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Lynch KM, Cabeen RP, Toga AW. Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI. Hum Brain Mapp 2024; 45:e26528. [PMID: 37994234 PMCID: PMC10789199 DOI: 10.1002/hbm.26528] [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: 07/06/2023] [Revised: 10/10/2023] [Accepted: 10/19/2023] [Indexed: 11/24/2023] Open
Abstract
Neocortical maturation is a dynamic process that proceeds in a hierarchical manner; however, the spatiotemporal organization of cortical microstructure with diffusion MRI has yet to be fully defined. This study characterized cortical microstructural maturation using diffusion MRI (fwe-diffusion tensor imaging [DTI] and neurite orientation dispersion and density imaging [NODDI] multicompartment modeling) in a cohort of 637 children and adolescents between 8 and 21 years of age. We found spatially heterogeneous developmental patterns broadly demarcated into functional domains where NODDI metrics increased, and fwe-DTI metrics decreased with age. By applying nonlinear growth models in a vertex-wise analysis, we observed a general posterior-to-anterior pattern of maturation, where the fwe-DTI measures mean diffusivity and radial diffusivity reached peak maturation earlier than the NODDI metrics neurite density index. Using non-negative matrix factorization, we found occipito-parietal cortical regions that correspond to lower order sensory domains mature earlier than fronto-temporal higher order association domains. Our findings corroborate previous histological and neuroimaging studies that show spatially varying patterns of cortical maturation that may reflect unique developmental processes of cytoarchitectonically determined regional patterns of change.
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Affiliation(s)
- Kirsten M. Lynch
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| | - Ryan P. Cabeen
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
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2
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Parekh SA, Wren-Jarvis J, Lazerwitz M, Rowe MA, Powers R, Bourla I, Cai LT, Chu R, Trimarchi K, Garcia R, Marco EJ, Mukherjee P. Hemispheric lateralization of white matter microstructure in children and its potential role in sensory processing dysfunction. Front Neurosci 2023; 17:1088052. [PMID: 37139524 PMCID: PMC10149818 DOI: 10.3389/fnins.2023.1088052] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/28/2023] [Indexed: 05/05/2023] Open
Abstract
Diffusion tensor imaging (DTI) studies have demonstrated white matter microstructural differences between the left and right hemispheres of the brain. However, the basis of these hemispheric asymmetries is not yet understood in terms of the biophysical properties of white matter microstructure, especially in children. There are reports of altered hemispheric white matter lateralization in ASD; however, this has not been studied in other related neurodevelopmental disorders such as sensory processing disorder (SPD). Firstly, we postulate that biophysical compartment modeling of diffusion MRI (dMRI), such as Neurite Orientation Dispersion and Density Imaging (NODDI), can elucidate the hemispheric microstructural asymmetries observed from DTI in children with neurodevelopmental concerns. Secondly, we hypothesize that sensory over-responsivity (SOR), a common type of SPD, will show altered hemispheric lateralization relative to children without SOR. Eighty-seven children (29 females, 58 males), ages 8-12 years, presenting at a community-based neurodevelopmental clinic were enrolled, 48 with SOR and 39 without. Participants were evaluated using the Sensory Processing 3 Dimensions (SP3D). Whole brain 3 T multi-shell multiband dMRI (b = 0, 1,000, 2,500 s/mm2) was performed. Tract Based Spatial Statistics were used to extract DTI and NODDI metrics from 20 bilateral tracts of the Johns Hopkins University White-Matter Tractography Atlas and the lateralization Index (LI) was calculated for each left-right tract pair. With DTI metrics, 12 of 20 tracts were left lateralized for fractional anisotropy and 17/20 tracts were right lateralized for axial diffusivity. These hemispheric asymmetries could be explained by NODDI metrics, including neurite density index (18/20 tracts left lateralized), orientation dispersion index (15/20 tracts left lateralized) and free water fraction (16/20 tracts lateralized). Children with SOR served as a test case of the utility of studying LI in neurodevelopmental disorders. Our data demonstrated increased lateralization in several tracts for both DTI and NODDI metrics in children with SOR, which were distinct for males versus females, when compared to children without SOR. Biophysical properties from NODDI can explain the hemispheric lateralization of white matter microstructure in children. As a patient-specific ratio, the lateralization index can eliminate scanner-related and inter-individual sources of variability and thus potentially serve as a clinically useful imaging biomarker for neurodevelopmental disorders.
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Affiliation(s)
- Shalin A. Parekh
- Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, CA, United States
| | - Jamie Wren-Jarvis
- Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, CA, United States
| | - Maia Lazerwitz
- Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, CA, United States
- Cortica Healthcare, San Rafael, CA, United States
| | - Mikaela A. Rowe
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, United States
| | - Rachel Powers
- Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, CA, United States
- Cortica Healthcare, San Rafael, CA, United States
| | - Ioanna Bourla
- Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, CA, United States
| | - Lanya T. Cai
- Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, CA, United States
| | - Robyn Chu
- Cortica Healthcare, San Rafael, CA, United States
| | | | | | | | - Pratik Mukherjee
- Department of Radiology and Biomedical Imaging, University of California–San Francisco, San Francisco, CA, United States
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3
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Schijven D, Postema MC, Fukunaga M, Matsumoto J, Miura K, de Zwarte SMC, van Haren NEM, Cahn W, Hulshoff Pol HE, Kahn RS, Ayesa-Arriola R, Ortiz-García de la Foz V, Tordesillas-Gutierrez D, Vázquez-Bourgon J, Crespo-Facorro B, Alnæs D, Dahl A, Westlye LT, Agartz I, Andreassen OA, Jönsson EG, Kochunov P, Bruggemann JM, Catts SV, Michie PT, Mowry BJ, Quidé Y, Rasser PE, Schall U, Scott RJ, Carr VJ, Green MJ, Henskens FA, Loughland CM, Pantelis C, Weickert CS, Weickert TW, de Haan L, Brosch K, Pfarr JK, Ringwald KG, Stein F, Jansen A, Kircher TTJ, Nenadić I, Krämer B, Gruber O, Satterthwaite TD, Bustillo J, Mathalon DH, Preda A, Calhoun VD, Ford JM, Potkin SG, Chen J, Tan Y, Wang Z, Xiang H, Fan F, Bernardoni F, Ehrlich S, Fuentes-Claramonte P, Garcia-Leon MA, Guerrero-Pedraza A, Salvador R, Sarró S, Pomarol-Clotet E, Ciullo V, Piras F, Vecchio D, Banaj N, Spalletta G, Michielse S, van Amelsvoort T, Dickie EW, Voineskos AN, Sim K, Ciufolini S, Dazzan P, Murray RM, Kim WS, Chung YC, Andreou C, Schmidt A, Borgwardt S, McIntosh AM, Whalley HC, Lawrie SM, du Plessis S, Luckhoff HK, Scheffler F, Emsley R, Grotegerd D, Lencer R, Dannlowski U, Edmond JT, Rootes-Murdy K, Stephen JM, Mayer AR, Antonucci LA, Fazio L, Pergola G, Bertolino A, Díaz-Caneja CM, Janssen J, Lois NG, Arango C, Tomyshev AS, Lebedeva I, Cervenka S, Sellgren CM, Georgiadis F, Kirschner M, Kaiser S, Hajek T, Skoch A, Spaniel F, Kim M, Kwak YB, Oh S, Kwon JS, James A, Bakker G, Knöchel C, Stäblein M, Oertel V, Uhlmann A, Howells FM, Stein DJ, Temmingh HS, Diaz-Zuluaga AM, Pineda-Zapata JA, López-Jaramillo C, Homan S, Ji E, Surbeck W, Homan P, Fisher SE, Franke B, Glahn DC, Gur RC, Hashimoto R, Jahanshad N, Luders E, Medland SE, Thompson PM, Turner JA, van Erp TGM, Francks C. Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium. Proc Natl Acad Sci U S A 2023; 120:e2213880120. [PMID: 36976765 PMCID: PMC10083554 DOI: 10.1073/pnas.2213880120] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 02/03/2023] [Indexed: 03/29/2023] Open
Abstract
Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
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Affiliation(s)
- Dick Schijven
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
| | - Merel C. Postema
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam1081 HZ, The Netherlands
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki444-8585, Japan
| | - Junya Matsumoto
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Kenichiro Miura
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Sonja M. C. de Zwarte
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - Neeltje E. M. van Haren
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center Sophia Children's Hospital, Rotterdam3015 CN, The Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - Hilleke E. Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
| | - René S. Kahn
- Department of Psychiatry, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht3584 CG, The Netherlands
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY10029
- The Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, New York, NY10468
| | - Rosa Ayesa-Arriola
- Department of Psychiatry, Instituto de Investigación Marqués de Valdecilla, University Hospital Marqués de Valdecilla, Santander39008, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander39011, Spain
| | - Víctor Ortiz-García de la Foz
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, Instituto de Investigación Sanitaria Valdecilla, School of Medicine, University of Cantabria, Santander39011, Spain
| | - Diana Tordesillas-Gutierrez
- Department of Radiology, Instituto de Investigación Marqués de Valdecilla, Marqués de Valdecilla University Hospital, Santander39011, Spain
- Advanced Computing and e-Science, Instituto de Física de Cantabria, Universidad de Cantabria - Consejo Superior de Investigaciones Científicas, Santander39005, Spain
| | - Javier Vázquez-Bourgon
- Department of Psychiatry, Instituto de Investigación Marqués de Valdecilla, University Hospital Marqués de Valdecilla, Santander39008, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
| | - Benedicto Crespo-Facorro
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Psychiatry, School of Medicine, University of Sevilla, University Hospital Virgen del Rocío, Consejo Superior de Investigaciones Científicas - Instituto de Biomedicina de Sevilla, Sevilla41013, Spain
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychology, University of Oslo, Oslo0373, Norway
- Bjørknes College, Oslo0456, Norway
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo0373, Norway
| | - Lars T. Westlye
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychology, University of Oslo, Oslo0373, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo0372, Norway
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo0450, Norway
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo0373, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo0372, Norway
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo0450, Norway
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD21201
| | - Jason M. Bruggemann
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Edith Collins Centre (Translational Research in Alcohol, Drugs & Toxicology), Sydney Local Health District, Sydney2050, Australia
- Specialty of Addiction Medicine, Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney2006, Australia
| | - Stanley V. Catts
- School of Medicine, The University of Queensland, Brisbane4006, Australia
| | - Patricia T. Michie
- School of Psychological Sciences, University of Newcastle, Newcastle2308, Australia
| | - Bryan J. Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane4072, Australia
- Queensland Centre for Mental Health Research, The University of Queensland, Brisbane4076, Australia
| | - Yann Quidé
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Paul E. Rasser
- Centre for Brain and Mental Health Research, University of Newcastle, Newcastle2308, Australia
- Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Newcastle2308, Australia
- Hunter Medical Research Institute, Newcastle2305, Australia
| | - Ulrich Schall
- Centre for Brain and Mental Health Research, University of Newcastle, Newcastle2308, Australia
| | - Rodney J. Scott
- School of Biomedical Science and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle2308, Australia
| | - Vaughan J. Carr
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Melissa J. Green
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
| | - Frans A. Henskens
- School of Medicine and Public Health, University of Newcastle, Newcastle2308, Australia
- PRC for Health Behaviour, Hunter Medical Research Institute, Newcastle2305, Australia
| | - Carmel M. Loughland
- School of Medicine and Public Health, University of Newcastle, Newcastle2308, Australia
- Hunter New England Mental Health Service, Newcastle2305, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne3053, Australia
| | - Cynthia Shannon Weickert
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY13210
| | - Thomas W. Weickert
- School of Psychiatry, University of New South Wales, Sydney2033, Australia
- Neuroscience Research Australia, Sydney2031, Australia
- Department of Neuroscience and Physiology, Upstate Medical University, Syracuse, NY13210
| | - Lieuwe de Haan
- Early Psychosis Department, Department of Psychiatry, Amsterdam UMC (location AMC), Amsterdam1105 AZ, The Netherlands
- Arkin Institute for Mental Health, Amsterdam1033 NN, The Netherlands
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Kai G. Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
- Core-Facility Brainimaging, Faculty of Medicine, Philipps-Universität Marburg, Marburg35032, Germany
| | - Tilo T. J. Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Marburg35032, Germany
| | - Bernd Krämer
- Department of General Psychiatry, Section for Experimental Psychopathology and Neuroimaging, Heidelberg University, Heidelberg69115, Germany
| | - Oliver Gruber
- Department of General Psychiatry, Section for Experimental Psychopathology and Neuroimaging, Heidelberg University, Heidelberg69115, Germany
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Lifespan Brain Institute, University of Pennsylvania & Children's Hospital of Philadelphia, Philadelphia, PA19104
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
| | - Juan Bustillo
- Department of Psychiatry and Neuroscience, University of New Mexico, Albuquerque, NM87106
| | - Daniel H. Mathalon
- Department of Psychiatry and Behavioral Sciences and Weill Institute for Neurosciences, University of California, San Francisco, CA94143
- Mental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA94121
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
| | - Vince D. Calhoun
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA30303
| | - Judith M. Ford
- San Francisco VA Medical Center, University of California, San Francisco, CA94121
| | - Steven G. Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
- Long Beach VA Health Care System, Long Beach, CA90822
| | - Jingxu Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Hong Xiang
- Chongqing University Three Gorges Hospital, Chongqing404188, P.R. China
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing100096, P.R. China
| | - Fabio Bernardoni
- Division of Psychological and Social Medicine and Developmental Neurosciences, Translational Developmental Neuroscience Section, Technische Universität Dresden, University Hospital C.G. Carus, Dresden01307, Germany
- Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden01307, Germany
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Translational Developmental Neuroscience Section, Technische Universität Dresden, University Hospital C.G. Carus, Dresden01307, Germany
- Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Technische Universität Dresden, Faculty of Medicine, University Hospital C.G. Carus, Dresden01307, Germany
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Maria Angeles Garcia-Leon
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Benito Menni Complex Assistencial en Salut Mental, Barcelona08830, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona08035, Spain
- Mental Health Research Networking Center (Ciber del Área de Salud Mental), Madrid28029, Spain
| | - Valentina Ciullo
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome00179, Italy
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX77030
| | - Stijn Michielse
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Erin W. Dickie
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, TorontoM5S 2S1, Canada
- Department of Psychiatry, University of Toronto, TorontoM5T 1R8, Canada
| | - Aristotle N. Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, TorontoM5S 2S1, Canada
- Department of Psychiatry, University of Toronto, TorontoM5T 1R8, Canada
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore539747, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore119228, Singapore
| | - Simone Ciufolini
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Robin M. Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, LondonSE5 8AF, United Kingdom
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju54896, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University-Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju54896, Republic of Korea
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University Medical School, Jeonju54896, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University-Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju54896, Republic of Korea
| | - Christina Andreou
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
| | - André Schmidt
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
| | - Stefan Borgwardt
- Department of Psychiatry, University Psychiatric Clinics (Universitäre Psychiatrische Kliniken), University of Basel, Basel4002, Switzerland
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
| | - Andrew M. McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Heather C. Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Stephen M. Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, EdinburghEH16 4SB, United Kingdom
| | - Stefan du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
- Stellenbosch University Genomics of Brain Disorders Research Unit, South African Medical Research Council, Cape Town7505, South Africa
| | - Hilmar K. Luckhoff
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
| | - Freda Scheffler
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
| | - Robin Emsley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch7505, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck23562, Germany
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster48149, Germany
| | - Jesse T. Edmond
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
| | - Kelly Rootes-Murdy
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
| | | | | | - Linda A. Antonucci
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, Bari70121, Italy
| | - Leonardo Fazio
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari70121, Italy
- Psychiatry Unit, Bari University Hospital, Bari70121, Italy
| | - Covadonga M. Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
- School of Medicine, Universidad Complutense, Madrid28040, Spain
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
| | - Noemi G. Lois
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid28009, Spain
- Ciber del Área de Salud Mental, Instituto de Salud Carlos III, Madrid28029, Spain
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid28009, Spain
- School of Medicine, Universidad Complutense, Madrid28040, Spain
| | - Alexander S. Tomyshev
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow115522, Russian Federation
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal Analysis, Mental Health Research Center, Moscow115522, Russian Federation
| | - Simon Cervenka
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
- Department of Medical Sciences, Psychiatry, Uppsala University, Uppsala751 85, Sweden
| | - Carl M. Sellgren
- Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm113 64, Sweden
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm171 65, Sweden
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Montreal Neurological Institute, McGill University, MontrealH3A 2B4, Canada
| | - Stefan Kaiser
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Department of Psychiatry, Division of Adult Psychiatry, Geneva University Hospitals, Geneva1202, Switzerland
| | - Tomas Hajek
- National Institute of Mental Health, Klecany250 67, Czech Republic
- Department of Psychiatry, Dalhousie University, HalifaxB3H 2E2, Canada
| | - Antonin Skoch
- National Institute of Mental Health, Klecany250 67, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague140 21, Czech Republic
| | - Filip Spaniel
- National Institute of Mental Health, Klecany250 67, Czech Republic
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul08826, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul08826, Republic of Korea
| | - Sanghoon Oh
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul08826, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul08826, Republic of Korea
| | - Anthony James
- Department of Psychiatry, University of Oxford, OxfordOX3 7JX, United Kingdom
| | - Geor Bakker
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht University, Maastricht6229 ER, The Netherlands
| | - Christian Knöchel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Michael Stäblein
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Viola Oertel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main60528, Germany
| | - Anne Uhlmann
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Department of Child and Adolescent Psychiatry, Technische Universität Dresden, Dresden01187, Germany
| | - Fleur M. Howells
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
| | - Dan J. Stein
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town7935, South Africa
- SA MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town, Cape Town7505, South Africa
| | - Henk S. Temmingh
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town7935, South Africa
| | - Ana M. Diaz-Zuluaga
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Julian A. Pineda-Zapata
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Carlos López-Jaramillo
- Department of Psychiatry, Research Group in Psychiatry (GIPSI), Faculty of Medicine, Universidad de Antioquia, Medellín050010, Colombia
| | - Stephanie Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Experimental Psychopathology and Psychotherapy, Department of Psychology, University of Zurich, Zurich8050, Switzerland
| | - Ellen Ji
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Werner Surbeck
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
| | - Philipp Homan
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich (PUK), Zurich8008, Switzerland
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY11030
- Division of Psychiatry Research, Zucker Hillside Hospital, Northwell Health, New York, NY11004
- Department of Psychiatry, Zucker School of Medicine at Northwell/Hofstra, New York, NY11549
| | - Simon E. Fisher
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
| | - Barbara Franke
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
| | - David C. Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA02115
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT06102
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA19104
- Lifespan Brain Institute, University of Pennsylvania & Children's Hospital of Philadelphia, Philadelphia, PA19104
- Department of Radiology, Perelman School of Medicine, Philadelphia, PA19104
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA19104
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Center of Neurology and Psychiatry, National Institute of Mental Health, Tokyo187-8551, Japan
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Eileen Luders
- School of Psychology, University of Auckland, Auckland1010, New Zealand
- Department of Women’s and Children’s Health, Uppsala University, Uppsala752 37, Sweden
- Laboratory of Neuro Imaging, School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Sarah E. Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane4006, Australia
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA90033
| | - Jessica A. Turner
- Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA30303
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology and Emory University, Atlanta, GA30303
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA92697
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA92697
| | - Clyde Francks
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen6525 XD, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen6500 HB, The Netherlands
- Department of Human Genetics, Radboud University Medical Center, Nijmegen6525 GA, The Netherlands
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Lynch KM, Cabeen RP, Toga AW. Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.31.534636. [PMID: 37034810 PMCID: PMC10081273 DOI: 10.1101/2023.03.31.534636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Neocortical maturation is a dynamic process that proceeds in a hierarchical manner; however, the spatiotemporal organization of cortical microstructure with diffusion MRI has yet to be fully defined. This study characterized cortical microstructural maturation using diffusion MRI (fwe-DTI and NODDI multi-compartment modeling) in a cohort of 637 children and adolescents between 8 and 21 years of age. We found spatially heterogeneous developmental patterns broadly demarcated into functional domains where NODDI metrics increased and fwe-DTI metrics decreased with age. Using non-negative matrix factorization, we found cortical regions that correspond to lower-order sensory regions mature earlier than higher-order association regions. Our findings corroborate previous histological and neuroimaging studies that show spatially-varying patterns of cortical maturation that may reflect unique developmental processes of cytoarchitectonically-determined regional patterns of change.
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Affiliation(s)
- Kirsten M. Lynch
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
| | - Ryan P. Cabeen
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging (LONI), USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
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5
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Cabeen RP, Toga AW, Allman JM. Mapping frontoinsular cortex from diffusion microstructure. Cereb Cortex 2023; 33:2715-2733. [PMID: 35753692 PMCID: PMC10016069 DOI: 10.1093/cercor/bhac237] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/20/2022] [Accepted: 05/21/2022] [Indexed: 11/13/2022] Open
Abstract
We developed a novel method for mapping the location, surface area, thickness, and volume of frontoinsular cortex (FI) using structural and diffusion magnetic resonance imaging. FI lies in the ventral part of anterior insular cortex and is characterized by its distinctive population von Economo neurons (VENs). Functional neuroimaging studies have revealed its involvement in affective processing, and histopathology has implicated VEN loss in behavioral-variant frontotemporal dementia and chronic alcoholism; however, structural neuroimaging of FI has been relatively limited. We delineated FI by jointly modeling cortical surface geometry and its coincident diffusion microstructure parameters. We found that neurite orientation dispersion in cortical gray matter can be used to map FI in specific individuals, and the derived measures reflect a range of behavioral factors in young adults from the Human Connectome Project (N=1052). FI volume was larger in the left hemisphere than the right (31%), and the percentage volume of FI was larger in women than men (15.3%). FI volume was associated with measures of decision-making (delay discounting, substance abuse), emotion (negative intrusive thinking and perception of hostility), and social behavior (theory of mind and working memory for faces). The common denominator is that larger FI size is related to greater self-control and social awareness.
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Affiliation(s)
- Ryan P Cabeen
- Laboratory of Neuro Imaging, USC Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, United States
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90033, United States
| | - John M Allman
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States
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6
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Turi Z, Hananeia N, Shirinpour S, Opitz A, Jedlicka P, Vlachos A. Dosing Transcranial Magnetic Stimulation of the Primary Motor and Dorsolateral Prefrontal Cortices With Multi-Scale Modeling. Front Neurosci 2022; 16:929814. [PMID: 35898411 PMCID: PMC9309210 DOI: 10.3389/fnins.2022.929814] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 05/27/2022] [Indexed: 11/15/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) can depolarize cortical neurons through the intact skin and skull. The characteristics of the induced electric field (E-field) have a major impact on specific outcomes of TMS. Using multi-scale computational modeling, we explored whether the stimulation parameters derived from the primary motor cortex (M1) induce comparable macroscopic E-field strengths and subcellular/cellular responses in the dorsolateral prefrontal cortex (DLPFC). To this aim, we calculated the TMS-induced E-field in 16 anatomically realistic head models and simulated the changes in membrane voltage and intracellular calcium levels of morphologically and biophysically realistic human pyramidal cells in the M1 and DLPFC. We found that the conventional intensity selection methods (i.e., motor threshold and fixed intensities) produce variable macroscopic E-fields. Consequently, it was challenging to produce comparable subcellular/cellular responses across cortical regions with distinct folding characteristics. Prospectively, personalized stimulation intensity selection could standardize the E-fields and the subcellular/cellular responses to repetitive TMS across cortical regions and individuals. The suggested computational approach points to the shortcomings of the conventional intensity selection methods used in clinical settings. We propose that multi-scale modeling has the potential to overcome some of these limitations and broaden our understanding of the neuronal mechanisms for TMS.
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Affiliation(s)
- Zsolt Turi
- Department of Neuroanatomy, Faculty of Medicine, Institute of Anatomy and Cell Biology, University of Freiburg, Freiburg, Germany
| | - Nicholas Hananeia
- Faculty of Medicine, Interdisciplinary Centre for 3Rs in Animal Research, Justus-Liebig-University, Giessen, Germany
| | - Sina Shirinpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Peter Jedlicka
- Faculty of Medicine, Interdisciplinary Centre for 3Rs in Animal Research, Justus-Liebig-University, Giessen, Germany
| | - Andreas Vlachos
- Department of Neuroanatomy, Faculty of Medicine, Institute of Anatomy and Cell Biology, University of Freiburg, Freiburg, Germany
- Center BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
- Center for Basics in Neuromodulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- *Correspondence: Andreas Vlachos
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7
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Brain Functional Connectivity Asymmetry: Left Hemisphere Is More Modular. Symmetry (Basel) 2022. [DOI: 10.3390/sym14040833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Graph-theoretical approaches are increasingly used to study the brain and may enhance our understanding of its asymmetries. In this paper, we hypothesize that the structure of the left hemisphere is, on average, more modular. To this end, we analyzed resting-state functional magnetic resonance imaging data of 90 healthy subjects. We computed functional connectivity by Pearson’s correlation coefficient, turned the matrix into an unweighted graph by keeping a certain percentage of the strongest connections, and quantified modularity separately for the subgraph formed by each hemisphere. Our results show that the left hemisphere is more modular. The result is consistent across a range of binarization thresholds, regardless of whether the two hemispheres are thresholded together or separately. This illustrates that graph-theoretical analysis can provide a robust characterization of lateralization of brain functional connectivity.
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8
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Sha Z, van Rooij D, Anagnostou E, Arango C, Auzias G, Behrmann M, Bernhardt B, Bolte S, Busatto GF, Calderoni S, Calvo R, Daly E, Deruelle C, Duan M, Duran FLS, Durston S, Ecker C, Ehrlich S, Fair D, Fedor J, Fitzgerald J, Floris DL, Franke B, Freitag CM, Gallagher L, Glahn DC, Haar S, Hoekstra L, Jahanshad N, Jalbrzikowski M, Janssen J, King JA, Lazaro L, Luna B, McGrath J, Medland SE, Muratori F, Murphy DGM, Neufeld J, O'Hearn K, Oranje B, Parellada M, Pariente JC, Postema MC, Remnelius KL, Retico A, Rosa PGP, Rubia K, Shook D, Tammimies K, Taylor MJ, Tosetti M, Wallace GL, Zhou F, Thompson PM, Fisher SE, Buitelaar JK, Francks C. Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium. Mol Psychiatry 2022; 27:2114-2125. [PMID: 35136228 PMCID: PMC9126820 DOI: 10.1038/s41380-022-01452-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 12/23/2021] [Accepted: 01/14/2022] [Indexed: 12/30/2022]
Abstract
Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.
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Affiliation(s)
- Zhiqiang Sha
- Department of Language & Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
| | - Daan van Rooij
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and Department of Pediatrics, University of Toronto, Toronto, ON, Canada
| | - Celso Arango
- Child and Adolescent Psychiatry Department, Institute of Psychiatry and Mental Health, Gregorio Maran General University Hospital, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - Guillaume Auzias
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Universit, CNRS, Marseille, France
| | - Marlene Behrmann
- Department of Psychology and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Boris Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Sven Bolte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, Perth, WA, Australia
| | - Geraldo F Busatto
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Sara Calderoni
- IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Rosa Calvo
- Department of Child and Adolescent Psychiatry and Psychology Hospital Clinic, Psychiatry Unit, Department of Medicine, 2017SGR881, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience King's College London, London, UK
| | - Christine Deruelle
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Universit, CNRS, Marseille, France
| | - Meiyu Duan
- BioKnow Health Informatics Lab, College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Fabio Luis Souza Duran
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Sarah Durston
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
- The Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Stefan Ehrlich
- Department of Child and Adolescent Psychiatry & Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Damien Fair
- Institute of Child Development, Department of Pediatrics, Masonic Institute of the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Jennifer Fedor
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jacqueline Fitzgerald
- Department of Psychiatry, School of Medicine, Trinity College, Dublin, Ireland
- The Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Dorothea L Floris
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
| | - Louise Gallagher
- Department of Psychiatry, School of Medicine, Trinity College, Dublin, Ireland
- The Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, 02115-5724, USA
- Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Shlomi Haar
- Department of Brain Sciences, Imperial College London, London, UK
| | - Liesbeth Hoekstra
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Joost Janssen
- Child and Adolescent Psychiatry Department, Institute of Psychiatry and Mental Health, Gregorio Maran General University Hospital, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - Joseph A King
- Department of Child and Adolescent Psychiatry & Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Luisa Lazaro
- Department of Child and Adolescent Psychiatry and Psychology Hospital Clinic, Psychiatry Unit, Department of Medicine, 2017SGR881, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jane McGrath
- Department of Psychiatry, School of Medicine, Trinity College, Dublin, Ireland
- The Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Filippo Muratori
- IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Declan G M Murphy
- The Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Behavioural Genetics Clinic, Adult Autism Service, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation NHS Trust, London, UK
| | - Janina Neufeld
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Kirsten O'Hearn
- Department of Physiology and Pharmacology, Wake Forest Baptist Medical Center, Winston-Salem, NC, USA
| | - Bob Oranje
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mara Parellada
- Child and Adolescent Psychiatry Department, Institute of Psychiatry and Mental Health, Gregorio Maran General University Hospital, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - Jose C Pariente
- Magnetic Resonance Image Core Facility, IDIBAPS (Institut d'Investigacions Biomdiques August Pi i Sunyer), Barcelona, Spain
| | - Merel C Postema
- Department of Language & Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Karl Lundin Remnelius
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Alessandra Retico
- National Institute for Nuclear Physics, Pisa Division, Largo B. Pontecorvo 3, Pisa, Italy
| | - Pedro Gomes Penteado Rosa
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Katya Rubia
- Institute of Psychiatry, King's College London, London, UK
| | - Devon Shook
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kristiina Tammimies
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region, Stockholm, Sweden
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Womens and Childrens Health, Karolinska Institutet and Child and Adolescent Psychiatry, Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
| | - Margot J Taylor
- Diagnostic Imaging, The Hospital for Sick Children, and Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | | | - Gregory L Wallace
- Department of Speech, Language, and Hearing Sciences, The George Washington University, Washington, DC, USA
| | - Fengfeng Zhou
- BioKnow Health Informatics Lab, College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA
| | - Simon E Fisher
- Department of Language & Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Clyde Francks
- Department of Language & Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
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9
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Schlüter C, Fraenz C, Friedrich P, Güntürkün O, Genç E. Neurite density imaging in amygdala nuclei reveals interindividual differences in neuroticism. Hum Brain Mapp 2022; 43:2051-2063. [PMID: 35049113 PMCID: PMC8933246 DOI: 10.1002/hbm.25775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 12/23/2021] [Accepted: 12/30/2021] [Indexed: 11/23/2022] Open
Abstract
Neuroticism is known to have significant health implications. While previous research revealed that interindividual differences in the amygdala function are associated with interindividual differences in neuroticism, the impact of the amygdala’s structure and especially microstructure on variations in neuroticism remains unclear. Here, we present the first study using NODDI to examine the association between the in vivo microstructural architecture of the amygdala and neuroticism at the level of neurites. We, therefore, acquired brain images from 221 healthy participants using advanced multi‐shell diffusion‐weighted imaging. Because the amygdala comprises several nuclei, we, moreover, used a high‐resolution T1 image to automatically segment the amygdala into eight different nuclei. Neuroticism and its facets have been assessed using the NEO‐PI‐R. Finally, we associated neuroticism and its facets with the volume and microstructure of the amygdala nuclei. Statistical analysis revealed that lower neurite density in the lateral amygdala nucleus (La) was significantly associated with higher scores in depression, one of the six neuroticism facets. The La is the sensory relay of the amygdala, filtering incoming information based on previous experiences. Reduced neurite density and related changes in the dendritic structure of the La could impair its filtering function. This again might cause harmless sensory information to be misevaluated as threatening and lead to the altered amygdala responsivity as reported in previous studies investigating the functional correlates of neuroticism and neuroticism‐related disorders like depression.
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Affiliation(s)
- Caroline Schlüter
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Christoph Fraenz
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany.,Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany
| | - Patrick Friedrich
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Onur Güntürkün
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Erhan Genç
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany.,Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany
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10
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Ruthig P, Schönwiesner M. Common principles in the lateralisation of auditory cortex structure and function for vocal communication in primates and rodents. Eur J Neurosci 2022; 55:827-845. [PMID: 34984748 DOI: 10.1111/ejn.15590] [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: 06/25/2021] [Accepted: 12/24/2021] [Indexed: 11/27/2022]
Abstract
This review summarises recent findings on the lateralisation of communicative sound processing in the auditory cortex (AC) of humans, non-human primates, and rodents. Functional imaging in humans has demonstrated a left hemispheric preference for some acoustic features of speech, but it is unclear to which degree this is caused by bottom-up acoustic feature selectivity or top-down modulation from language areas. Although non-human primates show a less pronounced functional lateralisation in AC, the properties of AC fields and behavioral asymmetries are qualitatively similar. Rodent studies demonstrate microstructural circuits that might underlie bottom-up acoustic feature selectivity in both hemispheres. Functionally, the left AC in the mouse appears to be specifically tuned to communication calls, whereas the right AC may have a more 'generalist' role. Rodents also show anatomical AC lateralisation, such as differences in size and connectivity. Several of these functional and anatomical characteristics are also lateralized in human AC. Thus, complex vocal communication processing shares common features among rodents and primates. We argue that a synthesis of results from humans, non-human primates, and rodents is necessary to identify the neural circuitry of vocal communication processing. However, data from different species and methods are often difficult to compare. Recent advances may enable better integration of methods across species. Efforts to standardise data formats and analysis tools would benefit comparative research and enable synergies between psychological and biological research in the area of vocal communication processing.
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Affiliation(s)
- Philip Ruthig
- Faculty of Life Sciences, Leipzig University, Leipzig, Sachsen.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig
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11
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Mundorf A, Peterburs J, Ocklenburg S. Asymmetry in the Central Nervous System: A Clinical Neuroscience Perspective. Front Syst Neurosci 2021; 15:733898. [PMID: 34970125 PMCID: PMC8712556 DOI: 10.3389/fnsys.2021.733898] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 11/25/2021] [Indexed: 01/20/2023] Open
Abstract
Recent large-scale neuroimaging studies suggest that most parts of the human brain show structural differences between the left and the right hemisphere. Such structural hemispheric asymmetries have been reported for both cortical and subcortical structures. Interestingly, many neurodevelopmental and psychiatric disorders have been associated with altered functional hemispheric asymmetries. However, findings concerning the relation between structural hemispheric asymmetries and disorders have largely been inconsistent, both within specific disorders as well as between disorders. In the present review, we compare structural asymmetries from a clinical neuroscience perspective across different disorders. We focus especially on recent large-scale neuroimaging studies, to concentrate on replicable effects. With the notable exception of major depressive disorder, all reviewed disorders were associated with distinct patterns of alterations in structural hemispheric asymmetries. While autism spectrum disorder was associated with altered structural hemispheric asymmetries in a broader range of brain areas, most other disorders were linked to more specific alterations in brain areas related to cognitive functions that have been associated with the symptomology of these disorders. The implications of these findings are highlighted in the context of transdiagnostic approaches to psychopathology.
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Affiliation(s)
- Annakarina Mundorf
- Institute for Systems Medicine and Department of Human Medicine, MSH Medical School Hamburg, Hamburg, Germany
| | - Jutta Peterburs
- Institute for Systems Medicine and Department of Human Medicine, MSH Medical School Hamburg, Hamburg, Germany
| | - Sebastian Ocklenburg
- Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
- Department of Psychology, MSH Medical School Hamburg, Hamburg, Germany
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12
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Friedrich P, Patil KR, Mochalski LN, Li X, Camilleri JA, Kröll JP, Wiersch L, Eickhoff SB, Weis S. Is it left or is it right? A classification approach for investigating hemispheric differences in low and high dimensionality. Brain Struct Funct 2021; 227:425-440. [PMID: 34882263 PMCID: PMC8844166 DOI: 10.1007/s00429-021-02418-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 10/18/2021] [Indexed: 11/09/2022]
Abstract
Hemispheric asymmetries, i.e., differences between the two halves of the brain, have extensively been studied with respect to both structure and function. Commonly employed pairwise comparisons between left and right are suitable for finding differences between the hemispheres, but they come with several caveats when assessing multiple asymmetries. What is more, they are not designed for identifying the characterizing features of each hemisphere. Here, we present a novel data-driven framework—based on machine learning-based classification—for identifying the characterizing features that underlie hemispheric differences. Using voxel-based morphometry data from two different samples (n = 226, n = 216), we separated the hemispheres along the midline and used two different pipelines: First, for investigating global differences, we embedded the hemispheres into a two-dimensional space and applied a classifier to assess if the hemispheres are distinguishable in their low-dimensional representation. Second, to investigate which voxels show systematic hemispheric differences, we employed two classification approaches promoting feature selection in high dimensions. The two hemispheres were accurately classifiable in both their low-dimensional (accuracies: dataset 1 = 0.838; dataset 2 = 0.850) and high-dimensional (accuracies: dataset 1 = 0.966; dataset 2 = 0.959) representations. In low dimensions, classification of the right hemisphere showed higher precision (dataset 1 = 0.862; dataset 2 = 0.894) compared to the left hemisphere (dataset 1 = 0.818; dataset 2 = 0.816). A feature selection algorithm in the high-dimensional analysis identified voxels that most contribute to accurate classification. In addition, the map of contributing voxels showed a better overlap with moderate to highly lateralized voxels, whereas conventional t test with threshold-free cluster enhancement best resembled the LQ map at lower thresholds. Both the low- and high-dimensional classifiers were capable of identifying the hemispheres in subsamples of the datasets, such as males, females, right-handed, or non-right-handed participants. Our study indicates that hemisphere classification is capable of identifying the hemisphere in their low- and high-dimensional representation as well as delineating brain asymmetries. The concept of hemisphere classifiability thus allows a change in perspective, from asking what differs between the hemispheres towards focusing on the features needed to identify the left and right hemispheres. Taking this perspective on hemispheric differences may contribute to our understanding of what makes each hemisphere special.
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Affiliation(s)
- Patrick Friedrich
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Lisa N Mochalski
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Xuan Li
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Julia A Camilleri
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Jean-Philippe Kröll
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Lisa Wiersch
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Susanne Weis
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
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13
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Abstract
Asymmetries in the functional and structural organization of the nervous system are widespread in the animal kingdom and especially characterize the human brain. Although there is little doubt that asymmetries arise through genetic and nongenetic factors, an overarching model to explain the development of functional lateralization patterns is still lacking. Current genetic psychology collects data on genes relevant to brain lateralizations, while animal research provides information on the cellular mechanisms mediating the effects of not only genetic but also environmental factors. This review combines data from human and animal research (especially on birds) and outlines a multi-level model for asymmetry formation. The relative impact of genetic and nongenetic factors varies between different developmental phases and neuronal structures. The basic lateralized organization of a brain is already established through genetically controlled embryonic events. During ongoing development, hemispheric specialization increases for specific functions and subsystems interact to shape the final functional organization of a brain. In particular, these developmental steps are influenced by environmental experiences, which regulate the fine-tuning of neural networks via processes that are referred to as ontogenetic plasticity. The plastic potential of the nervous system could be decisive for the evolutionary success of lateralized brains.
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14
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Lubben N, Ensink E, Coetzee GA, Labrie V. The enigma and implications of brain hemispheric asymmetry in neurodegenerative diseases. Brain Commun 2021; 3:fcab211. [PMID: 34557668 PMCID: PMC8454206 DOI: 10.1093/braincomms/fcab211] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 07/16/2021] [Accepted: 08/10/2021] [Indexed: 01/15/2023] Open
Abstract
The lateralization of the human brain may provide clues into the pathogenesis and progression of neurodegenerative diseases. Though differing in their presentation and underlying pathologies, neurodegenerative diseases are all devastating and share an intriguing theme of asymmetrical pathology and clinical symptoms. Parkinson’s disease, with its distinctive onset of motor symptoms on one side of the body, stands out in this regard, but a review of the literature reveals asymmetries in several other neurodegenerative diseases. Here, we review the lateralization of the structure and function of the healthy human brain and the common genetic and epigenetic patterns contributing to the development of asymmetry in health and disease. We specifically examine the role of asymmetry in Parkinson’s disease, Alzheimer’s disease, amyotrophic lateral sclerosis, and multiple sclerosis, and interrogate whether these imbalances may reveal meaningful clues about the origins of these diseases. We also propose several hypotheses for how lateralization may contribute to the distinctive and enigmatic features of asymmetry in neurodegenerative diseases, suggesting a role for asymmetry in the choroid plexus, neurochemistry, protein distribution, brain connectivity and the vagus nerve. Finally, we suggest how future studies may reveal novel insights into these diseases through the lens of asymmetry.
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Affiliation(s)
- Noah Lubben
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Elizabeth Ensink
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Gerhard A Coetzee
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Viviane Labrie
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI 49503, USA
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15
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McKenna F, Babb J, Miles L, Goff D, Lazar M. Reduced Microstructural Lateralization in Males with Chronic Schizophrenia: A Diffusional Kurtosis Imaging Study. Cereb Cortex 2021; 30:2281-2294. [PMID: 31819950 DOI: 10.1093/cercor/bhz239] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Decreased brain lateralization is considered a trait marker of schizophrenia. Whereas reductions in both functional and macrostructural gray matter laterality in schizophrenia are well established, the investigation of gray matter microstructural lateralization has so far been limited to a small number of ex vivo studies, which limits the understanding of neurobiological substrates involved and development of adequate treatments. The aim of the current study was to assess in vivo gray matter microstructure lateralization patterns in schizophrenia by employing the diffusion kurtosis imaging (DKI)-derived mean kurtosis (MK) metric. MK was calculated for 18 right-handed males with chronic schizophrenia and 19 age-matched healthy control participants in 46 bilateral gray matter regions of interest (ROI). Microstructural laterality indexes (μLIs) were calculated for each subject and ROI, and group comparisons were conducted across regions. The relationship between μLI values and performance on the Wisconsin Card Sorting Test (WCST) was also evaluated. We found that compared with healthy controls, males with chronic schizophrenia had significantly decreased μLI across cortical and subcortical gray matter regions, which was correlated with poorer performance on the WCST. Our results suggest the ability of DKI-derived MK to capture gray matter microstructural lateralization pathology in vivo.
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Affiliation(s)
- Faye McKenna
- Department of Radiology, Center for Biomedical Imaging, New York, NY 10016, USA.,Sackler Institute of Graduate Biomedical Sciences New York University School of Medicine, New York, NY 10016, USA
| | - James Babb
- Department of Radiology, Center for Biomedical Imaging, New York, NY 10016, USA
| | - Laura Miles
- Department of Radiology, Center for Biomedical Imaging, New York, NY 10016, USA
| | - Donald Goff
- Department of Psychiatry, New York University School of Medicine, New York, NY 10016, USA
| | - Mariana Lazar
- Department of Radiology, Center for Biomedical Imaging, New York, NY 10016, USA.,Sackler Institute of Graduate Biomedical Sciences New York University School of Medicine, New York, NY 10016, USA
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16
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Broca's area and the search for anatomical asymmetry: commentary and perspectives. Brain Struct Funct 2021; 227:441-449. [PMID: 34390415 DOI: 10.1007/s00429-021-02357-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 07/28/2021] [Indexed: 10/20/2022]
Abstract
We present a brief commentary on the field's search for an anatomical asymmetry between Broca's area and its homologue in the non-dominant hemisphere, focusing on a selection of studies, including research from the last decade. We demonstrate that, several years after the influential review of Keller and colleagues from 2009, and despite recent advances in neuroimaging, the existence of a structural asymmetry of Broca's area is still controversial. This is especially the case for studies of the macroanatomy of this region. We point out the inconsistencies in methodology across studies that could account for the discrepancy in results. Investigations of the microstructure of Broca's area show a trend of a leftward asymmetry, but it is still unclear how these results relate to language dominance. We suggest that it may be necessary to combine multiple metrics in a systematic manner to find robust asymmetries and to expand the regional scope of structural investigations. Finally, based on the current state of the literature, we should not rule out the possibility that language dominance may simply not be reflected in local anatomical differences in the brain.
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17
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Gerrits R, Verhelst H, Dhollander T, Xiang L, Vingerhoets G. Structural perisylvian asymmetry in naturally occurring atypical language dominance. Brain Struct Funct 2021; 227:573-586. [PMID: 34173870 DOI: 10.1007/s00429-021-02323-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 06/14/2021] [Indexed: 01/15/2023]
Abstract
Functional and anatomical hemispheric asymmetries abound in the neural language system, yet the relationship between them remains elusive. One attractive proposal is that structural interhemispheric differences reflect or even drive functional language laterality. However, studies on structure-function couplings either find that left and right language dominant individuals display similar leftward structural asymmetry or yield inconsistent results. The current study aimed to replicate and extend prior work by comparing structural asymmetries between neurologically healthy left-handers with right hemispheric language dominance (N = 24) and typically lateralized left-handed controls (N = 39). Based on structural MRI data, anatomical measures of six 'language-related' perisylvian structures were derived, including the surface area of five gray matter regions with known language functions and the FDC (combined fiber density and fiber-bundle cross-sectional area) of the arcuate fasciculus. Only the surface area of the pars triangularis and the anterior insula differed significantly between participant groups, being on average leftward asymmetric in those with typical dominance, but right lateralized in volunteers with atypical language specialization. However, these findings did not survive multiple testing correction and the asymmetry of these structures demonstrated much inter-individual variability in either subgroup. By integrating our findings with those reported previously we conclude that while some perisylvian anatomical asymmetries may differ subtly between typical and atypical speech dominants at the group level, they serve as poor participant-specific predictors of hemispheric language specialization.
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Affiliation(s)
- Robin Gerrits
- Department of Experimental Psychology, Ghent University, Ghent, Belgium.
| | - Helena Verhelst
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Li Xiang
- Centre for Reproductive Health, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Guy Vingerhoets
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
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18
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Lucignani M, Breschi L, Espagnet MCR, Longo D, Talamanca LF, Placidi E, Napolitano A. Reliability on multiband diffusion NODDI models: A test retest study on children and adults. Neuroimage 2021; 238:118234. [PMID: 34091031 DOI: 10.1016/j.neuroimage.2021.118234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 05/07/2021] [Accepted: 06/01/2021] [Indexed: 02/05/2023] Open
Abstract
Neurite Orientation Dispersion and Density Imaging (NODDI) and Bingham-NODDI diffusion MRI models are nowadays very well-known models in the field of diffusion MRI as they represent powerful tools for the estimation of brain microstructure. In order to efficiently translate NODDI imaging findings into the diagnostic clinical practice, a test-retest approach would be useful to assess reproducibility and reliability of NODDI biomarkers, thus providing validation on precision of different fitting toolboxes. In this context, we conducted a test-retest study with the aim to assess the effects of different factors (i.e. fitting algorithms, multiband acceleration, shell configuration, age of subject and hemispheric side) on diffusion models reliability, assessed in terms of Intra-class Correlation Coefficient (ICC) and Variation Factor (VF). To this purpose, data from pediatric and adult subjects were acquired with Simultaneous-MultiSlice (SMS) imaging method with two different acceleration factor (AF) and four b-values, subsequently combined in seven shell configurations. Data were then fitted with two different GPU-based algorithms to speed up the analysis. Results show that each factor investigated had a significant effect on reliability of several diffusion parameters. Particularly, both datasets reveal very good ICC values for higher AF, suggesting that faster acquisitions do not jeopardize the reliability and are useful to decrease motion artifacts. Although very small reliability differences appear when comparing shell configurations, more extensive diffusion parameters variability results when considering shell configuration with lower b-values, especially for simple model like NODDI. Also fitting tools have a significant effect on reliability, but their difference occurs in both datasets and AF, so it appears to be independent from either misalignment and motion artifacts, or noise and SNR. The main achievement of the present study is to show how 10 min multi-shell diffusion MRI acquisition for NODDI acquisition can have reliable results in WM. More complex models do not appear to be more prone to less data acquisition as well as noisier data thus stressing the idea of Bingham-NODDI having greater sensitivity to true subject variability.
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Affiliation(s)
- Martina Lucignani
- Medical Physics Department, Bambino Gesù Children's Hospital IRCCS, Rome, Italy
| | - Laura Breschi
- Medical Physics Department, Bambino Gesù Children's Hospital IRCCS, Rome, Italy
| | - Maria Camilla Rossi Espagnet
- Neuroradiology Unit, Bambino Gesù Children's Hospital IRCCS, Rome, Italy; Nesmos Department, Sapienza University, Rome, Italy
| | - Daniela Longo
- Neuroradiology Unit, Bambino Gesù Children's Hospital IRCCS, Rome, Italy
| | | | - Elisa Placidi
- Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Medical Physics UOC, Rome, Italy
| | - Antonio Napolitano
- Medical Physics Department, Bambino Gesù Children's Hospital IRCCS, Rome, Italy.
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19
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Little G, Beaulieu C. Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy. Neuroimage 2021; 237:118105. [PMID: 33933593 DOI: 10.1016/j.neuroimage.2021.118105] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 04/14/2021] [Accepted: 04/16/2021] [Indexed: 10/21/2022] Open
Abstract
To extract Diffusion Tensor Imaging (DTI) parameters from the human cortex, the inner and outer boundaries of the cortex are usually defined on 3D-T1-weighted images and then applied to the co-registered DTI. However, this analysis requires the acquisition of an additional high-resolution structural image that may not be practical in various imaging studies. Here an automatic cortical boundary segmentation method was developed to work directly only on the native DTI images by using fractional anisotropy (FA) maps and mean diffusion weighted images (DWI), the latter with acceptable gray-white matter image contrast. This new method was compared to the conventional cortical segmentations generated from high-resolution T1 structural images in 5 participants. In addition, the proposed method was applied to 15 healthy young adults (10 cross-sectional, 5 test-retest) to measure FA, MD, and radiality of the primary eigenvector across the cortex on whole-brain 1.5 mm isotropic images acquired in 3.5 min at 3T. The proposed method generated reasonable segmentations of the cortical boundaries for all individuals and large proportions of the proposed method segmentations (more than 85%) were within ±1 mm from those generated with the conventional approach on higher resolution T1 structural images. Both FA (~0.15) and MD (~0.77 × 10-3 mm2/s) extracted halfway between the cortical boundaries were relatively stable across the cortex, although focal regions such as the posterior bank of the central sulcus, anterior insula, and medial temporal lobe showed higher FA. The primary eigenvectors were primarily oriented radially to the middle cortical surface, but there were tangential orientations in the sulcal fundi as well as in the posterior bank of the central sulcus. The proposed method demonstrates the feasibility and accuracy of cortical analysis in native DTI space while avoiding the acquisition of other imaging contrasts like 3D T1-weighted scans.
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Affiliation(s)
- Graham Little
- Department of Biomedical Engineering, University of Alberta, 1098 Research Transition Facility, 8308-114 Street, Edmonton, Alberta T6G 2V2, Canada.
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, 1098 Research Transition Facility, 8308-114 Street, Edmonton, Alberta T6G 2V2, Canada.
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20
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Cabeen RP, Toga AW, Allman JM. Frontoinsular cortical microstructure is linked to life satisfaction in young adulthood. Brain Imaging Behav 2021; 15:2775-2789. [PMID: 33825124 DOI: 10.1007/s11682-021-00467-y] [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] [Accepted: 03/01/2021] [Indexed: 10/21/2022]
Abstract
Life satisfaction is a component of subjective well-being that reflects a global judgement of the quality of life according to an individual's own needs and expectations. As a psychological construct, it has attracted attention due to its relationship to mental health, resilience to stress, and other factors. Neuroimaging studies have identified neurobiological correlates of life satisfaction; however, they are limited to functional connectivity and gray matter morphometry. We explored features of gray matter microstructure obtained through compartmental modeling of multi-shell diffusion MRI data, and we examined cortical microstructure in frontoinsular cortex in a cohort of 807 typical young adults scanned as part of the Human Connectome Project. Our experiments identified the orientation dispersion index (ODI), and analogously fractional anisotropy (FA), of frontoinsular cortex as a robust set of anatomically-specific lateralized diffusion MRI microstructure features that are linked to life satisfaction, independent of other demographic, socioeconomic, and behavioral factors. We further validated our findings in a secondary test-retest dataset and found high reliability of our imaging metrics and reproducibility of outcomes. In our analysis of twin and non-twin siblings, we found basic microstructure in frontoinsular cortex to be strongly genetically determined. We also found a more moderate but still very significant genetic role in determining microstructure as it relates to life satisfaction in frontoinsular cortex. Our findings suggest a potential linkage between well-being and microscopic features of frontoinsular cortex, which may reflect cellular morphology and architecture and may more broadly implicate the integrity of the homeostatic processing performed by frontoinsular cortex as an important component of an individual's judgements of life satisfaction.
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Affiliation(s)
- Ryan P Cabeen
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - John M Allman
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
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21
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Bisiacchi P, Cainelli E. Structural and functional brain asymmetries in the early phases of life: a scoping review. Brain Struct Funct 2021; 227:479-496. [PMID: 33738578 PMCID: PMC8843922 DOI: 10.1007/s00429-021-02256-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Accepted: 03/07/2021] [Indexed: 12/13/2022]
Abstract
Asymmetry characterizes the brain in both structure and function. Anatomical asymmetries explain only a fraction of functional variability in lateralization, with structural and functional asymmetries developing at different periods of life and in different ways. In this work, we perform a scoping review of the cerebral asymmetries in the first brain development phases. We included all English-written studies providing direct evidence of hemispheric asymmetries in full-term neonates, foetuses, and premature infants, both at term post-conception and before. The final analysis included 57 studies. The reviewed literature shows large variability in the used techniques and methodological procedures. Most structural studies investigated the temporal lobe, showing a temporal planum more pronounced on the left than on the right (although not all data agree), a morphological asymmetry already present from the 29th week of gestation. Other brain structures have been poorly investigated, and the results are even more discordant. Unlike data on structural asymmetries, functional data agree with each other, identifying a leftward dominance for speech stimuli and an overall dominance of the right hemisphere in all other functional conditions. This generalized dominance of the right hemisphere for all conditions (except linguistic stimuli) is in line with theories stating that the right hemisphere develops earlier and that its development is less subject to external influences because it sustains functions necessary to survive.
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Affiliation(s)
- Patrizia Bisiacchi
- Department of General Psychology, University of Padova, Via Venezia, 8, 35121, Padova, Italy. .,Padova Neuroscience Centre, PNC, Padova, Italy.
| | - Elisa Cainelli
- Department of General Psychology, University of Padova, Via Venezia, 8, 35121, Padova, Italy
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22
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Seethaler M, Lauseker M, Ernst K, Rémi J, Vollmar C, Noachtar S, Kaufmann E. Hemispheric differences in the duration of focal onset seizures. Acta Neurol Scand 2021; 143:248-255. [PMID: 33011970 DOI: 10.1111/ane.13356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 09/15/2020] [Accepted: 09/27/2020] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To assess hemispheric differences in the duration of focal onset seizures and its association with clinical and demographic factors. METHODS A retrospective analysis was performed on adult patients with drug-resistant unifocal epilepsy, who underwent intracranial EEG recording between 01/2006 and 06/2016. Seizure duration was determined based on the subdural and/or stereo-EEG (sEEG) recordings. Hemispheric differences in seizure duration were statistically evaluated with regard to clinical and demographic data. RESULTS In total, 69 patients and 654 focal onset seizures were included. The duration of seizures with left-hemispheric onset (n = 297) was by trend longer (91.88 ± 93.92 s) than of right-hemispheric seizures (n = 357; 71.03 ± 68.53 s; p = .193). Significant hemispheric differences in seizures duration were found in temporal lobe seizures (n = 225; p = .013), especially those with automotor manifestation (n = 156; p = .045). A prolonged duration was also found for left-hemispheric onset seizures with secondary generalized commencing during waking state (n = 225; p = .034), but not during sleep. A similar hemispheric difference in seizure duration was found in female patients (p = .040), but not in men. CONCLUSIONS Hemispheric differences in seizure duration were revealed with significantly longer durations in case of left-hemispheric seizure onset. The observed differences in seizure duration might result from brain asymmetry and add new aspects to the understanding of seizure propagation and termination.
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Affiliation(s)
- Magdalena Seethaler
- Epilepsy Center, Department of Neurology University Hospital, LMU Munich Munich Germany
- Department of Psychiatry and Psychotherapy Charité University Medicine and St. Hedwig Hospital Berlin Germany
| | - Michael Lauseker
- Institute for Medical Information Processing, Biometry, and Epidemiology LMU Munich Munich Germany
| | - Katharina Ernst
- Epilepsy Center, Department of Neurology University Hospital, LMU Munich Munich Germany
| | - Jan Rémi
- Epilepsy Center, Department of Neurology University Hospital, LMU Munich Munich Germany
| | - Christian Vollmar
- Epilepsy Center, Department of Neurology University Hospital, LMU Munich Munich Germany
| | - Soheyl Noachtar
- Epilepsy Center, Department of Neurology University Hospital, LMU Munich Munich Germany
| | - Elisabeth Kaufmann
- Epilepsy Center, Department of Neurology University Hospital, LMU Munich Munich Germany
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23
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MORC1 methylation and BDI are associated with microstructural features of the hippocampus and medial prefrontal cortex. J Affect Disord 2021; 282:91-97. [PMID: 33401128 DOI: 10.1016/j.jad.2020.12.056] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 12/14/2020] [Accepted: 12/17/2020] [Indexed: 01/16/2023]
Abstract
BACKGROUND Alterations in the hippocampus and prefrontal cortex (PFC) have frequently been reported in depressed patients. These parameters might prove to be a consistent finding in depression. In addition, peripheral DNA methylation of the MORC1 gene promoter showed stable associations with depression across independent samples. However, the question arises whether MORC1, supposedly acting as transcription factor, might also be involved in neurobiological alterations accompanying depression. This study further analyses the role of MORC1 in depression by investigating a potential correlation between peripheral MORC1 DNA methylation and neuronal structural properties previously associated with depression in humans. METHODS Beck Depression Inventory (BDI) was assessed in 52 healthy participants. DNA was extracted from buccal cells and MORC1 methylation correlated with micro- and macrostructural properties derived from magnetic resonance imaging (MRI) and neurite orientation dispersion and density imaging (NODDI) in the hippocampus and medial prefrontal cortex (mPFC). RESULTS MORC1 methylation was associated with volume reduction and neurite orientation dispersion and density markers in the hippocampus and mPFC. BDI was positively associated with neurite orientation dispersion and density markers in the hippocampus. LIMITATIONS The study was conducted in a small sample of healthy participants with subclinical depressive symptoms. Peripheral tissue was analyzed. CONCLUSION We found significant negative associations between peripheral MORC1 methylation and macro- and microstructural markers in the hippocampus and mPFC. Thus, MORC1 might be involved in neurobiological properties. Studies investigating neuronal methylation patterns of MORC1 are needed to support this hypothesis.
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24
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Guadalupe T, Kong XZ, Akkermans SEA, Fisher SE, Francks C. Relations between hemispheric asymmetries of grey matter and auditory processing of spoken syllables in 281 healthy adults. Brain Struct Funct 2021; 227:561-572. [PMID: 33502621 PMCID: PMC8844177 DOI: 10.1007/s00429-021-02220-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 01/14/2021] [Indexed: 11/29/2022]
Abstract
Most people have a right-ear advantage for the perception of spoken syllables, consistent with left hemisphere dominance for speech processing. However, there is considerable variation, with some people showing left-ear advantage. The extent to which this variation is reflected in brain structure remains unclear. We tested for relations between hemispheric asymmetries of auditory processing and of grey matter in 281 adults, using dichotic listening and voxel-based morphometry. This was the largest study of this issue to date. Per-voxel asymmetry indexes were derived for each participant following registration of brain magnetic resonance images to a template that was symmetrized. The asymmetry index derived from dichotic listening was related to grey matter asymmetry in clusters of voxels corresponding to the amygdala and cerebellum lobule VI. There was also a smaller, non-significant cluster in the posterior superior temporal gyrus, a region of auditory cortex. These findings contribute to the mapping of asymmetrical structure–function links in the human brain and suggest that subcortical structures should be investigated in relation to hemispheric dominance for speech processing, in addition to auditory cortex.
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Affiliation(s)
- Tulio Guadalupe
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Wundtlaan 1, Nijmegen, The Netherlands
| | - Xiang-Zhen Kong
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Wundtlaan 1, Nijmegen, The Netherlands.,Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
| | - Sophie E A Akkermans
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.,Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Wundtlaan 1, Nijmegen, The Netherlands.,Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Wundtlaan 1, Nijmegen, The Netherlands. .,Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
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25
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Rollins CPE, Garrison JR, Arribas M, Seyedsalehi A, Li Z, Chan RCK, Yang J, Wang D, Liò P, Yan C, Yi ZH, Cachia A, Upthegrove R, Deakin B, Simons JS, Murray GK, Suckling J. Evidence in cortical folding patterns for prenatal predispositions to hallucinations in schizophrenia. Transl Psychiatry 2020; 10:387. [PMID: 33159044 PMCID: PMC7648757 DOI: 10.1038/s41398-020-01075-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 09/30/2020] [Accepted: 10/22/2020] [Indexed: 12/26/2022] Open
Abstract
All perception is a construction of the brain from sensory input. Our first perceptions begin during gestation, making fetal brain development fundamental to how we experience a diverse world. Hallucinations are percepts without origin in physical reality that occur in health and disease. Despite longstanding research on the brain structures supporting hallucinations and on perinatal contributions to the pathophysiology of schizophrenia, what links these two distinct lines of research remains unclear. Sulcal patterns derived from structural magnetic resonance (MR) images can provide a proxy in adulthood for early brain development. We studied two independent datasets of patients with schizophrenia who underwent clinical assessment and 3T MR imaging from the United Kingdom and Shanghai, China (n = 181 combined) and 63 healthy controls from Shanghai. Participants were stratified into those with (n = 79 UK; n = 22 Shanghai) and without (n = 43 UK; n = 37 Shanghai) hallucinations from the PANSS P3 scores for hallucinatory behaviour. We quantified the length, depth, and asymmetry indices of the paracingulate and superior temporal sulci (PCS, STS), which have previously been associated with hallucinations in schizophrenia, and constructed cortical folding covariance matrices organized by large-scale functional networks. In both ethnic groups, we demonstrated a significantly shorter left PCS in patients with hallucinations compared to those without, and to healthy controls. Reduced PCS length and STS depth corresponded to focal deviations in their geometry and to significantly increased covariance within and between areas of the salience and auditory networks. The discovery of neurodevelopmental alterations contributing to hallucinations establishes testable models for these enigmatic, sometimes highly distressing, perceptions and provides mechanistic insight into the pathological consequences of prenatal origins.
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Affiliation(s)
- Colleen P. E. Rollins
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Jane R. Garrison
- grid.5335.00000000121885934Department of Psychology, University of Cambridge, Cambridge, UK
| | - Maite Arribas
- grid.5335.00000000121885934Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK ,grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
| | - Aida Seyedsalehi
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK ,grid.450563.10000 0004 0412 9303Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Zhi Li
- grid.9227.e0000000119573309Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Raymond C. K. Chan
- grid.9227.e0000000119573309Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Junwei Yang
- grid.5335.00000000121885934Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
| | - Duo Wang
- grid.5335.00000000121885934Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
| | - Pietro Liò
- grid.5335.00000000121885934Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
| | - Chao Yan
- grid.22069.3f0000 0004 0369 6365Key Laboratory of Brain Functional Genomics (MOE & STCSM), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Zheng-hui Yi
- grid.16821.3c0000 0004 0368 8293Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Arnaud Cachia
- Université de Paris, LaPsyDÉ, CNRS, F-75005 Paris, France ,Université de Paris, IPNP, INSERM, F-75005 Paris, France
| | - Rachel Upthegrove
- grid.6572.60000 0004 1936 7486Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - Bill Deakin
- grid.5379.80000000121662407Neuroscience and Psychiatry Unit, The University of Manchester, Manchester, UK
| | - Jon S. Simons
- grid.5335.00000000121885934Department of Psychology, University of Cambridge, Cambridge, UK
| | - Graham K. Murray
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Cambridge, UK ,grid.450563.10000 0004 0412 9303Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - John Suckling
- grid.5335.00000000121885934Department of Psychiatry, University of Cambridge, Cambridge, UK
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26
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Unmasking the relevance of hemispheric asymmetries—Break on through (to the other side). Prog Neurobiol 2020; 192:101823. [DOI: 10.1016/j.pneurobio.2020.101823] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Revised: 04/17/2020] [Accepted: 05/13/2020] [Indexed: 12/21/2022]
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27
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Ocklenburg S, Berretz G, Packheiser J, Friedrich P. Laterality 2020: entering the next decade. Laterality 2020; 26:265-297. [DOI: 10.1080/1357650x.2020.1804396] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Sebastian Ocklenburg
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr-University Bochum, Bochum, Germany
| | - Gesa Berretz
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr-University Bochum, Bochum, Germany
| | - Julian Packheiser
- Institute of Cognitive Neuroscience, Biopsychology, Department of Psychology, Ruhr-University Bochum, Bochum, Germany
| | - Patrick Friedrich
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
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28
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Friedrich P, Fraenz C, Schlüter C, Ocklenburg S, Mädler B, Güntürkün O, Genç E. The Relationship Between Axon Density, Myelination, and Fractional Anisotropy in the Human Corpus Callosum. Cereb Cortex 2020; 30:2042-2056. [DOI: 10.1093/cercor/bhz221] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2019] [Revised: 07/26/2019] [Accepted: 08/21/2019] [Indexed: 02/06/2023] Open
Abstract
Abstract
The corpus callosum serves the functional integration and interaction between the two hemispheres. Many studies investigate callosal microstructure via diffusion tensor imaging (DTI) fractional anisotropy (FA) in geometrically parcellated segments. However, FA is influenced by several different microstructural properties such as myelination and axon density, hindering a neurobiological interpretation. This study explores the relationship between FA and more specific measures of microstructure within the corpus callosum in a sample of 271 healthy participants. DTI tractography was used to assess 11 callosal segments and gain estimates of FA. We quantified axon density and myelination via neurite orientation dispersion and density imaging (NODDI) to assess intra-neurite volume fraction and a multiecho gradient spin-echo sequence estimating myelin water fraction. The results indicate three common factors in the distribution of FA, myelin content and axon density, indicating potentially shared rules of topographical distribution. Moreover, the relationship between measures varied across the corpus callosum, suggesting that FA should not be interpreted uniformly. More specific magnetic resonance imaging-based quantification techniques, such as NODDI and multiecho myelin water imaging, may thus play a key role in future studies of clinical trials and individual differences.
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Affiliation(s)
- Patrick Friedrich
- Department of Psychology, Institute of Cognitive Neuroscience, Biopsychology, Ruhr University Bochum, 44801 Bochum, Germany
- Brain Connectivity and Behaviour Laboratory (BCBLab), Sorbonne Universities, 75013 Paris, France
| | - Christoph Fraenz
- Department of Psychology, Institute of Cognitive Neuroscience, Biopsychology, Ruhr University Bochum, 44801 Bochum, Germany
| | - Caroline Schlüter
- Department of Psychology, Institute of Cognitive Neuroscience, Biopsychology, Ruhr University Bochum, 44801 Bochum, Germany
| | - Sebastian Ocklenburg
- Department of Psychology, Institute of Cognitive Neuroscience, Biopsychology, Ruhr University Bochum, 44801 Bochum, Germany
| | - Burkhard Mädler
- Health Systems Department, Philips GmBH, 22335 Hamburg, Germany
| | - Onur Güntürkün
- Department of Psychology, Institute of Cognitive Neuroscience, Biopsychology, Ruhr University Bochum, 44801 Bochum, Germany
| | - Erhan Genç
- Department of Psychology, Institute of Cognitive Neuroscience, Biopsychology, Ruhr University Bochum, 44801 Bochum, Germany
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29
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Schmitz J, Fraenz C, Schlüter C, Friedrich P, Kumsta R, Moser D, Güntürkün O, Genç E, Ocklenburg S. Schizotypy and altered hemispheric asymmetries: The role of cilia genes. Psychiatry Res Neuroimaging 2019; 294:110991. [PMID: 31683112 DOI: 10.1016/j.pscychresns.2019.110991] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 10/22/2019] [Accepted: 10/23/2019] [Indexed: 12/27/2022]
Abstract
Schizophrenia patients have a higher probability of altered structural and functional differences between the left and right hemisphere. Schizotypy as its nonclinical manifestation has been related to a higher incidence of non-right-handedness and atypical right-hemispheric language dominance. It has been suggested that genes involved in cilia function might link brain asymmetry and neurodevelopmental disorders. We assessed DNA methylation in the promoter regions of seven candidate genes involved in cilia function and psychiatric disorders from buccal cells and investigated their association with schizotypy and language lateralization in 60 healthy adults. Moreover, we determined microstructural properties of the planum temporale in a subsample of 52 subjects using neurite orientation dispersion and density imaging (NODDI). We found a significant association between schizotypy and DNA methylation in the AHI1 promoter region. Moreover, AHI1 DNA methylation significantly predicted language lateralization and asymmetry in estimated planum temporale neurite density. Finally, stronger leftward asymmetry in estimated neurite density was associated with a more pronounced right ear advantage (left hemisphere dominance) in the forced-right condition of the dichotic listening task, measuring attentional modulation of language lateralization. Our results are in line with a shared molecular basis of schizotypy and functional hemispheric asymmetries that is based on cilia function.
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Affiliation(s)
- Judith Schmitz
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University, Bochum, Germany.
| | - Christoph Fraenz
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University, Bochum, Germany
| | - Caroline Schlüter
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University, Bochum, Germany
| | - Patrick Friedrich
- Brain Connectivity and Behaviour Laboratory (BCBLab), Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle (GIN), Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Robert Kumsta
- Genetic Psychology, Department of Psychology, Ruhr University, Bochum, Germany
| | - Dirk Moser
- Genetic Psychology, Department of Psychology, Ruhr University, Bochum, Germany
| | - Onur Güntürkün
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University, Bochum, Germany
| | - Erhan Genç
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University, Bochum, Germany
| | - Sebastian Ocklenburg
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University, Bochum, Germany
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30
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Genç E, Fraenz C, Schlüter C, Friedrich P, Voelkle MC, Hossiep R, Güntürkün O. The Neural Architecture of General Knowledge. EUROPEAN JOURNAL OF PERSONALITY 2019. [DOI: 10.1002/per.2217] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Cognitive performance varies widely between individuals and is highly influenced by structural and functional properties of the brain. In the past, neuroscientific research was principally concerned with fluid intelligence, while neglecting its equally important counterpart crystallized intelligence. Crystallized intelligence is defined as the depth and breadth of knowledge and skills that are valued by one's culture. The accumulation of crystallized intelligence is guided by information storage capacities and is likely to be reflected in an individual's level of general knowledge. In spite of the significant role general knowledge plays for everyday life, its neural foundation largely remains unknown. In a large sample of 324 healthy individuals, we used standard magnetic resonance imaging along with functional magnetic resonance imaging and diffusion tensor imaging to examine different estimates of brain volume and brain network connectivity and assessed their predictive power with regard to both general knowledge and fluid intelligence. Our results demonstrate that an individual's level of general knowledge is associated with structural brain network connectivity beyond any confounding effects exerted by age or sex. Moreover, we found fluid intelligence to be best predicted by cortex volume in male subjects and functional network connectivity in female subjects. Combined, these findings potentially indicate different neural architectures for information storage and information processing. © 2019 European Association of Personality Psychology
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Affiliation(s)
- Erhan Genç
- Department of Psychology, Biopsychology, Ruhr University Bochum, Bochum, Germany
| | - Christoph Fraenz
- Department of Psychology, Biopsychology, Ruhr University Bochum, Bochum, Germany
| | - Caroline Schlüter
- Department of Psychology, Biopsychology, Ruhr University Bochum, Bochum, Germany
| | - Patrick Friedrich
- Department of Psychology, Biopsychology, Ruhr University Bochum, Bochum, Germany
| | - Manuel C. Voelkle
- Department of Psychology, Psychological Research Methods, Humboldt University Berlin, Berlin, Germany
| | - Rüdiger Hossiep
- Department of Psychology, Team Test Development, Ruhr University Bochum, Bochum, Germany
| | - Onur Güntürkün
- Department of Psychology, Biopsychology, Ruhr University Bochum, Bochum, Germany
- Stellenbosch Institute for Advanced Study (STIAS), Wallenberg Research Centre at Stellenbosch University, Stellenbosch, South Africa
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