Altered EEG-derived functional brain states in Parkinson's disease with mild cognitive impairment

Abstract

Abstract The neurobiological mechanism underpinning cognitive impairment in Parkinson's disease remains poorly understood, although it increasingly points to aberrant spatiotemporal switching among large-scale network configurations. Leveraging the high temporal resolution of source-reconstructed EEG, we characterized these microstate alterations and their direct coupling with cognitive performance. This study used an enhanced Leading eigenvector dynamics analysis framework on source-reconstructed EEG data to probe the temporal properties and transition dynamics of brain functional states in Parkinson's disease patients with and without mild cognitive impairment. EEG signals were projected into source space via individual MRI-constrained source imaging, producing time series from 400 cortical regions. Recurring brain states were identified based on instantaneous phase coherence. We computed each state occupancy rate, state duration, and transition probabilities in both Parkinson's disease patients with and without mild cognitive impairment groups. Correlations with Montreal Cognitive Assessment scores were assessed. By identifying four recurrent brain states (states A–D), Parkinson's disease patients with mild cognitive impairment exhibited increased state occupancy rate and state duration in state B and decreased engagement in state D. In addition, transitions into state D from other states were significantly diminished in the mild cognitive impairment group. Crucially, both the temporal expression and kinetic accessibility of state D were positively correlated with Montreal Cognitive Assessment scores, suggesting that this integrated configuration underpins high-order cognitive function and may serve as a neural marker of cognitive resilience in Parkinson's disease. Cognitive deterioration in Parkinson's disease is fundamentally associated with disrupted brain state dynamics, marked by a pathological hyper-convergence towards state B and a systemic attrition of state D. These alterations likely reflect impaired attentional control and network rigidity, and may serve as dynamic biomarkers and therapeutic targets for Parkinson's disease-related cognitive decline.