It is widely recognized that continuous sensory feedback plays a crucial role in accurate motor control in everyday life. Feedback information is used to adapt force output and to correct errors. While primary motor cortex contralateral to the movement (cM1) plays a dominant role in this control, converging evidence supports the idea that ipsilateral primary motor cortex (iM1) also directly contributes to hand and finger movements. Similarly, when visual feedback is available, primary visual cortex (V1) and its interactions with the motor network also become important for accurate motor performance. To elucidate this issue, we performed and integrated behavioral and electroencephalography (EEG) measurements during isometric compression of a compliant rubber bulb, at 10% and 30% of maximum voluntary contraction, both with and without visual feedback. We used a semi-blind approach (functional source separation (FSS)) to identify separate functional sources of mu-frequency (8–13Hz) EEG responses in cM1, iM1 and V1. Here for the first time, we have used orthogonal FSS to extract multiple sources, by using the same functional constraint, providing the ability to extract different sources that oscillate in the same frequency range but that have different topographic distributions. We analyzed the single-trial timecourses of mu power event-related desynchronization (ERD) in these sources and linked them with force measurements to understand which aspects are most important for good task performance. Whilst the amplitude of mu power was not related to contraction force in any of the sources, it was able to provide information on performance quality. We observed stronger ERDs in both contralateral and ipsilateral motor sources during trials where contraction force was most consistently maintained. This effect was most prominent in the ipsilateral source, suggesting the importance of iM1 to accurate performance. This ERD effect was sustained throughout the duration of visual feedback trials, but only present at the start of no feedback trials, consistent with more variable performance in the absence of feedback. Overall, we found that the behavior of the ERD in iM1 was the most informative aspect concerning the accuracy of the contraction performance, and the ability to maintain a steady level of contraction. This new approach of using FSS to extract multiple orthogonal sources provides the ability to investigate both contralateral and ipsilateral nodes of the motor network without the need for additional information (e.g. electromyography). The enhanced signal-to-noise ratio provided by FSS opens the possibility of extracting complex EEG features on an individual trial basis, which is crucial for a more nuanced understanding of fine motor performance, as well as for applications in brain-computer interfacing.

中文翻译：

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同侧初级运动皮层在精细收缩和准确表现期间在视觉运动网络中的作用

人们普遍认为，连续的感觉反馈在日常生活中的精确运动控制中起着至关重要的作用。反馈信息用于调整力输出和纠正错误。虽然运动对侧的初级运动皮层 (cM1) 在这种控制中起主导作用，但越来越多的证据支持同侧初级运动皮层 (iM1) 也直接促成手和手指运动的观点。同样，当视觉反馈可用时，初级视觉皮层 (V1) 及其与运动网络的相互作用对于准确的运动表现也很重要。为了阐明这个问题，我们在顺应橡胶球的等长压缩过程中进行并整合了行为和脑电图 (EEG) 测量，在最大自主收缩的 10% 和 30% 时，无论有无视觉反馈。我们使用半盲方法（功能源分离（FSS））来识别单独的功能源亩-频率（8-13Hz) cM1、iM1 和 V1 中的脑电图反应。在这里，我们第一次使用正交 FSS 来提取多个源，通过使用相同的功能约束，提供了提取在相同频率范围内振荡但具有不同地形分布的不同源的能力。我们分析了这些来源中 mu 功率事件相关去同步 (ERD) 的单次试验时间过程，并将它们与力测量联系起来，以了解哪些方面对良好的任务表现最重要。虽然幅度亩在任何来源中，功率都与收缩力无关，它能够提供有关性能质量的信息。我们在收缩力最持续保持的试验中观察到对侧和同侧运动源的 ERD 更强。这种效应在同侧源中最为突出，表明 iM1 对准确性能的重要性。这种 ERD 效应在整个视觉反馈试验期间持续存在，但仅在无反馈试验开始时出现，这与在没有反馈的情况下表现出更多可变性一致。总体而言，我们发现 iM1 中 ERD 的行为是有关收缩性能准确性和保持稳定收缩水平的能力的最具信息性的方面。这种使用 FSS 提取多个正交源的新方法提供了研究运动网络的对侧和同侧节点的能力，而无需额外的信息（例如肌电图）。FSS 提供的增强信噪比开启了在个体试验的基础上提取复杂 EEG 特征的可能性，这对于更细致地理解精细运动性能以及脑机接口中的应用至关重要。