Reduced Effective Connectivity In The Motor Cortex In Parkinson'S Disease

BRAIN SCIENCES(2021)

引用 9|浏览4
暂无评分
摘要
Fast rhythms excess is a hallmark of Parkinson's Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls. First, we fitted multivariate auto-regressive models to the EEG source waveforms. Second, we estimated causal connections using Granger Causality, which provide information on connections' strength and directionality. Lastly, we sought significant differences connectivity patterns between the two populations characterizing the network graph features-i.e., global efficiency and node strength. Causal brain networks in PD show overall poorer and weaker connections compared to controls quantified as a reduction of global efficiency. Motor areas appear almost isolated, with a strongly impoverished information flow particularly from parietal and occipital cortices. This striking isolation of motor areas may reflect an impaired sensory-motor integration in PD. The identification of defective nodes/edges in PD network may be a biomarker of disease and a potential target for future interventional trials.
更多
查看译文
关键词
EEG, Granger causality, MultiVariate AutoRegressive models, global efficiency, sensory-motor integration
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要