Leuthardt Eric C, Schalk Gerwin, Roland Jarod, Rouse Adam, Moran Daniel W
Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Neurosurg Focus. 2009 Jul;27(1):E4. doi: 10.3171/2009.4.FOCUS0979.
The notion that a computer can decode brain signals to infer the intentions of a human and then enact those intentions directly through a machine is becoming a realistic technical possibility. These types of devices are known as brain-computer interfaces (BCIs). The evolution of these neuroprosthetic technologies could have significant implications for patients with motor disabilities by enhancing their ability to interact and communicate with their environment. The cortical physiology most investigated and used for device control has been brain signals from the primary motor cortex. To date, this classic motor physiology has been an effective substrate for demonstrating the potential efficacy of BCI-based control. However, emerging research now stands to further enhance our understanding of the cortical physiology underpinning human intent and provide further signals for more complex brain-derived control. In this review, the authors report the current status of BCIs and detail the emerging research trends that stand to augment clinical applications in the future.
计算机能够解码大脑信号以推断人类意图，然后通过机器直接实现这些意图，这一概念正成为一种现实的技术可能性。这类设备被称为脑机接口（BCI）。这些神经假体技术的发展可能会对运动障碍患者产生重大影响，因为它们能增强患者与环境互动和交流的能力。研究最多且用于设备控制的皮层生理学是来自初级运动皮层的大脑信号。迄今为止，这种经典的运动生理学一直是证明基于BCI控制潜在功效的有效基础。然而，新兴研究现在有望进一步加深我们对支撑人类意图的皮层生理学的理解，并为更复杂的脑源控制提供更多信号。在这篇综述中，作者报告了脑机接口的现状，并详细阐述了有望在未来扩大临床应用的新兴研究趋势。
