Brain Computer Interface: Inference of Spatial Field

描述(申请人提供)：脑-机-接口(BCI)提取和分类从大脑记录的电信号，允许用户绕过运动系统，仅凭思想控制硬件，如计算机光标或假肢设备。锁定的ALS或严重脊髓损伤患者的实际应用已经在实验室环境中得到证明；然而，当前的方法依赖于受试者使用反馈来训练他们的思维，并且经常导致用户在非实验室、自定速条件下的精神疲劳和不可靠。这里提出的翻译研究试图通过从与自愿到达运动的预定目标相关的大脑顶区的电活动中提取信息来解决这些问题。将编写一种算法，将以眼睛为中心的坐标中预期空间场的电生理签名转换为计算机屏幕的空间特征。这种推断方法有望在自定进度的非实验室条件下提供对用户意图的更稳健的检测。贡献包括为残疾人口改进的辅助技术，以及有关感觉运动处理的基础神经科学方面的新的普遍知识。

DESCRIPTION (provided by applicant): Brain-Computer-Interfaces (BCIs) extract and classify electrical signals recorded from the brain to allow users to bypass the motor system and control hardware such as a computer cursor or a prosthetic device by thoughts alone. Practical applications for locked-in patients with ALS or severe spinal cord injury have been demonstrated in laboratory settings; however, current methods rely on the subjects to train their thoughts using feedback and often lead to user mental fatigue and unreliability in non-laboratory, self-paced conditions. The translational research proposed here seeks to address those issues by extracting information from the electrical activity in parietal regions of the brain associated with the intended targets of voluntary reaching movements. An algorithm will be written to translate those electrophysiological signatures of intended spatial field in eye-centered coordinates into spatial features of the computer screen. This inferential method is expected to provide more robust detection of the user's intentions under self-paced, non-laboratory conditions. Contributions include improved assistive technologies for disabled populations as well as new generalizable knowledge in basic neuroscience regarding sensorimotor processing.