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

Autor:	Seidlitz J; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA. Electronic address: jakob.seidlitz@nih.gov., Váša F; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK., Shinn M; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK., Romero-Garcia R; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK., Whitaker KJ; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK., Vértes PE; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK., Wagstyl K; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK., Kirkpatrick Reardon P; Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA., Clasen L; Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA., Liu S; Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA., Messinger A; Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA., Leopold DA; Laboratory of Neuropsychology, National Institute of Mental Health, Bethesda, MD 20892, USA; Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, Bethesda, MD 20892, USA., Fonagy P; Research Department of Clinical, Educational and Health Psychology, University College London, London WC1E 6BT, UK., Dolan RJ; Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London WC1N 3BG, UK; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London WC1B 5EH, UK., Jones PB; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK., Goodyer IM; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK., Raznahan A; Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA., Bullmore ET; University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK; ImmunoPsychiatry, Immuno-Inflammation Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage SG1 2NY, UK.
Jazyk:	angličtina
Zdroj:	Neuron [Neuron] 2018 Jan 03; Vol. 97 (1), pp. 231-247.e7. Date of Electronic Publication: 2017 Dec 21.
DOI:	10.1016/j.neuron.2017.11.039
Abstrakt:	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 organization 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 with 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. (Copyright © 2017 Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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