Volkova Ksenia, Lebedev Mikhail A, Kaplan Alexander, Ossadtchi Alexei
Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia.
Center for Biotechnology Development, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.
Front Neuroinform. 2019 Dec 3;13:74. doi: 10.3389/fninf.2019.00074. eCollection 2019.
Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.
皮质脑电图(ECoG)有望为患有神经功能障碍的患者提供有效的神经假体解决方案。与其他侵入性方法相比,这种记录技术兼具足够的时间和空间分辨率,且医疗并发症风险较低。ECoG在临床实践中常用于癫痫患者的术前皮质图谱绘制。在过去二十年中,利用ECoG的研究大幅增加,包括通过不同复杂程度的解码算法从ECoG活动中提取行为相关信息的范例。几个研究团队已在开发由脑机接口(BCI)驱动的辅助设备方面取得进展,这些接口可从多通道ECoG记录中解码运动指令。在此,我们回顾该领域的发展历程及其近期趋势,并讨论未来潜在的发展领域。