Syrov Nikolay, Muhammad Daha Garba, Medvedeva Alexandra, Yakovlev Lev, Kaplan Alexander, Lebedev Mikhail
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, Russia.
Laboratory for Neurophysiology and Neuro-Computer Interfaces, Department of Human and Animal Physiology, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia.
Psychophysiology. 2025 Jan;62(1):e14708. doi: 10.1111/psyp.14708. Epub 2024 Oct 14.
This study investigates the cortical correlates of motor response control and monitoring, using the Theory of Event Coding (TEC) as a framework to investigate signals related to low-level sensory processing of motor reafference and high-level response monitoring, including verification of response outcomes with the internal model. We used a visuomotor paradigm with two targets at different distances from the participant. For the recorded movement-related cortical potentials (MRCPs), we analyzed their different components and assessed the movement phases during which they are active. Residual iteration decomposition (RIDE) and multivariate pattern analysis (MVPA) were used for this analysis. Using RIDE, we separated MRCPs into signals related to different parallel processes of visuomotor transformation: stimulus processing (S-cluster), motor response preparation and execution (R-cluster), and intermediate processes (C-cluster). We revealed sequential activation in the R-cluster, with execution-related negative components and positive contralateral peaks reflecting reafference processing. We also identified the motor post-imperative negative variation within the R-cluster, highlighting the response outcome evaluation process included in the action file. Our findings extend the understanding of C-cluster signals, typically associated with stimulus-response mapping, by demonstrating C-activation from the preparatory stages through to response termination, highlighting its participation in action monitoring. In addition, we highlighted the ability of MVPA to identify movement-related attribute encoding: where statistical analysis showed independence of stimulus processing activity from movement distance, MVPA revealed distance-related differences in the S-cluster within a time window aligned with the lateralized readiness potential (LRP). This highlights the importance of integrating RIDE and MVPA to uncover the intricate neural dynamics of motor control, sensory integration, and response monitoring.
本研究以事件编码理论（TEC）为框架，调查运动反应控制与监测的皮质相关性，以研究与运动再传入的低级感觉处理以及高级反应监测相关的信号，包括使用内部模型对反应结果进行验证。我们采用了一种视觉运动范式，其中有两个与参与者距离不同的目标。对于记录的与运动相关的皮质电位（MRCPs），我们分析了它们的不同成分，并评估了它们活跃的运动阶段。使用了残差迭代分解（RIDE）和多变量模式分析（MVPA）进行此分析。通过RIDE，我们将MRCPs分离为与视觉运动转换的不同并行过程相关的信号：刺激处理（S簇）、运动反应准备与执行（R簇）以及中间过程（C簇）。我们揭示了R簇中的顺序激活，其中与执行相关的负成分和对侧正峰反映了再传入处理。我们还在R簇中识别出运动命令后负变化，突出了动作文件中包含的反应结果评估过程。我们的研究结果扩展了对通常与刺激-反应映射相关的C簇信号的理解，通过证明从准备阶段到反应终止的C激活，突出了其在动作监测中的参与。此外，我们强调了MVPA识别与运动相关属性编码的能力：在统计分析显示刺激处理活动与运动距离无关的情况下，MVPA揭示了在与侧化准备电位（LRP）对齐的时间窗口内S簇中与距离相关的差异。这突出了整合RIDE和MVPA以揭示运动控制、感觉整合和反应监测的复杂神经动力学的重要性。
