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Updated: Jun 23, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
The genetic architecture of cortical similarity networks
Isaac Sebenius1,2,3, Varun Warrier4,5, Richard A I Bethlehem5
1Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom. iss31@cam.ac.uk.
Abstract:
The genetic architecture of human brain networks is central to understanding cortical organisation and evolution, the causal links between brain structure and function, and the pathogenesis of neuropsychiatric disorders. Using N > 48,000 subjects, we investigated common genetic effects on Morphometric INverse Divergence (MIND), a heritable, multi-modal structural MRI metric of inter-areal similarity and connectivity. Genetic correlations between MIND network edges were largely reducible to two gradients, each aligned with distance from one of the two phylogenetically primitive areas (paleocortex and archicortex) predicted by the dual origin theory of cortical evolution. MIND was more heritable than comparable measures of functional (f)MRI connectivity, and the paleocortically-aligned MIND gradient was genetically correlated with, and causally predictive of, fMRI connectivity. Finally, we identified genetic overlaps between MIND gradients and neuropsychiatric and biomedical traits. These results provide fresh insight into the dual origins of the cortex and their implications for brain function and health.
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