Dysfunctional Brain Dynamics of Parkinson's Disease and the Effect of Acute Deep Brain Stimulation.

Zhibao Li,Kun Liang,Qiao Wang,Hui Qiao,Guoping Ren,Chunlei Han,Fangang Meng,Qun Wang,Jianguo Zhang,Chong Liu

doi:10.3389/fnins.2021.697909

Abstract

Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease, and deep brain stimulation (DBS) can effectively alleviate PD symptoms. Although previous studies have detected network features of PD and DBS, few studies have considered their dynamic characteristics.Objective: We tested two hypotheses. (1) Reduced brain dynamics, as evidenced by slowed microstate dynamic change, is a characteristic of PD and is related to the movement disorders of patients with PD. (2) Therapeutic acute DBS can partially reverse slow brain dynamics in PD to healthy levels.Methods: We used electroencephalography (EEG) microstate analysis based on high density (256-channel) EEG to detect the effects of PD and DBS on brain dynamic changes on a sub-second timescale. We compared 21 healthy controls (HCs) with 20 patients with PD who were in either DBS-OFF or DBS-ON states. Assessment of movement disorder using the Unified Parkinson's Disease Rating Scale III was correlated with microstate parameters.Results: Compared with HCs, patients with PD displayed a longer mean microstate duration with reduced occurrence per second, which were significantly associated with movement disorders. In patients with PD, some parameters of microstate analysis were restored toward healthy levels after DBS.Conclusions: Resting-state EEG microstate analysis is an important tool for investigating brain dynamic changes in PD and DBS. PD can slow down brain dynamic change, and therapeutic acute DBS can partially reverse this change toward a healthy level.

Highlights

Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease (Reich and Savitt, 2019)
Several studies have shown that PD induces abnormal topology of brain functional connectivity within the triple network model [the default mode network (DMN), the salience network (SN), and the executive/frontoparietal network (FPN)] and in other networks, including motor and visual networks (Skidmore et al, 2011; Baggio et al, 2014; Lebedev et al, 2014; Gorges et al, 2015; Luo et al, 2015; Putcha et al, 2015; Tinaz et al, 2016)
There were no significant differences in age or gender between patients with PD and healthy controls (HCs)

Summary

Introduction

Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease (Reich and Savitt, 2019). It is characterized by a series of motor symptoms, such as tremor, stiffness, slowness, and imbalance, and various non-motor (non-movement) symptoms, such as depression, sleep disturbances, and dementia (Armstrong and Okun, 2020). The brain network abnormalities in patients with PD are not local or limited to several neural circuits but are large scale and distributed. Parkinson’s disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease, and deep brain stimulation (DBS) can effectively alleviate PD symptoms. Previous studies have detected network features of PD and DBS, few studies have considered their dynamic characteristics

Methods

Results

Discussion

Conclusion