ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

心理科学进展 ›› 2026, Vol. 34 ›› Issue (3): 441-460.doi: 10.3724/SP.J.1042.2026.0441 cstr: 32111.14.2026.0441

• 研究方法 • 上一篇    下一篇

同步TMS-EEG技术在心理学研究中的应用

郭新宇, 汤煜尧, 张丹丹   

  1. 四川师范大学脑与心理科学研究院, 成都 610066
  • 收稿日期:2025-10-14 出版日期:2026-03-15 发布日期:2026-01-07
  • 基金资助:
    国家自然科学基金面上项目(32271102)支持

Applications of TMS-EEG in psychological research: Neurophysiological assessment, causal neural mechanisms, and closed-loop modulation

GUO Xinyu, TANG Yuyao, ZHANG Dandan   

  1. Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
  • Received:2025-10-14 Online:2026-03-15 Published:2026-01-07

摘要: 同步经颅磁刺激-脑电图(transcranial magnetic stimulation-electroencephalography, TMS-EEG)是一种将经颅磁刺激与脑电记录同步整合的技术。一方面, EEG能够记录TMS脉冲引起的瞬时神经电生理反应, 另一方面, TMS脉冲的施加也能基于所记录的EEG信号来进行状态依赖的精准调控。本文结合这两个特点提出并系统梳理了同步TMS-EEG在心理学研究中的三种主要应用模式:神经生理评估、因果性揭示神经机制以及大脑闭环调控。文章将围绕这三条主线, 区分并比较不同模式在工作机制、实验方案与应用目标上的差异, 并结合近10年的心理学相关研究, 梳理各模式已有研究的主要发现, 以期为应用同步TMS-EEG技术提供清晰的理论框架与实践指南。

关键词: 同步经颅磁刺激-脑电图, 神经生理评估, 虚拟损伤, 因果性神经机制, 闭环调控

Abstract: Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) has become an increasingly important methodological tool in psychological and cognitive neuroscience research, as it enables direct perturbation of cortical activity while simultaneously capturing neural responses with high temporal resolution. Rather than providing correlational evidence alone, concurrent TMS-EEG allows researchers to probe the causal organization, temporal dynamics, and state-dependency of brain networks underlying cognition and emotion. Despite rapid growth in empirical applications over the past decade, existing studies remain conceptually fragmented, and a unified framework that systematically distinguishes different modes of TMS-EEG usage in psychological research is still lacking. The present review addresses this gap by proposing a three-mode framework that organizes concurrent TMS-EEG applications into (1) neurophysiological assessment, (2) causal neural mechanisms, and (3) closed-loop modulation. This framework represents the core conceptual innovation of the review, as it clarifies how identical technical components—online TMS delivery and concurrent EEG recording—serve fundamentally different scientific purposes depending on experimental logic, stimulation timing, and analytical goals. First, in the neurophysiological assessment mode, TMS-EEG is used as an active probing technique to characterize cortical excitability, excitation-inhibition balance, oscillatory dynamics, and large-scale connectivity. TMS-evoked potential (TEP), TMS-related spectral perturbation (TRSP), and propagation of evoked responses across distant cortical regions provide quantitative biomarkers of neural function beyond spontaneous EEG activity. By synthesizing recent clinical and non-clinical studies, this review highlights how specific TEP components (e.g., N45, N100), frequency-specific oscillatory responses, and interregional signal propagation have been applied to identify abnormalities in disorders such as depression, schizophrenia, Alzheimer's disease, and disorders of consciousness. Importantly, TMS-EEG-based assessment extends classical TMS-EMG approaches beyond the motor system, enabling whole-brain evaluation of cortical and network-level physiology. Second, in the causal neural mechanism mode, concurrent TMS-EEG is employed to transiently perturb targeted brain regions at specific task-relevant time points, allowing researchers to identify when and how a given region contributes to cognitive or emotional processes. This approach is mainly based on a “virtual lesion” logic and directly recording the neural consequences of perturbation, including changes in event-related potentials, oscillatory activity, and information propagation. The review systematically summarizes evidence demonstrating how TMS-EEG has been used to delineate the temporal windows of regional involvement, reveal directionality of interregional interactions, and map dynamic information flow during perception, attention, language processing, action preparation, and emotion regulation. A key contribution of this section is the integration of single-site and multi-site stimulation studies within a unified causal framework, highlighting how sequential or coordinated perturbations can uncover hierarchical and cooperative network dynamics. Third, the review identifies closed-loop TMS-EEG as an emerging and transformative application mode. In contrast to open-loop stimulation paradigms, closed-loop approaches use real-time EEG features—such as oscillatory phase or power—to trigger TMS pulses contingent on the current brain state. This mode enables state-dependent, individualized neuromodulation and provides a direct experimental test of brain-state-behavior relationships. The review synthesizes recent studies demonstrating phase-specific modulation of cortical excitability, enhancement of synaptic-like plasticity, and improvements in cognitive performance through closed-loop stimulation. By integrating methodological advances in real-time signal processing and artifact suppression, the review highlights closed-loop TMS-EEG as a critical bridge between basic causal neuroscience and precision intervention. Across these three modes, the present review advances the field by articulating a progressive methodological logic, moving from basic physiological measurement, to causal exploration, and ultimately to precise modulation of brain function. Finally, the review discusses current methodological challenges—including stimulation timing uncertainty, variability of regulatory effects, and artifact control—and outlines future directions, such as connectivity-based stimulation timing, multi-site closed-loop paradigms, and real-time artifact removal. Overall, this review provides an integrated conceptual and methodological reference for researchers seeking to apply concurrent TMS-EEG to the study of psychological processes and their neural mechanisms.

Key words: TMS-EEG, neurophysiological assessment, virtual lesion, causal neural mechanisms, closed-loop modulation