Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Group of Psychiatric Neuroscience, Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Piazza Giulio Cesare, 11, Bari, 70121, Italy.
Brain Topogr. 2024 Oct 2;38(1):1. doi: 10.1007/s10548-024-01083-x.
Microstates represent brief periods of quasi-stable electroencephalography (EEG) scalp topography, offering insights into dynamic fluctuations in event-related potential (ERP) topographies. Despite this, there is a lack of a comprehensive systematic overview of microstate findings concerning cognitive face processing. This review aims to summarize ERP findings on face processing using microstate analyses and assess their effectiveness in characterizing face-related neural representations. A literature search was conducted for microstate ERP studies involving healthy individuals and psychiatric populations, utilizing PubMed, Google Scholar, Web of Science, PsychInfo, and Scopus databases. Twenty-two studies were identified, primarily focusing on healthy individuals (n = 16), with a smaller subset examining psychiatric populations (n = 6). The evidence reviewed in this study suggests that various microstates are consistently associated with distinct ERP stages involved in face processing, encompassing the processing of basic visual facial features to more complex functions such as analytical processing, facial recognition, and semantic representations. Furthermore, these studies shed light on atypical attentional neural mechanisms in Autism Spectrum Disorder (ASD), facial recognition deficits among emotional dysregulation disorders, and encoding and semantic dysfunctions in Post-Traumatic Stress Disorder (PTSD). In conclusion, this review underscores the practical utility of ERP microstate analyses in investigating face processing. Methodologies have evolved towards greater automation and data-driven approaches over time. Future research should aim to forecast clinical outcomes and conduct validation studies to directly demonstrate the efficacy of such analyses in inverse space.
微状态代表了短暂的准稳定脑电图 (EEG) 头皮地形图时期，为事件相关电位 (ERP) 地形图的动态波动提供了深入了解。尽管如此，对于认知面孔处理的微状态发现，缺乏全面的系统综述。本综述旨在总结使用微状态分析进行的面孔处理的 ERP 研究结果，并评估其对面相关神经表示进行特征描述的有效性。使用 PubMed、Google Scholar、Web of Science、PsychInfo 和 Scopus 数据库对涉及健康个体和精神科人群的微状态 ERP 研究进行了文献检索。确定了 22 项研究，主要集中在健康个体（n=16），较小的一部分研究了精神科人群（n=6）。本研究回顾的证据表明，各种微状态与参与面孔处理的不同 ERP 阶段密切相关，包括基本视觉面部特征的处理到更复杂的功能，如分析处理、面部识别和语义表示。此外，这些研究揭示了自闭症谱系障碍 (ASD) 中注意力神经机制的异常、情绪失调障碍中面部识别缺陷以及创伤后应激障碍 (PTSD) 中的编码和语义功能障碍。总之，本综述强调了 ERP 微状态分析在研究面孔处理中的实际效用。随着时间的推移，方法已经朝着更大的自动化和数据驱动方法发展。未来的研究应该旨在预测临床结果，并进行验证研究，以直接证明此类分析在逆空间中的有效性。
