Exploring dynamic alpha band connectivity in Parkinsons disease: A novel approach to postural control assessment using the BioVRSea paradigm
Gargiulo, P.; Pescaglia, F.; Guerrini, L.; Gelormini, C.; Aubonnet, R.; Thormar, G. O.; Di Lorenzo, G.; Jonsson, H.; Hassan, M.
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ObjectiveParkinsons 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). ApproachIn 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 Parkinsons group were compared with those of 22 age-matched healthy controls (CTR). From functional connectivity between brain regions, we employed novel techniques that use clustering algorithms to identify brain network states (BNSs). These BNSs define brain dynamics and can be compared with resting-state networks (RSNs) to further explore and identify neural alterations in individuals with PD. Main ResultsSix distinct BNSs were identified, with the dorsal attention network (DAN) dominant in five states. A significant reduction in the occurrence of BNS2 (p=0.005) was observed in PD patients during the PRE movement and visuomotor (MOV) phases compared to CTR. This reduced occurrence of BNS2 suggests impaired visuomotor integration in PD patients during PC tasks. DAN dominance highlights its crucial role in maintaining attentional control during the task. SignificanceThe 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.
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