Investigating robust associations between functional connectivity based on graph theory and general intelligence.

ABSTRACT: Previous research investigating relations between general intelligence and graph-theoretical properties of the brain's intrinsic functional network has yielded contradictory results. A promising approach to tackle such mixed findings is multi-center analysis. For this study, we analyzed data from four independent data sets (total N > 2000) to identify robust associations amongst samples between g factor scores and global as well as node-specific graph metrics. On the global level, g showed no significant associations with global efficiency or small-world propensity in any sample, but significant positive associations with global clustering coefficient in two samples. On the node-specific level, elastic-net regressions for nodal efficiency and local clustering yielded no brain areas that ex

SUBMITTER: Metzen D 

PROVIDER: S-EPMC10791664 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature