Subthalamic stimulation modulates motor network in Parkinson’s disease: recover, relieve and remodel

Author:

Chu Chunguang1,Liu Shang1,He Naying2,Zeng Zhitong3,Wang Jiang1,Zhang Zhen1,Zeljic Kristina4,van der Stelt Odin5,Sun Bomin3ORCID,Yan Fuhua2ORCID,Liu Chen1ORCID,Li Dianyou3ORCID,Zhang Chencheng356ORCID

Affiliation:

1. School of Electrical and Information Engineering, Tianjin University , Tianjin 300072 , China

2. Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai 200025 , China

3. Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai 200020 , China

4. Centre for Applied Vision Research, City, University of London , London EC1V 0HB , UK

5. Clinical Neuroscience Center, Ruijin Hospital LuWan Branch, Shanghai Jiao Tong University School of Medicine , Shanghai 200020 , China

6. Shanghai Research Center for Brain Science and Brain-Inspired Technology , Shanghai 202163 , China

Abstract

Abstract Aberrant dynamic switches between internal brain states are believed to underlie motor dysfunction in Parkinson’s disease. Deep brain stimulation of the subthalamic nucleus is a well-established treatment for the motor symptoms of Parkinson’s disease, yet it remains poorly understood how subthalamic stimulation modulates the whole-brain intrinsic motor network state dynamics. To investigate this, we acquired resting-state functional magnetic resonance imaging time-series data from 27 medication-free patients with Parkinson’s disease (mean age: 64.8 years, standard deviation: 7.6) who had deep brain stimulation electrodes implanted in the subthalamic nucleus, in both on and off stimulation states. Sixteen matched healthy individuals were included as a control group. We adopted a powerful data-driven modelling approach, known as a hidden Markov model, to disclose the emergence of recurring activation patterns of interacting motor regions (whole-brain intrinsic motor network states) via the blood oxygen level-dependent signal detected in the resting-state functional magnetic resonance imaging time-series data from all participants. The estimated hidden Markov model disclosed the dynamics of distinct whole-brain motor network states, including frequency of occurrence, state duration, fractional coverage and their transition probabilities. Notably, the data-driven decoding of whole-brain intrinsic motor network states revealed that subthalamic stimulation reshaped functional network expression and stabilized state transitions. Moreover, subthalamic stimulation improved motor symptoms by modulating key trajectories of state transition within whole-brain intrinsic motor network states. This modulation mechanism of subthalamic stimulation was manifested in three significant effects: recovery, relieving and remodelling effects. Significantly, recovery effects correlated with improvements in tremor and posture symptoms induced by subthalamic stimulation (P < 0.05). Furthermore, subthalamic stimulation was found to restore a relatively low level of fluctuation of functional connectivity in all motor regions to a level closer to that of healthy participants. Also, changes in the fluctuation of functional connectivity between motor regions were associated with improvements in tremor and gait symptoms (P < 0.05). These findings fill a gap in our knowledge of the role of subthalamic stimulation at the level of neural activity, revealing the regulatory effects of subthalamic stimulation on whole-brain inherent motor network states in Parkinson’s disease. Our results provide mechanistic insight and explanation for how subthalamic stimulation modulates motor symptoms in Parkinson’s disease.

Funder

National Natural Science Foundation of China

Shanghai Sailing Program

Shanghai Research Center for Brain Science and Brain-Inspired Technology

Publisher

Oxford University Press (OUP)

Subject

Neurology (clinical)

Reference61 articles.

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