Tracking dynamic EEG connectivity in schizophrenia and bipolar disorder

Abstract

Abstract Psychotic syndromes, such as schizophrenia (SCZ) and bipolar disorder (BD), significantly disrupt brain electrical activity, with functional connectivity (FC) being particularly affected. However, FC is often estimated as a static measure, overlooking the brain dynamic fluctuations that naturally occur, even at rest. In this study, we investigated alterations in dynamic FC (dFC) using resting-state electroencephalographic (EEG) data from SCZ patients, BD patients, and age-matched healthy control (HC) subjects. To achieve this, the instantaneous amplitude correlation (IAC) was computed for each EEG recording within the canonical frequency bands. We then analyzed the first- to fourth-order cumulants of the average strength (aS) time series derived from the IAC matrices. Statistically significant differences were obtained between the SCZ and HC groups in aS mean (first-order cumulant) and aS skewness (third-order cumulant) at the gamma band, while the BD group reported differences against the HC group in aS mean at the delta band. Additionally, both disorders exhibited altered aS skewness in the beta band; these findings suggest disruptions in interneuronal communication, manifesting as “pathologically Gaussian” aS distributions over time. Our results highlight the potential of dFC analysis to uncover brain function anomalies that remain undetected with conventional approaches.