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Related Experiment Video

Updated: May 16, 2025

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
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Cortical Structure in Nodes of the Default Mode Network Estimates General Intelligence.

Abhinav Yadav1,2,3, Archana Purushotham1,3,4,5

  • 1Institute for Stem Cell Science and Regenerative Medicine, Bangalore, India.

Brain and Behavior
|May 13, 2025
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Summary

Brain network structure, specifically cortical thickness and gyrification in the Default Mode Network (DMN), is linked to general intelligence (g). These brain metrics may help estimate individual intelligence scores.

Keywords:
cortical thicknessdefault mode networkgeneral intelligencelocal gyrification index

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Human Intelligence

Background:

  • Emerging research links functional brain networks to intelligence.
  • The relationship between specific network structures and intelligence remains largely unexplored.

Purpose of the Study:

  • To investigate the association between the general intelligence factor (g) and the structural properties of brain networks.
  • To explore if cortical thickness (CT) and local gyrification index (LGI) in network nodes correlate with intelligence.

Main Methods:

  • Utilized magnetic resonance imaging (MRI) on 44 healthy adults.
  • Examined CT, LGI, and voxel-based morphometry in Default Mode Network (DMN) and task-positive network (TPN) nodes.
  • Employed a novel repeated analysis strategy with multiple g estimates to ensure result reliability.

Main Results:

  • Found significant correlations between CT and LGI in medial and temporal DMN nodes and general intelligence (g).
  • CT showed negative correlations (‑0.52 to ‑0.25), while LGI demonstrated positive correlations (0.22 to 0.41).
  • Developed linear regression models using these parameters, achieving a median adjusted R² of 0.25 for estimating individual g scores.

Conclusions:

  • Cortical thickness and gyrification in specific Default Mode Network regions are reliably associated with general intelligence.
  • Linear regression models incorporating these structural brain parameters show potential for estimating the g factor.