INTRODUCTION: A growing number of studies implicate functional brain networks in intelligence, but it is unclear if network nodal structure relates to intelligence.

METHODS: Using MRI, we studied the relationship of the general intelligence factor (g) with cortical thickness (CT), local gyrification index (LGI), and voxel-based morphometry in the nodes of the default mode network (DMN) and task-positive network (TPN) in a cohort of 44 young, healthy adults. Employing a novel strategy, we performed repeated analyses with multiple sets of g estimates to remove false positives.

RESULTS: CT and LGI in medial and temporal nodes of the DMN were reliably correlated with g (p < 0.05; Pearson's coefficient: ‑0.52 to ‑0.25 and 0.22 to 0.41, respectively). Linear regression models were developed with these parameters to estimate individual g scores, with a median adj. R of 0.25.

CONCLUSION: Cortical thickness and gyrification in key nodes of the Default Mode Network correlate with intelligence. Linear regression models with these cortical parameters may provide an estimate of the g factor.