Electroencephalographic Microstate Correlates of Fluid Intelligence

• Main Author: Khanna, Arjun R.
• Format: Others
• Language: en
• Published: Harvard University 2016
• Online Access: http://nrs.harvard.edu/urn-3:HUL.InstRepos:27007746

The neurobiological correlates of human fluid intelligence (Gf) remain elusive. Converging lines of evidence suggest a pivotal role for the efficiency and connectivity of anatomically-defined brain networks, but little is known about Gf-related electrophysiological dynamics of these networks occurring at native timescales, such as those measured via electroencephalography (EEG). Spatiotemporal analysis of state-space dynamics of the EEG signal, involving examination of fast-changing, recurring, topographically-defined electric patterns termed “microstates,” may enable investigation of the electrophysiological activity of distributed cortical networks and their relation to brain characteristics, including Gf. Here, we correlated EEG microstate patterns with multiple fluid intelligence measures, and assessed changes in microstate patterns after cognitive training aimed at improving intelligence. We found that the frequency of activation of specific brain topographies, spatially associated with visual (microstate B) and executive control (microstate C) networks, were inversely related to Gf scores. When Gf scores were separated into two distinct “dimensions” of intelligence using latent factor analysis, each “dimension” correlated with a different microstate, suggesting that each microstate class represents a distinct cognitive modality. Cognitive training resulted in a posterior shift in the topography of microstate C, possibly reflecting increased prefrontal inhibitory control over parietal brain regions. These results highlight the role of fast-changing brain electrical states related to visual and executive functions in Gf, as well as the mechanisms behind Gf enhancement after cognitive training.