Cortical Structure in Nodes of the Default Mode Network predicts General Intelligence
Archana Purushotham, Abhinav Yadav
preprint DOI: 10.21203/rs.3.rs-1367163/v1 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Observational cohort |
|---|---|
| Sample size | 44 |
| Population | Young, healthy adults |
| Topics | Default mode network |
| Key findings | Cortical thickness and gyrification in medial and temporal nodes of the Default Mode Network correlate with general intelligence and can predict individual g scores. |
Abstract
Abstract A growing number of studies implicate functional brain networks in intelligence, but it is unclear if network nodal structure relates to intelligence. 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. CT and LGI in medial and temporal nodes of the DMN were reliably correlated with g (P < 0.05; r: 0.31–0.41). A linear regression model developed with these parameters (adj. R2: 0.15–0.40) could predict individual g scores. Cortical thickness and gyrification in key nodes of the Default Mode Network correlate with intelligence and can predict g in individual subjects.