Spatial-Temporal Discriminative Restricted Boltzmann Machine for Event-Related Potential Detection and Analysis
Spatial-Temporal Discriminative Restricted Boltzmann Machine for Event-Related Potential Detection and Analysis
复制标题
用于事件相关电位检测和分析的空间-时间判别受限玻尔兹曼机
DOI：
10.1109/tnsre.2019.2892960
复制
发表时间：
2019-02-01
影响因子：
4.9
通讯作者：
Li, Yuanqing
中科院分区：
文献类型：
--
作者：
Li, Jingcong;Yu, Zhu Liang;Li, Yuanqing
事件相关电位（ERP）的低信噪比和复杂的时空特征使其检测成为一个具有挑战性的问题。传统的检测方法通常依赖于整体平均技术，这可能会删除ERP信号中微妙但重要的信息，导致检测性能差。受区分限制玻尔兹曼机（DRBM）在特征提取和分类方面的良好性能的启发，提出了一种时空DRBM（ST-DRBM）方法，用于提取ERP的时空特征。实验结果和统计分析表明，所提出的方法是能够实现国家的最先进的ERP检测性能。ST-DRBM不仅是一种有效的ERP检测器，也是一种实用的ERP分析工具。基于该模型，不同会话的ERP信号中发现了相似的头皮分布和时间变化，这表明跨会话ERP检测的可行性。由于其先进的性能和有效的分析技术，ST-DRBM是基于ERP的脑机接口和神经科学研究的前景。
Detecting event-related potential (ERP) is a challenging problem because of its low signal-to-noise ratio and complex spatial-temporal features. Conventional detection methods usually rely on the ensemble averaging technique, which may eliminate subtle but important information in ERP signals and lead to poor detection performance. Inspired by the good performance of discriminative restricted Boltzmann machine (DRBM) in feature extraction and classification, we propose a spatial-temporal DRBM (ST-DRBM) to extract spatial and temporal features for ERP detection. The experimental results and statistical analyses demonstrate that the proposed method is able to achieve state-of-the-art ERP detection performance. The ST-DRBM is not only an effective ERP detector, but also a practical tool for ERP analysis. Based on the proposed model, similar scalp distribution and temporal variations were found in the ERP signals of different sessions, which indicated the feasibility of cross-session ERP detection. Given its state-of-the-art performance and effective analytical technique, ST-DRBM is promising for ERP-based brain-computer interfaces and neuroscience research.