神经工程与脑-机接口

Neural engineering and brain-computer interface

神经工程是近年来在生物医学工程领域备受关注的学科发展新方向。它运用神经科学和工程学的方法来分析神经功能并为神经功能缺失与紊乱的修复提供新的解决问题的方案;而脑-机接口则是当前神经工程领域中最活跃的研究方向之一。脑-机接口是在脑与计算机或其他外部设备之间建立的直接的通信和交流通道。在脑-机接口系统中,具有特定模式的脑信号携带着受试者希望表达的意愿,计算机将接收到的脑信号转换成相应的控制命令,于是那些有运动障碍的残疾人就可以利用脑-机接口系统来实现与外界的交流与对外部设备的控制。在基于脑电信号的脑-机接口系统中,受试者产生的脑信号大致可以分为内源性(endogenous)和外源性(exogenous)两类。其中外源性的成分主要取决于外部物理刺激(视觉、听觉或触觉)的参数而与认知行为无关;而内源性成分则主要由认知行为产生而与外部的物理刺激无关。在许多情况下,脑-机接口中的瞬态诱发电位通常都同时包含着内源性和外源性两种成分。寻找新的脑-机接口模式使之能显著提升记录脑电信号中的内源性与外源性成分在脑-机接口研究中具有重要意义。本文中将介绍一种基于运动起始时刻(motion-onset)的新的脑-机接口实验范式。本文的最后还探讨了脑-机接口未来发展的趋势与展望。

Neural engineering is an emerging research area in biomedical engineering. Neural engineering brings to bear neuroscience and engineering methods to analyze neurological function as well as to design solutions to problems associated with neurological limitations and dysfunction. Currently, brain-computer interface has become one of the most active research directions in neural engineering. Brain-computer interface （BCI） is a direct non-muscular communication or control channel between brain and computeror external devices. In a BCI system, users produce special pattern of brain signals which encode his/her intention, and computer will translate the signals into control commends so that people with severe motor disorders can use it for communication or controls. Electroencephalogram （EEG） based BCI is a non-invasive technology and probably the most acceptable system for various users. In EEG based BCI systems, brain signals are usually be classified as endogenous and exogenous. The exogenous components are determined by the parameters of the physical stimulus （visual, auditory or tactile） rather than by a cognitive event, whereas the endogenous components are determined by some cognitive event rather than by the physical stimulus. In many cases, transient evoked potentials adopted in BCI systems are composed of both endogenous and exogenous components, seeking for new BCI modalities, which can significant enhance both endogenous and exogenous components in recorded EEG signals is of great importance in BCI system development. A novel design of BCI paradigms based on motiononset visual evoked potentials is presented. Finally, an overview of the trend and future development of BCI is discussed.