Brain State Transition Disruptions in Alzheimer's Disease: Insights from EEG State Dynamics

Seyed Majid Razavi, Triet M. Tran, Steven E. Wilson, Sina Khanmohammadi

Abstract: Alzheimer's Disease (AD) has been associated with reduced neuroplasticity, but the extent to which such reduction impacts large-scale neural dynamics is not yet fully understood. Here, we use a network dynamics analysis framework based on Laplacian Eigenmaps to study the disruptions of brain state transitions associated with AD. Specifically, we utilize the Normalized Variability Index (NVI) to quantify the consistency of nonlinear brain state transitions in resting state electroencephalogram (EEG). Our results show that AD patients tend to have significantly lower NVI values compared to control subjects, reflecting more consistent brain state transitions. The difference was most significant in the Beta band, which has been associated with memory encoding and retrieval. Overall, our results suggest a reduced flexibility in brain state transitions among Alzheimer's patients. These results could provide new insights into large-scale neural dynamics in Alzheimer's disease and pave the path for developing new biomarkers for early detection and diagnosis.