Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Giustiniani 3, 35128, Padova, Italy.
Padova Neuroscience Center, University of Padova, Via Orus 2, 35131, Padova, Italy.
Brain Topogr. 2024 May;37(3):475-478. doi: 10.1007/s10548-023-00967-8. Epub 2023 May 17.
Stroke recovery trajectories vary substantially. The need for tracking and prognostic biomarkers in stroke is utmost for prognostic and rehabilitative goals: electroencephalography (EEG) advanced signal analysis may provide useful tools toward this aim. EEG microstates quantify changes in configuration of neuronal generators of short-lasting periods of coordinated synchronized communication within large-scale brain networks: this feature is expected to be impaired in stroke. To characterize the spatio-temporal signatures of EEG microstates in stroke survivors in the acute/subacute phase, EEG microstate analysis was performed in 51 first-ever ischemic stroke survivors [(28-82) years, 24 with right hemisphere (RH) lesion] who underwent a resting-state EEG recording in the acute and subacute phase (from 48 h up to 42 days after the event). Microstates were characterized based on 4 parameters: global explained variance (GEV), mean duration, occurrences per second, and percentage of coverage. Wilcoxon Rank Sum tests were performed to compare features of each microstate across the two groups [i.e., left hemisphere (LH) and right hemisphere (RH) stroke survivors]. The canonical microstate map D, characterized by a mostly frontal topography, displayed greater GEV, occurrence per second, and percentage of coverage in LH than in RH stroke survivors (p < 0.05). The EEG microstate map B, with a left-frontal to right-posterior topography, and F, with an occipital-to-frontal topography, exhibited a greater GEV in RH than in LH stroke survivors (p = 0.015). EEG microstates identified specific topographic maps which characterize stroke survivors' lesioned hemisphere in the acute and early subacute phase. Microstate features offer an additional tool to identify different neural reorganization.
中风的恢复轨迹差异很大。为了实现预后和康复目标,中风患者非常需要追踪和预测生物标志物:脑电图(EEG)高级信号分析可能为此目的提供有用的工具。EEG 微状态量化了在大尺度脑网络中短暂协调同步通讯的神经元发生器构型变化:预计这种特征在中风中会受损。为了在急性/亚急性阶段的中风幸存者中描述 EEG 微状态的时空特征,对 51 名首次发生的缺血性中风幸存者([28-82]岁,24 名右侧大脑半球[RH]病变)进行了 EEG 微状态分析,他们在急性和亚急性阶段(事件后 48 小时至 42 天)进行了静息状态 EEG 记录。微状态基于 4 个参数进行特征描述:全局解释方差(GEV)、平均持续时间、每秒发生次数和覆盖率百分比。Wilcoxon 秩和检验用于比较两组(即左侧大脑半球[LH]和右侧大脑半球[RH]中风幸存者)的每个微状态的特征。特征主要呈额状分布的典型微状态图 D 在 LH 中风幸存者中比 RH 中风幸存者显示出更大的 GEV、每秒发生次数和覆盖率百分比(p < 0.05)。具有左额-右后状分布的 EEG 微状态图 B 和具有枕状-额状分布的 F 图在 RH 中风幸存者中显示出比 LH 中风幸存者更大的 GEV(p = 0.015)。EEG 微状态确定了特定的拓扑图,这些图在急性和早期亚急性阶段描绘了中风幸存者的病变半球。微状态特征提供了一种额外的工具来识别不同的神经重组。