Connectivity of EEG synchronization networks increases for Parkinson's disease patients with freezing of gait.
Connectivity of EEG synchronization networks increases for Parkinson's disease patients with freezing of gait.
复制标题
步态冻结的帕金森病患者脑电图同步网络的连通性增强。
DOI：
10.1038/s42003-021-02544-w
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发表时间：
2021-08-30
影响因子：
5.9
通讯作者：
Bartsch RP
中科院分区：
文献类型：
--
作者：
Asher EE;Plotnik M;Günther M;Moshel S;Levy O;Havlin S;Kantelhardt JW;Bartsch RP
步态冻结（FoG）是帕金森病（PD）患者常见的一种阵发性步态障碍，其特征是突然发作无法产生有效的向前迈步。最近的研究表明，在FoG期间，基底神经节中局部场电位的β频率增加，然而，对PD患者不同大脑位置和频带之间的同步性的全面研究很少。在这里，通过开发基于网络科学和非线性动力学的工具，我们分析了三组具有不同FoG严重程度的PD患者的脑电图（EEG）脑电波的同步网络。我们发现随着PD和FoG严重程度的增加，不同大脑位置之间的EEG幅度同步性更高（更强的网络链接）。这些结果在不同频带（θ、α、β、γ）之间是一致的，并且与特定的运动任务（行走、站立、手敲击）无关，这表明PD和FoG严重程度的增加与广泛的大脑频率范围内的更强EEG网络相关。PD/FoG严重程度与整体EEG同步的直接关系的观察以及我们提出的EEG同步网络方法可用于评估FoG倾向，并有助于进一步了解PD和导致FoG的病理生理学。Asher等人使用基于网络科学和非线性动力学的工具，分析了三组具有不同步态冻结（FoG）严重程度的帕金森病（PD）患者的脑电图脑电波同步网络。他们的研究结果表明，PD/FoG严重程度与整体EEG同步之间存在潜在关系，他们的方法可用于帮助进一步了解导致FoG的病理生理学。
Freezing of gait (FoG), a paroxysmal gait disturbance commonly experienced by patients with Parkinson’s disease (PD), is characterized by sudden episodes of inability to generate effective forward stepping. Recent studies have shown an increase in beta frequency of local-field potentials in the basal-ganglia during FoG, however, comprehensive research on the synchronization between different brain locations and frequency bands in PD patients is scarce. Here, by developing tools based on network science and non-linear dynamics, we analyze synchronization networks of electroencephalography (EEG) brain waves of three PD patient groups with different FoG severity. We find higher EEG amplitude synchronization (stronger network links) between different brain locations as PD and FoG severity increase. These results are consistent across frequency bands (theta, alpha, beta, gamma) and independent of the specific motor task (walking, still standing, hand tapping) suggesting that an increase in severity of PD and FoG is associated with stronger EEG networks over a broad range of brain frequencies. This observation of a direct relationship of PD/FoG severity with overall EEG synchronization together with our proposed EEG synchronization network approach may be used for evaluating FoG propensity and help to gain further insight into PD and the pathophysiology leading to FoG. Asher et al analyzed synchronization networks of electroencephalography brain waves from three Parkinson’s disease (PD) patient groups with different freezing of gait (FoG) severity using tools based on network science and non-linear dynamics. Their findings suggest that there is a potential relationship between PD/FoG severity and overall EEG synchronization and their approach could be used to help gain further insight into the pathophysiology leading to FoG.