Spatiotemporal complexity patterns of resting-state bioelectrical activity explain fluid intelligence: Sex matters

Area of Science:

• Neuroscience
• Cognitive Science
• Information Theory

Background:

• Neural complexity is theorized to underpin efficient information processing.
• The precise relationship between brain activity complexity and cognitive abilities like fluid intelligence requires further elucidation.

Purpose of the Study:

• To investigate the association between fluid intelligence (gf) and resting-state electroencephalography (rsEEG) complexity.
• To examine how rsEEG complexity varies across different timescales and electrode locations in relation to gf.

Main Methods:

• Analysis of 6-minute eyes-open resting-state EEG data from 119 participants.
• Utilized multivariate multiscale sample entropy (mMSE) to quantify information richness in rsEEG across multiple channels and timescales.
• Fluid intelligence (gf) was derived from six standardized intelligence tests.

Main Results:

• Partial least square regression identified rsEEG complexity at coarse timescales in the frontoparietal network (FPN) and fine timescales in the temporo-parietal regions as key predictors of higher gf.
• Sex moderated the relationship: in men, gf correlated positively with coarse timescale complexity in the FPN and with both fine and coarse timescales in the parietal region.
• In women, gf showed positive associations with overall and coarse complexity in the FPN, but negative associations with fine timescale complexity in parietal and centro-temporal regions.

Conclusions:

• Distinct temporal pathways (fine and coarse timescales) characterizing rsEEG complexity are crucial for effective information processing.
• The findings highlight the complex interplay between neural complexity, fluid intelligence, and sex-specific brain activity patterns.