Schroeder Karen E, Chestek Cynthia A
Department of Biomedical Engineering, University of Michigan Ann Arbor, MI, USA.
Department of Biomedical Engineering, University of MichiganAnn Arbor, MI, USA; Neuroscience Graduate Program, University of Michigan Medical SchoolAnn Arbor, MI, USA; Center for Consciousness Science, University of Michigan Medical SchoolAnn Arbor, MI, USA; Department of Electrical Engineering and Computer Science, University of MichiganAnn Arbor, MI, USA; Robotics Graduate Program, University of MichiganAnn Arbor, MI, USA.
Front Neurosci. 2016 Jun 28;10:291. doi: 10.3389/fnins.2016.00291. eCollection 2016.
Brain-machine interfaces (BMIs) decode brain activity to control external devices. Over the past two decades, the BMI community has grown tremendously and reached some impressive milestones, including the first human clinical trials using chronically implanted intracortical electrodes. It has also contributed experimental paradigms and important findings to basic neuroscience. In this review, we discuss neuroscience achievements stemming from BMI research, specifically that based upon upper limb prosthetic control with intracortical microelectrodes. We will focus on three main areas: first, we discuss progress in neural coding of reaches in motor cortex, describing recent results linking high dimensional representations of cortical activity to muscle activation. Next, we describe recent findings on learning and plasticity in motor cortex on various time scales. Finally, we discuss how bidirectional BMIs have led to better understanding of somatosensation in and related to motor cortex.
脑机接口(BMI)通过解码大脑活动来控制外部设备。在过去二十年中,BMI领域取得了巨大发展,并达成了一些令人瞩目的里程碑,包括首次使用长期植入的皮层内电极进行人体临床试验。它还为基础神经科学贡献了实验范式和重要发现。在本综述中,我们将探讨BMI研究带来的神经科学成就,特别是基于皮层内微电极的上肢假肢控制研究。我们将聚焦于三个主要领域:第一,我们讨论运动皮层中伸手动作的神经编码进展,描述将皮层活动的高维表征与肌肉激活联系起来的最新研究成果。接下来,我们阐述运动皮层在不同时间尺度上学习和可塑性方面的最新发现。最后,我们讨论双向BMI如何增进了对运动皮层及其相关体感的理解。