TY - JOUR
T1 - Enhancing Attention Network Spatiotemporal Dynamics for Motor Rehabilitation in Parkinson's Disease
AU - Pei, Guangying
AU - Hu, Mengxuan
AU - Ouyang, Jian
AU - Jin, Zhaohui
AU - Wang, Kexin
AU - Meng, Detao
AU - Wang, Yixuan
AU - Chen, Keke
AU - Wang, Li
AU - Cao, Li Zhi
AU - Funahashi, Shintaro
AU - Yan, Tianyi
AU - Fang, Boyan
N1 - Publisher Copyright:
Copyright © 2025 Guangying Pei et al.
PY - 2025
Y1 - 2025
N2 - Optimizing resource allocation for Parkinson’s disease (PD) motor rehabilitation necessitates identifying biomarkers of responsiveness and dynamic neuroplasticity signatures underlying efficacy. A cohort study of 52 early-stage PD patients undergoing 2-week multidisciplinary intensive rehabilitation therapy (MIRT) was conducted, which stratified participants into responders and nonresponders. A multimodal analysis of resting-state electroencephalography (EEG) microstates and functional magnetic resonance imaging (fMRI) coactivation patterns was performed to characterize MIRT-induced spatiotemporal network reorganization. Responders demonstrated clinically meaningful improvement in motor symptoms, exceeding the minimal clinically important difference threshold of 3.25 on the Unified PD Rating Scale part III, alongside significant reductions in bradykinesia and a significant enhancement in quality-of-life scores at the 3-month followup. Resting-state EEG in responders showed a significant attenuation in microstate C and a significant enhancement in microstate D occurrences, along with significantly increased transitions from microstate A/B to D, which significantly correlated with motor function, especially in bradykinesia gains. Concurrently, fMRI analyses identified a prolonged dwell time of the dorsal attention network coactivation/ventral attention network deactivation pattern, which was significantly inversely associated with microstate C occurrence and significantly linked to motor improvement. The identified brain spatiotemporal neural markers were validated using machine learning models to assess the efficacy of MIRT in motor rehabilitation for PD patients, achieving an average accuracy rate of 86%. These findings suggest that MIRT may facilitate a shift in neural networks from sensory processing to higher-order cognitive control, with the dynamic reallocation of attentional resources. This preliminary study validates the necessity of integrating cognitive–motor strategies for the motor rehabilitation of PD and identifies novel neural markers for assessing treatment efficacy.
AB - Optimizing resource allocation for Parkinson’s disease (PD) motor rehabilitation necessitates identifying biomarkers of responsiveness and dynamic neuroplasticity signatures underlying efficacy. A cohort study of 52 early-stage PD patients undergoing 2-week multidisciplinary intensive rehabilitation therapy (MIRT) was conducted, which stratified participants into responders and nonresponders. A multimodal analysis of resting-state electroencephalography (EEG) microstates and functional magnetic resonance imaging (fMRI) coactivation patterns was performed to characterize MIRT-induced spatiotemporal network reorganization. Responders demonstrated clinically meaningful improvement in motor symptoms, exceeding the minimal clinically important difference threshold of 3.25 on the Unified PD Rating Scale part III, alongside significant reductions in bradykinesia and a significant enhancement in quality-of-life scores at the 3-month followup. Resting-state EEG in responders showed a significant attenuation in microstate C and a significant enhancement in microstate D occurrences, along with significantly increased transitions from microstate A/B to D, which significantly correlated with motor function, especially in bradykinesia gains. Concurrently, fMRI analyses identified a prolonged dwell time of the dorsal attention network coactivation/ventral attention network deactivation pattern, which was significantly inversely associated with microstate C occurrence and significantly linked to motor improvement. The identified brain spatiotemporal neural markers were validated using machine learning models to assess the efficacy of MIRT in motor rehabilitation for PD patients, achieving an average accuracy rate of 86%. These findings suggest that MIRT may facilitate a shift in neural networks from sensory processing to higher-order cognitive control, with the dynamic reallocation of attentional resources. This preliminary study validates the necessity of integrating cognitive–motor strategies for the motor rehabilitation of PD and identifies novel neural markers for assessing treatment efficacy.
UR - http://www.scopus.com/pages/publications/105008440112
U2 - 10.34133/cbsystems.0293
DO - 10.34133/cbsystems.0293
M3 - Article
AN - SCOPUS:105008440112
SN - 2097-1087
VL - 6
JO - Cyborg and Bionic Systems
JF - Cyborg and Bionic Systems
M1 - 0293
ER -