Neural interactions in local cortical networks critically depend on the distance between interacting elements: the shorter the distance, the stronger the interactions. Here we quantified these interactions in six cortical areas of 854 individuals, including mo-nozygotic and dizygotic twins, nontwin siblings, and nonrelated individuals. We found that the strength of zero-lag correlation between prewhitened, resting-state, blood level oxygenation-dependent functional magnetic resonance imaging time series decreased with distance as a power law. The rate of decrease, b, varied among individuals by ~1.9☓, was highly correlated between hemispheres, but differed among areas (by ~1.2☓) in a systematic fashion, becoming progressively less steep from frontal to occipital areas. With respect to twin status, b was significantly correlated between monozy-gotic twins, less so between dizygotic twins or nontwin siblings, and not at all in nonrelated individuals. These results quantify the lawful, distance-related cortical interactions and demonstrate, for the first time, the heritability of their power law. NEW & NOTEWORTHY Local cortical circuitry involves orderly neuronal interactions. A key feature of these interactions is that they are stronger the closer the interacting neurons. Here we quantified this crucial dependence of neural interactions on distance with functional magnetic resonance imaging and found that the strength of interactions decreases with distance as a power law that is very similar in all cortical lobes and heritable. These findings identify an invariant and heritable property of local cortical organization.
Bibliographical noteFunding Information:
This study was supported by the American Legion Brain Sciences Chair, University of Minnesota. Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 National Institutes of Health (NIH) institutes and centers that support the NIH Blueprint for Neuroscience Research and by the McDonnell Center for Systems Neuroscience at Washington University.
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- Cerebral cortex
- Local cortical circuits