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

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

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.

Publication types

  • Research Support, N.I.H., Intramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cerebral Cortex / anatomy & histology*
  • Cerebral Cortex / physiology*
  • Cognition / physiology*
  • Connectome / methods*
  • Female
  • Humans
  • Intelligence / physiology
  • Macaca
  • Magnetic Resonance Imaging
  • Male
  • Neural Pathways / anatomy & histology*
  • Neural Pathways / physiology*
  • Young Adult