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首页> 美国卫生研究院文献>Cognitive Neurodynamics >Hemispheric asymmetry non-linear analysis of EEG during emotional responses from idiopathic Parkinson’s disease patients
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Hemispheric asymmetry non-linear analysis of EEG during emotional responses from idiopathic Parkinson’s disease patients

机译：特发性帕金森病患者情绪反应期间脑电的半球不对称非线性分析

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Recent studies show right hemisphere has a unique contribution to emotion processing. The present study investigated EEG using non-linear measures during emotional processing in PD patients with respect to motor symptom asymmetry (i.e., most affected body side). We recorded 14-channel wireless EEGs from 20 PD patients and 10 healthy age-matched controls (HC) by eliciting emotions such as happiness, sadness, fear, anger, surprise and disgust. PD patients were divided into two groups, based on most affected body side and unilateral motor symptom severity: left side-affected (LPD, n = 10) or right side-affected PD patients (RPD, n = 10). Nonlinear analysis of these emotional EEGs were performed by using approximate entropy, correlation dimension, detrended fluctuation analysis, fractal dimension, higher order spectra, hurst exponent (HE), largest Lyapunov exponent and sample entropy. The extracted features were ranked using analysis of variance based on F value. The ranked features were then fed into classifiers namely fuzzy K-nearest neighbor and support vector machine to obtain optimal performance using minimum number of features. From the experimental results, we found that (a) classification performance across all frequency bands performed well in recognizing emotional states of LPD, RPD, and HC; (b) the emotion-specific features were mainly related to higher frequency bands; and (c) predominantly LPD patients (inferred right-hemisphere pathology) were more impaired in emotion processing compared to RPD, as showed by a poorer classification performance. The results suggest that asymmetric neuronal degeneration in PD patients may contribute to the impairment of emotional communication.
机译：最近的研究表明，右半球对情绪处理具有独特的贡献。本研究以运动症状不对称（即受影响最大的身体一侧）为基础，在PD患者的情绪处理过程中使用非线性测量方法调查了脑电图。我们通过诱发情绪，如幸福，悲伤，恐惧，愤怒，惊奇和厌恶，记录了来自20位PD患者和10位年龄匹配的健康对照（HC）的14通道无线EEG。根据受影响最严重的身体一侧和单侧运动症状的严重程度，PD患者分为两组：左侧受影响的患者（LPD，n = 10）或右侧受影响的PD患者（RPD，n = 10）。通过使用近似熵，相关维，去趋势波动分析，分形维，高阶谱，赫斯特指数（HE），最大Lyapunov指数和样本熵对这些情绪EEG进行非线性分析。使用基于F值的方差分析对提取的特征进行排名。然后将排序后的特征输入到分类器中，即模糊K最近邻和支持向量机，以使用最少数量的特征获得最佳性能。从实验结果中，我们发现：（a）在识别LPD，RPD和HC的情绪状态时，所有频段的分类表现都很好； （b）特定于情绪的特征主要与较高频段有关； （c）与LPD相比，主要是LPD患者（推断为右半球病理）在情感加工方面受到的损害更大，这表现为较差的分类表现。结果表明，PD患者的神经元不对称变性可能会导致情感交流障碍。

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