1
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Ekerdt C, Menks WM, Fernández G, McQueen JM, Takashima A, Janzen G. White matter connectivity linked to novel word learning in children. Brain Struct Funct 2024:10.1007/s00429-024-02857-6. [PMID: 39325144 DOI: 10.1007/s00429-024-02857-6] [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: 02/20/2024] [Accepted: 09/03/2024] [Indexed: 09/27/2024]
Abstract
Children and adults are excellent word learners. Increasing evidence suggests that the neural mechanisms that allow us to learn words change with age. In a recent fMRI study from our group, several brain regions exhibited age-related differences when accessing newly learned words in a second language (L2; Takashima et al. Dev Cogn Neurosci 37, 2019). Namely, while the Teen group (aged 14-16 years) activated more left frontal and parietal regions, the Young group (aged 8-10 years) activated right frontal and parietal regions. In the current study we analyzed the structural connectivity data from the aforementioned study, examining the white matter connectivity of the regions that showed age-related functional activation differences. Age group differences in streamline density as well as correlations with L2 word learning success and their interaction were examined. The Teen group showed stronger connectivity than the Young group in the right arcuate fasciculus (AF). Furthermore, white matter connectivity and memory for L2 words across the two age groups correlated in the left AF and the right anterior thalamic radiation (ATR) such that higher connectivity in the left AF and lower connectivity in the right ATR was related to better memory for L2 words. Additionally, connectivity in the area of the right AF that exhibited age-related differences predicted word learning success. The finding that across the two age groups, stronger connectivity is related to better memory for words lends further support to the hypothesis that the prolonged maturation of the prefrontal cortex, here in the form of structural connectivity, plays an important role in the development of memory.
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Affiliation(s)
- Clara Ekerdt
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands.
| | - Willeke M Menks
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
- Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Guillén Fernández
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
| | - James M McQueen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
- Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - Atsuko Takashima
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Gabriele Janzen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University and Radboud University Medical Centre, Nijmegen, the Netherlands
- Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands
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2
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Serrarens C, Ruiz-Fernandez J, Otter M, Campforts BCM, Stumpel CTRM, Linden DEJ, van Amelsvoort TAMJ, Kashyap S, Vingerhoets C. Intracortical myelin across laminae in adult individuals with 47,XXX: a 7 Tesla MRI study. Cereb Cortex 2024; 34:bhae343. [PMID: 39183364 PMCID: PMC11345119 DOI: 10.1093/cercor/bhae343] [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: 04/12/2024] [Revised: 07/31/2024] [Accepted: 08/12/2024] [Indexed: 08/27/2024] Open
Abstract
47,XXX (Triple X syndrome) is a sex chromosome aneuploidy characterized by the presence of a supernumerary X chromosome in affected females and is associated with a variable cognitive, behavioral, and psychiatric phenotype. The effect of a supernumerary X chromosome in affected females on intracortical microstructure is currently unknown. Therefore, we conducted 7 Tesla structural MRI and compared T1 (ms), as a proxy for intracortical myelin (ICM), across laminae of 21 adult women with 47,XXX and 22 age-matched typically developing females using laminar analyses. Relationships between phenotypic traits and T1 values in 47,XXX were also investigated. Adults with 47,XXX showed higher bilateral T1 across supragranular laminae in the banks of the superior temporal sulcus, and in the right inferior temporal gyrus, suggesting decreases of ICM primarily within the temporal cortex in 47,XXX. Higher social functioning in 47,XXX was related to larger inferior temporal gyrus ICM content. Our findings indicate an effect of a supernumerary X chromosome in adult-aged women on ICM across supragranular laminae within the temporal cortex. These findings provide insight into the role of X chromosome dosage on ICM across laminae. Future research is warranted to further explore the functional significance of altered ICM across laminae in 47,XXX.
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Affiliation(s)
- Chaira Serrarens
- Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Institute (MHeNS), Maastricht University, Maastricht, 6200 MD, The Netherlands
| | - Julia Ruiz-Fernandez
- Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Institute (MHeNS), Maastricht University, Maastricht, 6200 MD, The Netherlands
- INSERM U1299, Centre Borelli UMR 9010, ENS-Paris-Saclay, Université Paris Saclay, Paris, France
| | - Maarten Otter
- Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Institute (MHeNS), Maastricht University, Maastricht, 6200 MD, The Netherlands
- Medical Department, SIZA, Arnhem, 6800 AM, The Netherlands
| | - Bea C M Campforts
- Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Institute (MHeNS), Maastricht University, Maastricht, 6200 MD, The Netherlands
| | - Constance T R M Stumpel
- Department of Clinical Genetics and School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, 6229 ER, The Netherlands
| | - David E J Linden
- Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Institute (MHeNS), Maastricht University, Maastricht, 6200 MD, The Netherlands
| | - Therese A M J van Amelsvoort
- Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Institute (MHeNS), Maastricht University, Maastricht, 6200 MD, The Netherlands
| | - Sriranga Kashyap
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, 6229 EV, The Netherlands
- Krembil Brain Institute, University Health Network, Toronto, ON M5T 2S8, Canada
| | - Claudia Vingerhoets
- Department of Psychiatry and Neuropsychology, Mental Health and Neuroscience Institute (MHeNS), Maastricht University, Maastricht, 6200 MD, The Netherlands
- ‘s Heeren Loo Zorggroep, Amersfoort, 3818 LA, The Netherlands
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3
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Bahar N, Cler GJ, Krishnan S, Asaridou SS, Smith HJ, Willis HE, Healy MP, Watkins KE. Differences in Cortical Surface Area in Developmental Language Disorder. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:288-314. [PMID: 38832358 PMCID: PMC11093399 DOI: 10.1162/nol_a_00127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 11/08/2023] [Indexed: 06/05/2024]
Abstract
Approximately 7% of children have developmental language disorder (DLD), a neurodevelopmental condition associated with persistent language learning difficulties without a known cause. Our understanding of the neurobiological basis of DLD is limited. Here, we used FreeSurfer to investigate cortical surface area and thickness in a large cohort of 156 children and adolescents aged 10-16 years with a range of language abilities, including 54 with DLD, 28 with a history of speech-language difficulties who did not meet criteria for DLD, and 74 age-matched controls with typical language development (TD). We also examined cortical asymmetries in DLD using an automated surface-based technique. Relative to the TD group, those with DLD showed smaller surface area bilaterally in the inferior frontal gyrus extending to the anterior insula, in the posterior temporal and ventral occipito-temporal cortex, and in portions of the anterior cingulate and superior frontal cortex. Analysis of the whole cohort using a language proficiency factor revealed that language ability correlated positively with surface area in similar regions. There were no differences in cortical thickness, nor in asymmetry of these cortical metrics between TD and DLD. This study highlights the importance of distinguishing between surface area and cortical thickness in investigating the brain basis of neurodevelopmental disorders and suggests the development of cortical surface area to be of importance to DLD. Future longitudinal studies are required to understand the developmental trajectory of these cortical differences in DLD and how they relate to language maturation.
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Affiliation(s)
- Nilgoun Bahar
- Department of Experimental Psychology & Wellcome Trust Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Gabriel J. Cler
- Department of Experimental Psychology & Wellcome Trust Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Speech & Hearing Sciences, University of Washington, Seattle, WA, USA
| | - Saloni Krishnan
- Department of Experimental Psychology & Wellcome Trust Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychology, Royal Holloway, University of London, Egham Hill, Surrey, UK
| | - Salomi S. Asaridou
- Department of Experimental Psychology & Wellcome Trust Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Harriet J. Smith
- Department of Experimental Psychology & Wellcome Trust Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- MRC Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Hanna E. Willis
- Department of Experimental Psychology & Wellcome Trust Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - Máiréad P. Healy
- Department of Experimental Psychology & Wellcome Trust Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Kate E. Watkins
- Department of Experimental Psychology & Wellcome Trust Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
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4
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Eichner C, Berger P, Klein CC, Friederici AD. Lateralization of dorsal fiber tract targeting Broca's area concurs with language skills during development. Prog Neurobiol 2024; 236:102602. [PMID: 38582324 DOI: 10.1016/j.pneurobio.2024.102602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 01/26/2024] [Accepted: 04/03/2024] [Indexed: 04/08/2024]
Abstract
Language is bounded to the left hemisphere in the adult brain and the functional lateralization can already be observed early during development. Here we investigate whether this is paralleled by a lateralization of the white matter structural language network. We analyze the strength and microstructural properties of language-related fiber tracts connecting temporal and frontal cortices with a separation of two dorsal tracts, one targeting the posterior Broca's area (BA44) and one targeting the precentral gyrus (BA6). In a large sample of young children (3-6 years), we demonstrate that, in contrast to the BA6-targeting tract, the microstructural asymmetry of the BA44-targeting fiber tract significantly correlates locally with different aspects of development. While the asymmetry in its anterior segment reflects age, the asymmetry in its posterior segment is associated with the children's language skills. These findings demonstrate a fine-grained structure-to-function mapping in the lateralized network and go beyond our current view of language-related human brain maturation.
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Affiliation(s)
- Cornelius Eichner
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Philipp Berger
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany; Research Group Milestones of Early Cognitive Development, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Cheslie C Klein
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany; Research Group Milestones of Early Cognitive Development, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany.
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5
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Li X, Ng KK, Wong JJY, Zhou JH, Yow WQ. Brain gray matter morphometry relates to onset age of bilingualism and theory of mind in young and older adults. Sci Rep 2024; 14:3193. [PMID: 38326334 PMCID: PMC10850089 DOI: 10.1038/s41598-023-48710-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 11/29/2023] [Indexed: 02/09/2024] Open
Abstract
Lifelong bilingualism may result in neural reserve against decline not only in the general cognitive domain, but also in social cognitive functioning. In this study, we show the brain structural correlates that are associated with second language age of acquisition (L2AoA) and theory of mind (the ability to reason about mental states) in normal aging. Participants were bilingual adults (46 young, 50 older) who completed a theory-of-mind task battery, a language background questionnaire, and an anatomical MRI scan to obtain cortical morphometric features (i.e., gray matter volume, thickness, and surface area). Findings indicated a theory-of-mind decline in older adults compared to young adults, controlling for education and general cognition. Importantly, earlier L2AoA and better theory-of-mind performance were associated with larger volume, higher thickness, and larger surface area in the bilateral temporal, medial temporal, superior parietal, and prefrontal brain regions. These regions are likely to be involved in mental representations, language, and cognitive control. The morphometric association with L2AoA in young and older adults were comparable, but its association with theory of mind was stronger in older adults than young adults. The results demonstrate that early bilingual acquisition may provide protective benefits to intact theory-of-mind abilities against normal age-related declines.
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Affiliation(s)
- Xiaoqian Li
- Humanities, Arts and Social Sciences, Singapore University of Technology and Design, Singapore, Singapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Joey Ju Yu Wong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
| | - W Quin Yow
- Humanities, Arts and Social Sciences, Singapore University of Technology and Design, Singapore, Singapore.
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6
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Liang X, Sun L, Liao X, Lei T, Xia M, Duan D, Zeng Z, Li Q, Xu Z, Men W, Wang Y, Tan S, Gao JH, Qin S, Tao S, Dong Q, Zhao T, He Y. Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence. Nat Commun 2024; 15:784. [PMID: 38278807 PMCID: PMC10817914 DOI: 10.1038/s41467-024-44863-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 01/08/2024] [Indexed: 01/28/2024] Open
Abstract
Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.
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Affiliation(s)
- Xinyuan Liang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Lianglong Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, Beijing, 100875, China
| | - Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Mingrui Xia
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Dingna Duan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Zilong Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Zhilei Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
- Beijing City Key Laboratory for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
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7
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Jiang W, Zhou Z, Li G, Yin W, Wu Z, Wang L, Ghanbari M, Li G, Yap PT, Howell BR, Styner MA, Yacoub E, Hazlett H, Gilmore JH, Keith Smith J, Ugurbil K, Elison JT, Zhang H, Shen D, Lin W. Mapping the evolution of regional brain network efficiency and its association with cognitive abilities during the first twenty-eight months of life. Dev Cogn Neurosci 2023; 63:101284. [PMID: 37517139 PMCID: PMC10400876 DOI: 10.1016/j.dcn.2023.101284] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 06/20/2023] [Accepted: 07/23/2023] [Indexed: 08/01/2023] Open
Abstract
Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels.
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Affiliation(s)
- Weixiong Jiang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhen Zhou
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Guoshi Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Weiyan Yin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhengwang Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Li Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Maryam Ghanbari
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Gang Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Pew-Thian Yap
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - Martin A Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, USA
| | - Heather Hazlett
- Department of Psychiatry, University of North Carolina at Chapel Hill, USA; Department of Radiology, University of North Carolina at Chapel Hill, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, USA
| | - J Keith Smith
- Department of Radiology, University of North Carolina at Chapel Hill, USA
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, USA; Department of Pediatrics, University of Minnesota, USA
| | - Han Zhang
- Biomedical Engineering, Shanghai Tech University, Shanghai, China
| | - Dinggang Shen
- Biomedical Engineering, Shanghai Tech University, Shanghai, China; Shanghai Clinical Research and Trial Center, Shanghai 201210, China
| | - Weili Lin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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8
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Schilling KG, Chad JA, Chamberland M, Nozais V, Rheault F, Archer D, Li M, Gao Y, Cai L, Del'Acqua F, Newton A, Moyer D, Gore JC, Lebel C, Landman BA. White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.25.559330. [PMID: 37808645 PMCID: PMC10557619 DOI: 10.1101/2023.09.25.559330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Maxime Chamberland
- Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands
| | | | - Francois Rheault
- Medical Imaging and Neuroinformatic (MINi) Lab, Department of Computer Science, University of Sherbrooke, Canada
| | - Derek Archer
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, 37212, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Muwei Li
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yurui Gao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Leon Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Flavio Del'Acqua
- NatbrainLab, Department of Forensics and Neurodevelopmental Sciences, King's College London, London UK
| | - Allen Newton
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel Moyer
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - John C Gore
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Catherine Lebel
- Alberta Children's Hospital Research Institute (ACHRI), Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Bennett A Landman
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
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9
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Rahayel S, Tremblay C, Vo A, Misic B, Lehéricy S, Arnulf I, Vidailhet M, Corvol JC, Gagnon JF, Postuma RB, Montplaisir J, Lewis S, Matar E, Ehgoetz Martens K, Borghammer P, Knudsen K, Hansen AK, Monchi O, Gan-Or Z, Dagher A. Mitochondrial function-associated genes underlie cortical atrophy in prodromal synucleinopathies. Brain 2023; 146:3301-3318. [PMID: 36826230 PMCID: PMC10393413 DOI: 10.1093/brain/awad044] [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: 09/20/2022] [Revised: 01/12/2023] [Accepted: 02/03/2023] [Indexed: 02/25/2023] Open
Abstract
Isolated rapid eye movement sleep behaviour disorder (iRBD) is a sleep disorder characterized by the loss of rapid eye movement sleep muscle atonia and the appearance of abnormal movements and vocalizations during rapid eye movement sleep. It is a strong marker of incipient synucleinopathy such as dementia with Lewy bodies and Parkinson's disease. Patients with iRBD already show brain changes that are reminiscent of manifest synucleinopathies including brain atrophy. However, the mechanisms underlying the development of this atrophy remain poorly understood. In this study, we performed cutting-edge imaging transcriptomics and comprehensive spatial mapping analyses in a multicentric cohort of 171 polysomnography-confirmed iRBD patients [67.7 ± 6.6 (49-87) years; 83% men] and 238 healthy controls [66.6 ± 7.9 (41-88) years; 77% men] with T1-weighted MRI to investigate the gene expression and connectivity patterns associated with changes in cortical thickness and surface area in iRBD. Partial least squares regression was performed to identify the gene expression patterns underlying cortical changes in iRBD. Gene set enrichment analysis and virtual histology were then done to assess the biological processes, cellular components, human disease gene terms, and cell types enriched in these gene expression patterns. We then used structural and functional neighbourhood analyses to assess whether the atrophy patterns in iRBD were constrained by the brain's structural and functional connectome. Moreover, we used comprehensive spatial mapping analyses to assess the specific neurotransmitter systems, functional networks, cytoarchitectonic classes, and cognitive brain systems associated with cortical changes in iRBD. All comparisons were tested against null models that preserved spatial autocorrelation between brain regions and compared to Alzheimer's disease to assess the specificity of findings to synucleinopathies. We found that genes involved in mitochondrial function and macroautophagy were the strongest contributors to the cortical thinning occurring in iRBD. Moreover, we demonstrated that cortical thinning was constrained by the brain's structural and functional connectome and that it mapped onto specific networks involved in motor and planning functions. In contrast with cortical thickness, changes in cortical surface area were related to distinct genes, namely genes involved in the inflammatory response, and to different spatial mapping patterns. The gene expression and connectivity patterns associated with iRBD were all distinct from those observed in Alzheimer's disease. In summary, this study demonstrates that the development of brain atrophy in synucleinopathies is constrained by specific genes and networks.
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Affiliation(s)
- Shady Rahayel
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
| | - Christina Tremblay
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Andrew Vo
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Bratislav Misic
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
| | - Stéphane Lehéricy
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Isabelle Arnulf
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Marie Vidailhet
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Jean-Christophe Corvol
- Institut du Cerveau–Paris Brain Institute–ICM, INSERM, CNRS, Sorbonne Université, Paris 75013, France
| | - Jean-François Gagnon
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Psychology, University of Quebec in Montreal, Montreal H2X 3P2, Canada
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal H3W 1W5, Canada
| | - Ronald B Postuma
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Neurology, Montreal General Hospital, Montreal H3G 1A4, Canada
| | - Jacques Montplaisir
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal H4J 1C5, Canada
- Department of Psychiatry, University of Montreal, Montreal H3T 1J4, Canada
| | - Simon Lewis
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
| | - Elie Matar
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
| | - Kaylena Ehgoetz Martens
- ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, University of Sydney, Camperdown NSW 2050, Australia
- Department of Kinesiology, University of Waterloo, Waterloo N2L 3G1, Canada
| | - Per Borghammer
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Karoline Knudsen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Allan K Hansen
- Department of Nuclear Medicine and PET, Aarhus University Hospital, Aarhus DK-8200, Denmark
| | - Oury Monchi
- Research Centre, Institut universitaire de gériatrie de Montréal, Montreal H3W 1W5, Canada
- Department of Radiology, Radio-Oncology, and Nuclear Medicine, University of Montreal, Montreal H3T 1A4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
| | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
- Department of Human Genetics, McGill University, Montreal H3A 0C7, Canada
| | - Alain Dagher
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal H3A 1A1, Canada
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10
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Pretzsch CM, Ecker C. Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review. Front Neurosci 2023; 17:1172779. [PMID: 37457001 PMCID: PMC10347684 DOI: 10.3389/fnins.2023.1172779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 06/09/2023] [Indexed: 07/18/2023] Open
Abstract
Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.
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Affiliation(s)
- Charlotte M. Pretzsch
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
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11
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Van Rheenen TE, Cotton SM, Dandash O, Cooper RE, Ringin E, Daglas-Georgiou R, Allott K, Chye Y, Suo C, Macneil C, Hasty M, Hallam K, McGorry P, Fornito A, Yücel M, Pantelis C, Berk M. Increased cortical surface area but not altered cortical thickness or gyrification in bipolar disorder following stabilisation from a first episode of mania. Prog Neuropsychopharmacol Biol Psychiatry 2023; 122:110687. [PMID: 36427550 DOI: 10.1016/j.pnpbp.2022.110687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 11/08/2022] [Accepted: 11/16/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND Despite reports of altered brain morphology in established bipolar disorder (BD), there is limited understanding of when these morphological abnormalities emerge. Assessment of patients during the early course of illness can help to address this gap, but few studies have examined surface-based brain morphology in patients at this illness stage. METHODS We completed a secondary analysis of baseline data from a randomised control trial of BD individuals stabilised after their first episode of mania (FEM). The magnetic resonance imaging scans of n = 35 FEM patients and n = 29 age-matched healthy controls were analysed. Group differences in cortical thickness, surface area and gyrification were assessed at each vertex of the cortical surface using general linear models. Significant results were identified at p < 0.05 using cluster-wise correction. RESULTS The FEM group did not differ from healthy controls with regards to cortical thickness or gyrification. However, there were two clusters of increased surface area in the left hemisphere of FEM patients, with peak coordinates falling within the lateral occipital cortex and pars triangularis. CONCLUSIONS Cortical thickness and gyrification appear to be intact in the aftermath of a first manic episode, whilst cortical surface area in the inferior/middle prefrontal and occipitoparietal cortex is increased compared to age-matched controls. It is possible that increased surface area in the FEM group is the outcome of abnormalities in a premorbidly occurring process. In contrast, the findings raise the hypothesis that cortical thickness reductions seen in past studies of individuals with more established BD may be more attributable to post-onset factors.
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Affiliation(s)
- Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia.
| | - Sue M Cotton
- Orygen, Parkville, VIC, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Orwa Dandash
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging Facility, Monash University, Australia
| | - Rebecca E Cooper
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Elysha Ringin
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Rothanthi Daglas-Georgiou
- Orygen, Parkville, VIC, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Kelly Allott
- Orygen, Parkville, VIC, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Yann Chye
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging Facility, Monash University, Australia
| | - Chao Suo
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging Facility, Monash University, Australia
| | - Craig Macneil
- Orygen Youth Health Clinical Program, Parkville, VIC, Australia
| | - Melissa Hasty
- Orygen Youth Health Clinical Program, Parkville, VIC, Australia
| | - Karen Hallam
- The Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, Australia
| | - Patrick McGorry
- Orygen, Parkville, VIC, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging Facility, Monash University, Australia
| | - Murat Yücel
- Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging Facility, Monash University, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Florey Institute of Neuroscience and Mental Health, Clayton, VIC, Australia
| | - Michael Berk
- Orygen, Parkville, VIC, Australia; Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia; The Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, Australia; Barwon Health, PO Box 281, Geelong, Victoria, 3220, Australia
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12
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Sánchez SM, Schmidt H, Gallardo G, Anwander A, Brauer J, Friederici AD, Knösche TR. White matter brain structure predicts language performance and learning success. Hum Brain Mapp 2023; 44:1445-1455. [PMID: 36399515 PMCID: PMC9921223 DOI: 10.1002/hbm.26132] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 09/01/2022] [Accepted: 10/11/2022] [Indexed: 11/19/2022] Open
Abstract
Individual differences in the ability to process language have long been discussed. Much of the neural basis of these, however, is yet unknown. Here we investigated the relationship between long-range white matter connectivity of the brain, as revealed by diffusion tractography, and the ability to process syntactically complex sentences in the participants' native language as well as the improvement thereof by multiday training. We identified specific network motifs by singular value decomposition that indeed related white matter structural connectivity to individual language processing performance. First, for two such motifs, one in the left and one in the right hemisphere, their individual prevalence significantly predicted the individual language performance, suggesting an anatomical predisposition for the individual ability to process syntactically complex sentences. Both motifs comprise a number of cortical regions, but seem to be dominated by areas known for the involvement in working memory rather than the classical language network itself. Second, we identified another left hemispheric network motif, whose change of prevalence over the training period significantly correlated with the individual change in performance, thus reflecting training induced white matter plasticity. This motif comprises diverse cortical areas including regions known for their involvement in language processing, working memory and motor functions. The present findings suggest that individual differences in language processing and learning can be explained, in part, by individual differences in the brain's white matter structure. Brain structure may be a crucial factor to be considered when discussing variations in human cognitive performance, more generally.
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Affiliation(s)
- Stella M Sánchez
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.,Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany.,Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Helmut Schmidt
- Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany.,Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
| | - Guillermo Gallardo
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alfred Anwander
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Jens Brauer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Friedrich Schiller University, Office of the Vice-President for Young Researchers, Jena, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Thomas R Knösche
- Max Planck Institute for Human Cognitive and Brain Sciences, Brain Networks Group, Leipzig, Germany.,Institute of Biomedical Engineering and Informatics, TU Ilmenau, Ilmenau, Germany
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13
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Hölig C, Guerreiro MJS, Lingareddy S, Kekunnaya R, Röder B. Sight restoration in congenitally blind humans does not restore visual brain structure. Cereb Cortex 2023; 33:2152-2161. [PMID: 35580850 DOI: 10.1093/cercor/bhac197] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 11/14/2022] Open
Abstract
It is unknown whether impaired brain structure after congenital blindness is reversible if sight is restored later in life. Using structural magnetic resonance imaging, visual cortical surface area and cortical thickness were assessed in a large group of 21 sight-recovery individuals who had been born blind and who months or years later gained sight through cataract removal surgery. As control groups, we included 27 normally sighted individuals, 10 individuals with permanent congenital blindness, and 11 sight-recovery individuals with a late onset of cataracts. Congenital cataract-reversal individuals had a lower visual cortical surface area and a higher visual cortical thickness than normally sighted controls. These results corresponded to those of congenitally permanently blind individuals suggesting that impaired brain structure did not recover. Crucially, structural brain alterations in congenital-cataract reversal individuals were associated with a lower post-surgery visual acuity. No significant changes in visual cortex structure were observed in sight-recovery individuals with late onset cataracts. The results demonstrate that impaired structural brain development due to visual deprivation from birth is not fully reversible and limits functional recovery. Additionally, they highlight the crucial importance of prevention measures in the context of other types of aberrant childhood environments including low socioeconomic status and adversity.
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Affiliation(s)
- Cordula Hölig
- Biological Psychology and Neuropsychology, University of Hamburg, 20146 Hamburg, Germany
| | - Maria J S Guerreiro
- Biological Psychology and Neuropsychology, University of Hamburg, 20146 Hamburg, Germany.,Biological Psychology, Carl von Ossietzky University of Oldenburg, 26111 Oldenburg, Germany
| | | | - Ramesh Kekunnaya
- Jasti V Ramanamma Children's Eye Care Center, Child Sight Institute, LV Prasad Eye Institute, 50034 Hyderabad, India
| | - Brigitte Röder
- Biological Psychology and Neuropsychology, University of Hamburg, 20146 Hamburg, Germany
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14
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Longitudinal Changes in Cortical Surface Area Associated With Transition to Psychosis in Adolescents at Clinical High Risk for the Disease. J Am Acad Child Adolesc Psychiatry 2023; 62:593-600. [PMID: 36638884 DOI: 10.1016/j.jaac.2023.01.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 08/22/2022] [Accepted: 01/03/2023] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Identifying biomarkers of transition to psychosis in individuals at clinical high risk for psychosis (CHR-P) is essential to understanding the mechanisms underlying the disease. Although cross-sectional abnormalities in cortical surface area (CSA) have been demonstrated in individuals at CHR-P who transition to psychosis (CHR-P-T) compared with those who do not (CHR-P-NT), how CSA longitudinally develops remains unclear, especially in younger individuals. We set out to compare CSA in adolescents at CHR-P and healthy controls (HC) over 2 points in time. METHOD A longitudinal multicenter study was performed in adolescents at CHR-P in comparison to HC and according to transition to psychosis. Magnetic resonance imaging scans were acquired at baseline, at 18-month follow-up, or at the time of transition. Images were pre-processed and hemisphere and regional CSA were computed using FreeSurfer. Between-group analyses were performed with linear mixed-effects models. RESULTS A total of 313 scans (107 CHR-P and 102 HC) were included in the analysis. At 18 months, the rate of transition to psychosis in CHR-P was 23.4%. Adolescents at CHR-P-T presented greater age-related decrease in CSA in the left parietal and occipital lobes compared with HC, and in the bilateral parietal lobe and right frontal lobe relative to CHR-P-NT. These results were not influenced by antipsychotic treatment, cannabis use, or intelligence quotient (IQ). CONCLUSION Adolescents at CHR-P that developed a psychotic disorder presented different developmental trajectories of CSA relative to those who did not. A relatively greater decrease in CSA in the parietal and frontal lobes may index clinical transition to psychosis in adolescents at CHR-P.
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15
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Cheong Y, Nishitani S, Yu J, Habata K, Kamiya T, Shiotsu D, Omori IM, Okazawa H, Tomoda A, Kosaka H, Jung M. The effects of epigenetic age and its acceleration on surface area, cortical thickness, and volume in young adults. Cereb Cortex 2022; 32:5654-5663. [PMID: 35196707 DOI: 10.1093/cercor/bhac043] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/20/2022] [Accepted: 01/21/2022] [Indexed: 01/25/2023] Open
Abstract
DNA methylation age has been used in recent studies as an epigenetic marker of accelerated cellular aging, whose contribution to the brain structural changes was lately acknowledged. We aimed to characterize the association of epigenetic age (i.e. estimated DNA methylation age) and its acceleration with surface area, cortical thickness, and volume in healthy young adults. Using the multi-tissue method (Horvath S. DNA methylation age of human tissues and cell types. 2013. Genome Biol 14), epigenetic age was computed with saliva sample. Epigenetic age acceleration was derived from residuals after adjusting epigenetic age for chronological age. Multiple regression models were computed for 148 brain regions for surface area, cortical thickness, and volume using epigenetic age or accelerated epigenetic age as a predictor and controlling for sex. Epigenetic age was associated with surface area reduction of the left insula. It was also associated with cortical thinning and volume reduction in multiple regions, with prominent changes of cortical thickness in the left temporal regions and of volume in the bilateral orbital gyri. Finally, accelerated epigenetic age was negatively associated with right cuneus gyrus volume. Our findings suggest that understanding the mechanisms of epigenetic age acceleration in young individuals may yield valuable insights into the relationship between epigenetic aging and the cortical change and on the early development of neurocognitive pathology among young adults.
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Affiliation(s)
- Yongjeon Cheong
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
| | - Shota Nishitani
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan
| | - Jinyoung Yu
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
| | - Kaie Habata
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Taku Kamiya
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Daichi Shiotsu
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Ichiro M Omori
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Hidehiko Okazawa
- Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan.,Biomedical Imaging Research Center, University of Fukui, Eiheiji, Fukui 910-1193, Japan
| | - Akemi Tomoda
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan
| | - Hirotaka Kosaka
- Research Center for Child Mental Development, University of Fukui, Eiheiji, Fukui 910-1193, Japan.,Division of Developmental Higher Brain Functions, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan.,Department of Neuropsychiatry, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji, Fukui 910-1193, Japan
| | - Minyoung Jung
- Cognitive Science Research Group, Korea Brain Research Institute, Daegu 41062, South Korea
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16
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Klein CC, Berger P, Goucha T, Friederici AD, Grosse Wiesmann C. Children’s syntax is supported by the maturation of BA44 at 4 years, but of the posterior STS at 3 years of age. Cereb Cortex 2022; 33:5426-5435. [PMID: 36408641 PMCID: PMC10152089 DOI: 10.1093/cercor/bhac430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 09/07/2022] [Accepted: 09/26/2022] [Indexed: 11/22/2022] Open
Abstract
Abstract
Within the first years of life, children learn major aspects of their native language. However, the ability to process complex sentence structures, a core faculty in human language called syntax, emerges only slowly. A milestone in syntax acquisition is reached around the age of 4 years, when children learn a variety of syntactic concepts. Here, we ask which maturational changes in the child’s brain underlie the emergence of syntactically complex sentence processing around this critical age. We relate markers of cortical brain maturation to 3- and 4-year-olds’ sentence processing in contrast to other language abilities. Our results show that distinct cortical brain areas support sentence processing in the two age groups. Sentence production abilities at 3 years were associated with increased surface area in the most posterior part of the left superior temporal sulcus, whereas 4-year-olds showed an association with cortical thickness in the left posterior part of Broca’s area, i.e. BA44. The present findings suggest that sentence processing abilities rely on the maturation of distinct cortical regions in 3- compared to 4-year-olds. The observed shift to more mature regions involved in processing syntactically complex sentences may underlie behavioral milestones in syntax acquisition at around 4 years.
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Affiliation(s)
- Cheslie C Klein
- Max Planck Institute for Human Cognitive and Brain Sciences Department of Neuropsychology, , Stephanstraße 1a, Leipzig 04103 , Germany
- Max Planck Institute for Human Cognitive and Brain Sciences Research Group Milestones of Early Cognitive Development, , Stephanstraße 1a, Leipzig 04103 , Germany
| | - Philipp Berger
- Max Planck Institute for Human Cognitive and Brain Sciences Department of Neuropsychology, , Stephanstraße 1a, Leipzig 04103 , Germany
- Max Planck Institute for Human Cognitive and Brain Sciences Research Group Milestones of Early Cognitive Development, , Stephanstraße 1a, Leipzig 04103 , Germany
| | - Tomás Goucha
- Max Planck Institute for Human Cognitive and Brain Sciences Department of Neuropsychology, , Stephanstraße 1a, Leipzig 04103 , Germany
| | - Angela D Friederici
- Max Planck Institute for Human Cognitive and Brain Sciences Department of Neuropsychology, , Stephanstraße 1a, Leipzig 04103 , Germany
| | - Charlotte Grosse Wiesmann
- Max Planck Institute for Human Cognitive and Brain Sciences Research Group Milestones of Early Cognitive Development, , Stephanstraße 1a, Leipzig 04103 , Germany
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17
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Huang Y, Wu Z, Wang F, Hu D, Li T, Guo L, Wang L, Lin W, Li G. Mapping developmental regionalization and patterns of cortical surface area from 29 post-menstrual weeks to 2 years of age. Proc Natl Acad Sci U S A 2022; 119:e2121748119. [PMID: 35939665 PMCID: PMC9388141 DOI: 10.1073/pnas.2121748119] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 06/27/2022] [Indexed: 11/18/2022] Open
Abstract
Surface area of the human cerebral cortex expands extremely dynamically and regionally heterogeneously from the third trimester of pregnancy to 2 y of age, reflecting the spatial heterogeneity of the underlying microstructural and functional development of the cerebral cortex. However, little is known about the developmental patterns and regionalization of cortical surface area during this critical stage, due to the lack of high-quality imaging data and accurate computational tools for pediatric brain MRI data. To fill this critical knowledge gap, by leveraging 1,037 high-quality MRI scans with the age between 29 post-menstrual weeks and 24 mo from 735 pediatric subjects in two complementary datasets, i.e., the Baby Connectome Project (BCP) and the developing Human Connectome Project (dHCP), and state-of-the-art dedicated image-processing tools, we unprecedentedly parcellate the cerebral cortex into a set of distinct subdivisions purely according to the developmental patterns of the cortical surface. Our discovered developmentally distinct subdivisions correspond well to structurally and functionally meaningful regions and reveal spatially contiguous, hierarchical, and bilaterally symmetric patterns of early cortical surface expansion. We also show that high-order association subdivisions, where cortical folds emerge later during prenatal stages, undergo more dramatic cortical surface expansion during infancy, compared with the central regions, especially the sensorimotor and insula cortices, thus forming a distinct central-pole division in early cortical surface expansion. These results provide an important reference for exploring and understanding dynamic early brain development in health and disease.
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Affiliation(s)
- Ying Huang
- School of Automation, Northwestern Polytechnical University, Xi’an 710071, China
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Zhengwang Wu
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Fan Wang
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Dan Hu
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Tengfei Li
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Lei Guo
- School of Automation, Northwestern Polytechnical University, Xi’an 710071, China
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Weili Lin
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
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Patel Y, Shin J, Abé C, Agartz I, Alloza C, Alnæs D, Ambrogi S, Antonucci LA, Arango C, Arolt V, Auzias G, Ayesa-Arriola R, Banaj N, Banaschewski T, Bandeira C, Başgöze Z, Cupertino RB, Bau CHD, Bauer J, Baumeister S, Bernardoni F, Bertolino A, Bonnin CDM, Brandeis D, Brem S, Bruggemann J, Bülow R, Bustillo JR, Calderoni S, Calvo R, Canales-Rodríguez EJ, Cannon DM, Carmona S, Carr VJ, Catts SV, Chenji S, Chew QH, Coghill D, Connolly CG, Conzelmann A, Craven AR, Crespo-Facorro B, Cullen K, Dahl A, Dannlowski U, Davey CG, Deruelle C, Díaz-Caneja CM, Dohm K, Ehrlich S, Epstein J, Erwin-Grabner T, Eyler LT, Fedor J, Fitzgerald J, Foran W, Ford JM, Fortea L, Fuentes-Claramonte P, Fullerton J, Furlong L, Gallagher L, Gao B, Gao S, Goikolea JM, Gotlib I, Goya-Maldonado R, Grabe HJ, Green M, Grevet EH, Groenewold NA, Grotegerd D, Gruber O, Haavik J, Hahn T, Harrison BJ, Heindel W, Henskens F, Heslenfeld DJ, Hilland E, Hoekstra PJ, Hohmann S, Holz N, Howells FM, Ipser JC, Jahanshad N, Jakobi B, Jansen A, Janssen J, Jonassen R, Kaiser A, Kaleda V, Karantonis J, King JA, Kircher T, Kochunov P, Koopowitz SM, Landén M, Landrø NI, Lawrie S, Lebedeva I, Luna B, Lundervold AJ, MacMaster FP, Maglanoc LA, Mathalon DH, McDonald C, McIntosh A, Meinert S, Michie PT, Mitchell P, Moreno-Alcázar A, Mowry B, Muratori F, Nabulsi L, Nenadić I, O'Gorman Tuura R, Oosterlaan J, Overs B, Pantelis C, Parellada M, Pariente JC, Pauli P, Pergola G, Piarulli FM, Picon F, Piras F, Pomarol-Clotet E, Pretus C, Quidé Y, Radua J, Ramos-Quiroga JA, Rasser PE, Reif A, Retico A, Roberts G, Rossell S, Rovaris DL, Rubia K, Sacchet M, Salavert J, Salvador R, Sarró S, Sawa A, Schall U, Scott R, Selvaggi P, Silk T, Sim K, Skoch A, Spalletta G, Spaniel F, Stein DJ, Steinsträter O, Stolicyn A, Takayanagi Y, Tamm L, Tavares M, Teumer A, Thiel K, Thomopoulos SI, Tomecek D, Tomyshev AS, Tordesillas-Gutiérrez D, Tosetti M, Uhlmann A, Van Rheenen T, Vazquez-Bourgón J, Vernooij MW, Vieta E, Vilarroya O, Weickert C, Weickert T, Westlye LT, Whalley H, Willinger D, Winter A, Wittfeld K, Yang TT, Yoncheva Y, Zijlmans JL, Hoogman M, Franke B, van Rooij D, Buitelaar J, Ching CRK, Andreassen OA, Pozzi E, Veltman D, Schmaal L, van Erp TGM, Turner J, Castellanos FX, Pausova Z, Thompson P, Paus T. Virtual Ontogeny of Cortical Growth Preceding Mental Illness. Biol Psychiatry 2022; 92:299-313. [PMID: 35489875 PMCID: PMC11080987 DOI: 10.1016/j.biopsych.2022.02.959] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 02/02/2022] [Accepted: 02/23/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.
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Affiliation(s)
- Yash Patel
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Jean Shin
- The Hospital for Sick Children and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Christoph Abé
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ingrid Agartz
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Dag Alnæs
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Sonia Ambrogi
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Linda A Antonucci
- Departments of Education Science, Psychology, Communication Science, University of Bari Aldo Moro, Bari, Italy
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain; School of Medicine, Universidad Complutense, Madrid, Spain
| | - Volker Arolt
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Guillaume Auzias
- National Centre for Scientific Research, Aix-Marseille University, Marseille, France
| | - Rosa Ayesa-Arriola
- Department of Psychiatry, Marques de Valdecilla University Hospital, Instituto de Investigación Valdecilla, CIBERSAM, School of Medicine, University of Cantabria, Santander, Spain
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Cibele Bandeira
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Zeynep Başgöze
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota
| | | | - Claiton H D Bau
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Jochen Bauer
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fabio Bernardoni
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Alessandro Bertolino
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Caterina Del Mar Bonnin
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Silvia Brem
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry, University of Zürich, Zurich, Switzerland
| | | | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Juan R Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, New Mexico
| | - Sara Calderoni
- Department of Developmental Neuroscience, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Rosa Calvo
- Institute of Neuroscience, Hospital Clinic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, CIBERSAM, Barcelona, Spain
| | | | - Dara M Cannon
- Clinical Neuroimaging Lab, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Susanna Carmona
- Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | | | - Stanley V Catts
- School of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Sneha Chenji
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Qian Hui Chew
- Research Division, Institute of Mental Health, Singapore, Singapore
| | - David Coghill
- Department of Paediatrics, Department of Psychiatry, University of Melbourne, Parkville, Australia; Department of Psychiatry, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Colm G Connolly
- Department of Biomedical Sciences, Florida State University, Tallahassee, Florida
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Benedicto Crespo-Facorro
- Department of Psychiatry, Virgen del Rocio University Hospital, Universidad de Sevilla, Instituto de Biomedicina de Sevilla, CIBERSAM, Sevilla, Spain
| | - Kathryn Cullen
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Christopher G Davey
- Department of Psychiatry, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Christine Deruelle
- National Centre for Scientific Research, Aix-Marseille University, Marseille, France
| | | | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Jeffery Epstein
- Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Tracy Erwin-Grabner
- Laboratory of Systems Neuroscience and Imaging in Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Jennifer Fedor
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jacqueline Fitzgerald
- Trinity Institute of Neuroscience, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - William Foran
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Judith M Ford
- San Francisco Veterans Affairs Medical Center, San Francisco, California
| | - Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | | | | | - Lisa Furlong
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Louise Gallagher
- Discipline of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Bingchen Gao
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Jose M Goikolea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - Ian Gotlib
- Department of Psychology, Stanford University, Stanford, California
| | - Roberto Goya-Maldonado
- Laboratory of Systems Neuroscience and Imaging in Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | | | - Eugenio H Grevet
- Department of Psychiatry, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Nynke A Groenewold
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ben J Harrison
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, Australia
| | - Walter Heindel
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Frans Henskens
- School of Medicine & Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Dirk J Heslenfeld
- Experimental and Clinical Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eva Hilland
- Norwegian Centre for Mental Disorders Research NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pieter J Hoekstra
- Department of Child and Adolescent Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Fleur M Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Jonathan C Ipser
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Neda Jahanshad
- USC Mark and Mary Stevens Neuroimaging and Informatics Institute, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Babette Jakobi
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Andreas Jansen
- Core Facility Brain imaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria del Hospital Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Madrid, Spain
| | - Rune Jonassen
- Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway
| | - Anna Kaiser
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | - James Karantonis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Parkville, Australia
| | - Joseph A King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, Germany
| | - Tilo Kircher
- Department of Psychiatry, Marburg University, Marburg, Germany
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland
| | - Sheri-Michelle Koopowitz
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Mikael Landén
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | | | - Stephen Lawrie
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Astri J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
| | - Frank P MacMaster
- Departments of Psychiatry and Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Luigi A Maglanoc
- Department for Data Capture and Collections Management, University Center for Information Technology, University of Oslo, Oslo, Norway
| | - Daniel H Mathalon
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, California
| | - Colm McDonald
- Galway Neuroscience Centre, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Andrew McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Patricia T Michie
- School of Psychology, College of Engineering, Science and Environment, The University of Newcastle, Callaghan, New South Wales, Australia
| | | | - Ana Moreno-Alcázar
- FIDMAG Germanes Hospitalàries Research Foundation, Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia
| | - Filippo Muratori
- Department of Developmental Neuroscience, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Leila Nabulsi
- Clinical Neuroimaging Lab, Center for Neuroimaging, Cognition and Genomics, Galway Neuroscience Centre, College of Medicine, Nursing, and Health Sciences, National University of Ireland Galway, Galway, Ireland
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | | | - Jaap Oosterlaan
- Clinical Neuropsychology Section, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Carlton South, Victoria, Australia
| | - Mara Parellada
- School of Medicine, Universidad Complutense, Madrid, Spain
| | - Jose C Pariente
- Magnetic Resonance Imaging core facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Paul Pauli
- Department of Psychology (Biological Psychology, Clinical Psychology, and Psychotherapy), University of Würzburg, Würzburg, Germany
| | - Giulio Pergola
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Francesco Maria Piarulli
- Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Felipe Picon
- Graduate Program in Psychiatry and Behavioral Sciences, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | | | - Clara Pretus
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - J Antoni Ramos-Quiroga
- Department of Psychiatry, Hospital Universitari Vall d'Hebrón, CIBERSAM, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Paul E Rasser
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt-Goethe University, Frankfurt am Main, Germany
| | | | | | - Susan Rossell
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Victoria, Australia
| | - Diego Luiz Rovaris
- Department of Physiology and Biophysics, Instituto de Ciencias Biomédicas Universidade de São Paulo, São Paulo, Brazil
| | - Katya Rubia
- Child & Adolescent Psychiatry, King's College London, London, United Kingdom
| | - Matthew Sacchet
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Harvard Medical School, Belmont, Massachusetts
| | - Josep Salavert
- FIDMAG Germanes Hospitalàries Research Foundation, Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain
| | | | | | - Akira Sawa
- Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Ulrich Schall
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Rodney Scott
- Hunter Medical Research Institute, Newcastle, New South Wales, Australia
| | - Pierluigi Selvaggi
- Azienda Ospedaliero-Universitaria Consorziale Policlinico di Bari, Bari, Italy
| | - Tim Silk
- School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, Santa Lucia Foundation Scientific Institute for Research, Hospitalization and Healthcare, Rome, Italy
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
| | - Dan J Stein
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Olaf Steinsträter
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Aleks Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Yoichiro Takayanagi
- Department of Neuropsychiatry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Leanne Tamm
- Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Maria Tavares
- Department of Genetics, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Sophia I Thomopoulos
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
| | | | - Diana Tordesillas-Gutiérrez
- Department of Radiology, University Hospital Marqués de Valdecilla, Instituto de Investigación Valdecilla, Santander, Spain
| | - Michela Tosetti
- Laboratory of Medical Physics and Magnetic Resonance, Scientific Institute for Research, Hospitalization and Healthcare Stella Maris Foundation, Pisa, Italy
| | - Anne Uhlmann
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Germany
| | - Tamsyn Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Javier Vazquez-Bourgón
- Department of Psychiatry, Marques de Valdecilla University Hospital, Instituto de Investigación Valdecilla, CIBERSAM, School of Medicine, University of Cantabria, Santander, Spain
| | - Meike W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Eduard Vieta
- Institute of Neuroscience, Hospital Clinic, University of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, CIBERSAM, Barcelona, Spain
| | - Oscar Vilarroya
- Department of Psychiatry, Autonomous University of Barcelona, Cerdanyola del Valles, Spain
| | - Cynthia Weickert
- Department of Neuroscience and Physiology, University of New South Wales, Sydney, Australia
| | | | - Lars T Westlye
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Heather Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - David Willinger
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital, University of Zürich, Zurich, Switzerland
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases, Site Rostock/Greifswald, Greifswald, Germany
| | - Tony T Yang
- Department of Psychiatry and Behavioral Sciences, Division of Child and Adolescent Psychiatry, University of California San Francisco, San Francisco, California
| | | | - Jendé L Zijlmans
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Barbara Franke
- Departments of Human Genetics and Psychiatry, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Daan van Rooij
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jan Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Elena Pozzi
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Dick Veltman
- Department of Psychiatry, Amsterdam UMC, VUMC, Amsterdam, The Netherlands
| | - Lianne Schmaal
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California
| | | | | | - Zdenka Pausova
- The Hospital for Sick Children and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Paul Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, California
| | - Tomas Paus
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada; Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montréal, Montreal, Quebec, Canada.
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Berger P, Friederici AD, Grosse Wiesmann C. Maturational Indices of the Cognitive Control Network Are Associated with Inhibitory Control in Early Childhood. J Neurosci 2022; 42:6258-6266. [PMID: 35817578 PMCID: PMC9374117 DOI: 10.1523/jneurosci.2235-21.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 05/20/2022] [Accepted: 05/24/2022] [Indexed: 11/21/2022] Open
Abstract
Goal-directed behavior crucially relies on our capacity to suppress impulses and predominant behavioral responses. This ability, called inhibitory control, emerges in early childhood with marked improvements between 3 and 4 years. Here, we ask which brain structures are related to the emergence of this critical ability. Using a multimodal approach, we relate the pronounced behavioral improvements in different facets of 3- and 4-year-olds' (N = 37, 20 female) inhibitory control to structural indices of maturation in the developing brain assessed with MRI. Our results show that cortical and subcortical structure of core regions in the adult cognitive control network, including the PFC, thalamus, and the inferior parietal cortices, is associated with early inhibitory functioning in preschool children. Probabilistic tractography revealed an association of frontoparietal (i.e., the superior longitudinal fascicle) and thalamocortical connections with early inhibitory control. Notably, these associations to brain structure were distinct for different facets of early inhibitory control, often referred to as motivational ("hot") and cognitive ("cold") inhibitory control. Our findings thus reveal the structural brain networks and connectivity related to the emergence of this core faculty of human cognition.SIGNIFICANCE STATEMENT The capacity to suppress impulses and behavioral responses is crucial for goal-directed behavior. This ability, called inhibitory control, develops between the ages of 3 and 4 years. The factors behind this developmental milestone have been debated intensely for decades; however, the brain structure that underlies the emergence of inhibitory control in early childhood is largely unknown. Here, we relate the pronounced behavioral improvements in inhibitory control between 3 and 4 years with structural brain markers of gray matter and white matter maturation. Using a multimodal approach that combines analyses of cortical surface structure, subcortical structures, and white matter connectivity, our results reveal the structural brain networks and connectivity related to this core faculty of human cognition.
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Affiliation(s)
- Philipp Berger
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany
- Research Group Milestones of Early Cognitive Development, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany
| | - Charlotte Grosse Wiesmann
- Research Group Milestones of Early Cognitive Development, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany
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20
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Myoraku A, Lang A, Taylor CT, Scott Mackin R, Meyerhoff DJ, Mueller S, Strigo IA, Tosun D. Age-dependent brain morphometry in Major Depressive disorder. Neuroimage Clin 2021; 33:102924. [PMID: 34959051 PMCID: PMC8718744 DOI: 10.1016/j.nicl.2021.102924] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 12/01/2021] [Accepted: 12/20/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is a complex disorder that affects nearly 264 million people worldwide. Structural brain abnormalities in multiple neuroanatomical networks have been implicated in the etiology of MDD, but the degree to which MDD affects brain structure during early to late adulthood is unclear. METHODS We examined morphometry of brain regions commonly implicated in MDD, including the amygdala, hippocampus, anterior cingulate gyrus, lateral orbitofrontal gyrus, subgenual cortex, and insular cortex subregions, from early to late adulthood. Harmonized measures for gray matter (GM) volume and cortical thickness of each region were estimated cross-sectionally for 305 healthy controls (CTLs) and 247 individuals with MDD (MDDs), collated from four research cohorts. We modeled the nonlinear associations of age with GM volume and cortical thickness using generalized additive modeling and tested for age-dependent group differences. RESULTS Overall, all investigated regions exhibited smaller GM volume and thinner cortical measures with increasing age. Compared to age matched CTLs, MDDs had thicker cortices and greater GM volume from early adulthood until early middle age (average 35 years), but thinner cortices and smaller GM volume during and after middle age in the lateral orbital gyrus and all insular subregions. Deviations of the MDD and CTL models for both GM volume and cortical thickness in these regions started as early as age 18. CONCLUSIONS The analyses revealed that brain morphometry differences between MDDs and CTLs are dependent on age and brain region. The significant age-by-group interactions in the lateral orbital frontal gyrus and insular subregions make these regions potential targets for future longitudinal studies of MDD.
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Affiliation(s)
- Alison Myoraku
- Northern California Institute for Research and Education, San Francisco, CA 94121, United States; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, United States; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, United States.
| | - Adam Lang
- Northern California Institute for Research and Education, San Francisco, CA 94121, United States
| | - Charles T Taylor
- Department of Psychiatry, University of California, San Diego School of Medicine, San Diego, CA 92093, United States
| | - R Scott Mackin
- Northern California Institute for Research and Education, San Francisco, CA 94121, United States; Department of Psychiatry and Behavioral Sciences, Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA 94143, United States
| | - Dieter J Meyerhoff
- Northern California Institute for Research and Education, San Francisco, CA 94121, United States; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, United States
| | - Susanne Mueller
- Northern California Institute for Research and Education, San Francisco, CA 94121, United States; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, United States
| | - Irina A Strigo
- Department of Psychiatry, University of California San Francisco, San Francisco, CA 94143, United States; Emotion and Pain Laboratory, San Francisco Veterans Affairs Health Care Center, San Francisco, CA 94121, United States
| | - Duygu Tosun
- Northern California Institute for Research and Education, San Francisco, CA 94121, United States; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, United States
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21
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Qi T, Schaadt G, Friederici AD. Associated functional network development and language abilities in children. Neuroimage 2021; 242:118452. [PMID: 34358655 PMCID: PMC8463838 DOI: 10.1016/j.neuroimage.2021.118452] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 07/14/2021] [Accepted: 08/03/2021] [Indexed: 11/26/2022] Open
Abstract
During childhood, the brain is gradually converging to the efficient functional architecture observed in adults. How the brain's functional architecture evolves with age, particularly in young children, is however, not well understood. We examined the functional connectivity of the core language regions, in association with cortical growth and language abilities, in 175 young children in the age range of 4 to 9 years. We analyzed the brain's developmental changes using resting-state functional and T1-weighted structural magnetic resonance imaging data. The results showed increased functional connectivity strength with age between the pars triangularis of the left inferior frontal gyrus and left temporoparietal regions (cohen's d = 0.54, CI: 0.24 - 0.84), associated with children's language abilities. Stronger functional connectivity between bilateral prefrontal and temporoparietal regions was associated with better language abilities regardless of age. In addition, the stronger functional connectivity between the left inferior frontal and temporoparietal regions was associated with larger surface area and thinner cortical thickness in these regions, which in turn was associated with superior language abilities. Thus, using functional and structural brain indices, coupled with behavioral measures, we elucidate the association of functional language network development, language ability, and cortical growth, thereby adding to our understanding of the neural basis of language acquisition in young children.
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Affiliation(s)
- Ting Qi
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Gesa Schaadt
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Education and Psychology, Free University of Berlin, Berlin, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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22
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Darayi M, Hoffman ME, Sayut J, Wang S, Demirci N, Consolini J, Holland MA. Computational models of cortical folding: A review of common approaches. J Biomech 2021; 139:110851. [PMID: 34802706 DOI: 10.1016/j.jbiomech.2021.110851] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 08/09/2021] [Accepted: 10/26/2021] [Indexed: 11/29/2022]
Abstract
The process of gyrification, by which the brain develops the intricate pattern of gyral hills and sulcal valleys, is the result of interactions between biological and mechanical processes during brain development. Researchers have developed a vast array of computational models in order to investigate cortical folding. This review aims to summarize these studies, focusing on five essential elements of the brain that affect development and gyrification and how they are represented in computational models: (i) the constraints of skull, meninges, and cerebrospinal fluid; (ii) heterogeneity of cortical layers and regions; (iii) anisotropic behavior of subcortical fiber tracts; (iv) material properties of brain tissue; and (v) the complex geometry of the brain. Finally, we highlight areas of need for future simulations of brain development.
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Affiliation(s)
- Mohsen Darayi
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Mia E Hoffman
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - John Sayut
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Shuolun Wang
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Nagehan Demirci
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Jack Consolini
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA
| | - Maria A Holland
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA; Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA.
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23
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Norbom LB, Ferschmann L, Parker N, Agartz I, Andreassen OA, Paus T, Westlye LT, Tamnes CK. New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings. Prog Neurobiol 2021; 204:102109. [PMID: 34147583 DOI: 10.1016/j.pneurobio.2021.102109] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/26/2021] [Accepted: 06/15/2021] [Indexed: 12/11/2022]
Abstract
Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.
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Affiliation(s)
- Linn B Norbom
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway
| | - Nadine Parker
- Institute of Medical Science, University of Toronto, Ontario, Canada
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway
| | - Ole A Andreassen
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Tomáš Paus
- ECOGENE-21, Chicoutimi, Quebec, Canada; Department of Psychology and Psychiatry, University of Toronto, Ontario, Canada; Department of Psychiatry and Centre hospitalier universitaire Sainte-Justine, University of Montreal, Canada
| | - Lars T Westlye
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway
| | - Christian K Tamnes
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
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24
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Warling A, Yavi M, Clasen LS, Blumenthal JD, Lalonde FM, Raznahan A, Liu S. Sex Chromosome Dosage Effects on White Matter Structure in the Human Brain. Cereb Cortex 2021; 31:5339-5353. [PMID: 34117759 DOI: 10.1093/cercor/bhab162] [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: 03/12/2021] [Revised: 04/29/2021] [Accepted: 05/18/2021] [Indexed: 11/14/2022] Open
Abstract
Sex chromosome aneuploidies, a group of neurogenetic conditions characterized by aberrant sex chromosome dosage (SCD), are associated with increased risks for psychopathology as well as alterations in gray matter structure. However, we still lack a comprehensive understanding of potential SCD-associated changes in white matter structure, or knowledge of how these changes might relate to known alterations in gray matter anatomy. Thus, here, we use voxel-based morphometry on structural neuroimaging data to provide the first comprehensive maps of regional white matter volume (WMV) changes across individuals with varying SCD (n = 306). We show that mounting X- and Y-chromosome dosage are both associated with widespread WMV decreases, including in cortical, subcortical, and cerebellar tracts, as well as WMV increases in the genu of the corpus callosum and posterior thalamic radiation. We also correlate X- and Y-chromosome-linked WMV changes in certain regions to measures of internalizing and externalizing psychopathology. Finally, we demonstrate that SCD-driven WMV changes show a coordinated coupling with SCD-driven gray matter volume changes. These findings represent the most complete maps of X- and Y-chromosome effects on human white matter to date, and show how such changes connect to psychopathological symptoms and gray matter anatomy.
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Affiliation(s)
- Allysa Warling
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mani Yavi
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Liv S Clasen
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jonathan D Blumenthal
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - François M Lalonde
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
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25
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Johnson MH, Charman T, Pickles A, Jones EJH. Annual Research Review: Anterior Modifiers in the Emergence of Neurodevelopmental Disorders (AMEND)-a systems neuroscience approach to common developmental disorders. J Child Psychol Psychiatry 2021; 62:610-630. [PMID: 33432656 PMCID: PMC8609429 DOI: 10.1111/jcpp.13372] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/25/2020] [Indexed: 02/06/2023]
Abstract
We present the Anterior Modifiers in the Emergence of Neurodevelopmental Disorders (AMEND) framework, designed to reframe the field of prospective studies of neurodevelopmental disorders. In AMEND we propose conceptual, statistical and methodological approaches to separating markers of early-stage perturbations from later developmental modifiers. We describe the evidence for, and features of, these interacting components before outlining analytical approaches to studying how different profiles of early perturbations and later modifiers interact to produce phenotypic outcomes. We suggest this approach could both advance our theoretical understanding and clinical approach to the emergence of developmental psychopathology in early childhood.
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Affiliation(s)
- Mark H. Johnson
- Centre for Brain and Cognitive DevelopmentDepartment of Psychological SciencesBirkbeck, University of LondonLondonUK
- Department of PsychologyUniversity of CambridgeCambridgeUK
| | - Tony Charman
- Department of PsychologyInstitute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK
| | - Andrew Pickles
- Department of Biostatistics and Health InformaticsInstitute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK
| | - Emily J. H. Jones
- Centre for Brain and Cognitive DevelopmentDepartment of Psychological SciencesBirkbeck, University of LondonLondonUK
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26
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Abé C, Adebahr R, Liberg B, Mannfolk C, Lebedev A, Eriksson J, Långström N, Rahm C. Brain structure and clinical profile point to neurodevelopmental factors involved in pedophilic disorder. Acta Psychiatr Scand 2021; 143:363-374. [PMID: 33355922 PMCID: PMC7986195 DOI: 10.1111/acps.13273] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [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: 12/16/2020] [Accepted: 12/16/2020] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Pedophilic disorder (PD) is characterized bypersistent, intense sexual attraction to prepubertal children that the individual has acted on, or causes marked distress or interpersonal difficulty. Although prior research suggests that PD has neurodevelopmental underpinnings, the evidence remains sparse. To aid the understanding of etiology and treatment development, we quantified neurobiological and clinical correlates of PD. METHOD We compared 55 self-referred, help-seeking, non-forensic male patients with DSM-5 PD with 57 age-matched, healthy male controls (HC) on clinical, neuropsychological, and structural brain imaging measures (cortical thickness and surface area, subcortical and white matter volumes). Structural brain measures were related to markers for aberrant neurodevelopment including IQ, and the 2nd to 4th digit ratio (2D:4D). RESULTS PD was associated with psychiatric disorder comorbidity and ADHD and autism spectrum disorder symptoms. PD patients had lower total IQ than HC. PD individuals exhibited cortical surface area abnormalities in regions belonging to the brain's default mode network and showed abnormal volume of white matter underlying those regions. PD subjects had smaller hippocampi and nuclei accumbens than HC. Findings were not related to history of child-related sexual offending. IQ correlated negatively with global expression of PD-related brain features and 2D:4D correlated with surface area in PD. CONCLUSIONS In the largest single-center study to date, we delineate psychiatric comorbidity, neurobiological and cognitive correlates of PD. Our morphometric findings, their associations with markers of aberrant neurodevelopment, and psychiatric comorbidities suggest that neurodevelopmental mechanisms are involved in PD. The findings may need consideration in future development of clinical management of PD patients.
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Affiliation(s)
- Christoph Abé
- Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
| | - Roberth Adebahr
- ANOVAKarolinska University HospitalStockholmSweden,Department of Clinical Sciences (Psychiatry)Umeå UniversityUmeåSweden
| | - Benny Liberg
- Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
| | - Christian Mannfolk
- Centre for Psychiatry ResearchDepartment of Clinical NeuroscienceKarolinska Institutet, and Stockholm Health Care ServicesStockholmSweden
| | - Alexander Lebedev
- Department of Clinical NeuroscienceKarolinska InstitutetStockholmSweden
| | | | - Niklas Långström
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden,National Board of Health & WelfareStockholmSweden
| | - Christoffer Rahm
- Centre for Psychiatry ResearchDepartment of Clinical NeuroscienceKarolinska Institutet, and Stockholm Health Care ServicesStockholmSweden
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27
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Rajagopalan V, Pioro EP. Degeneration of gray and white matter differs between hypometabolic and hypermetabolic brain regions in a patient with ALS-FTD: a longitudinal MRI - PET multimodal study. Amyotroph Lateral Scler Frontotemporal Degener 2021; 22:127-132. [PMID: 32924608 DOI: 10.1080/21678421.2020.1818784] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 08/29/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVE [18F]-fluoro-2-deoxy-d-glucose positron emission tomography (18F-FDG PET) imaging and magnetic resonance imaging (MRI) of brain in ALS patients with frontotemporal lobe dementia (ALS-FTD) reveal hypometabolism and hypermetabolism, as well as gray matter (GM) and white matter (WM) abnormalities in different brain regions, respectively. Hypometabolism arising from neuronal dysfunction or loss is the most recognized pathophysiologic change in neurodegeneration, whereas mechanisms underlying hypermetabolism remain unclear. We hypothesize that hypometabolic and hypermetabolic brain regions in ALS-FTD represent differential degeneration of GM and WM structures, as revealed by co-registered MRI in a two time-point longitudinal multimodal study. Methods: A 69-year-old female with ALS-FTD underwent 18F-FDG PET, diffusion tensor imaging (DTI), and T1-weighted MRI at baseline (15 months after symptom onset), and 20.4 months later. Cerebral glucose metabolism rate, cortical thickness, cortical area, and WM network changes were measured longitudinally. Results and conclusion: The patient had symptoms and signs of bulbar-onset upper motor neuron (UMN)-predominant ALS with language and behavioral dysfunction. Evaluation at baseline showed bulbar dysfunction, and impaired language and executive function. At follow-up, worsened bulbar and other motor functions, and prominent FTD both reflected significant progression. Cortical thickness and surface area showed differential involvement in the hypometabolic and hypermetabolic regions. WM connections from frontal regions to other brain regions were completely absent by graph theory-based network analysis when compared to temporal regions indicating prominent frontal lobe degeneration. Structural neuroimaging reveals different patterns of GM and WM involvement in the hypometabolic and hypermetabolic brain regions in a patient with ALS-FTD.
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Affiliation(s)
- Venkateswaran Rajagopalan
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science Pilani, Hyderabad, India
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Erik P Pioro
- Department of Neurology, Cleveland Clinic, Cleveland, OH, USA, and
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
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28
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A Multi-Modal MRI Analysis of Cortical Structure in Relation to Gender Dysphoria, Sexual Orientation, and Age in Adolescents. J Clin Med 2021; 10:jcm10020345. [PMID: 33477567 PMCID: PMC7831120 DOI: 10.3390/jcm10020345] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/20/2020] [Accepted: 12/23/2020] [Indexed: 01/18/2023] Open
Abstract
Gender dysphoria (GD) is characterized by distress due to an incongruence between experienced gender and sex assigned at birth. Sex-differentiated brain regions are hypothesized to reflect the experienced gender in GD and may play a role in sexual orientation development. Magnetic resonance brain images were acquired from 16 GD adolescents assigned female at birth (AFAB) not receiving hormone therapy, 17 cisgender girls, and 14 cisgender boys (ages 12–17 years) to examine three morphological and microstructural gray matter features in 76 brain regions: surface area (SA), cortical thickness (CT), and T1 relaxation time. Sexual orientation was represented by degree of androphilia-gynephilia and sexual attraction strength. Multivariate analyses found that cisgender boys had larger SA than cisgender girls and GD AFAB. Shorter T1, reflecting denser, macromolecule-rich tissue, correlated with older age and stronger gynephilia in cisgender boys and GD AFAB, and with stronger attractions in cisgender boys. Thus, cortical morphometry (mainly SA) was related to sex assigned at birth, but not experienced gender. Effects of experienced gender were found as similarities in correlation patterns in GD AFAB and cisgender boys in age and sexual orientation (mainly T1), indicating the need to consider developmental trajectories and sexual orientation in brain studies of GD.
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29
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Abstract
The ability to reason about other people’s thoughts and beliefs characterizes the complex social interaction among humans. This ability, called Theory of Mind (ToM), has long been argued to develop around 4 y when children start explicitly reasoning about others' beliefs. However, when tested nonverbally, infants already show action expectations congruent with others’ beliefs before the age of 2 y. Do these behaviors reflect different systems for understanding others’ minds—an early and a later developing one—or when does ToM develop? We show that these abilities are supported by the maturation of independent brain networks, suggesting different systems for explicit verbal ToM and early nonverbal action expectations. Human social interaction crucially relies on the ability to infer what other people think. Referred to as Theory of Mind (ToM), this ability has long been argued to emerge around 4 y of age when children start passing traditional verbal ToM tasks. This developmental dogma has recently been questioned by nonverbal ToM tasks passed by infants younger than 2 y of age. How do young children solve these tests, and what is their relation to the later-developing verbal ToM reasoning? Are there two different systems for nonverbal and verbal ToM, and when is the developmental onset of mature adult ToM? To address these questions, we related markers of cortical brain structure (i.e., cortical thickness and surface area) of 3- and 4-y-old children to their performance in novel nonverbal and traditional verbal TM tasks. We showed that verbal ToM reasoning was supported by cortical surface area and thickness of the precuneus and temporoparietal junction, classically involved in ToM in adults. Nonverbal ToM reasoning, in contrast, was supported by the cortical structure of a distinct and independent neural network including the supramarginal gyrus also involved in emotional and visual perspective taking, action observation, and social attention or encoding biases. This neural dissociation suggests two systems for reasoning about others’ minds—mature verbal ToM that emerges around 4 y of age, whereas nonverbal ToM tasks rely on different earlier-developing possibly social-cognitive processes.
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30
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Schmitt JE, Raznahan A, Liu S, Neale MC. The genetics of cortical myelination in young adults and its relationships to cerebral surface area, cortical thickness, and intelligence: A magnetic resonance imaging study of twins and families. Neuroimage 2020; 206:116319. [PMID: 31678229 PMCID: PMC7871660 DOI: 10.1016/j.neuroimage.2019.116319] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2019] [Revised: 10/14/2019] [Accepted: 10/26/2019] [Indexed: 11/19/2022] Open
Abstract
The cerebral cortex contains a significant quantity of intracortical myelin, but the genetics of cortical myelination (CM) in humans is not well understood. Relatively novel MRI-derived measures now enable the investigation of cortical myelination in large samples. In this study, we use a genetically-informative neuroimaging sample of 1096 young adult subjects from the Human Connectome Project in order to investigate genetic and environmental variation in CM and its relationships with cerebral surface area (SA) and cortical thickness (CT). We found that genetic factors account for approximately 50% of the observed individual differences in mean cortical myelin, 75% of the variation in total SA, and 85% of the variance in global mean CT. Although significant genetic influences were found throughout the cortex, both CM and SA demonstrated a posterior predominance, with disproportionately strong effects in the parietal and occipital lobes and significantly overlapping heritability maps (p < 0.001). Yet despite showing similar spatial heritability patterns, we found evidence that CM is genetically independent from SA at both global and vertex levels; genetically-mediated relationships between CM and CT were similarly small in magnitude. We also found small but statistically significant genetic associations between NIH Toolbox Total Cognition score and CM in the temporal lobe and insula. SA-cognition and CT-cognition correlations were less widespread compared to CM and both patterns were similar to those reported in prior studies.
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Affiliation(s)
- J Eric Schmitt
- Departments of Radiology and Psychiatry, Division of Neuroradiology, Brain Behavior Laboratory, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
| | - Armin Raznahan
- Developmental Neurogenomics Unit, National Institute of Mental Health, Building 10, Room 4C110, 10 Center Drive, Bethesda, MD, 20892, USA.
| | - Siyuan Liu
- Developmental Neurogenomics Unit, National Institute of Mental Health, Building 10, Room 4C110, 10 Center Drive, Bethesda, MD, 20892, USA.
| | - Michael C Neale
- Departments of Psychiatry and Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA, 23298-980126, USA.
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Kuhl U, Friederici AD, Skeide MA, Friederici AD, Emmrich F, Brauer J, Wilcke A, Neef N, Boltze J, Skeide M, Kirsten H, Schaadt G, Müller B, Kraft I, Czepezauer I, Dörr L. Early cortical surface plasticity relates to basic mathematical learning. Neuroimage 2020; 204:116235. [DOI: 10.1016/j.neuroimage.2019.116235] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Revised: 09/09/2019] [Accepted: 09/27/2019] [Indexed: 01/20/2023] Open
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Ball G, Beare R, Seal ML. Charting shared developmental trajectories of cortical thickness and structural connectivity in childhood and adolescence. Hum Brain Mapp 2019; 40:4630-4644. [PMID: 31313446 PMCID: PMC6865644 DOI: 10.1002/hbm.24726] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 06/05/2019] [Accepted: 07/05/2019] [Indexed: 12/12/2022] Open
Abstract
The cortex is organised into broadly hierarchical functional systems with distinct neuroanatomical characteristics reflected by macroscopic measures of cortical morphology. Diffusion-weighted magnetic resonance imaging allows the delineation of areal connectivity, changes to which reflect the ongoing maturation of white matter tracts. These developmental processes are intrinsically linked with timing coincident with the development of cognitive function. In this study, we use a data-driven multivariate approach, nonnegative matrix factorisation, to define cortical regions that co-vary together across a large paediatric cohort (n = 456) and are associated with specific subnetworks of cortical connectivity. We find that age between 3 and 21 years is associated with accelerated cortical thinning in frontoparietal regions, whereas relative thinning of primary motor and sensory regions is slower. Together, the subject-specific weights of the derived set of cortical components can be combined to predict chronological age. Structural connectivity networks reveal a relative increase in strength in connection within, as opposed to between hemispheres that vary in line with cortical changes. We confirm our findings in an independent sample.
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Affiliation(s)
- Gareth Ball
- Developmental ImagingMurdoch Children's Research InstituteMelbourneVictoriaAustralia
| | - Richard Beare
- Developmental ImagingMurdoch Children's Research InstituteMelbourneVictoriaAustralia
| | - Marc L. Seal
- Developmental ImagingMurdoch Children's Research InstituteMelbourneVictoriaAustralia
- Department of PaediatricsUniversity of MelbourneMelbourneVictoriaAustralia
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Qi T, Schaadt G, Friederici AD. Cortical thickness lateralization and its relation to language abilities in children. Dev Cogn Neurosci 2019; 39:100704. [PMID: 31476670 PMCID: PMC6892251 DOI: 10.1016/j.dcn.2019.100704] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 08/07/2019] [Accepted: 08/21/2019] [Indexed: 10/26/2022] Open
Abstract
The humans' brain asymmetry is observed in the early stages of life and known to change further with age. The developmental trajectory of such an asymmetry has been observed for language, as one of the most lateralized cognitive functions. However, it remains unclear how these age-related changes in structural asymmetry are related to changes in language performance. We collected longitudinal structural magnetic resonance imaging data of children from 5 to 6 years to investigate structural asymmetry development and its linkage to the improvement of language comprehension abilities. Our results showed substantial changes of language performance across time, which were associated with changes of cortical thickness asymmetry in the triangular part of the inferior frontal gyrus (IFG), constituting a portion of Broca's area. This suggests that language improvement is influenced by larger cortical thinning in the left triangular IFG compared to the right. This asymmetry in children's brain at age 5 and 6 years was further associated with the language performance at 7 years. To our knowledge, this is the first longitudinal study to demonstrate that children's improvement in sentence comprehension seems to depend on structural asymmetry changes in the IFG, further highlighting its crucial role in language acquisition.
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Affiliation(s)
- Ting Qi
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Gesa Schaadt
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic of Cognitive Neurology, Medical Faculty, University Leipzig, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Qi T, Schaadt G, Cafiero R, Brauer J, Skeide MA, Friederici AD. The emergence of long-range language network structural covariance and language abilities. Neuroimage 2019; 191:36-48. [DOI: 10.1016/j.neuroimage.2019.02.014] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 01/28/2019] [Accepted: 02/05/2019] [Indexed: 01/12/2023] Open
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