基于静息态脑电图的卒中后抑郁脑网络异常特征研究

目的 基于静息态脑电图探索卒中后抑郁（post-stroke depression，PSD）脑网络特征异常改变，提取 客观生物标志物。 方法 回顾性分析深圳市人民医院脑电数据库中缺血性卒中慢性期患者病例资料，收集静息态 脑电图与汉密尔顿抑郁量表（Hamilton depression scale，HAMD）、MMSE及NIHSS评分资料。以HAMD评分 ≥20分为分界值，并通过病灶位置及体积匹配将患者分为PSD组和卒中后非抑郁（post stroke nondepression， PSND）组。脑电图数据预处理后，分别基于相干性虚部及能量包络在皮层源层面建立不同 频段功能连接矩阵，采用基于网络的统计方法分析两组间差异。 结果 与PSND组比较，PSD组患者①基于相干性虚部的脑网络连接在δ频段减弱，以顶叶脑区连接 减弱更明显；θ频段减弱，以左侧额顶颞枕、边缘叶及右侧额叶连接减弱更明显；γ频段增强，以左 侧额叶、边缘叶及右侧顶叶脑区连接增强更明显；②基于能量包络的脑网络连接在α频段增强，以双 侧顶枕叶脑区连接增强更明显。 结论 PSD患者脑网络发生异常改变，静息态脑电图是揭示这种改变的有效工具。

Characteristics of Resting State Brain Network in Post-stroke Depression

Objective To investigate the changes of brain network and markers of post-stroke depression (PSD)
by resting-state electroencephalogram (rsEEG).
Methods The EEG data of patients with chronic cerebral infarction in Department of Neurology
of Shenzhen People’s Hospital were retrospectively analyzed. The rsEEG data and the scores of
Hamilton depression scale (HAMD), MMSE and NIHSS were collected. Patients were divided into
PSD group(HAMD score ≥20 points) and post-stroke non-depression group (PSND group, HAMD
score <20 points), and the two groups were matched for the location and size of infarction. After
preprocessing the EEG data, the functional connection matrices of different frequency bands were
established at the cortical source level based on the imaginary part of coherency and the power
envelope, and the differences between the two groups were analyzed using network-based statistical
method.
Results Compared with the PSND group, the patients in PSD group: (1) the brain network
connection based on the imaginary part of coherency was weakened in the delta frequency band,
especially in the parietal lobe; and decreased in the theta frequency band, especially in the left
hemisphere, marginal lobe and the right frontal lobe; and enhanced in the gamma frequency band,
especially in the left frontal lobe, marginal lobe and right parietal lobe; (2) the power envelopebased
brain network connection was enhanced in the alpha frequency band, especially in bilateralparietal and occipital lobes.
Conclusions Abnormal changes of the brain networks occurred in patients with post-stroke
depression, and rsEEG was an effective tool to reveal the changes.