パーキンソン病における動的アルファバンド結合の探求：BioVRSeaパラダイムを用いた姿勢制御評価への新規アプローチ

Parkinson's Disease (PD) is a neurological disorder characterized by impaired postural control (PC) and balance issues. To date, few studies have explored the relationship between brain activity and responses during specific tasks designed to challenge balance in individuals with PD. Our exploratory research employs an innovative paradigm to assess PC by integrating virtual reality (VR) and electroencephalography (EEG). In the study, 20 individuals diagnosed with PD who self-reported postural instability participated in the BioVRSea paradigm. This paradigm tested their PC using visuomotor stimuli and collected EEG signals to assess brain responses throughout the experiment. The results of the Parkinson's group were compared with those of 22 age-matched healthy controls (CTR). From the functional connectivity between brain regions, we extracted brain network states (BNSs) using the k-means++ clustering algorithm. These BNSs capture the dynamic organization of brain activity and were compared with canonical resting-state networks (RSNs) to investigate neural alterations in individuals with PD. Six distinct BNSs were identified, with the dorsal attention network (DAN) dominant in five states. A significant reduction in the coverage of BNS2 was observed in PD patients during both the PRE (adjusted p-value = 0.019) and MOV (adjusted p-value = 0.036) phases compared to CTR. This reduced BNS2 coverage suggests impaired visuomotor integration in PD patients during PC tasks. DAN dominance highlights its crucial role in maintaining attentional control during the task. The findings of this study highlight the potential of using brain dynamics as a biomarker of neural dysfunction in PD, especially during specific PC tasks. Altered BNSs, particularly in networks associated with attention and sensorimotor integration, reveal key neural deficits related to PD.