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

Seidlitz, J.; Vaša, F.; Shinn, M.; Romero-Garcia, R.; Whitaker, K. J.; Vertes, P. E.; Reardon, P. K.; Clasen, L.; Messinger, A.; Leopold, D. A.; Fonagy, P.; Dolan, R. J.; Jones, P. B.; Goodyer, I. M.; the NSPN Consortium,; Raznahan, A.; Bullmore, E. T.

doi:10.1101/135855

bioRxiv · 10.1101/135855

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

Seidlitz, J.·Vaša, F.·Shinn, M.·Romero-Garcia, R.·Whitaker, K. J.·Vertes, P. E.·Reardon, P. K.·Clasen, L.·Messinger, A.·Leopold, D. A.·Fonagy, P.·Dolan, R. J.·Jones, P. B.·Goodyer, I. M.·the NSPN Consortium,·Raznahan, A.·Bullmore, E. T.

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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 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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Seidlitz, J., Vaša, F., Shinn, M., Romero-Garcia, R., Whitaker, K. J., Vertes, P. E., Reardon, P. K., Clasen, L., Messinger, A., Leopold, D. A., Fonagy, P., Dolan, R. J., Jones, P. B., Goodyer, I. M., the NSPN Consortium,, Raznahan, A., Bullmore, E. T.. 2017-05-09. Morphometric Similarity Networks Detect Microscale Cortical Organisation And Predict Inter-Individual Cognitive Variation. https://doi.org/10.1101/135855

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