This study aims to find an effective method to evaluate the efficacy of cognitive training of spatial memory under a virtual reality environment, by classifying the EEG signals of subjects in the early and late stages of spatial cognitive training. This study proposes a new EEG signal analysis method based on Multivariate Permutation Conditional Mutual Information-Multi-Spectral Image (MPCMIMSI). This method mainly considers the relationship between the coupled features of EEG signals in different channel pairs and transforms the multivariate permutation conditional mutual information features into multi-spectral images. Then, a convolutional neural networks (CNN) model classifies the resultant image data into different stages of cognitive training to objectively assess the efficacy of the training. Compared to the multi-spectral image transformation method based on Granger causality analysis (GCA) and permutation conditional mutual information (PCMI), the MPCMIMSI led to better classification performance, which can be as high as 95% accuracy. More specifically, the Theta-Beta2-Gamma-band combination has the best accuracy. The proposed MPCMIMSI method outperforms the multi-spectral image transformation methods based on GCA and PCMI in terms of classification performance. The MPCMIMSI feature in the Theta-Beta2-Gamma band is an effective biomarker for assessing the efficacy of spatial memory training. The proposed EEG feature-extraction method based on MPCMIMSI offers a new window to characterize spatial information of the noninvasive EEG recordings and might apply to assessing other brain functions.

中文翻译：

---

基于多元排列条件互信息-多光谱图像的空间认知能力评估的脑电信号分析

本研究旨在通过对空间认知训练早期和晚期受试者的脑电信号进行分类，找到一种有效的方法来评估虚拟现实环境下的空间记忆认知训练的效果。这项研究提出了一种新的基于多元排列条件互信息多光谱图像（MPCMIMSI）的脑电信号分析方法。该方法主要考虑了不同通道对中脑电信号耦合特征之间的关系，并将多元置换条件互信息特征转换为多光谱图像。然后，卷积神经网络（CNN）模型将所得图像数据分类为认知训练的不同阶段，以客观地评估训练的有效性。与基于Granger因果分析（GCA）和置换条件互信息（PCMI）的多光谱图像变换方法相比，MPCMIMSI具有更好的分类性能，准确率可高达95％。更具体地说，Theta-Beta2-Gamma波段组合具有最佳精度。提出的MPCMIMSI方法在分类性能方面优于基于GCA和PCMI的多光谱图像转换方法。Theta-Beta2-Gamma波段中的MPCMIMSI功能是评估空间记忆训练功效的有效生物标记。提出的基于MPCMIMSI的EEG特征提取方法为表征非侵入性EEG记录的空间信息提供了一个新窗口，并且可能适用于评估其他脑功能。