Modular structure of intrinsic brain networks explains differences in human intelligence

General intelligence is a fundamental determinant of academic and life success. While previous human brain imaging research has identified correlates of intelligence localized in separate regions of the brain, more recent work... [ view full abstract ]

General intelligence is a fundamental determinant of academic and life success. While previous human brain imaging research has identified correlates of intelligence localized in separate regions of the brain, more recent work examines how interactions between these regions in functional networks contribute to human intelligence. The brain’s functional network topology is characterized by substantial modularity. Nevertheless, how interactions within and between network modules contribute to human intelligence is only poorly understood. We modeled subject-specific brain network graphs from functional MRI resting-state data (N=309) and examined whole brain (global) and region-specific (local) modularity. There was no association between intelligence and whole brain modularity. However, node-type classification analyses revealed significantly fewer ultra-peripheral nodes in brain networks of more intelligent people, suggesting less segregated information processing. Region-specific analyses identified four regions in which within-module connectivity (within-module degree centrality Z-score) and between-module connectivity (participation coefficient) showed opposite associations with intelligence: In the right anterior insula (AI), higher intelligence was associated with more between- and less within-module connections, while the reverse was true for the bilateral temporo-parietal junction (TPJ) and right superior frontal gyrus (SFG). AI has previously been associated with the detection, evaluation, and selection of relevant information for cognitive processing, while TPJ is involved in shielding cognitive processes against interference from irrelevant information. The specific brain modularity profile observed for more intelligent people suggests that higher network integration of AI in combination with stronger segregation of TPJ facilitates both processes simultaneously, which enables successful cognitive performance and ultimately contributes to high intelligence.