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1. The genetics of spatiotemporal variation in cortical thickness in youth

Author: J. Eric Schmitt, Aaron Alexander-Bloch, Jakob Seidlitz, Armin Raznahan, and Michael C. Neale
Subjects: Biology (General), QH301-705.5
Abstract: Abstract Prior studies have shown strong genetic effects on cortical thickness (CT), structural covariance, and neurodevelopmental trajectories in childhood and adolescence. However, the importance of genetic factors on the induction of spatiotemporal variation during neurodevelopment remains poorly understood. Here, we explore the genetics of maturational coupling by examining 308 MRI-derived regional CT measures in a longitudinal sample of 677 twins and family members. We find dynamic inter-regional genetic covariation in youth, with the emergence of regional subnetworks in late childhood and early adolescence. Three critical neurodevelopmental epochs in genetically-mediated maturational coupling were identified, with dramatic network strengthening near eleven years of age. These changes are associated with statistically-significant (empirical p-value
Published: 2024
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2. Case Report: Low-grade glioma with NF1 loss of function mimicking diffuse intrinsic pontine glioma

Author: Joshua D. Bernstock, Paramesh V. Karandikar, Jason A. Chen, Jakob Seidlitz, Gregory K. Friedman, David M. Meredith, Kevin X. Liu, Daphne Haas-Kogan, David A. Reardon, and Pier Paolo Peruzzi
Subjects: DIPG, pontine glioma, NF1, biopsy-based diagnosis, glioma, Surgery, RD1-811
Abstract: Intrinsic, expansile pontine tumors typically occur in the pediatric population. These tumors characteristically present as diffuse intrinsic pontine glioma (DIPG), which is now considered as diffuse midline glioma (DMG), H3K27-mutated of the pons. DIPG has limited treatment options and a poor prognosis, and the value of tissue diagnosis from an invasive biopsy remains controversial. This study presents the case of a 19-year-old female with clinical and imaging hallmarks of DIPG, who underwent a biopsy of a tumor in the region of the right middle cerebellar peduncle. Her lesional cells were negative for H3K27M alterations and had low-grade histologic features. Next-generation sequencing revealed a frameshift mutation in the NF1 gene as the likely driver mutation. These features suggest a diagnosis of a low-grade glioma associated with NF1 loss of function, with far-reaching consequences regarding both treatment strategy and prognosis. This case provides support for the utility of diagnostic tissue biopsy in cases of suspected DIPG.
Published: 2024
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3. Transcriptional cartography integrates multiscale biology of the human cortex

Author: Konrad Wagstyl, Sophie Adler, Jakob Seidlitz, Simon Vandekar, Travis T Mallard, Richard Dear, Alex R DeCasien, Theodore D Satterthwaite, Siyuan Liu, Petra E Vértes, Russell T Shinohara, Aaron Alexander-Bloch, Daniel H Geschwind, and Armin Raznahan
Subjects: cortex, transcriptomics, neuroimaging, multiscale, Medicine, Science, Biology (General), QH301-705.5
Abstract: The cerebral cortex underlies many of our unique strengths and vulnerabilities, but efforts to understand human cortical organization are challenged by reliance on incompatible measurement methods at different spatial scales. Macroscale features such as cortical folding and functional activation are accessed through spatially dense neuroimaging maps, whereas microscale cellular and molecular features are typically measured with sparse postmortem sampling. Here, we integrate these distinct windows on brain organization by building upon existing postmortem data to impute, validate, and analyze a library of spatially dense neuroimaging-like maps of human cortical gene expression. These maps allow spatially unbiased discovery of cortical zones with extreme transcriptional profiles or unusually rapid transcriptional change which index distinct microstructure and predict neuroimaging measures of cortical folding and functional activation. Modules of spatially coexpressed genes define a family of canonical expression maps that integrate diverse spatial scales and temporal epochs of human brain organization – ranging from protein–protein interactions to large-scale systems for cognitive processing. These module maps also parse neuropsychiatric risk genes into subsets which tag distinct cyto-laminar features and differentially predict the location of altered cortical anatomy and gene expression in patients. Taken together, the methods, resources, and findings described here advance our understanding of human cortical organization and offer flexible bridges to connect scientific fields operating at different spatial scales of human brain research.
Published: 2024
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4. The molecular genetic landscape of human brain size variation

Author: Jakob Seidlitz, Travis T. Mallard, Jacob W. Vogel, Younga H. Lee, Varun Warrier, Gareth Ball, Oskar Hansson, Leanna M. Hernandez, Ayan S. Mandal, Konrad Wagstyl, Michael V. Lombardo, Eric Courchesne, Joseph T. Glessner, Theodore D. Satterthwaite, Richard A.I. Bethlehem, Joshua D. Bernstock, Shinya Tasaki, Bernard Ng, Chris Gaiteri, Jordan W. Smoller, Tian Ge, Raquel E. Gur, Michael J. Gandal, and Aaron F. Alexander-Bloch
Subjects: CP: Neuroscience, Biology (General), QH301-705.5
Abstract: Summary: Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.
Published: 2023
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5. Two human brain systems micro-structurally associated with obesity

Author: Manfred G Kitzbichler, Daniel Martins, Richard AI Bethlehem, Richard Dear, Rafael Romero-Garcia, Varun Warrier, Jakob Seidlitz, Ottavia Dipasquale, Federico Turkheimer, Mara Cercignani, Edward T Bullmore, and Neil A Harrison
Subjects: NODDI, BMI, GWAS, WHR, UK Biobank, Medicine, Science, Biology (General), QH301-705.5
Abstract: The relationship between obesity and human brain structure is incompletely understood. Using diffusion-weighted MRI from ∼30,000 UK Biobank participants, we test the hypothesis that obesity (waist-to-hip ratio, WHR) is associated with regional differences in two micro-structural MRI metrics: isotropic volume fraction (ISOVF), an index of free water, and intra-cellular volume fraction (ICVF), an index of neurite density. We observed significant associations with obesity in two coupled but distinct brain systems: a prefrontal/temporal/striatal system associated with ISOVF and a medial temporal/occipital/striatal system associated with ICVF. The ISOVF~WHR system colocated with expression of genes enriched for innate immune functions, decreased glial density, and high mu opioid (MOR) and other neurotransmitter receptor density. Conversely, the ICVF~WHR system co-located with expression of genes enriched for G-protein coupled receptors and decreased density of MOR and other receptors. To test whether these distinct brain phenotypes might differ in terms of their underlying shared genetics or relationship to maps of the inflammatory marker C-reactive Protein (CRP), we estimated the genetic correlations between WHR and ISOVF (rg = 0.026, P = 0.36) and ICVF (rg = 0.112, P < 9×10−4) as well as comparing correlations between WHR maps and equivalent CRP maps for ISOVF and ICVF (P
Published: 2023
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6. Multivariate genomic architecture of cortical thickness and surface area at multiple levels of analysis

Author: Andrew D. Grotzinger, Travis T. Mallard, Zhaowen Liu, Jakob Seidlitz, Tian Ge, and Jordan W. Smoller
Subjects: Science
Abstract: The current study identifies five genomic subclusters of brain regions for cortical thickness and surface area characterized by high levels of shared genetic signal. These subclusters map onto biological and functional parcellations of the cortex.
Published: 2023
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7. Regional gene expression signatures are associated with sex-specific functional connectivity changes in depression

Author: Aleksandr Talishinsky, Jonathan Downar, Petra E. Vértes, Jakob Seidlitz, Katharine Dunlop, Charles J. Lynch, Heather Whalley, Andrew McIntosh, Fidel Vila-Rodriguez, Zafiris J. Daskalakis, Daniel M. Blumberger, and Conor Liston
Subjects: Science
Abstract: The neural substrates of depression may differ by sex. Here the authors show that depression is associated with distinct brain connectivity changes in men and in women that are explained by sex-specific transcriptomic signatures involving genes previously implicated in synapse function, immune signalling, and depression risk.
Published: 2022
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8. Translational potential of human brain charts

Author: Saashi A. Bedford, Jakob Seidlitz, and Richard A. I. Bethlehem
Subjects: Medicine (General), R5-920
Published: 2022
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9. Multivariate GWAS of psychiatric disorders and their cardinal symptoms reveal two dimensions of cross-cutting genetic liabilities

Author: Travis T. Mallard, Richard Karlsson Linnér, Andrew D. Grotzinger, Sandra Sanchez-Roige, Jakob Seidlitz, Aysu Okbay, Ronald de Vlaming, S. Fleur W. Meddens, Abraham A. Palmer, Lea K. Davis, Elliot M. Tucker-Drob, Kenneth S. Kendler, Matthew C. Keller, Philipp D. Koellinger, and K. Paige Harden
Subjects: psychiatric genetics, psychiatric disorders, transdiagnostic, genome-wide association study, genetic correlation, pleiotropy, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract: Summary: Understanding which biological pathways are specific versus general across diagnostic categories and levels of symptom severity is critical to improving nosology and treatment of psychopathology. Here, we combine transdiagnostic and dimensional approaches to genetic discovery for the first time, conducting a novel multivariate genome-wide association study of eight psychiatric symptoms and disorders broadly related to mood disturbance and psychosis. We identify two transdiagnostic genetic liabilities that distinguish between common forms of psychopathology versus rarer forms of serious mental illness. Biological annotation revealed divergent genetic architectures that differentially implicated prenatal neurodevelopment and neuronal function and regulation. These findings inform psychiatric nosology and biological models of psychopathology, as they suggest that the severity of mood and psychotic symptoms present in serious mental illness may reflect a difference in kind rather than merely in degree.
Published: 2022
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10. Imbalanced social-communicative and restricted repetitive behavior subtypes of autism spectrum disorder exhibit different neural circuitry

Author: Natasha Bertelsen, Isotta Landi, Richard A. I. Bethlehem, Jakob Seidlitz, Elena Maria Busuoli, Veronica Mandelli, Eleonora Satta, Stavros Trakoshis, Bonnie Auyeung, Prantik Kundu, Eva Loth, Guillaume Dumas, Sarah Baumeister, Christian F. Beckmann, Sven Bölte, Thomas Bourgeron, Tony Charman, Sarah Durston, Christine Ecker, Rosemary J. Holt, Mark H. Johnson, Emily J. H. Jones, Luke Mason, Andreas Meyer-Lindenberg, Carolin Moessnang, Marianne Oldehinkel, Antonio M. Persico, Julian Tillmann, Steve C. R. Williams, Will Spooren, Declan G. M. Murphy, Jan K. Buitelaar, the EU-AIMS LEAP group, Simon Baron-Cohen, Meng-Chuan Lai, and Michael V. Lombardo
Subjects: Biology (General), QH301-705.5
Abstract: Natasha Bertelsen et al. develop a computational model to categorize patients with autism spectrum disorder (ASD) into distinct subgroups, based on social-communicative or restricted repetitive behaviors. By integrating publicly available neuroimaging and genetic data, they report neural and molecular signatures in two of these subgroups, altogether highlighting subtle differences in neural circuitry and genomic networks that could underlie phenotypic differences among ASD patients.
Published: 2021
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11. Cortical structural differences in major depressive disorder correlate with cell type-specific transcriptional signatures

Author: Jiao Li, Jakob Seidlitz, John Suckling, Feiyang Fan, Gong-Jun Ji, Yao Meng, Siqi Yang, Kai Wang, Jiang Qiu, Huafu Chen, and Wei Liao
Subjects: Science
Abstract: The correlation between brain structural changes in major depressive disorder (MDD) and gene expression is unclear. Here, the authors explore the correlation between cell type-specific gene expression changes and cortical structural difference in individuals with major depressive disorder.
Published: 2021
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12. Author Correction: Transcriptomic and cellular decoding of regional brain vulnerability to neurogenetic disorders

Author: Jakob Seidlitz, Ajay Nadig, Siyuan Liu, Richard A. I. Bethlehem, Petra E. Vértes, Sarah E. Morgan, František Váša, Rafael Romero-Garcia, François M. Lalonde, Liv S. Clasen, Jonathan D. Blumenthal, Casey Paquola, Boris Bernhardt, Konrad Wagstyl, Damon Polioudakis, Luis de la Torre-Ubieta, Daniel H. Geschwind, Joan C. Han, Nancy R. Lee, Declan G. Murphy, Edward T. Bullmore, and Armin Raznahan
Subjects: Science
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2020
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13. Transcriptomic and cellular decoding of regional brain vulnerability to neurogenetic disorders

Author: Jakob Seidlitz, Ajay Nadig, Siyuan Liu, Richard A. I. Bethlehem, Petra E. Vértes, Sarah E. Morgan, František Váša, Rafael Romero-Garcia, François M. Lalonde, Liv S. Clasen, Jonathan D. Blumenthal, Casey Paquola, Boris Bernhardt, Konrad Wagstyl, Damon Polioudakis, Luis de la Torre-Ubieta, Daniel H. Geschwind, Joan C. Han, Nancy R. Lee, Declan G. Murphy, Edward T. Bullmore, and Armin Raznahan
Subjects: Science
Abstract: How neurodevelopmental disorder-associated risk genes are translated into spatially patterned brain vulnerabilities is unclear. Here, the authors show that disorder-specific patterns of neuroanatomical changes are aligned to brain expression maps of disease risk genes in healthy subjects.
Published: 2020
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14. A comprehensive macaque fMRI pipeline and hierarchical atlas

Author: Benjamin Jung, Paul A. Taylor, Jakob Seidlitz, Caleb Sponheim, Pierce Perkins, Leslie G. Ungerleider, Daniel Glen, and Adam Messinger
Subjects: Stereotaxic, Template, Alignment, Monkey, Nonhuman primate, fMRI analysis, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Functional neuroimaging research in the non-human primate (NHP) has been advancing at a remarkable rate. The increase in available data establishes a need for robust analysis pipelines designed for NHP neuroimaging and accompanying template spaces to standardize the localization of neuroimaging results. Our group recently developed the NIMH Macaque Template (NMT), a high-resolution population average anatomical template and associated neuroimaging resources, providing researchers with a standard space for macaque neuroimaging . Here, we release NMT v2, which includes both symmetric and asymmetric templates in stereotaxic orientation, with improvements in spatial contrast, processing efficiency, and segmentation. We also introduce the Cortical Hierarchy Atlas of the Rhesus Macaque (CHARM), a hierarchical parcellation of the macaque cerebral cortex with varying degrees of detail. These tools have been integrated into the neuroimaging analysis software AFNI to provide a comprehensive and robust pipeline for fMRI processing, visualization and analysis of NHP data. AFNI's new @animal_warper program can be used to efficiently align anatomical scans to the NMT v2 space, and afni_proc.py integrates these results with full fMRI processing using macaque-specific parameters: from motion correction through regression modeling. Taken together, the NMT v2 and AFNI represent an all-in-one package for macaque functional neuroimaging analysis, as demonstrated with available demos for both task and resting state fMRI.
Published: 2021
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15. A collaborative resource platform for non-human primate neuroimaging

Author: Adam Messinger, Nikoloz Sirmpilatze, Katja Heuer, Kep Kee Loh, Rogier B. Mars, Julien Sein, Ting Xu, Daniel Glen, Benjamin Jung, Jakob Seidlitz, Paul Taylor, Roberto Toro, Eduardo A. Garza-Villarreal, Caleb Sponheim, Xindi Wang, R. Austin Benn, Bastien Cagna, Rakshit Dadarwal, Henry C. Evrard, Pamela Garcia-Saldivar, Steven Giavasis, Renée Hartig, Claude Lepage, Cirong Liu, Piotr Majka, Hugo Merchant, Michael P. Milham, Marcello G.P. Rosa, Jordy Tasserie, Lynn Uhrig, Daniel S. Margulies, and P. Christiaan Klink
Subjects: Open science, Resource sharing, Toolbox, Pipeline, Structural, Functional, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field .
Published: 2021
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16. CIVET-Macaque: An automated pipeline for MRI-based cortical surface generation and cortical thickness in macaques

Author: Claude Lepage, Konrad Wagstyl, Benjamin Jung, Jakob Seidlitz, Caleb Sponheim, Leslie Ungerleider, Xindi Wang, Alan C. Evans, and Adam Messinger
Subjects: Surface-based morphometry, Surface registration, Rhesus monkey, Template, Atlas, Primate, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: The MNI CIVET pipeline for automated extraction of cortical surfaces and evaluation of cortical thickness from in-vivo human MRI has been extended for processing macaque brains. Processing is performed based on the NIMH Macaque Template (NMT), as the reference template, with the anatomical parcellation of the surface following the D99 and CHARM atlases. The modifications needed to adapt CIVET to the macaque brain are detailed. Results have been obtained using CIVET-macaque to process the anatomical scans of the 31 macaques used to generate the NMT and another 95 macaques from the PRIME-DE initiative. It is anticipated that the open usage of CIVET-macaque will promote collaborative efforts in data collection and processing, sharing, and automated analyses from which the non-human primate brain imaging field will advance.
Published: 2021
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17. Sharing voxelwise neuroimaging results from rhesus monkeys and other species with Neurovault

Author: Andrew S. Fox, Daniel Holley, Peter Christiaan Klink, Spencer A. Arbuckle, Carol A. Barnes, Jörn Diedrichsen, Sze Chai Kwok, Colin Kyle, J. Andrew Pruszynski, Jakob Seidlitz, XuFeng Zhou, Russell A. Poldrack, and Krzysztof J. Gorgolewski
Subjects: Nonhuman primate, Neuroimaging, Data sharing, PET, fMRI, Animal, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Animal neuroimaging studies can provide unique insights into brain structure and function, and can be leveraged to bridge the gap between animal and human neuroscience. In part, this power comes from the ability to combine mechanistic interventions with brain-wide neuroimaging. Due to their phylogenetic proximity to humans, nonhuman primate neuroimaging holds particular promise. Because nonhuman primate neuroimaging studies are often underpowered, there is a great need to share data amongst translational researchers. Data sharing efforts have been limited, however, by the lack of standardized tools and repositories through which nonhuman neuroimaging data can easily be archived and accessed. Here, we provide an extension of the Neurovault framework to enable sharing of statistical maps and related voxelwise neuroimaging data from other species and template-spaces. Neurovault, which was previously limited to human neuroimaging data, now allows researchers to easily upload and share nonhuman primate neuroimaging results. This promises to facilitate open, integrative, cross-species science while affording researchers the increased statistical power provided by data aggregation. In addition, the Neurovault code-base now enables the addition of other species and template-spaces. Together, these advances promise to bring neuroimaging data sharing to research in other species, for supplemental data, location-based atlases, and data that would otherwise be relegated to a ''file-drawer''. As increasing numbers of researchers share their nonhuman neuroimaging data on Neurovault, this resource will enable novel, large-scale, cross-species comparisons that were previously impossible.
Published: 2021
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18. Dispersion of functional gradients across the adult lifespan

Author: Richard A.I. Bethlehem, Casey Paquola, Jakob Seidlitz, Lisa Ronan, Boris Bernhardt, Cam-CAN Consortium, and Kamen A. Tsvetanov
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Ageing is commonly associated with changes to segregation and integration of functional brain networks, but, in isolation, current network-based approaches struggle to elucidate changes across the many axes of functional organisation. However, the advent of gradient mapping techniques in neuroimaging provides a new means of studying functional organisation in a multi-dimensional connectivity space. Here, we studied ageing and behaviourally-relevant differences in a three-dimensional connectivity space using the Cambridge Centre for Ageing Neuroscience cohort (n = 643). Building on gradient mapping techniques, we developed a set of measures to quantify the dispersion within and between functional communities. We detected a strong shift of the visual network across the adult lifespan from an extreme to a more central position in the 3D gradient space. In contrast, the dispersion distance between transmodal communities (dorsal attention, ventral attention, frontoparietal and default mode) did not change. However, these communities themselves were increasingly dispersed with increasing age, reflecting more dissimilar functional connectivity profiles within each community. Increasing dispersion of frontoparietal, attention and default mode networks, in particular, were associated negatively with cognition, measured by fluid intelligence. By using a technique that explicitly captures the ordering of functional systems in a multi-dimensional hierarchical framework, we identified behaviorally-relevant age-related differences of within and between network organisation. We propose that the study of functional gradients across the adult lifespan could provide insights that may facilitate the development of new strategies to maintain cognitive ability across the lifespan in health and disease.
Published: 2020
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19. A multi-scale cortical wiring space links cellular architecture and functional dynamics in the human brain.

Author: Casey Paquola, Jakob Seidlitz, Oualid Benkarim, Jessica Royer, Petr Klimes, Richard A I Bethlehem, Sara Larivière, Reinder Vos de Wael, Raul Rodríguez-Cruces, Jeffery A Hall, Birgit Frauscher, Jonathan Smallwood, and Boris C Bernhardt
Subjects: Biology (General), QH301-705.5
Abstract: The vast net of fibres within and underneath the cortex is optimised to support the convergence of different levels of brain organisation. Here, we propose a novel coordinate system of the human cortex based on an advanced model of its connectivity. Our approach is inspired by seminal, but so far largely neglected models of cortico-cortical wiring established by postmortem anatomical studies and capitalises on cutting-edge in vivo neuroimaging and machine learning. The new model expands the currently prevailing diffusion magnetic resonance imaging (MRI) tractography approach by incorporation of additional features of cortical microstructure and cortico-cortical proximity. Studying several datasets and different parcellation schemes, we could show that our coordinate system robustly recapitulates established sensory-limbic and anterior-posterior dimensions of brain organisation. A series of validation experiments showed that the new wiring space reflects cortical microcircuit features (including pyramidal neuron depth and glial expression) and allowed for competitive simulations of functional connectivity and dynamics based on resting-state functional magnetic resonance imaging (rs-fMRI) and human intracranial electroencephalography (EEG) coherence. Our results advance our understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human brain organisation. Our evaluations demonstrate the cortical wiring space bridges across scales of neural organisation and can be easily translated to single individuals.
Published: 2020
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20. Cortical morphology at birth reflects spatiotemporal patterns of gene expression in the fetal human brain.

Author: Gareth Ball, Jakob Seidlitz, Jonathan O'Muircheartaigh, Ralica Dimitrova, Daphna Fenchel, Antonios Makropoulos, Daan Christiaens, Andreas Schuh, Jonathan Passerat-Palmbach, Jana Hutter, Lucilio Cordero-Grande, Emer Hughes, Anthony Price, Jo V Hajnal, Daniel Rueckert, Emma C Robinson, and A David Edwards
Subjects: Biology (General), QH301-705.5
Abstract: Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. We compared cortical morphology captured by high-resolution, multimodal magnetic resonance imaging (MRI) in n = 292 healthy newborn infants (mean age at birth = 39.9 weeks) with regional patterns of gene expression in the fetal cortex across gestation (n = 156 samples from 16 brains, aged 12 to 37 postconceptional weeks [pcw]). We tested the hypothesis that noninvasive measures of cortical structure at birth mirror areal differences in cortical gene expression across gestation, and in a cohort of n = 64 preterm infants (mean age at birth = 32.0 weeks), we tested whether cortical alterations observed after preterm birth were associated with altered gene expression in specific developmental cell populations. Neonatal cortical structure was aligned to differential patterns of cell-specific gene expression in the fetal cortex. Principal component analysis (PCA) of 6 measures of cortical morphology and microstructure showed that cortical regions were ordered along a principal axis, with primary cortex clearly separated from heteromodal cortex. This axis was correlated with estimated tissue maturity, indexed by differential expression of genes expressed by progenitor cells and neurons, and engaged in stem cell differentiation, neuron migration, and forebrain development. Preterm birth was associated with altered regional MRI metrics and patterns of differential gene expression in glial cell populations. The spatial patterning of gene expression in the developing cortex was thus mirrored by regional variation in cortical morphology and microstructure at term, and this was disrupted by preterm birth. This work provides a framework to link molecular mechanisms to noninvasive measures of cortical development in early life and highlights novel pathways to injury in neonatal populations at increased risk of neurodevelopmental disorder.
Published: 2020
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21. Sex-biased trajectories of amygdalo-hippocampal morphology change over human development

Author: Ari M. Fish, Ajay Nadig, Jakob Seidlitz, Paul K. Reardon, Catherine Mankiw, Cassidy L. McDermott, Jonathan D. Blumenthal, Liv S. Clasen, Francois Lalonde, Jason P. Lerch, M. Mallar Chakravarty, Russell T. Shinohara, and Armin Raznahan
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: The amygdala and hippocampus are two adjacent allocortical structures implicated in sex-biased and developmentally-emergent psychopathology. However, the spatiotemporal dynamics of amygdalo-hippocampal development remain poorly understood in healthy humans. The current study defined trajectories of volume and shape change for the amygdala and hippocampus by applying a multi-atlas segmentation pipeline (MAGeT-Brain) and semi-parametric mixed-effects spline modeling to 1,529 longitudinally-acquired structural MRI brain scans from a large, single-center cohort of 792 youth (403 males, 389 females) between the ages of 5 and 25 years old. We found that amygdala and hippocampus volumes both follow curvilinear and sexually dimorphic growth trajectories. These sex-biases were particularly striking in the amygdala: males showed a significantly later and slower adolescent deceleration in volume expansion (at age 20 years) than females (age 13 years). Shape analysis localized significant hot-spots of sex-biased anatomical development in sub-regional territories overlying rostral and caudal extremes of the CA1/2 in the hippocampus, and the centromedial nuclear group of the amygdala. In both sexes, principal components analysis revealed close integration of amygdala and hippocampus shape change along two main topographically-organized axes – low vs. high areal expansion, and early vs. late growth deceleration. These results (i) bring greater resolution to our spatiotemporal understanding of amygdalo-hippocampal development in healthy males and females, and (ii) uncover focal sex-differences in the structural maturation of the brain components that may contribute to differences in behavior and psychopathology that emerge during adolescence.
Published: 2020
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22. Characterization of autism spectrum disorder and neurodevelopmental profiles in youth with XYY syndrome

Author: Lisa Joseph, Cristan Farmer, Colby Chlebowski, Laura Henry, Ari Fish, Catherine Mankiw, Anastasia Xenophontos, Liv Clasen, Bethany Sauls, Jakob Seidlitz, Jonathan Blumenthal, Erin Torres, Audrey Thurm, and Armin Raznahan
Subjects: Sex chromosome aneuploidies, Autism spectrum disorder symptoms, Learning disabilities, Adaptive behavior, Cognitive functioning, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Background XYY syndrome is a sex chromosome aneuploidy that occurs in ~ 1/850 male births and is associated with increased risk for neurodevelopmental difficulties. However, the profile of neurodevelopmental impairments, including symptoms of autism spectrum disorder (ASD) in XYY remains poorly understood. This gap in knowledge has persisted in part due to lack of access to patient cohorts with dense and homogeneous phenotypic data. Methods We evaluated a single-center cohort of 64 individuals with XYY aged 5–25 years, using a standardized battery of cognitive and behavioral assessments spanning developmental milestones, IQ, adaptive behavior, academic achievement, behavioral problems, and gold-standard diagnostic instruments for ASD. Our goals were to (i) detail the neurodevelopmental profile of XYY with a focus on ASD diagnostic rates and symptom profiles, (ii) screen phenotypes for potential ascertainment bias effects by contrasting pre- vs. postnatally diagnosed XYY subgroups, and (iii) define major modules of phenotypic variation using graph-theoretical analysis. Results Although there was marked inter-individual variability, the average profile was characterized by some degree of developmental delay, and decreased IQ and adaptive behavior. Impairments were most pronounced for language and socio-communicative functioning. The rate of ASD was 14%, and these individuals exhibited autism symptom profiles resembling those observed in ASD without XYY. Most neurodevelopmental dimensions showed milder impairment among pre- vs. postnatally diagnosed individuals, with clinically meaningful differences in verbal IQ. Feature network analysis revealed three reliably separable modules comprising (i) cognition and academic achievement, (ii) broad domain psychopathology and adaptive behavior, and (iii) ASD-related features. Conclusions By adding granularity to our understanding of neurodevelopmental difficulties in XYY, these findings assist targeted clinical assessment of newly identified cases, motivate greater provision of specialized multidisciplinary support, and inform future efforts to integrate behavioral phenotypes in XYY with neurobiology. Trial registrations ClinicalTrials.gov NCT00001246, “89-M-0006: Brain Imaging of Childhood Onset Psychiatric Disorders, Endocrine Disorders and Healthy Controls.”
Published: 2018
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23. Versatility of nodal affiliation to communities

Author: Maxwell Shinn, Rafael Romero-Garcia, Jakob Seidlitz, František Váša, Petra E. Vértes, and Edward Bullmore
Subjects: Medicine, Science
Abstract: Abstract Graph theoretical analysis of the community structure of networks attempts to identify the communities (or modules) to which each node affiliates. However, this is in most cases an ill-posed problem, as the affiliation of a node to a single community is often ambiguous. Previous solutions have attempted to identify all of the communities to which each node affiliates. Instead of taking this approach, we introduce versatility, V, as a novel metric of nodal affiliation: V ≈ 0 means that a node is consistently assigned to a specific community; V >> 0 means it is inconsistently assigned to different communities. Versatility works in conjunction with existing community detection algorithms, and it satisfies many theoretically desirable properties in idealised networks designed to maximise ambiguity of modular decomposition. The local minima of global mean versatility identified the resolution parameters of a hierarchical community detection algorithm that least ambiguously decomposed the community structure of a social (karate club) network and the mouse brain connectome. Our results suggest that nodal versatility is useful in quantifying the inherent ambiguity of modular decomposition.
Published: 2017
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24. Shifts in myeloarchitecture characterise adolescent development of cortical gradients

Author: Casey Paquola, Richard AI Bethlehem, Jakob Seidlitz, Konrad Wagstyl, Rafael Romero-Garcia, Kirstie J Whitaker, Reinder Vos de Wael, Guy B Williams, NSPN Consortium, Petra E Vértes, Daniel S Margulies, Boris Bernhardt, and Edward T Bullmore
Subjects: adolescence, MRI, microstructure, hierarchy, gradients, transcriptomics, Medicine, Science, Biology (General), QH301-705.5
Abstract: We studied an accelerated longitudinal cohort of adolescents and young adults (n = 234, two time points) to investigate dynamic reconfigurations in myeloarchitecture. Intracortical profiles were generated using magnetization transfer (MT) data, a myelin-sensitive magnetic resonance imaging contrast. Mixed-effect models of depth specific intracortical profiles demonstrated two separate processes i) overall increases in MT, and ii) flattening of the MT profile related to enhanced signal in mid-to-deeper layers, especially in heteromodal and unimodal association cortices. This development was independent of morphological changes. Enhanced MT in mid-to-deeper layers was found to spatially co-localise specifically with gene expression markers of oligodendrocytes. Interregional covariance analysis revealed that these intracortical changes contributed to a gradual differentiation of higher-order from lower-order systems. Depth-dependent trajectories of intracortical myeloarchitectural development contribute to the maturation of structural hierarchies in the human neocortex, providing a model for adolescent development that bridges microstructural and macroscopic scales of brain organisation.
Published: 2019
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25. Microstructural and functional gradients are increasingly dissociated in transmodal cortices.

Author: Casey Paquola, Reinder Vos De Wael, Konrad Wagstyl, Richard A I Bethlehem, Seok-Jun Hong, Jakob Seidlitz, Edward T Bullmore, Alan C Evans, Bratislav Misic, Daniel S Margulies, Jonathan Smallwood, and Boris C Bernhardt
Subjects: Biology (General), QH301-705.5
Abstract: While the role of cortical microstructure in organising neural function is well established, it remains unclear how structural constraints can give rise to more flexible elements of cognition. While nonhuman primate research has demonstrated a close structure-function correspondence, the relationship between microstructure and function remains poorly understood in humans, in part because of the reliance on post mortem analyses, which cannot be directly related to functional data. To overcome this barrier, we developed a novel approach to model the similarity of microstructural profiles sampled in the direction of cortical columns. Our approach was initially formulated based on an ultra-high-resolution 3D histological reconstruction of an entire human brain and then translated to myelin-sensitive magnetic resonance imaging (MRI) data in a large cohort of healthy adults. This novel method identified a system-level gradient of microstructural differentiation traversing from primary sensory to limbic regions that followed shifts in laminar differentiation and cytoarchitectural complexity. Importantly, while microstructural and functional gradients described a similar hierarchy, they became increasingly dissociated in transmodal default mode and fronto-parietal networks. Meta-analytic decoding of these topographic dissociations highlighted involvement in higher-level aspects of cognition, such as cognitive control and social cognition. Our findings demonstrate a relative decoupling of macroscale functional from microstructural gradients in transmodal regions, which likely contributes to the flexible role these regions play in human cognition.
Published: 2019
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26. Audiovisual Delay as a Novel Cue to Visual Distance.

Author: Philip Jaekl, Jakob Seidlitz, Laurence R Harris, and Duje Tadin
Subjects: Medicine, Science
Abstract: For audiovisual sensory events, sound arrives with a delay relative to light that increases with event distance. It is unknown, however, whether humans can use these ubiquitous sound delays as an information source for distance computation. Here, we tested the hypothesis that audiovisual delays can both bias and improve human perceptual distance discrimination, such that visual stimuli paired with auditory delays are perceived as more distant and are thereby an ordinal distance cue. In two experiments, participants judged the relative distance of two repetitively displayed three-dimensional dot clusters, both presented with sounds of varying delays. In the first experiment, dot clusters presented with a sound delay were judged to be more distant than dot clusters paired with equivalent sound leads. In the second experiment, we confirmed that the presence of a sound delay was sufficient to cause stimuli to appear as more distant. Additionally, we found that ecologically congruent pairing of more distant events with a sound delay resulted in an increase in the precision of distance judgments. A control experiment determined that the sound delay duration influencing these distance judgments was not detectable, thereby eliminating decision-level influence. In sum, we present evidence that audiovisual delays can be an ordinal cue to visual distance.
Published: 2015
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27. Intrinsic activity development unfolds along a sensorimotor–association cortical axis in youth

Author: Valerie J. Sydnor, Bart Larsen, Jakob Seidlitz, Azeez Adebimpe, Aaron F. Alexander-Bloch, Dani S. Bassett, Maxwell A. Bertolero, Matthew Cieslak, Sydney Covitz, Yong Fan, Raquel E. Gur, Ruben C. Gur, Allyson P. Mackey, Tyler M. Moore, David R. Roalf, Russell T. Shinohara, and Theodore D. Satterthwaite
Subjects: General Neuroscience
Published: 2023
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28. Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder

Author: Amanda M. Buch, Petra E. Vértes, Jakob Seidlitz, So Hyun Kim, Logan Grosenick, and Conor Liston
Subjects: General Neuroscience
Published: 2023
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29. Traumatic stress load and stressor reactivity score associated with accelerated gray matter maturation in youths indexed by normative models

Author: Ting Yat Wong, Tyler M. Moore, Jakob Seidlitz, Kenneth S. L. Yuen, Kosha Ruparel, Ran Barzilay, Monica E. Calkins, Aaron F. Alexander-Bloch, Theodore D. Satterthwaite, Raquel E. Gur, and Ruben C. Gur
Subjects: Cellular and Molecular Neuroscience, Psychiatry and Mental health, Molecular Biology
Published: 2022
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30. Mapping human brain charts cross-sectionally and longitudinally

Author: Maria A. Di Biase, Ye Ella Tian, Richard A. I. Bethlehem, Jakob Seidlitz, Aaron. F. Alexander-Bloch, B.T. Thomas Yeo, and Andrew Zalesky
Subjects: Multidisciplinary
Abstract: Brain scans acquired across large, age-diverse cohorts have facilitated recent progress in establishing normative brain aging charts. Here, we ask the critical question of whether cross-sectional estimates of age-related brain trajectories resemble those directly measured from longitudinal data. We show that age-related brain changes inferred from cross-sectionally mapped brain charts can substantially underestimate actual changes measured longitudinally. We further find that brain aging trajectories vary markedly between individuals and are difficult to predict with population-level age trends estimated cross-sectionally. Prediction errors relate modestly to neuroimaging confounds and lifestyle factors. Our findings provide explicit evidence for the importance of longitudinal measurements in ascertaining brain development and aging trajectories.
Published: 2023
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31. Integrative transcriptomic and metabolic analyses of the mammalian hibernating brain identifies a key role for succinate dehydrogenase in ischemic tolerance

Author: Joshua D. Bernstock, Cory M. Willis, Monica Emili Garcia-Segura, Edoardo Gaude, Daniela Anni, Yan-ja Lee, Luke W. Thomas, Alva Casey, Nunzio Vicario, Tommaso Leonardi, Alexandra M. Nicaise, Florian A. Gessler, Saef Izzy, Mario R. Buffelli, Jakob Seidlitz, Shriya Srinivasan, Michael P. Murphy, Margaret Ashcroft, Marco Cambiaghi, John M. Hallenbeck, and Luca Peruzzotti-Jametti
Subjects: Article
Abstract: Ischemic stroke results in a loss of tissue homeostasis and integrity, the underlying pathobiology of which stems primarily from the depletion of cellular energy stores and perturbation of available metabolites1. Hibernation in thirteen-lined ground squirrels (TLGS),Ictidomys tridecemlineatus, provides a natural model of ischemic tolerance as these mammals undergo prolonged periods of critically low cerebral blood flow without evidence of central nervous system (CNS) damage2. Studying the complex interplay of genes and metabolites that unfolds during hibernation may provide novel insights into key regulators of cellular homeostasis during brain ischemia. Herein, we interrogated the molecular profiles of TLGS brains at different time points within the hibernation cycle via RNA sequencing coupled with untargeted metabolomics. We demonstrate that hibernation in TLGS leads to major changes in the expression of genes involved in oxidative phosphorylation and this is correlated with an accumulation of the tricarboxylic acid (TCA) cycle intermediates citrate, cis-aconitate, and α-ketoglutarate-αKG. Integration of the gene expression and metabolomics datasets led to the identification of succinate dehydrogenase (SDH) as the critical enzyme during hibernation, uncovering a break in the TCA cycle at that level. Accordingly, the SDH inhibitor dimethyl malonate (DMM) was able to rescue the effects of hypoxia on human neuronal cellsin vitroand in mice subjected to permanent ischemic strokein vivo. Our findings indicate that studying the regulation of the controlled metabolic depression that occurs in hibernating mammals may lead to novel therapeutic approaches capable of increasing ischemic tolerance in the CNS.
Published: 2023

32. The Influence of Pandemic-Related Worries During Pregnancy on Child Development at 12 Months

Author: Lauren K. White, Megan M. Himes, Rebecca Waller, Wanjikũ F.M. Njoroge, Barbara H. Chaiyachati, Ran Barzilay, Sara L. Kornfield, Heather H. Burris, Jakob Seidlitz, Julia Parish-Morris, Rebecca G. Brady, Emily D. Gerstein, Nina Laney, Raquel E. Gur, and Andrea Duncan
Abstract: The COVID-19 pandemic has been linked to increased risk for perinatal anxiety and depression among parents, as well as negative consequences for child development. Less is known about how worries arising from the pandemic during pregnancy are related to later child development, nor if resilience factors buffer negative consequences. The current study addresses this question in a prospective longitudinal design. Data was collected from a sub-study (n = 184) of a longitudinal study of pregnant individuals (total n = 1,173). During pregnancy (April 17-July 8, 2020) and the early postpartum period (August 11, 2020-March 2, 2021), participants completed online surveys. At 12 months postpartum (June 17, 2021-March 23, 2022), participants completed online surveys and a virtual laboratory visit, which included parent-child interaction tasks. We found more pregnancy-specific pandemic worries were prospectively related to lower levels of child socioemotional development based on parent report (B=-1.13, SE = .43, p = .007) and observer ratings (B=-0.13, SE = .07, p = .045), but not to parent-reported general developmental milestones. Parental emotion regulation in the early postpartum period moderated the association between pregnancy-specific pandemic worries and child socioemotional development such that pregnancy-specific pandemic worries did not related to worse child socioemotional development among parents with high (B=-.02, SE = .10, t=-.14, p = .89) levels of emotion regulation. Findings suggest the negative consequences of parental worry and distress during pregnancy on the early socioemotional development of children in the context of the COVID-19 pandemic. Results highlight that parental emotion regulation may represent a target for intervention to promote parental resilience and support optimized child development.
Published: 2023
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33. Brain growth charts of 'clinical controls' for quantitative analysis of clinically acquired brain MRI

Author: Jenna M. Schabdach, J. Eric Schmitt, Susan Sotardi, Arastoo Vossough, Savvas Andronikou, Timothy P. Roberts, Hao Huang, Viveknarayanan Padmanabhan, Alfredo Oritz-Rosa, Margaret Gardner, Sydney Covitz, Saashi A. Bedford, Ayan Mandal, Barbara H. Chaiyachati, Simon R. White, Ed Bullmore, Richard A.I. Bethlehem, Russell T. Shinohara, Benjamin Billot, J. Eugenio Iglesias, Satrajit Ghosh, Raquel E. Gur, Theodore D. Satterthwaite, David Roalf, Jakob Seidlitz, and Aaron Alexander-Bloch
Abstract: BackgroundBrain MRIs acquired in clinical settings represent a valuable and underutilized scientific resource for investigating neurodevelopment. Utilization of these clinical scans has been limited because of their clinical acquisition and technical heterogeneity. These barriers have curtailed the interpretability and scientific value of retrospective studies of clinically acquired brain MRIs, compared to studies of prospectively acquired research quality brain MRIs.PurposeTo develop a scalable and rigorous approach to generate clinical brain growth chart models, to benchmark neuroanatomical differences in clinical MRIs, and to validate clinically-derived brain growth charts against those derived from large-scale research studies.Materials and MethodsWe curated a set of clinical MRIScans withLimitedImagingPathology (SLIP) – so-called “clinical controls” – from an urban pediatric healthcare system acquired between 2005 and 2020. The curation process included manual review of signed radiology reports, as well as automated and manual quality review of images without gross pathology. We measured global and regional volumetric imaging phenotypes in the SLIP sample using two alternative, advanced image processing pipelines, and quantitatively compared clinical brain growth charts to research brain growth charts derived from >123,000 MRIs.ResultsThe curated SLIP dataset included 372 patients scanned between the ages of 28 days post-birth and 22.2 years across nine 3T MRI scanners. Clinical brain growth charts were highly similar to growth charts derived from large-scale research datasets, in terms of the normative developmental trajectories predicted by the models. The clinical indication of the scans did not significantly bias the output of clinical brain charts. Tens of thousands of additional healthcare system scans meet inclusion criteria to be included in future brain growth charts.ConclusionBrain charts derived from clinical-controls are highly similar to brain charts from research-controls, suggesting that curated clinical scans could be used to supplement research datasets.Summary StatementBrain growth charts of pediatric clinical MRIs with limited imaging pathology (N=372) are highly correlated with charts from a large aggregated set of research controls (N>120,000).Key ResultsA cohort of brain MRI scans with limited reported imaging pathology (N=372, 186 female; ages 0.07 - 22.2 years, median = 10.2) were identified using signed radiology reports and processed using two segmentation pipelines. Growth charts generated from these scans are highly correlated with growth charts from a large aggregated set of research controls (r range 0.990 - 0.999). There was no evidence of bias due to the reason for each scan.
Published: 2023
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34. Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging

Author: František Váša, Harriet Hobday, Ryan A. Stanyard, Richard E. Daws, Vincent Giampietro, Owen O'Daly, David J. Lythgoe, Jakob Seidlitz, Stefan Skare, Steven C. R. Williams, Andre F. Marquand, Robert Leech, and James H. Cole
Subjects: Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Neurology, Radiological and Ultrasound Technology, Brain, Humans, Reproducibility of Results, 220 Statistical Imaging Neuroscience, Neuroimaging, Radiology, Nuclear Medicine and imaging, Neurology (clinical), Anatomy, Magnetic Resonance Imaging, Multimodal Imaging
Abstract: Contains fulltext : 248878.pdf (Publisher’s version ) (Open Access) Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T(1) -weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T(1) -FLAIR, T(2) , T(2) *, T(2) -FLAIR, DWI and ADC contrasts, acquired in ~1 min), as well as to slower, more standard single-contrast T(1) -weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix T(1) -FLAIR and single-contrast T(1) -weighted scans, using correlations between voxels and regions of interest across participants, measures of within- and between-participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix-derived data using test-retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients.
Published: 2021
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35. Prefrontal connectomics: from anatomy to human imaging

Author: Suzanne N. Haber, Hesheng Liu, Jakob Seidlitz, and Edward T. Bullmore
Subjects: Nervous system, Connectomics, Computer science, Prefrontal Cortex, Neuroimaging, Network science, Review Article, Neural Pathways, Connectome, medicine, Animals, Humans, Prefrontal cortex, Pharmacology, Information processing, Brain, Cognition, Human brain, Magnetic Resonance Imaging, Psychiatry and Mental health, medicine.anatomical_structure, Nerve Net, Neuroscience
Abstract: The fundamental importance of prefrontal cortical connectivity to information processing and, therefore, disorders of cognition, emotion, and behavior has been recognized for decades. Anatomic tracing studies in animals have formed the basis for delineating the direct monosynaptic connectivity, from cells of origin, through axon trajectories, to synaptic terminals. Advances in neuroimaging combined with network science have taken the lead in developing complex wiring diagrams or connectomes of the human brain. A key question is how well these magnetic resonance imaging (MRI)-derived networks and hubs reflect the anatomic “hard wiring” first proposed to underlie the distribution of information for large-scale network interactions. In this review, we address this challenge by focusing on what is known about monosynaptic prefrontal cortical connections in non-human primates and how this compares to MRI-derived measurements of network organization in humans. First, we outline the anatomic cortical connections and pathways for each prefrontal cortex (PFC) region. We then review the available MRI-based techniques for indirectly measuring structural and functional connectivity, and introduce graph theoretical methods for analysis of hubs, modules, and topologically integrative features of the connectome. Finally, we bring these two approaches together, using specific examples, to demonstrate how monosynaptic connections, demonstrated by tract-tracing studies, can directly inform understanding of the composition of PFC nodes and hubs, and the edges or pathways that connect PFC to cortical and subcortical areas.
Published: 2021
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36. Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology

Author: Aaron Alexander-Bloch, Theodore D. Satterthwaite, Armin Raznahan, Michael P. Milham, Damien A. Fair, Allyson P. Mackey, Ting Xu, Danielle S. Bassett, Bart Larsen, Jakob Seidlitz, Adam Pines, David R. Roalf, Conor Liston, and Valerie J. Sydnor
Subjects: Cerebral Cortex, Neuronal Plasticity, Psychopathology, Socioemotional selectivity theory, Mental Disorders, General Neuroscience, Neuroimaging, Sensory system, Human brain, Biology, Article, medicine.anatomical_structure, Mentalization, medicine, Animals, Humans, Nerve Net, Association (psychology), Neuroscience
Abstract: Summary The human brain undergoes a prolonged period of cortical development that spans multiple decades. During childhood and adolescence, cortical development progresses from lower-order, primary and unimodal cortices with sensory and motor functions to higher-order, transmodal association cortices subserving executive, socioemotional, and mentalizing functions. The spatiotemporal patterning of cortical maturation thus proceeds in a hierarchical manner, conforming to an evolutionarily rooted, sensorimotor-to-association axis of cortical organization. This developmental program has been characterized by data derived from multimodal human neuroimaging and is linked to the hierarchical unfolding of plasticity-related neurobiological events. Critically, this developmental program serves to enhance feature variation between lower-order and higher-order regions, thus endowing the brain's association cortices with unique functional properties. However, accumulating evidence suggests that protracted plasticity within late-maturing association cortices, which represents a defining feature of the human developmental program, also confers risk for diverse developmental psychopathologies.
Published: 2021
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37. Two human brain systems micro-structurally associated with obesity

Author: Manfred G Kitzbichler, Daniel Martins, Richard AI Bethlehem, Richard Dear, Rafael Romero-Garcia, Varun Warrier, Jakob Seidlitz, Ottavia Dipasquale, Federico Turkheimer, Mara Cercignani, Edward T Bullmore, and Neil A Harrison
Abstract: The relationship between obesity and brain structure is incompletely understood. Using diffusion-weighted MRI from ∼30,000 UK Biobank participants we test the hypothesis that obesity (waist-to-hip ratio, WHR) is associated with regional differences in two micro-structural MRI metrics: isotropic volume fraction (ISOVF), an index of free water, and intra-cellular volume fraction (ICVF), an index of neurite density. We observed significant associations with obesity in two coupled but distinct brain systems: a prefrontal-temporal-striatal system associated with ISOVF and a medial temporal-occipital-striatal system associated with ICVF. The ISOVF∼WHR system colocated with expression of genes enriched for innate immune functions, decreased glial density, and high mu opioid (MOR) and other neurotransmitter receptor density. Conversely, the ICVF∼WHR system co-located with expression of genes enriched for G-protein coupled receptors and decreased density of MOR and other receptors. To test whether these distinct brain phenotypes might differ in terms of their underlying shared genetics or relationship to maps of the inflammatory marker C-reactive Protein (CRP), we estimated the genetic correlations between WHR and ISOVF (rg= 0.026,P= 0.36) and ICVF (rg= 0.112,P <9 × 10−4) as well as comparing correlations between WHR maps and equivalent CRP maps for ISOVF and ICVF (p
Published: 2022
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38. Cortical morphometric vulnerability to generalised epilepsy reflects chromosome‐ and cell type‐specific transcriptomic signatures

Author: Jiao Li, Simon S. Keller, Jakob Seidlitz, Huafu Chen, Bing Li, Yifei Weng, Yao Meng, Siqi Yang, Qiang Xu, Qirui Zhang, Fang Yang, Guangming Lu, Boris C. Bernhardt, Zhiqiang Zhang, and Wei Liao
Subjects: Histology, Neurology, Physiology (medical), Neurology (clinical), Pathology and Forensic Medicine
Abstract: Generalised epilepsy is thought to involve distributed brain networks. However, the molecular and cellular factors that render different brain regions more vulnerable to epileptogenesis remain largely unknown. We aimed to investigate epilepsy-related morphometric similarity network (MSN) abnormalities at the macroscale level and their relationships with microscale gene expressions at the microscale level.We compared the MSN of genetic generalised epilepsy with generalised tonic-clonic seizure patients (GGE-GTCS, n = 101) to demographically matched healthy controls (HC, n = 150). Cortical MSNs were estimated by combining seven morphometric features derived from structural magnetic resonance imaging for each individual. Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen Human Brain Atlas.GGE-GTCS patients exhibited decreased regional MSNs in primary motor, prefrontal and temporal regions and increases in occipital, insular and posterior cingulate cortices, when compared with the HC. These case-control neuroimaging differences were validated using split-half analyses and were not affected by medication or drug response effects. When assessing associations with gene expression, genes associated with GGE-GTCS-related MSN differences were enriched in several biological processes, including 'synapse organisation', 'neurotransmitter transport' pathways and excitatory/inhibitory neuronal cell types. Collectively, the GGE-GTCS-related cortical vulnerabilities were associated with chromosomes 4, 5, 11 and 16 and were dispersed bottom-up at the cellular, pathway and disease levels, which contributed to epileptogenesis, suggesting diverse neurobiologically relevant enrichments in GGE-GTCS.By bridging the gaps between transcriptional signatures and in vivo neuroimaging, we highlighted the importance of using MSN abnormalities of the human brain in GGE-GTCS patients to investigate disease-relevant genes and biological processes.
Published: 2022
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39. MIND Networks: Robust Estimation of Structural Similarity from Brain MRI

Author: Isaac Sebenius, Jakob Seidlitz, Varun Warrier, Richard A I Bethlehem, Aaron Alexander-Bloch, Travis T Mallard, Rafael Romero Garcia, Edward T Bullmore, and Sarah E Morgan
Abstract: Structural similarity networks are a central focus of magnetic resonance imaging (MRI) research into human brain connectomes in health and disease. We present Morphometric INverse Divergence (MIND), a robust method to estimate within-subject structural similarity between cortical areas based on the Kullback-Leibler divergence between the multivariate distributions of their structural features. Compared to the prior approach of morphometric similarity networks (MSNs) on N>10,000 data from the ABCD cohort, MIND networks were more consistent with known cortical symmetry, cytoarchitecture, and (in N=19 macaques) gold-standard tract-tracing connectivity, and were more invariant to cortical parcellation. Importantly, MIND networks were remarkably coupled with cortical gene co-expression, providing fresh evidence for the unified architecture of brain structure and transcription. Using kinship (N=1282) and genetic data (N=4085), we characterized the heritability of MIND phenotypes, identifying stronger genetic influence on the relationship between structurally divergent regions compared to structurally similar regions. Overall, MIND presents a biologically-validated lens for analyzing the structural organization of the cortex using readily-available MRI measurements.
Published: 2022
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40. Three transcriptional axes underpin anatomy, development, and disorders of the human cortex

Author: Aurina Arnatkeviciute, Richard A.I. Bethlehem, Konrad Wagstyl, Ross Markello, Petra E. Vértes, Jakob Seidlitz, and Richard Dear
Abstract: The Allen Human Brain Atlas (AHBA) has catalysed many discoveries linking macroscale brain organisation to microscale neurobiology, including the existence of a transcriptional axis stretching from sensorimotor to association cortices. However, the complex spatial structure of the human cortex likely includes multiple gradients of gene expression that have yet to be characterised. Here, we reveal two additional transcriptional axes that are anatomically differentiated and have distinct profiles of metabolic and immune function, cytoarchitecture, and developmental trajectory. Moreover, we validate the three transcriptional axes in external data, show they explain more than half of spatial variation across key anatomical and functional neuroimaging maps, and demonstrate they are dissociably aligned with maps of autism, depression, and schizophrenia from one of the largest case-control imaging datasets. Together, these results reveal how human brain anatomy, development, and disorders are patterned along multiple cortical axes underpinned by the intrinsic structure of gene transcription.
Published: 2022
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41. Assessing a multivariate model of brain-mediated genetic influences on disordered eating in the ABCD cohort

Author: Margaret L. Westwater, Travis T. Mallard, Varun Warrier, Richard A.I. Bethlehem, Dustin Scheinost, Christian Grillon, Paul C. Fletcher, Jakob Seidlitz, and Monique Ernst
Abstract: Eating disorders (EDs) are complex psychiatric conditions that often emerge during adolescence, and affected individuals frequently demonstrate high rates of psychiatric comorbidity, particularly with depressive and anxiety disorders. Although risk for EDs reflects both genetic and neurobiological factors, knowledge of how genetic risk for EDs relates to neurobiology and psychiatric symptoms during critical developmental periods remains limited. We therefore implemented a novel multivariate framework, which sought to advance knowledge of the etiology of EDs by simultaneously estimating associations between genetic risk, brain structure and ED-related psychopathology symptoms in over 4,500 adolescents of European ancestry from the Adolescent Brain and Cognitive Development study (M(SD)age=119.29(7.49) months). Polygenic scores for anorexia nervosa (AN PGS) and body mass index (BMI PGS) were generated and related to three morphometric brain features— cortical thickness, surface area and subcortical grey matter volume—and to latent psychopathology factors using structural equation modeling. We identified a three-factor structure of ED-related psychopathology symptoms: eating, distress and fear factors. Increased BMI PGS were uniquely associated with greater eating factor scores, whereas AN PGS were unrelated to psychopathology factors. Moreover, genetic risk for high BMI and for AN had distinct neural correlates, where greater BMI PGS predicted widespread increases in cortical thickness and reductions in surface area while AN PGS were nominally related to reduced caudate volume. Altered default mode and visual network thickness was associated with greater eating factor scores, whereas distress and fear factor scores reflected a shared reduction in somatomotor network thickness. Our novel findings indicate that greater genetic risk for high BMI and altered cortical thickness of canonical brain networks underpin ED symptomatology in early adolescence. As neurobiological factors appear to shape disordered eating earlier in the life course than previously thought, these results underscore the need for early detection and intervention efforts for EDs.
Published: 2022
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42. Conserved whole-brain spatiomolecular gradients shape adult brain functional organization

Author: Jacob W Vogel, Aaron Alexander-Bloch, Konrad Wagstyl, Maxwell Bertolero, Ross Markello, Adam Pines, Valerie J Sydnor, Alex Diaz-Papkovich, Justine Hansen, Alan C Evans, Boris Bernhardt, Bratislav Misic, Theodore Satterthwaite, and Jakob Seidlitz
Abstract: Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, how these gradients relate to adult brain function, and whether they are maintained in the adult brain, remains unknown. Here we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately predicts the location of unseen brain tissue samples, ii) delineates known functional territories, and iii) explains the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical functional hierarchies differentiating primary sensory cortex from association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two non-human primate datasets, and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well known morphogens (e.g., PAX6 and SIX3), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.
Published: 2022
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43. The genetics of cortical organisation and development: A study of 2,347 neuroimaging phenotypes

Author: Varun Warrier, Eva-Maria Stauffer, Qin Qin Huang, Emilie M. Wigdor, Eric A.W. Slob, Jakob Seidlitz, Lisa Ronan, Sofie Valk, Travis T. Mallard, Andrew D. Grotzinger, Rafael Romero-Garcia, Simon Baron-Cohen, Daniel H. Geschwind, Madeline Lancaster, Graham K. Murray, Michael J. Gandal, Aaron Alexander-Bloch, Hyejung Won, Hilary C. Martin, Edward T. Bullmore, Richard A.I. Bethlehem, and Apollo - University of Cambridge Repository
Abstract: Our understanding of the genetic architecture of the human cerebral cortex is limited both in terms of the diversity of brain structural phenotypes and the anatomical granularity of their associations with genetic variants. Here, we conducted genome-wide association meta-analysis of 13 structural and diffusion magnetic resonance imaging derived cortical phenotypes, measured globally and at 180 bilaterally averaged regions in 36,843 individuals from the UK Biobank and the ABCD cohorts. These phenotypes include cortical thickness, surface area, grey matter volume, and measures of folding, neurite density, and water diffusion. We identified 4,349 experiment-wide significant loci associated with global and regional phenotypes. Multiple lines of analyses identified four genetic latent structures and causal relationships between surface area and some measures of cortical folding. These latent structures partly relate to different underlying gene expression trajectories during development and are enriched for different cell types. We also identified differential enrichment for neurodevelopmental and constrained genes and demonstrate that common genetic variants associated with surface area and volume specifically are associated with cephalic disorders. Finally, we identified complex inter-phenotype and inter-regional genetic relationships among the 13 phenotypes which reflect developmental differences among them. These analyses help refine the role of common genetic variants in human cortical development and organisation.One sentence summaryGWAS of 2,347 neuroimaging phenotypes shed light on the global and regional genetic organisation of the cortex, underlying cellular and developmental processes, and links to neurodevelopmental and cephalic disorders.
Published: 2022

44. Grey and white matter microstructure is associated with polygenic risk for schizophrenia

Author: Edward T. Bullmore, Graham K. Murray, Jakob Seidlitz, Rafael Romero-Garcia, Richard A. I. Bethlehem, Varun Warrier, and Eva-Maria Stauffer
Subjects: education.field_of_study, Population, Brain morphometry, Biology, medicine.disease, White matter, Cellular and Molecular Neuroscience, Psychiatry and Mental health, medicine.anatomical_structure, Schizophrenia, Mendelian randomization, Fractional anisotropy, medicine, Mechanisms of schizophrenia, education, Molecular Biology, Neuroscience, Insula
Abstract: Recent discovery of approximately 270 common genetic variants associated with schizophrenia has enabled polygenic risk scores (PRS) to be measured in the population. We hypothesized that normal variation in PRS would be associated with magnetic resonance imaging (MRI) phenotypes of brain morphometry and tissue composition. We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (Nmax = 29,878) who had multiple micro- and macrostructural MRI metrics measured at each of 180 cortical areas, seven subcortical structures, and 15 major white matter tracts. Linear mixed-effect models were used to investigate associations between PRS and brain structure at global and regional scales, controlled for multiple comparisons. Polygenic risk was significantly associated with reduced neurite density index (NDI) at global brain scale, at 149 cortical regions, five subcortical structures, and 14 white matter tracts. Other microstructural parameters, e.g., fractional anisotropy, that were correlated with NDI were also significantly associated with PRS. Genetic effects on multiple MRI phenotypes were co-located in temporal, cingulate, and prefrontal cortical areas, insula, and hippocampus. Post-hoc bidirectional Mendelian randomization analyses provided preliminary evidence in support of a causal relationship between (reduced) thalamic NDI and (increased) risk of schizophrenia. Risk-related reduction in NDI is plausibly indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks. Cortical, subcortical, and white matter microstructure may be linked to the genetic mechanisms of schizophrenia.
Published: 2021
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45. Regional White Matter Scaling in the Human Brain

Author: Theodore D. Satterthwaite, Amanda L. Rodrigue, Tyler M. Moore, Siyuan Liu, David R. Roalf, Edward T. Bullmore, Cassidy L. McDermott, David C. Glahn, Armin Raznahan, Jakob Seidlitz, Ajay Nadig, Ruben C. Gur, Allysa Warling, and Raquel E. Gur
Subjects: Adult, Male, Adolescent, Splenium, Biology, Corpus callosum, Corpus Callosum, Cohort Studies, White matter, Young Adult, Neuroimaging, Cortex (anatomy), Fractional anisotropy, Image Processing, Computer-Assisted, medicine, Humans, Gray Matter, Child, Research Articles, Biological Variation, Individual, General Neuroscience, Brain, Reproducibility of Results, Organ Size, Human brain, Magnetic Resonance Imaging, White Matter, Diffusion Magnetic Resonance Imaging, medicine.anatomical_structure, Nonlinear Dynamics, Brain size, Anisotropy, Female, Neuroscience
Abstract: Anatomical organization of the primate cortex varies as a function of total brain size, where possession of a larger brain is accompanied by disproportionate expansion of associative cortices alongside a relative contraction of sensorimotor systems. However, equivalent scaling maps are not yet available for regional white matter anatomy. Here, we use three large-scale neuroimaging datasets to examine how regional white matter volume (WMV) scales with interindividual variation in brain volume among typically developing humans (combined N = 2391: 1247 females, 1144 males). We show that WMV scaling is regionally heterogeneous: larger brains have relatively greater WMV in anterior and posterior regions of cortical white matter, as well as the genu and splenium of the corpus callosum, but relatively less WMV in most subcortical regions. Furthermore, regions of positive WMV scaling tend to connect previously-defined regions of positive gray matter scaling in the cortex, revealing a coordinated coupling of regional gray and white matter organization with naturally occurring variations in human brain size. However, we also show that two commonly studied measures of white matter microstructure, fractional anisotropy (FA) and magnetization transfer (MT), scale negatively with brain size, and do so in a manner that is spatially unlike WMV scaling. Collectively, these findings provide a more complete view of anatomic scaling in the human brain, and offer new contexts for the interpretation of regional white matter variation in health and disease. SIGNIFICANCE STATEMENT Recent work has shown that, in humans, regional cortical and subcortical anatomy show systematic changes as a function of brain size variation. Here, we show that regional white matter structures also show brain-size related changes in humans. Specifically, white matter regions connecting higher-order cortical systems are relatively expanded in larger human brains, while subcortical and cerebellar white matter tracts responsible for unimodal sensory or motor functions are relatively contracted. This regional scaling of white matter volume (WMV) is coordinated with regional scaling of cortical anatomy, but is distinct from scaling of white matter microstructure. These findings provide a more complete view of anatomic scaling of the human brain, with relevance for evolutionary, basic, and clinical neuroscience.
Published: 2021
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46. Intrinsic Activity Develops Along a Sensorimotor-Association Cortical Axis in Youth

Author: Valerie J. Sydnor, Bart Larsen, Jakob Seidlitz, Azeez Adebimpe, Aaron Alexander-Bloch, Dani S. Bassett, Maxwell A. Bertolero, Matthew Cieslak, Sydney Covitz, Yong Fan, Raquel E. Gur, Ruben C. Gur, Allyson P. Mackey, Tyler M. Moore, David R. Roalf, Russell T. Shinohara, and Theodore D. Satterthwaite
Abstract: Animal studies of neurodevelopmental plasticity have shown that intrinsic brain activity evolves from high amplitude and globally synchronized to suppressed and sparse as plasticity declines and the cortex matures. Leveraging resting-state functional MRI data from 1033 individuals (8-23 years), we reveal that this stereotyped refinement of intrinsic activity occurs during human development and provides evidence for a cortical gradient of neurodevelopmental plasticity during childhood and adolescence. Specifically, we demonstrate that declines in the amplitude of intrinsic activity are initiated heterochronously across regions, coupled to the maturation of a plasticity-restricting structural feature, and temporally staggered along a hierarchical sensorimotor-association axis from ages 8 to 18. Youth from disadvantaged environments exhibit reduced intrinsic activity in regions further up the sensorimotor-association axis, suggestive of a reduced level of plasticity in late-maturing cortices. Our results uncover a hierarchical axis of neurodevelopment and offer insight into the temporal sequence of protracted neurodevelopmental plasticity in humans.
Published: 2022
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47. Sex differences in the functional topography of association networks in youth

Author: Sheila Shanmugan, Jakob Seidlitz, Zaixu Cui, Azeez Adebimpe, Danielle S. Bassett, Maxwell A. Bertolero, Christos Davatzikos, Damien A. Fair, Raquel E. Gur, Ruben C. Gur, Bart Larsen, Hongming Li, Adam Pines, Armin Raznahan, David R. Roalf, Russell T. Shinohara, Jacob Vogel, Daniel H. Wolf, Yong Fan, Aaron Alexander-Bloch, and Theodore D. Satterthwaite
Subjects: Adult, Cerebral Cortex, Male, Brain Mapping, Sex Characteristics, Multidisciplinary, Adolescent, Magnetic Resonance Imaging, Machine Learning, Young Adult, Neural Pathways, Humans, Female, Child
Abstract: Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy ( P < 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent results. Furthermore, transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography were spatially correlated with the expression of genes on the X chromosome. These results highlight the role of sex as a biological variable in shaping functional topography.
Published: 2022

48. A Critical Appraisal of Imaging Transcriptomics

Author: Ayan S. Mandal, Michael Gandal, Jakob Seidlitz, and Aaron Alexander-Bloch
Subjects: General Medicine
Published: 2022

49. Mapping gene transcription and neurocognition across human neocortex

Author: Jacob W. Vogel, Ross D. Markello, Justine Y. Hansen, Bratislav Misic, Jakob Seidlitz, and Danilo Bzdok
Subjects: Regulation of gene expression, 0303 health sciences, Neocortex, Social Psychology, Experimental and Cognitive Psychology, Cognition, Human brain, Biology, 03 medical and health sciences, Behavioral Neuroscience, 0302 clinical medicine, medicine.anatomical_structure, Gene expression, medicine, Hierarchical organization, Premovement neuronal activity, Gene, Neuroscience, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract: Regulation of gene expression drives protein interactions that govern synaptic wiring and neuronal activity. The resulting coordinated activity among neuronal populations supports complex psychological processes, yet how gene expression shapes cognition and emotion remains unknown. Here, we directly bridge the microscale and macroscale by mapping gene expression patterns to functional activation patterns across the cortical sheet. Applying unsupervised learning to the Allen Human Brain Atlas and Neurosynth databases, we identify a ventromedial-dorsolateral gradient of gene assemblies that separate affective and perceptual domains. This topographic molecular-psychological signature reflects the hierarchical organization of the neocortex, including systematic variations in cell type, myeloarchitecture, laminar differentiation and intrinsic network affiliation. In addition, this molecular-psychological signature strengthens over neurodevelopment and can be replicated in two independent repositories. Collectively, our results reveal spatially covarying transcriptomic and cognitive architectures, highlighting the influence that molecular mechanisms exert on psychological processes.
Published: 2021
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50. Brain charts for the human lifespan

Author: Armin Raznahan, Eric Courchesne, Andrea Parolin Jackowski, Kamen A. Tsvetanov, Cameron T. Ellis, R.C. Gur, Bin Bae J, Park Mtm, Pedro A. Valdes-Sosa, Simon N. Vandekar, Jacob W. Vogel, Juan Zhou, Machteld Marcelis, Kiho Im, Patricia Ellen Grant, Minhui Ouyang, Blesa Cabez M, Michael V. Lombardo, Sarah E. Morgan, James P. Boardman, Adamson C, Calhoun Vd, Delarue M, James H. Cole, Pichet Binette A, Roberto Toro, David H. Rowitch, Nynke A. Groenewold, Kevin M. Anderson, David T.W. Jones, Michael Schöll, Wang Ys, Aiden Corvin, R.E. Gur, Damien A. Fair, Gareth Ball, Herma Lina Schaare, Andrew Zalesky, Evdokia Anagnostou, Michael J. Meaney, Taki Y, Gareth J. Sullivan, Warrier, Petra E. Vértes, Chixiang Chen, Lisa T. Eyler, Wei Liao, Tomáš Paus, Jeremy A. Elman, Phillip McGuire, Hisham Ziauddeen, William S. Kremen, Etienne Vachon-Presseau, E.T. Bullmore, Christophe Tzourio, White, Hammill Cf, Mothersill D, Richard N. Henson, Jiang Qiu, Duncan E. Astle, Fabrice Crivello, Paul C. Fletcher, Chertavian C, Kim K, Jennifer Crosbie, Russell Schachar, Gabriel A. Devenyi, Manfred G. Kitzbichler, Tianye Jia, Trey Hedden, Sang Jae Lee, Ross D. Markello, Silke Kern, Ian M. Goodyer, Keith A. Johnson, Frauke Beyer, Bernard Mazoyer, A. Heinz, Sylvane Desrivières, Rosenberg, Gary Donohoe, Ong Mq, Alexander D. Edwards, Dan J. Stein, Nenad Medic, Zuo Xn, Travis T. Mallard, Peter Fonagy, Lindsay W. Victoria, Ingmar Skoog, Avram J. Holmes, Jason P. Lerch, Jed T. Elison, Jianfu Li, John H. Gilmore, Rosemary Holt, Caitlin K. Rollins, Carol E. Franz, Pedro Mario Pan, Saashi A Bedford, Yang N, Jonathan C Ipser, Richard A. I. Bethlehem, Tuulari Jj, Stolicyn A, Hua Huang, Bratislav Misic, Conor Liston, Ayub M, Lisa Ronan, Yeo Bt, Sophie Adler, Charles J. Lynch, Faith M. Gunning, Konrad Wagstyl, M. Mallar Chakravarty, John Suckling, Theodore D. Satterthwaite, Bharath Holla, Yap Seng Chong, Jinglei Lv, Jakob Seidlitz, Niall J Bourke, Xinlei Qian, Simon Baron-Cohen, Cynthia M. Ortinau, Deirel Paz Linares, Thyreau B, René S. Kahn, Aaron P. Schultz, Vanessa Cropley, Eric Westman, Mitchell Valdés-Sosa, Rik Ossenkoppele, André Zugman, Hasse Karlsson, Sylvia Villeneuve, Katja Heuer, Di Biase Ma, Margaret L. Westwater, Sofie L. Valk, David J. Sharp, Brigitte Landeau, Matthew Borzage, Kirsten A. Donald, Timothy Rittman, Richard Beare, Giovanni Abrahão Salum, Gunter Schumann, Ryuta Kawashima, Romero-Garcia R, John Blangero, Yun Hj, Russel T. Shinohara, Nicolas Crossley, Simon K. Warfield, Karen Pierce, George S. Alexopoulos, Katharine Dunlop, David C. Glahn, Francois Lalonde, Anqi Qiu, Lana Vasung, Gaël Chételat, Lídice Galán-García, Clifford R. Jack, Reisa A. Sperling, Anna Zettergren, Elizabeth Kelley, Arno Villringer, Andrea Mechelli, Benegal, Aaron Alexander-Bloch, Nicholas B. Turk-Browne, van Amelsvoort T, John D. Lewis, Heather C. Whalley, A. V. Witte, Zdenka Pausova, Joel T. Nigg, Heather J. Zar, Raymond J. Dolan, Christopher D. Smyser, Jay N. Giedd, Lena Palaniyappan, Ali Gholipour, Areces-Gonzalez A, Peter B. Jones, Jacqueline Hoare, Oskar Hansson, Linnea Karlsson, C Pantelis, Paly L, Bonnie Auyeung, Jorge Bosch-Bayard, Bethlehem, Richard [0000-0002-0714-0685], White, Simon [0000-0001-8642-7037], Astle, Duncan [0000-0002-7042-5392], Baron-Cohen, Simon [0000-0001-9217-2544], Henson, Rik [0000-0002-0712-2639], Jones, Peter [0000-0002-0387-880X], Kitzbichler, Manfred [0000-0002-4494-0753], Rittman, Timothy [0000-0003-1063-6937], Rowitch, David [0000-0002-0079-0060], Tsvetanov, Kamen A. [0000-0002-3178-6363], Westwater-Wozniak, Margaret [0000-0002-2918-0979], Ziauddeen, Hisham [0000-0003-4044-1719], Apollo - University of Cambridge Repository, British Academy, Autism Research Trust, National Institute of Mental Health (US), UK Research and Innovation, Medical Research Council (UK), National Institute for Health and Care Research (US), Wellcome Trust, University of Cambridge, Cambridge Biomedical Research Centre, University of Cambridge [UK] (CAM), University of Pennsylvania, Yale University [New Haven], Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie et imagerie des troubles neurologiques (PhIND), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Child and Adolescent Psychiatry Department [AP- HP Hôpital Robert Debré], AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Département de Neuroscience - Department of Neuroscience, Centre de Recherche Interdisciplinaire / Center for Research and Interdisciplinarity [Paris, France] (CRI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Med Staf Spec Psychiatrie (9), Neurology, Amsterdam Neuroscience - Neurodegeneration, 3R-BRAIN, AIBL, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Repository Without Borders Investigators, CALM Team, Cam-CAN, CCNP, COBRE, cVEDA, ENIGMA Developmental Brain Age Working Group, Developing Human Connectome Project, FinnBrain, Harvard Aging Brain Study, IMAGEN, KNE96, The Mayo Clinic Study of Aging, NSPN, POND, The PREVENT-AD Research Group, VETSA, [Bethlehem, R. A. I.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Auyeung, B.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Baron-Cohen, S.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Bedford, S. A.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Holt, R.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Lombardo, M. V.] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Cambridge, England, [Bethlehem, R. A. I.] Univ Cambridge, Dept Psychiat, Brain Mapping Unit, Cambridge, England, [Kitzbichler, M. G.] Univ Cambridge, Dept Psychiat, Brain Mapping Unit, Cambridge, England, [Seidlitz, J.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Vogel, J. W.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Gur, R. E.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Gur, R. C.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Jackowski, A. P.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Satterthwaite, T. D.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Alexander-Bloch, A. F.] Univ Penn, Dept Psychiat, Philadelphia, PA 19104 USA, [Seidlitz, J.] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA, [Alexander-Bloch, A. F.] Childrens Hosp Philadelphia, Dept Child & Adolescent Psychiat & Behav Sci, Philadelphia, PA 19104 USA, [Seidlitz, J.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Chertavian, C.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Gur, R. E.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Gur, R. C.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [Alexander-Bloch, A. F.] Childrens Hosp Philadelphia & Penn Med, Lifespan Brain Inst, Philadelphia, PA USA, [White, S. R.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Goodyer, I. M.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Henson, R. N.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Jones, P. B.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Kitzbichler, M. G.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Medic, N.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Morgan, S. E.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Romero-Garcia, R.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Ronan, L.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Suckling, J.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Vertes, P. E.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Warrier, V.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Westwater, M. L.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Ziauddeen, H.] Univ Cambridge, Dept Psychiat, Cambridge, England, [Bullmore, E. T.] Univ Cambridge, Dept Psychiat, Cambridge, England, [White, S. R.] Univ Cambridge, MRC Biostat Unit, Cambridge, England, [Vogel, J. W.] Univ Penn, Lifespan Informat & Neuroimaging Ctr, Philadelphia, PA 19104 USA, [Satterthwaite, T. D.] Univ Penn, Lifespan Informat & Neuroimaging Ctr, Philadelphia, PA 19104 USA, [Anderson, K. M.] Yale Univ, Dept Psychol, New Haven, CT USA, [Ellis, C. T.] Yale Univ, Dept Psychol, New Haven, CT USA, [Turk-Browne, N. B.] Yale Univ, Dept Psychol, New Haven, CT USA, [Adamson, C.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Ball, G.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Beare, R.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Jackowski, A. P.] Murdoch Childrens Res Inst, Dev Imaging, Melbourne, Vic, Australia, [Adamson, C.] Monash Univ, Dept Med, Melbourne, Vic, Australia, [Beare, R.] Monash Univ, Dept Med, Melbourne, Vic, Australia, [Adler, S.] UCL Great Ormond St Inst Child Hlth, London, England, [Alexopoulos, G. S.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Anagnostou, E.] Univ Toronto, Dept Pediat, Toronto, ON, Canada, [Anagnostou, E.] Holland Bloorview Kids Rehabil Hosp, Toronto, ON, Canada, [Pierce, K.] Holland Bloorview Kids Rehabil Hosp, Toronto, ON, Canada, [Areces-Gonzalez, A.] Univ Elect Sci & Technol China, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Paz-Linares, D.] Univ Elect Sci & Technol China, MOE Key Lab NeuroInformat, Clin Hosp, Chengdu Brain Sci Inst, Chengdu, Peoples R China, [Areces-Gonzalez, A.] Univ Pinar del Rio Hermanos Saiz Montes de Oca, Pinar Del Rio, Cuba, [Astle, D. E.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Henson, R. N.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Whalley, H. C.] Univ Cambridge, MRC Cognit & Brain Sci Unit, Cambridge, England, [Auyeung, B.] Univ Edinburgh, Sch Philosophy Psychol & Language Sci, Dept Psychol, Edinburgh, Midlothian, Scotland, [Pausova, Z.] Univ Edinburgh, Sch Philosophy Psychol & Language Sci, Dept Psychol, Edinburgh, Midlothian, Scotland, [Ayub, M.] Queens Univ, Dept Psychiat, Ctr Neurosci Studies, Kingston, ON, Canada, [Ayub, M.] UCL, Mental Hlth Neurosci Res Dept, Div Psychiat, London, England, [Bae, J.] Seoul Natl Univ, Bundang Hosp, Dept Neuropsychiat, Seongnam, South Korea, [Ball, G.] Univ Melbourne, Dept Paediat, Melbourne, Vic, Australia, [Baron-Cohen, S.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge Lifetime Asperger Syndrome Serv CLASS, Cambridge, England, [Benegal, V.] Natl Inst Mental Hlth & Neurosci NIMHANS, Ctr Addict Med, Bengaluru, India, [Beyer, F.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Villringer, A.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Witte, A. V.] Max Planck Inst Human Cognit & Brain Sci, Dept Neurol, Leipzig, Germany, [Blangero, J.] Univ Texas Rio Grande Valley, South Texas Diabet & Obes Inst, Dept Human Genet, Edinburg, TX USA, [Blesa Cabez, M.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Boardman, J. P.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Sullivan, G.] Univ Edinburgh, MRC Ctr Reprod Hlth, Edinburgh, Midlothian, Scotland, [Borzage, M.] Univ Southern Calif, Childrens Hosp Los Angeles, Keck Sch Med, Fetal & Neonatal Inst,Div Neonatol,Dept Pediat, Los Angeles, CA 90007 USA, [Bosch-Bayard, J. F.] Montreal Neurol Inst, Ludmer Ctr Neuroinformat & Mental Hlth, McGill Ctr Integrat Neurosci, Montreal, PQ, Canada, [Bosch-Bayard, J. F.] McGill Univ, Montreal, PQ, Canada, [Chakravarty, M. M.] McGill Univ, Montreal, PQ, Canada, [Bourke, N.] Imperial Coll London, Dept Brain Sci, London, England, [Sharp, D.] Imperial Coll London, Dept Brain Sci, London, England, [Alexander-Bloch, A. F.] Imperial Coll London, Dept Brain Sci, London, England, [Bourke, N.] Dementia Res Inst, Care Res & Technol Ctr, London, England, [Calhoun, V. D.] Georgia State Univ, Triinst Ctr Translat Res Neuroimaging & Data Sci, Georgia Inst Technol, Atlanta, GA 30303 USA, [Calhoun, V. D.] Emory Univ, Atlanta, GA 30322 USA, [Chakravarty, M. M.] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Comp Brain Anat CoBrA Lab, Montreal, PQ, Canada, [Chen, C.] Univ Penn, Penn Stat Imaging & Visualizat Ctr, Dept Biostat Epidemiol & Informat, Perelman Sch Med, Philadelphia, PA 19104 USA, [Shinohara, R. T.] Univ Penn, Penn Stat Imaging & Visualizat Ctr, Dept Biostat Epidemiol & Informat, Perelman Sch Med, Philadelphia, PA 19104 USA, [Chetelat, G.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Delarue, M.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Landeau, B.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Paly, L.] Normandie Univ, PhIND Physiopathol & Imaging Neurol Disorders, Inst Blood & Brain Caen Normandie, UNICAEN,INSERM,U1237, Caen, France, [Chong, Y. S.] Agcy Sci Technol & Res, Singapore Inst Clin Sci, Singapore, Singapore, [Chong, Y. S.] Natl Univ Singapore, Yong Loo Lin Sch Med, Dept Obstet & Gynaecol, Singapore, Singapore, [Cole, J. H.] UCL, Ctr Med Image Comp CMIC, London, England, [Cole, J. H.] UCL, Dementia Res Ctr DRC, London, England, [Corvin, A.] Trinity Coll Dublin, Dept Psychiat, Dublin, Ireland, [Costantino, M.] Douglas Mental Hlth Univ Inst, Cerebral Imaging Ctr, Verdun, PQ, Canada, [Costantino, M.] McGill Univ, Undergrad Program Neurosci, Montreal, PQ, Canada, [Courchesne, E.] Univ Calif San Diego, Dept Neurosci, San Diego, CA 92103 USA, [Courchesne, E.] Univ Calif San Diego, Autism Ctr Excellence, San Diego, CA 92103 USA, [Crivello, F.] Univ Bordeaux, Inst Neurodegenerat Disorders, CNRS UMR5293, CEA, Bordeaux, France, [Mazoyer, B.] Univ Bordeaux, Inst Neurodegenerat Disorders, CNRS UMR5293, CEA, Bordeaux, France, [Cropley, V. L.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Di Biase, M. A.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Lv, J.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Zalesky, A.] Univ Melbourne, Melbourne Neuropsychiat Ctr, Melbourne, Vic, Australia, [Hammill, C. F.] Hosp Sick Children, Toronto, ON, Canada, [Schachar, R. J.] Hosp Sick Children, Toronto, ON, Canada, [Crossley, N.] Pontificia Univ Catolica Chile, Sch Med, Dept Psychiat, Santiago, Chile, [Crossley, N.] Kings Coll London, Dept Psychosis Studies, Inst Psychiat Psychol & Neurosci, London, England, [McGuire, P.] Kings Coll London, Dept Psychosis Studies, Inst Psychiat Psychol & Neurosci, London, England, [Crossley, N.] Inst Milenio Intelligent Healthcare Engn, Santiago, Chile, [Delorme, R.] Robert Debre Univ Hosp, AP HP, Child & Adolescent Psychiat Dept, Paris, France, [Delorme, R.] Inst Pasteur, Human Genet & Cognit Funct, Paris, France, [Desrivieres, S.] Kings Coll London, Inst Psychiat Psychol & Neurosci, Social Genet & Dev Psychiat Ctr, London, England, [Devenyi, G. A.] Douglas Mental Hlth Univ Inst, McGill Dept Psychiat, Cerebral Imaging Ctr, Montreal, PQ, Canada, [Devenyi, G. A.] McGill Univ, Dept Psychiat, Montreal, PQ, Canada, [Di Biase, M. A.] Harvard Med Sch, Brigham & Womens Hosp, Dept Psychiat, Boston, MA 02115 USA, [Dolan, R.] UCL, Max Planck UCL Ctr Computat Psychiat & Ageing Res, London, England, [Dolan, R.] Wellcome Ctr Human Neuroimaging, London, England, [Wagstyl, K.] Wellcome Ctr Human Neuroimaging, London, England, [Donald, K. A.] Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Div Dev Paediat, Cape Town, South Africa, [Donald, K. A.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Groenewold, N. A.] Univ Cape Town, Neurosci Inst, Cape Town, South Africa, [Donohoe, G.] Natl Univ Ireland Galway, Sch Psychol, Ctr Neuroimaging Cognit & Genom NICOG, Galway, Ireland, [Dunlop, K.] Weill Cornell Med, Dept Psychiat, Weil Family Brain & Mind Res Inst, New York, NY USA, [Lynch, C.] Weill Cornell Med, Dept Psychiat, Weil Family Brain & Mind Res Inst, New York, NY USA, [Edwards, A. D.] Kings Coll London, Ctr Dev Brain, London, England, [Edwards, A. 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C.] Univ Cambridge, Dept Psychiat, Cambridge Biomed Campus, Cambridge, England, [Fletcher, P. C.] Wellcome Trust MRC Inst Metab Sci, Cambridge Biomed Campus, Cambridge, England, [Fletcher, P. C.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Jones, P. B.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Suckling, J.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Ziauddeen, H.] Cambridgeshire & Peterborough NHS Fdn Trust, Cambridge, England, [Fonagy, P.] UCL, Dept Clin Educ & Hlth Psychol, London, England, [Fonagy, P.] Anna Freud Natl Ctr Children & Families, London, England, [Galan-Garcia, L.] Cuban Ctr Neurosci, Havana, Cuba, [Valdes-Sosa, M. J.] Cuban Ctr Neurosci, Havana, Cuba, [Gholipour, A.] Boston Childrens Hosp, Computat Radiol Lab, Boston, MA USA, [Warfield, S. K.] Boston Childrens Hosp, Computat Radiol Lab, Boston, MA USA, [Giedd, J.] Univ Calif San Diego, Dept Child & Adolescent Psychiat, San Diego, CA 92103 USA, [Giedd, J.] Univ Calif San Diego, Dept Psychiat, San Diego, CA 92103 USA, [Gilmore, J. H.] Univ N Carolina, Dept Psychiat, Chapel Hill, NC 27515 USA, [Glahn, D. C.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Im, K.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Mathias, S. R.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Rodrigue, A.] Boston Childrens Hosp, Dept Psychiat, Boston, MA USA, [Glahn, D. C.] Harvard Med Sch, Boston, MA 02115 USA, [Im, K.] Harvard Med Sch, Boston, MA 02115 USA, [Johnson, K. A.] Harvard Med Sch, Boston, MA 02115 USA, [Mathias, S. R.] Harvard Med Sch, Boston, MA 02115 USA, [Rodrigue, A.] Harvard Med Sch, Boston, MA 02115 USA, [Schultz, A. P.] Harvard Med Sch, Boston, MA 02115 USA, [Sperling, R. A.] Harvard Med Sch, Boston, MA 02115 USA, [Grant, P. E.] Harvard Med Sch, Fetal Neonatal Neuroimaging & Dev Sci Ctr, Boston Childrens Hosp, Div Newborn Med & Neuroradiol, Boston, MA 02115 USA, [Groenewold, N. A.] Univ Cape Town, SA MRC Unit Child & Adolescent Hlth, Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Cape Town, South Africa, [Zar, H. J.] Univ Cape Town, SA MRC Unit Child & Adolescent Hlth, Red Cross War Mem Childrens Hosp, Dept Paediat & Child Hlth, Cape Town, South Africa, [Gunning, F. M.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Victoria, L. W.] Weill Cornell Med, Dept Psychiat, Weill Cornell Inst Geriatr Psychiat, New York, NY USA, [Hammill, C. 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E.] Alan Turing Inst, London, England, [Mothersill, D.] Natl Coll Ireland, Sch Business, Dept Psychol, Dublin, Ireland, [Mothersill, D.] Natl Univ Ireland Galway, Sch Psychol, Galway, Ireland, [Mothersill, D.] Natl Univ Ireland Galway, Ctr Neuroimaging & Cognit Genom, Galway, Ireland, [Mothersill, D.] Trinity Coll Dublin, Dept Psychiat, Dublin, Ireland, [Nigg, J.] Oregon Hlth & Sci Univ, Dept Psychiat, Sch Med, Portland, OR 97201 USA, [Ong, M. Q. W.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Qian, X.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Zhou, J. H.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Ortinau, C.] Washington Univ, Dept Pediat, St Louis, MO 63130 USA, [Ossenkoppele, R.] Vrije Univ Amsterdam, Alzheimer Ctr Amsterdam, Amsterdam UMC, Dept Neurol,Amsterdam Neurosci, Amsterdam, Netherlands, [Ossenkoppele, R.] Lund Univ, Clin Memory Res Unit, Lund, Sweden, [Palaniyappan, L.] Univ Western Ontario, Robarts Res Inst, London, ON, Canada, [Palaniyappan, L.] Univ Western Ontario, Brain & Mind Inst, London, ON, Canada, [Pan, P. M.] Fed Univ Sao Poalo UNIFESP, Dept Psychiat, Sao Poalo, Brazil, [Pan, P. M.] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Poalo, Brazil, [Zugman, A.] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Poalo, Brazil, [Pantelis, C.] Univ Melbourne, Dept Psychiat, Melbourne Neuropsychiat Ctr, Carlton, Vic, Australia, [Pantelis, C.] Melbourne Hlth, Carlton, Vic, Australia, [Pantelis, C.] Univ Melbourne, Melbourne Sch Engn, Parkville, Vic, Australia, [Pantelis, C.] Florey Inst Neurosci & Mental Hlth, Parkville, Vic, Australia, [Park, M. M.] Western Univ, Schulich Sch Med & Dent, Dept Psychiat, London, ON, Canada, [Rollins, C. K.] Univ Montreal, Dept Psychiat, Fac Med, Montreal, PQ, Canada, [Rollins, C. K.] Univ Montreal, CHU St Justine, Montreal, PQ, Canada, [Romero-Garcia, R.] Univ Toronto, Dept Psychiat, Toronto, ON, Canada, [Romero-Garcia, R.] Univ Toronto, Dept Psychol, Toronto, ON, Canada, [Rosenberg, M. D.] Univ Toronto, Dept Physiol, Toronto, ON, Canada, [Rosenberg, M. D.] Univ Toronto, Dept Nutr Sci, Toronto, ON, Canada, [Paz-Linares, D.] Cuban Neurosci Ctr, Havana, Cuba, [Pichet Binette, A.] McGill Univ, Fac Med, Dept Psychiat, Montreal, PQ, Canada, [Villeneuve, S.] McGill Univ, Fac Med, Dept Psychiat, Montreal, PQ, Canada, [Pichet Binette, A.] Douglas Mental Hlth Univ Inst, Montreal, PQ, Canada, [Villeneuve, S.] Douglas Mental Hlth Univ Inst, Montreal, PQ, Canada, [Qiu, J.] Southwest Univ, Sch Psychol, Chongqing, Peoples R China, [Qiu, A.] Natl Univ Singapore, N1 Inst Hlth, Dept Biomed Engn, Singapore, Singapore, [Rittman, T.] Univ Cambridge, Dept Clin Neurosci, Cambridge, England, [Tsvetanov, K. A.] Univ Cambridge, Dept Clin Neurosci, Cambridge, England, [Rollins, C. K.] Harvard Med Sch, Dept Neurol, Boston, MA 02115 USA, [Rollins, C. K.] Boston Childrens Hosp, Dept Neurol, Boston, MA USA, [Romero-Garcia, R.] Univ Seville, Dpto Fisiol Med & Biofis, Inst Biomed Sevilla IBiS HUVR CSIC, Seville, Spain, [Rosenberg, M. 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S.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Yang, N.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Yeo, B.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Zuo, X. N.] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China, [Wang, Y. S.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Yang, N.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Zuo, X. N.] Beijing Normal Univ, IDG McGovern Inst Brain Res, Dev Populat Neuroscience Res Ctr, Beijing, Peoples R China, [Wang, Y. S.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Yang, N.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Zuo, X. N.] Natl Basic Sci Data Ctr, Beijing, Peoples R China, [Wang, Y. S.] Chinese Acad Sci, Res Ctr Lifespan Dev Brain & Mind, Inst Psychol, Beijing, Peoples R China, [Yang, N.] Chinese Acad Sci, Res Ctr Lifespan Dev Brain & Mind, Inst Psychol, Beijing, Peoples R China, [Westman, E.] Karolinska Inst, Ctr Alzheimer Res, Dept Neurobiol Care Sci & Soc, Div Clin Geriatr, Stockholm, Sweden, [Witte, A. V.] Univ Leipzig, CRC 1052 Obes Mech, Fac Med, Leipzig, Germany, [Zhou, J. H.] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Sleep & Cognit, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Translat MR Res, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, N1 Inst Hlth, Singapore, Singapore, [Yeo, B.] Natl Univ Singapore, Inst Digital Med, Singapore, Singapore, [Yun, H.] Natl Univ Singapore, Integrat Sci & Engn Programme ISEP, Singapore, Singapore, [Zar, H. J.] Univ Melbourne, Dept Biomed Engn, Melbourne, Vic, Australia, [Zhou, J. H.] Natl Univ Singapore, Yong Loo Lin Sch Med, Ctr Translat Magnet Resonance Res, Singapore, Singapore, [Ziauddeen, H.] Univ Cambridge, Wellcome Trust MRC Inst Metab Sci, Cambridge, England, [Zugman, A.] NIMH, NIH, Bethesda, MD 20892 USA, [Zugman, A.] Escola Paulista Med, Dept Psychiat, Sao Paulo, Brazil, [Zuo, X. N.] Nanning Normal Univ, Sch Educ Sci, Key Lab Brain & Educ, Nanning, Peoples R China, British Academy Postdoctoral fellowship, NIMH, UKRI Medical Research Council, NIHR Cambridge Biomedical Research Centre, NIHR Senior Investigator award, MRC research infrastructure award, Commonwealth Scientific and Industrial Research Organisation (CSIRO), and Ontario Brain Institute
Subjects: 631/378/2649, OpenPain Project, KNE96, Growth, Psychiatric-disorders, DISEASE, 3R-BRAIN, Brain charts, MRI Brain, OASIS-3, Disease, CCNP, 631/378/2571, UMN BCP, Multidisciplinary, medicine.diagnostic_test, PSYCHIATRIC-DISORDERS, article, Brain, Human brain, ASSOCIATION, Magnetic Resonance Imaging, Harvard Aging Brain Study, The Mayo Clinic Study of Aging, NSPN, medicine.anatomical_structure, GROWTH, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], ddc:500, BURDEN, WHITE-MATTER, FinnBrain, Harvard Aging Brain Study, Organization, Mri, MRI, medicine.medical_specialty, Concurrent validity, MODELS, Cam-CAN, Longevity, CALM Team, POND, Neuroimaging, Burden, ORGANIZATION, AIBL, The PREVENT-AD Research Group, VETSA, Cortical thickness, Association, Physical medicine and rehabilitation, FinnBrain, IMAGEN, KNE96, White-matter, medicine, Humans, ASRB, 631/378/1689, COBRE, business.industry, 631/378/2611, Brain morphometry, Neurosciences, Alzheimer’s Disease Repository Without Borders Investigators, Magnetic resonance imaging, Alzheimer’s Disease Neuroimaging Initiative, Anthropometry, Body Height, Brain growth, Birth, 59/57, Normative, IMAGEN, ENIGMA Developmental Brain Age working group, NSPN, business, CCNP, 3R-BRAIN, CORTICAL THICKNESS, Developing Human Connectome Project, ENIGMA Developmental Brain Age working group, The PREVENT-AD Research Group, VETSA, Bullmore, E.T
Abstract: Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes., R.A.I.B. was supported by a British Academy Postdoctoral fellowship and by the Autism Research Trust. J. Seidlitz was supported by NIMH T32MH019112-29 and K08MH120564. S.R.W. was funded by UKRI Medical Research Council MC_UU_00002/2 and was supported by the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014). E.T.B. was supported by an NIHR Senior Investigator award and the Wellcome Trust collaborative award for the Neuroscience in Psychiatry Network. A.F.A.-B. was supported by NIMH K08MH120564. Data were curated and analysed using a computational facility funded by an MRC research infrastructure award (MR/M009041/1) to the School of Clinical Medicine, University of Cambridge and supported by the mental health theme of the NIHR Cambridge Biomedical Research Centre.
Published: 2022
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132 results on '"Jakob Seidlitz"'

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