. To gain an understanding of the network function it is imperative to identify and understand the network structure with respect to the underlying anatomical connectivity and the topographic organization. Here we show that the previously described resting-state network for the somatosensory area 3b comprises of distinct networks that are characteristic for different topographic representations. Seed-based resting-state functional connectivity analysis in macaque monkeys and humans using BOLD-fMRI signals from the face, the hand and rest of the medial somatosensory representations of area 3b revealed different correlation patterns. Both monkeys and humans have many similarities in the connectivity networks, although the networks are more complex in humans with many more nodes. In both the species face area network has the highest ipsilateral and contralateral connectivity, which included areas 3b and 4, and ventral premotor area. The area 3b hand network included ipsilateral hand representation in area 4. The emergent functional network structures largely reflect the known anatomical connectivity. Our results show that different body part representations in area 3b have independent functional networks perhaps reflecting differences in the behavioral use of different body parts. The results also show that large cortical areas if considered together, do not give a complete and accurate picture of the network architecture.
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Affiliation(s)
- John Thomas
- National Brain Research Centre, NH 8, Manesar 122052, Haryana, India
| | - Dixit Sharma
- National Brain Research Centre, NH 8, Manesar 122052, Haryana, India
| | - Sounak Mohanta
- National Brain Research Centre, NH 8, Manesar 122052, Haryana, India
| | - Neeraj Jain
- National Brain Research Centre, NH 8, Manesar 122052, Haryana, India.
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34
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Xu T, Nenning KH, Schwartz E, Hong SJ, Vogelstein JT, Goulas A, Fair DA, Schroeder CE, Margulies DS, Smallwood J, Milham MP, Langs G. Cross-species functional alignment reveals evolutionary hierarchy within the connectome. Neuroimage 2020; 223:117346. [PMID: 32916286 PMCID: PMC7871099 DOI: 10.1016/j.neuroimage.2020.117346] [Citation(s) in RCA: 105] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 08/04/2020] [Accepted: 08/31/2020] [Indexed: 11/22/2022] Open
Abstract
Evolution provides an important window into how cortical organization shapes function and vice versa. The complex mosaic of changes in brain morphology and functional organization that have shaped the mammalian cortex during evolution, complicates attempts to chart cortical differences across species. It limits our ability to fully appreciate how evolution has shaped our brain, especially in systems associated with unique human cognitive capabilities that lack anatomical homologues in other species. Here, we develop a function-based method for cross-species alignment that enables the quantification of homologous regions between humans and rhesus macaques, even when their location is decoupled from anatomical landmarks. Critically, we find cross-species similarity in functional organization reflects a gradient of evolutionary change that decreases from unimodal systems and culminates with the most pronounced changes in posterior regions of the default mode network (angular gyrus, posterior cingulate and middle temporal cortices). Our findings suggest that the establishment of the default mode network, as the apex of a cognitive hierarchy, has changed in a complex manner during human evolution - even within subnetworks.
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Affiliation(s)
- Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA.
| | - Karl-Heinz Nenning
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
| | - Ernst Schwartz
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria
| | - Seok-Jun Hong
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA
| | - Joshua T Vogelstein
- Department of Biomedical Engineering, Institute for Computational Medicine, Kavli Neuroscience Discovery Institute, Johns Hopkins University, MD, USA
| | - Alexandros Goulas
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Hamburg, Germany
| | - Damien A Fair
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, USA
| | - Charles E Schroeder
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA; Departments of neurosurgery and Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Daniel S Margulies
- Centre National de la Recherche Scientifique (CNRS) UMR 7225, Frontlab, Institut du Cerveau et de la Moelle Epinière, Paris, France
| | - Jonny Smallwood
- Department of Psychology, Queen's University, Kingston, Ontario, Canada; Psychology Department, University of York, York, UK
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Austria; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
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35
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Self-organization of cortical areas in the development and evolution of neocortex. Proc Natl Acad Sci U S A 2020; 117:29212-29220. [PMID: 33139564 DOI: 10.1073/pnas.2011724117] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
While the mechanisms generating the topographic organization of primary sensory areas in the neocortex are well studied, what generates secondary cortical areas is virtually unknown. Using physical parameters representing primary and secondary visual areas as they vary from monkey to mouse, we derived a network growth model to explore if characteristic features of secondary areas could be produced from correlated activity patterns arising from V1 alone. We found that V1 seeded variable numbers of secondary areas based on activity-driven wiring and wiring-density limits within the cortical surface. These secondary areas exhibited the typical mirror-reversal of map topography on cortical area boundaries and progressive reduction of the area and spatial resolution of each new map on the caudorostral axis. Activity-based map formation may be the basic mechanism that establishes the matrix of topographically organized cortical areas available for later computational specialization.
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36
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Pelekanos V, Premereur E, Mitchell DJ, Chakraborty S, Mason S, Lee ACH, Mitchell AS. Corticocortical and Thalamocortical Changes in Functional Connectivity and White Matter Structural Integrity after Reward-Guided Learning of Visuospatial Discriminations in Rhesus Monkeys. J Neurosci 2020; 40:7887-7901. [PMID: 32900835 PMCID: PMC7548693 DOI: 10.1523/jneurosci.0364-20.2020] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 06/30/2020] [Accepted: 07/25/2020] [Indexed: 12/14/2022] Open
Abstract
The frontal cortex and temporal lobes together regulate complex learning and memory capabilities. Here, we collected resting-state functional and diffusion-weighted MRI data before and after male rhesus macaque monkeys received extensive training to learn novel visuospatial discriminations (reward-guided learning). We found functional connectivity changes in orbitofrontal, ventromedial prefrontal, inferotemporal, entorhinal, retrosplenial, and anterior cingulate cortices, the subicular complex, and the dorsal, medial thalamus. These corticocortical and thalamocortical changes in functional connectivity were accompanied by related white matter structural alterations in the uncinate fasciculus, fornix, and ventral prefrontal tract: tracts that connect (sub)cortical networks and are implicated in learning and memory processes in monkeys and humans. After the well-trained monkeys received fornix transection, they were impaired in learning new visuospatial discriminations. In addition, the functional connectivity profile that was observed after the training was altered. These changes were accompanied by white matter changes in the ventral prefrontal tract, although the integrity of the uncinate fasciculus remained unchanged. Our experiments highlight the importance of different communication relayed among corticocortical and thalamocortical circuitry for the ability to learn new visuospatial associations (learning-to-learn) and to make reward-guided decisions.SIGNIFICANCE STATEMENT Frontal neural networks and the temporal lobes contribute to reward-guided learning in mammals. Here, we provide novel insight by showing that specific corticocortical and thalamocortical functional connectivity is altered after rhesus monkeys received extensive training to learn novel visuospatial discriminations. Contiguous white matter fiber pathways linking these gray matter structures, namely, the uncinate fasciculus, fornix, and ventral prefrontal tract, showed structural changes after completing training in the visuospatial task. Additionally, different patterns of functional and structural connectivity are reported after removal of subcortical connections within the extended hippocampal system, via fornix transection. These results highlight the importance of both corticocortical and thalamocortical interactions in reward-guided learning in the normal brain and identify brain structures important for memory capabilities after injury.
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Affiliation(s)
- Vassilis Pelekanos
- Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, United Kingdom
| | - Elsie Premereur
- Laboratory for Neuro- and Psychophysiology, KU Leuven, 3000 Leuven, Belgium
| | - Daniel J Mitchell
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom
| | - Subhojit Chakraborty
- Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
| | - Stuart Mason
- Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, United Kingdom
| | - Andy C H Lee
- Department of Psychology (Scarborough), University of Toronto, Toronto, Ontario M1C 1A4, Canada
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario M6A 2E1, Canada
| | - Anna S Mitchell
- Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, United Kingdom
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37
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Vanni S, Hokkanen H, Werner F, Angelucci A. Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models. Cereb Cortex 2020; 30:3483-3517. [PMID: 31897474 PMCID: PMC7233004 DOI: 10.1093/cercor/bhz322] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 12/02/2019] [Indexed: 12/22/2022] Open
Abstract
The cerebral cortex of primates encompasses multiple anatomically and physiologically distinct areas processing visual information. Areas V1, V2, and V5/MT are conserved across mammals and are central for visual behavior. To facilitate the generation of biologically accurate computational models of primate early visual processing, here we provide an overview of over 350 published studies of these three areas in the genus Macaca, whose visual system provides the closest model for human vision. The literature reports 14 anatomical connection types from the lateral geniculate nucleus of the thalamus to V1 having distinct layers of origin or termination, and 194 connection types between V1, V2, and V5, forming multiple parallel and interacting visual processing streams. Moreover, within V1, there are reports of 286 and 120 types of intrinsic excitatory and inhibitory connections, respectively. Physiologically, tuning of neuronal responses to 11 types of visual stimulus parameters has been consistently reported. Overall, the optimal spatial frequency (SF) of constituent neurons decreases with cortical hierarchy. Moreover, V5 neurons are distinct from neurons in other areas for their higher direction selectivity, higher contrast sensitivity, higher temporal frequency tuning, and wider SF bandwidth. We also discuss currently unavailable data that could be useful for biologically accurate models.
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Affiliation(s)
- Simo Vanni
- HUS Neurocenter, Department of Neurology, Helsinki University Hospital, 00290 Helsinki, Finland
- Department of Neurosciences, University of Helsinki, 00100 Helsinki, Finland
| | - Henri Hokkanen
- HUS Neurocenter, Department of Neurology, Helsinki University Hospital, 00290 Helsinki, Finland
- Department of Neurosciences, University of Helsinki, 00100 Helsinki, Finland
| | - Francesca Werner
- HUS Neurocenter, Department of Neurology, Helsinki University Hospital, 00290 Helsinki, Finland
- Department of Neurosciences, University of Helsinki, 00100 Helsinki, Finland
- Department of Biomedical and Neuromotor Sciences, University of Bologna, 40126 Bologna, Italy
| | - Alessandra Angelucci
- Department of Ophthalmology and Visual Sciences, Moran Eye Institute, University of Utah, Salt Lake City, UT 84132, USA
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38
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Pelekanos V, Mok RM, Joly O, Ainsworth M, Kyriazis D, Kelly MG, Bell AH, Kriegeskorte N. Rapid event-related, BOLD fMRI, non-human primates (NHP): choose two out of three. Sci Rep 2020; 10:7485. [PMID: 32366956 PMCID: PMC7198564 DOI: 10.1038/s41598-020-64376-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 04/15/2020] [Indexed: 12/03/2022] Open
Abstract
Human functional magnetic resonance imaging (fMRI) typically employs the blood-oxygen-level-dependent (BOLD) contrast mechanism. In non-human primates (NHP), contrast enhancement is possible using monocrystalline iron-oxide nanoparticles (MION) contrast agent, which has a more temporally extended response function. However, using BOLD fMRI in NHP is desirable for interspecies comparison, and the BOLD signal’s faster response function promises to be beneficial for rapid event-related (rER) designs. Here, we used rER BOLD fMRI in macaque monkeys while viewing real-world images, and found visual responses and category selectivity consistent with previous studies. However, activity estimates were very noisy, suggesting that the lower contrast-to-noise ratio of BOLD, suboptimal behavioural performance, and motion artefacts, in combination, render rER BOLD fMRI challenging in NHP. Previous studies have shown that rER fMRI is possible in macaques with MION, despite MION’s prolonged response function. To understand this, we conducted simulations of the BOLD and MION response during rER, and found that no matter how fast the design, the greater amplitude of the MION response outweighs the contrast loss caused by greater temporal smoothing. We conclude that although any two of the three elements (rER, BOLD, NHP) have been shown to work well, the combination of all three is particularly challenging.
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Affiliation(s)
- Vassilis Pelekanos
- Medical Research Council, Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK. .,Department of Experimental Psychology, University of Oxford, Oxford, UK. .,School of Medicine, University of Nottingham, Nottingham, UK.
| | - Robert M Mok
- Medical Research Council, Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.,Department of Experimental Psychology, University College London, London, UK
| | - Olivier Joly
- Medical Research Council, Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Matthew Ainsworth
- Medical Research Council, Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Diana Kyriazis
- Medical Research Council, Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Maria G Kelly
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Andrew H Bell
- Medical Research Council, Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Nikolaus Kriegeskorte
- Medical Research Council, Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.,Zuckerman Mind Brain Behavior Institute, Columbia University, New York, USA
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39
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Zhang T, Huang Y, Zhao L, He Z, Jiang X, Guo L, Hu X, Liu T. Identifying Cross-individual Correspondences of 3-hinge Gyri. Med Image Anal 2020; 63:101700. [PMID: 32361590 DOI: 10.1016/j.media.2020.101700] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 04/04/2020] [Accepted: 04/07/2020] [Indexed: 01/16/2023]
Abstract
Human brain alignment based on imaging data has long been an intriguing research topic. One of the challenges is the huge inter-individual variabilities, which are pronounced not only in cortical folding patterns, but also in the underlying structural and functional patterns. Also, it is still not fully understood how to link the cross-subject similarity of cortical folding patterns to the correspondences of structural brain wiring diagrams and brain functions. Recently, a specific cortical gyral folding pattern was identified, which is the conjunction of gyri from multiple directions and termed a "gyral hinge". These gyral hinges are characterized by the thickest cortices, the densest long-range fibers, and the most complex functional profiles in contrast to other gyri. In addition to their structural and functional importance, a small portion of 3-hinges found correspondences across subjects and even species by manual labeling. However, it is unclear if such cross-subject correspondences can be found for all 3-hinges, or if the correspondences are interpretable from structural and functional aspects. Given the huge variability of cortical folding patterns, we proposed a novel algorithm which jointly uses structural MRI-derived cortical folding patterns and diffusion-MRI-derived fiber shape features to estimate the correspondences. This algorithm was executed in a group-wise manner, whereby 3-hinges of all subjects were simultaneously aligned. The effectiveness of the algorithm was demonstrated by higher cross-subject 3-hinges' consistency with respect to structural and functional metrics, when compared with other methods. Our findings provide a novel approach to brain alignment and an insight to the linkage between cortical folding patterns and the underlying structural connective diagrams and brain functions.
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Affiliation(s)
- Tuo Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an, China.
| | - Ying Huang
- School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Lin Zhao
- School of Automation, Northwestern Polytechnical University, Xi'an, China; Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA
| | - Zhibin He
- School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Xi Jiang
- School of Life Science and Technology, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi'an, China
| | - Xiaoping Hu
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA
| | - Tianming Liu
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Athens, GA, USA
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MECP2 Duplication Causes Aberrant GABA Pathways, Circuits and Behaviors in Transgenic Monkeys: Neural Mappings to Patients with Autism. J Neurosci 2020; 40:3799-3814. [PMID: 32269107 DOI: 10.1523/jneurosci.2727-19.2020] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Revised: 03/15/2020] [Accepted: 03/16/2020] [Indexed: 12/21/2022] Open
Abstract
MECP2 gain-of-function and loss-of-function in genetically engineered monkeys recapitulates typical phenotypes in patients with autism, yet where MECP2 mutation affects the monkey brain and whether/how it relates to autism pathology remain unknown. Here we report a combination of gene-circuit-behavior analyses including MECP2 coexpression network, locomotive and cognitive behaviors, and EEG and fMRI findings in 5 MECP2 overexpressed monkeys (Macaca fascicularis; 3 females) and 20 wild-type monkeys (Macaca fascicularis; 11 females). Whole-genome expression analysis revealed MECP2 coexpressed genes significantly enriched in GABA-related signaling pathways, whereby reduced β-synchronization within fronto-parieto-occipital networks was associated with abnormal locomotive behaviors. Meanwhile, MECP2-induced hyperconnectivity in prefrontal and cingulate networks accounted for regressive deficits in reversal learning tasks. Furthermore, we stratified a cohort of 49 patients with autism and 72 healthy controls of 1112 subjects using functional connectivity patterns, and identified dysconnectivity profiles similar to those in monkeys. By establishing a circuit-based construct link between genetically defined models and stratified patients, these results pave new avenues to deconstruct clinical heterogeneity and advance accurate diagnosis in psychiatric disorders.SIGNIFICANCE STATEMENT Autism spectrum disorder (ASD) is a complex disorder with co-occurring symptoms caused by multiple genetic variations and brain circuit abnormalities. To dissect the gene-circuit-behavior causal chain underlying ASD, animal models are established by manipulating causative genes such as MECP2 However, it is unknown whether such models have captured any circuit-level pathology in ASD patients, as demonstrated by human brain imaging studies. Here, we use transgenic macaques to examine the causal effect of MECP2 overexpression on gene coexpression, brain circuits, and behaviors. For the first time, we demonstrate that the circuit abnormalities linked to MECP2 and autism-like traits in the monkeys can be mapped to a homogeneous ASD subgroup, thereby offering a new strategy to deconstruct clinical heterogeneity in ASD.
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Towards HCP-Style macaque connectomes: 24-Channel 3T multi-array coil, MRI sequences and preprocessing. Neuroimage 2020; 215:116800. [PMID: 32276072 DOI: 10.1016/j.neuroimage.2020.116800] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Revised: 03/16/2020] [Accepted: 03/23/2020] [Indexed: 11/23/2022] Open
Abstract
Macaque monkeys are an important animal model where invasive investigations can lead to a better understanding of the cortical organization of primates including humans. However, the tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the smaller macaque brain, high spatial, temporal, and angular resolutions combined with high signal-to-noise ratio are required to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enables adaptation of the Human Connectome Project (HCP) image acquisition protocols to the in-vivo macaque brain. In addition, we adapted HCP preprocessing methods to the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provides the necessary high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold accelerations for dMRI and fMRI. Automated FreeSurfer segmentation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI all performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. Analyses of functional connectivity in fMRI revealed high sensitivity as compared with those from publicly shared datasets. Tractography-based connectivity estimates correlated with tracer connectivity similarly to that achieved using ex-vivo dMRI. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available in studies of the human brain.
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Mandino F, Cerri DH, Garin CM, Straathof M, van Tilborg GAF, Chakravarty MM, Dhenain M, Dijkhuizen RM, Gozzi A, Hess A, Keilholz SD, Lerch JP, Shih YYI, Grandjean J. Animal Functional Magnetic Resonance Imaging: Trends and Path Toward Standardization. Front Neuroinform 2020; 13:78. [PMID: 32038217 PMCID: PMC6987455 DOI: 10.3389/fninf.2019.00078] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 12/19/2019] [Indexed: 12/21/2022] Open
Abstract
Animal whole-brain functional magnetic resonance imaging (fMRI) provides a non-invasive window into brain activity. A collection of associated methods aims to replicate observations made in humans and to identify the mechanisms underlying the distributed neuronal activity in the healthy and disordered brain. Animal fMRI studies have developed rapidly over the past years, fueled by the development of resting-state fMRI connectivity and genetically encoded neuromodulatory tools. Yet, comparisons between sites remain hampered by lack of standardization. Recently, we highlighted that mouse resting-state functional connectivity converges across centers, although large discrepancies in sensitivity and specificity remained. Here, we explore past and present trends within the animal fMRI community and highlight critical aspects in study design, data acquisition, and post-processing operations, that may affect the results and influence the comparability between studies. We also suggest practices aimed to promote the adoption of standards within the community and improve between-lab reproducibility. The implementation of standardized animal neuroimaging protocols will facilitate animal population imaging efforts as well as meta-analysis and replication studies, the gold standards in evidence-based science.
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Affiliation(s)
- Francesca Mandino
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research, Singapore, Singapore
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Domenic H. Cerri
- Center for Animal MRI, Department of Neurology, Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Clement M. Garin
- Direction de la Recherche Fondamentale, MIRCen, Institut de Biologie François Jacob, Commissariat à l’Énergie Atomique et aux Énergies Alternatives, Fontenay-aux-Roses, France
- Neurodegenerative Diseases Laboratory, Centre National de la Recherche Scientifique, UMR 9199, Université Paris-Sud, Université Paris-Saclay, Fontenay-aux-Roses, France
| | - Milou Straathof
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Geralda A. F. van Tilborg
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - M. Mallar Chakravarty
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
- Department of Biological and Biomedical Engineering, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
| | - Marc Dhenain
- Direction de la Recherche Fondamentale, MIRCen, Institut de Biologie François Jacob, Commissariat à l’Énergie Atomique et aux Énergies Alternatives, Fontenay-aux-Roses, France
- Neurodegenerative Diseases Laboratory, Centre National de la Recherche Scientifique, UMR 9199, Université Paris-Sud, Université Paris-Saclay, Fontenay-aux-Roses, France
| | - Rick M. Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Alessandro Gozzi
- Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Centre for Neuroscience and Cognitive Systems @ UNITN, Rovereto, Italy
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich–Alexander University Erlangen–Nürnberg, Erlangen, Germany
| | - Shella D. Keilholz
- Department of Biomedical Engineering, Georgia Tech, Emory University, Atlanta, GA, United States
| | - Jason P. Lerch
- Hospital for Sick Children, Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Wellcome Centre for Integrative NeuroImaging, University of Oxford, Oxford, United Kingdom
| | - Yen-Yu Ian Shih
- Center for Animal MRI, Department of Neurology, Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Joanes Grandjean
- Singapore Bioimaging Consortium, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Radiology and Nuclear Medicine, Donders Institute for Brain, Cognition, and Behaviour, Donders Institute, Radboud University Medical Center, Nijmegen, Netherlands
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Van Essen DC, Donahue CJ, Coalson TS, Kennedy H, Hayashi T, Glasser MF. Cerebral cortical folding, parcellation, and connectivity in humans, nonhuman primates, and mice. Proc Natl Acad Sci U S A 2019; 116:26173-26180. [PMID: 31871175 PMCID: PMC6936571 DOI: 10.1073/pnas.1902299116] [Citation(s) in RCA: 113] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Advances in neuroimaging and neuroanatomy have yielded major insights concerning fundamental principles of cortical organization and evolution, thus speaking to how well different species serve as models for human brain function in health and disease. Here, we focus on cortical folding, parcellation, and connectivity in mice, marmosets, macaques, and humans. Cortical folding patterns vary dramatically across species, and individual variability in cortical folding increases with cortical surface area. Such issues are best analyzed using surface-based approaches that respect the topology of the cortical sheet. Many aspects of cortical organization can be revealed using 1 type of information (modality) at a time, such as maps of cortical myelin content. However, accurate delineation of the entire mosaic of cortical areas requires a multimodal approach using information about function, architecture, connectivity, and topographic organization. Comparisons across the 4 aforementioned species reveal dramatic differences in the total number and arrangement of cortical areas, particularly between rodents and primates. Hemispheric variability and bilateral asymmetry are most pronounced in humans, which we evaluated using a high-quality multimodal parcellation of hundreds of individuals. Asymmetries include modest differences in areal size but not in areal identity. Analyses of cortical connectivity using anatomical tracers reveal highly distributed connectivity and a wide range of connection weights in monkeys and mice; indirect measures using functional MRI suggest a similar pattern in humans. Altogether, a multifaceted but integrated approach to exploring cortical organization in primate and nonprimate species provides complementary advantages and perspectives.
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Affiliation(s)
- David C. Van Essen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
| | - Chad J. Donahue
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
| | - Timothy S. Coalson
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
| | - Henry Kennedy
- Univ Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 200031, China
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, 650-0047, Japan
| | - Matthew F. Glasser
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
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Dondé C, Martinez A, Sehatpour P, Patel GH, Kraut R, Kantrowitz JT, Javitt DC. Neural and functional correlates of impaired reading ability in schizophrenia. Sci Rep 2019; 9:16022. [PMID: 31690846 PMCID: PMC6831596 DOI: 10.1038/s41598-019-52669-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 10/22/2019] [Indexed: 01/14/2023] Open
Abstract
Deficits in early auditory processing (EAP) are a core component of schizophrenia (SZ) and contribute significantly to impaired overall function. Here, we evaluate the potential contributions of EAP-related impairments in reading to functional capacity and outcome, relative to effects of auditory social cognitive and general neurocognitive dysfunction. Participants included 30-SZ and 28-controls of similar age, sex, and educational achievement. EAP was assessed using an auditory working memory (tone-matching) task. Phonological processing and reading Fluency were assessed using the Comprehensive Test of Phonological Processing and Woodcock-Johnson reading batteries, respectively. Auditory-related social cognition was assessed using measures of emotion/sarcasm recognition. Functional capacity and outcome were assessed using the UCSD Performance-based Skills Assessment and Specific Level of Functioning scale, respectively. fMRI resting-state functional-connectivity (rsFC) was used to evaluate potential underlying substrates. As predicted, SZ patients showed significant and interrelated deficits in both phonological processing (d = 0.74, p = 0.009) and reading fluency (d = 1.24, p < 0.00005). By contrast, single word reading (d = 0.35, p = 0.31) was intact. In SZ, deficits in EAP and phonological reading ability significantly predicted reduced functional capacity, but not functional outcome. By contrast, deficits in reading fluency significantly predicted impairments in both functional capacity and functional outcome. Moreover, deficits in reading fluency correlated with rsFC alterations among auditory thalamus, early auditory and auditory association regions. These findings indicate significant contributions of EAP deficits and functional connectivity changes in subcortical and early auditory regions to reductions in reading fluency, and of impaired reading ability to impaired functional outcome in SZ.
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Affiliation(s)
- Clément Dondé
- INSERM, U1028; CNRS, UMR5292; Lyon Neuroscience Research Center, Psychiatric Disorders: from Resistance to Response Team, Lyon, F-69000, France. .,University Lyon 1, Villeurbanne, F-69000, France. .,Centre Hospitalier Le Vinatier, Bron, France. .,Nathan Kline Institute, Orangeburg, NY, USA. .,Dept. of Psychiatry, Columbia University Medical Center/New York State Psychiatric Institute, New York, NY, USA.
| | - Antigona Martinez
- Nathan Kline Institute, Orangeburg, NY, USA.,Dept. of Psychiatry, Columbia University Medical Center/New York State Psychiatric Institute, New York, NY, USA
| | - Pejman Sehatpour
- Nathan Kline Institute, Orangeburg, NY, USA.,Dept. of Psychiatry, Columbia University Medical Center/New York State Psychiatric Institute, New York, NY, USA
| | - Gaurav H Patel
- Dept. of Psychiatry, Columbia University Medical Center/New York State Psychiatric Institute, New York, NY, USA
| | - Rebecca Kraut
- Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY, USA
| | - Joshua T Kantrowitz
- Nathan Kline Institute, Orangeburg, NY, USA.,Dept. of Psychiatry, Columbia University Medical Center/New York State Psychiatric Institute, New York, NY, USA
| | - Daniel C Javitt
- Nathan Kline Institute, Orangeburg, NY, USA. .,Dept. of Psychiatry, Columbia University Medical Center/New York State Psychiatric Institute, New York, NY, USA.
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Zhang S, Jiang X, Zhang W, Zhang T, Chen H, Zhao Y, Lv J, Guo L, Howell BR, Sanchez MM, Hu X, Liu T. Joint representation of connectome-scale structural and functional profiles for identification of consistent cortical landmarks in macaque brain. Brain Imaging Behav 2019; 13:1427-1443. [PMID: 30178424 PMCID: PMC6399084 DOI: 10.1007/s11682-018-9944-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Discovery and representation of common structural and functional cortical architectures has been a significant yet challenging problem for years. Due to the remarkable variability of structural and functional cortical architectures in human brain, it is challenging to jointly represent a common cortical architecture which can comprehensively encode both structure and function characteristics. In order to better understand this challenge and considering that macaque monkey brain has much less variability in structure and function compared with human brain, in this paper, we propose a novel computational framework to apply our DICCCOL (Dense Individualized and Common Connectivity-based Cortical Landmarks) and HAFNI (Holistic Atlases of Functional Networks and Interactions) frameworks on macaque brains, in order to jointly represent structural and functional connectome-scale profiles for identification of a set of consistent and common cortical landmarks across different macaque brains based on multimodal DTI and resting state fMRI (rsfMRI) data. Experimental results demonstrate that 100 consistent and common cortical landmarks are successfully identified via the proposed framework, each of which has reasonably accurate anatomical, structural fiber connection pattern, and functional correspondences across different macaque brains. This set of 100 landmarks offer novel insights into the structural and functional cortical architectures in macaque brains.
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Affiliation(s)
- Shu Zhang
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA
| | - Xi Jiang
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA
| | - Wei Zhang
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA
| | - Tuo Zhang
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA
- School of Automation, Northwestern Polytechnical University, Xi'an, People's Republic of China
| | - Hanbo Chen
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA
| | - Yu Zhao
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA
| | - Jinglei Lv
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA
- School of Automation, Northwestern Polytechnical University, Xi'an, People's Republic of China
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi'an, People's Republic of China
| | - Brittany R Howell
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Mar M Sanchez
- Department of Psychiatry & Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA.
| | - Xiaoping Hu
- Department of Bioengineering, UC Riverside, Riverside, CA, USA.
| | - Tianming Liu
- Cortical Architecture Imaging and Discovery Lab, Department of Computer Science and Bioimaging Research Center, The University of Georgia, Boyd GSRC 420, Athens, GA, 30602, USA.
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Nie B, Wang L, Hu Y, Liang S, Tan Z, Chai P, Tang Y, Shang J, Pan Z, Zhao X, Zhang X, Gong J, Zheng C, Xu H, Wey HY, Liang SH, Shan B. A population stereotaxic positron emission tomography brain template for the macaque and its application to ischemic model. Neuroimage 2019; 203:116163. [PMID: 31494249 DOI: 10.1016/j.neuroimage.2019.116163] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 07/03/2019] [Accepted: 09/03/2019] [Indexed: 10/26/2022] Open
Abstract
PURPOSE Positron emission tomography (PET) is a non-invasive imaging tool for the evaluation of brain function and neuronal activity in normal and diseased conditions with high sensitivity. The macaque monkey serves as a valuable model system in the field of translational medicine, for its phylogenetic proximity to man. To translation of non-human primate neuro-PET studies, an effective and objective data analysis platform for neuro-PET studies is needed. MATERIALS AND METHODS A set of stereotaxic templates of macaque brain, namely the Institute of High Energy Physics & Jinan University Macaque Template (HJT), was constructed by iteratively registration and averaging, based on 30 healthy rhesus monkeys. A brain atlas image was created in HJT space by combining sub-anatomical regions and defining new 88 bilateral functional regions, in which a unique integer was assigned for each sub-anatomical region. RESULTS The HJT comprised a structural MRI T1 weighted image (T1WI) template image, a functional FDG-PET template image, intracranial tissue segmentations accompanied with a digital macaque brain atlas image. It is compatible with various commercially available software tools, such as SPM and PMOD. Data analysis was performed on a stroke model compared with a group of healthy controls to demonstrate the usage of HJT. CONCLUSION We have constructed a stereotaxic template set of macaque brain named HJT, which standardizes macaque neuroimaging data analysis, supports novel radiotracer development and facilitates translational neuro-disorders research.
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Affiliation(s)
- Binbin Nie
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences & School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Lu Wang
- Department of Nuclear Medicine and PET/CT-MRI Center, The First Affiliated Hospital of Jinan University & Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Yichao Hu
- College of Information Engineering, Xiangtan University, Xiangtan, 411105, China
| | - Shengxiang Liang
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences & School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiqiang Tan
- Department of Nuclear Medicine and PET/CT-MRI Center, The First Affiliated Hospital of Jinan University & Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Pei Chai
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences & School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yongjin Tang
- Department of Nuclear Medicine and PET/CT-MRI Center, The First Affiliated Hospital of Jinan University & Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Jingjie Shang
- Department of Nuclear Medicine and PET/CT-MRI Center, The First Affiliated Hospital of Jinan University & Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Zhangsheng Pan
- Department of Nuclear Medicine and PET/CT-MRI Center, The First Affiliated Hospital of Jinan University & Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Xudong Zhao
- Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xiaofei Zhang
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA
| | - Jianxian Gong
- State Key Laboratory of Chemical Oncogenomics, Key Laboratory of Chemical Genomics, Peking University Shenzhen Graduate School, Shenzhen, 518055, China
| | - Chao Zheng
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Hao Xu
- Department of Nuclear Medicine and PET/CT-MRI Center, The First Affiliated Hospital of Jinan University & Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China.
| | - Hsiao-Ying Wey
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Steven H Liang
- Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA
| | - Baoci Shan
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences & School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, 100049, China; Department of Nuclear Medicine and PET/CT-MRI Center, The First Affiliated Hospital of Jinan University & Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, 200031, China.
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Eichert N, Verhagen L, Folloni D, Jbabdi S, Khrapitchev AA, Sibson NR, Mantini D, Sallet J, Mars RB. What is special about the human arcuate fasciculus? Lateralization, projections, and expansion. Cortex 2019; 118:107-115. [PMID: 29937266 PMCID: PMC6699597 DOI: 10.1016/j.cortex.2018.05.005] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Revised: 05/02/2018] [Accepted: 05/03/2018] [Indexed: 11/27/2022]
Abstract
Evolutionary adaptations of the human brain are the basis for our unique abilities such as language. An expansion of the arcuate fasciculus (AF), the dorsal language tract, in the human lineage involving left lateralization is considered canonical, but this hypothesis has not been tested in relation to other architectural adaptations in the human brain. Using diffusion-weighted MRI, we examined AF in the human and macaque and quantified species differences in white matter architecture and surface representations. To compare surface results in the two species, we transformed macaque representations to human space using a landmark-based monkey-to-human cortical expansion model. We found that the human dorsal AF, but not the ventral inferior fronto-occipital fasciculus (IFO), is left-lateralized. In the monkey AF is not lateralized. Moreover, compared to the macaque, human AF is relatively increased with respect to IFO. A comparison of human and transformed macaque surface representations suggests that cortical expansion alone cannot account for the species differences in the surface representation of AF. Our results show that the human AF has undergone critical anatomical modifications in comparison with the macaque AF. More generally, this work demonstrates that studies on the human brain specializations underlying the language connectome can benefit from current methodological advances in comparative neuroanatomy.
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Affiliation(s)
- Nicole Eichert
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom.
| | - Lennart Verhagen
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Davide Folloni
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Alexandre A Khrapitchev
- Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom
| | - Nicola R Sibson
- Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom
| | - Dante Mantini
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom; Research Centre for Motor Control and Neuroplasticity, KU Leuven, Heverlee, Belgium
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, the Netherlands
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Abstract
To aid in the analysis of rhesus macaque brain images, we aligned digitized anatomical regions from the widely used atlas of Paxinos et al. to a published magnetic resonance imaging (MRI) template based on a large number of subjects. Digitally labelled atlas images were aligned to the template in 2D and then in 3D. The resulting grey matter regions appear qualitatively to be well registered to the template. To quantitatively validate the procedure, MR brain images of 20 rhesus macaques were aligned to the template along with regions drawn by hand in striatal and cortical areas in each subject's MRI. There was good geometric overlap between the hand drawn regions and the template regions. Positron emission tomography (PET) images of the same subjects showing uptake of a dopamine D2 receptor ligand were aligned to the template space, and good agreement was found between tracer binding measures calculated using the hand drawn and template regions. In conclusion, an anatomically defined set of rhesus macaque brain regions has been aligned to an MRI template and has been validated for analysis of PET imaging in a subset of striatal and cortical areas. The entire set of over 200 regions is publicly available at https://www.nitrc.org/ . Graphical Abstract ᅟ.
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The Mouse Cortical Connectome, Characterized by an Ultra-Dense Cortical Graph, Maintains Specificity by Distinct Connectivity Profiles. Neuron 2019; 97:698-715.e10. [PMID: 29420935 DOI: 10.1016/j.neuron.2017.12.037] [Citation(s) in RCA: 112] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 08/30/2017] [Accepted: 12/22/2017] [Indexed: 11/21/2022]
Abstract
The inter-areal wiring pattern of the mouse cerebral cortex was analyzed in relation to a refined parcellation of cortical areas. Twenty-seven retrograde tracer injections were made in 19 areas of a 47-area parcellation of the mouse neocortex. Flat mounts of the cortex and multiple histological markers enabled detailed counts of labeled neurons in individual areas. The observed log-normal distribution of connection weights to each cortical area spans 5 orders of magnitude and reveals a distinct connectivity profile for each area, analogous to that observed in macaques. The cortical network has a density of 97%, considerably higher than the 66% density reported in macaques. A weighted graph analysis reveals a similar global efficiency but weaker spatial clustering compared with that reported in macaques. The consistency, precision of the connectivity profile, density, and weighted graph analysis of the present data differ significantly from those obtained in earlier studies in the mouse.
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Mars RB, O'Muircheartaigh J, Folloni D, Li L, Glasser MF, Jbabdi S, Bryant KL. Concurrent analysis of white matter bundles and grey matter networks in the chimpanzee. Brain Struct Funct 2019; 224:1021-1033. [PMID: 30569281 PMCID: PMC6499872 DOI: 10.1007/s00429-018-1817-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 12/11/2018] [Indexed: 01/22/2023]
Abstract
Understanding the phylogeny of the human brain requires an appreciation of brain organization of our closest animal relatives. Neuroimaging tools such as magnetic resonance imaging (MRI) allow us to study whole-brain organization in species which can otherwise not be studied. Here, we used diffusion MRI to reconstruct the connections of the cortical hemispheres of the chimpanzee. This allowed us to perform an exploratory analysis of the grey matter structures of the chimpanzee cerebral cortex and their underlying white matter connectivity profiles. We identified a number of networks that strongly resemble those found in other primates, including the corticospinal system, limbic connections through the cingulum bundle and fornix, and occipital-temporal and temporal-frontal systems. Notably, chimpanzee temporal cortex showed a strong resemblance to that of the human brain, providing some insight into the specialization of the two species' shared lineage.
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Affiliation(s)
- Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK.
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.
| | - Jonathan O'Muircheartaigh
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, London, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, Sackler Institute for Translational Neurodevelopment, London, UK
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK
- Division of Imaging Sciences and Biomedical Engineering, Centre for the Developing Brain, St Thomas' Hospital, King's College London, London, UK
| | - Davide Folloni
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Longchuan Li
- Marcus Autism Center, Children's Healthcare of Atlanta, Emory University, Atlanta, GA, USA
| | - Matthew F Glasser
- Departments of Radiology and Neuroscience, Washington University Medical School, Saint Louis, MO, USA
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Katherine L Bryant
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
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