从单试次神经生理时间序列中分离诱发与诱发后活动
Disentangling evoked and induced activity from single-trial neurophysiological time series
在神经功能受损疾病的治疗开发与评估中，诱发反应与诱导反应是基本的神经生理学读出指标。区分这两类反应对于解读单试次变异性、识别这些反应的决定因素，以及实现对皮层反应性的实时探测至关重要。然而，由于动态重叠，当关注皮层反应性的瞬时波动时，在单试次水平上分离诱发活动与诱导活动仍未得到解决。我们开发了诱发-持续/诱导分离器（Evoked-Ongoing/Induced Separator，EOIS），这是一个从单试次数据中分离事件诱发活动、持续活动和事件调制诱导活动的框架。EOIS 利用诱发成分与持续/诱导成分在 MEG 和实时 EEG 中各自不同的相位一致性特征来恢复这些成分，从而实现与被试无关的单试次时间序列分析，并将皮层反应变异性归因于特定成分。通过提供成分分辨的时间序列，EOIS 能够支持生物标志物优化、药效学读出和闭环神经调控，促进在个体和护理环境中的转化部署。
把单试次信号拆成诱发、持续和事件调制诱发三部分，为实时追踪皮层反应性提供了一种可跨被试使用的时间序列分解框架。
Evoked and induced responses are fundamental neurophysiological readouts in the development and assessment of treatments for disorders with impaired neural function. Distinguishing these responses is essential for interpreting single-trial variability, identifying the determinants of these responses, and enabling real-time probing of cortical responsiveness. However, because of dynamic overlap, separating evoked and induced activity remains unsolved at the single-trial level when instantaneous fluctuations of cortical responsiveness are of interest. We developed the Evoked-Ongoing/Induced Separator (EOIS), a framework for separating event-evoked, ongoing, and event-modulated induced activity from single-trial data. EOIS recovers evoked and ongoing/induced components by leveraging their distinct phase-consistency features in MEG and real-time EEG, enabling subject-agnostic single-trial time-series analysis and attribution of cortical response variability to specific components. By delivering component-resolved time series, EOIS enables biomarker refinement, pharmacodynamic readouts, and closed-loop neuromodulation, facilitating translational deployment across individuals and care settings.
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来源：bioRxiv · Neuroscience · biorxiv.org