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Morphometric Similarity Networks Detect Microscale Cortical Organisation and Predict Inter-Individual Cognitive Variation

View ORCID ProfileJakob Seidlitz, František Váša, Maxwell Shinn, Rafael Romero-Garcia, Kirstie J. Whitaker, Petra E. Vértes, Paul Kirkpatrick Reardon, Liv Clasen, Adam Messinger, David A. Leopold, Peter Fonagy, Raymond J. Dolan, Peter B. Jones, Ian M. Goodyer, the NSPN Consortium, Armin Raznahan, Edward T. Bullmore
doi: https://doi.org/10.1101/135855
Jakob Seidlitz
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
bDevelopmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
cLaboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
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  • ORCID record for Jakob Seidlitz
  • For correspondence: jms290@cam.ac.uk jakob.seidlitz@nih.gov
František Váša
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
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Maxwell Shinn
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
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Rafael Romero-Garcia
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
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Kirstie J. Whitaker
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
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Petra E. Vértes
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
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Paul Kirkpatrick Reardon
bDevelopmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
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Liv Clasen
bDevelopmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
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Adam Messinger
cLaboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA
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David A. Leopold
dLaboratory of Neuropsychology, National Institute of Mental Health, Bethesda, MD 20892, USA
eNeurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA
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Peter Fonagy
fResearch Department of Clinical, Educational and Health Psychology, University College London, London, WC1E 6BT, UK
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Raymond J. Dolan
gWellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London, WC1N 3BG, UK
hMax Planck UCL Centre for Computational Psychiatry and Ageing Research, London, WC1B 5EH, UK
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Peter B. Jones
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
iCambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, PE29 3RJ, UK
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Ian M. Goodyer
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
iCambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, PE29 3RJ, UK
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Armin Raznahan
bDevelopmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
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Edward T. Bullmore
aUniversity of Cambridge, Department of Psychiatry, Cambridge, CB2 0SZ, UK
iCambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, PE29 3RJ, UK
jImmunoPsychiatry, Immuno-Inflammation Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage SG1 2NY, UK
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Summary

Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping, based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organisation comprising modules and high-degree hubs. Human MSN modules recapitulate known cortical cytoarchitectonic divisions, and greater inter-regional morphometric similarity was associated with stronger inter-regional co-expression of genes enriched for neuronal terms. Comparing macaque MSNs to tract-tracing data confirmed that morphometric similarity was related to axonal connectivity. Finally, variation in the degree of human MSN nodes accounted for about 40% of between-subject variability in IQ. Morphometric similarity mapping provides a novel, robust and biologically plausible approach to understanding how human cortical networks underpin individual differences in psychological functions.

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Posted May 09, 2017.
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Morphometric Similarity Networks Detect Microscale Cortical Organisation and Predict Inter-Individual Cognitive Variation
Jakob Seidlitz, František Váša, Maxwell Shinn, Rafael Romero-Garcia, Kirstie J. Whitaker, Petra E. Vértes, Paul Kirkpatrick Reardon, Liv Clasen, Adam Messinger, David A. Leopold, Peter Fonagy, Raymond J. Dolan, Peter B. Jones, Ian M. Goodyer, the NSPN Consortium, Armin Raznahan, Edward T. Bullmore
bioRxiv 135855; doi: https://doi.org/10.1101/135855
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Morphometric Similarity Networks Detect Microscale Cortical Organisation and Predict Inter-Individual Cognitive Variation
Jakob Seidlitz, František Váša, Maxwell Shinn, Rafael Romero-Garcia, Kirstie J. Whitaker, Petra E. Vértes, Paul Kirkpatrick Reardon, Liv Clasen, Adam Messinger, David A. Leopold, Peter Fonagy, Raymond J. Dolan, Peter B. Jones, Ian M. Goodyer, the NSPN Consortium, Armin Raznahan, Edward T. Bullmore
bioRxiv 135855; doi: https://doi.org/10.1101/135855

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