EEG Microstate Dynamics Predict Cognitive Functioning in Older Adults
Primary Investigator (PI) Name
Tim Martin
Department
RCHSS – Psychological Science
Abstract
EEG Microstate Dynamics Predict Cognitive Functioning in Older Adults
Resting-state EEG microstates provide insight into the brain’s dynamic organization and have been linked to cognitive efficiency. In this study, we examined whether transition probabilities between specific microstates predicted overall cognitive performance. EEG data were collected from approximately 120 older adults, and Markov transition probabilities were calculated for transitions between four microstates at both pre- and post-assessment periods. Cognitive performance was measured using the NIH Toolbox Total Fully Corrected T-score. Correlational analyses revealed that post-assessment transitions from B→A were negatively associated with cognition (r = –.24, p = .008), whereas transitions from B→C were positively associated (r = .21, p = .022). A multiple regression including both predictors was also significant, F(2,117) = 4.26, p = .016, Adjusted R² = .05, and a standard error of 14.98. These results suggest that specific EEG microstate transitions reflect neural patterns linked to lower or higher cognitive performance, with the B→A transition potentially indicating less efficient brain-state dynamics.
Disciplines
Cognitive Psychology
EEG Microstate Dynamics Predict Cognitive Functioning in Older Adults
EEG Microstate Dynamics Predict Cognitive Functioning in Older Adults
Resting-state EEG microstates provide insight into the brain’s dynamic organization and have been linked to cognitive efficiency. In this study, we examined whether transition probabilities between specific microstates predicted overall cognitive performance. EEG data were collected from approximately 120 older adults, and Markov transition probabilities were calculated for transitions between four microstates at both pre- and post-assessment periods. Cognitive performance was measured using the NIH Toolbox Total Fully Corrected T-score. Correlational analyses revealed that post-assessment transitions from B→A were negatively associated with cognition (r = –.24, p = .008), whereas transitions from B→C were positively associated (r = .21, p = .022). A multiple regression including both predictors was also significant, F(2,117) = 4.26, p = .016, Adjusted R² = .05, and a standard error of 14.98. These results suggest that specific EEG microstate transitions reflect neural patterns linked to lower or higher cognitive performance, with the B→A transition potentially indicating less efficient brain-state dynamics.