Format

Send to

Choose Destination
Neuron. 2018 Jan 3;97(1):231-247.e7. doi: 10.1016/j.neuron.2017.11.039. Epub 2017 Dec 21.

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

Author information

1
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.
2
University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK.
3
Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA.
4
Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892, USA.
5
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.
6
Research Department of Clinical, Educational and Health Psychology, University College London, London WC1E 6BT, UK.
7
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.
8
University of Cambridge, Department of Psychiatry, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK.
9
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.

Abstract

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.

KEYWORDS:

IQ; MRI; connectome; cross-species; cytoarchitecture; gene expression; macaque; morphology; multi-modal

PMID:
29276055
PMCID:
PMC5763517
DOI:
10.1016/j.neuron.2017.11.039
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center