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Shining Light on the Human Brain: An Optical BCI for Communicating with Patients with Brain Injuries

机译:在人脑上闪耀光线:与脑损伤患者沟通的光学BCI

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Functional near-infrared spectroscopy (fNIRS) is an emerging optical technology that can be used to monitor brain function at the bedside. Recently, there has been a great interest in using fNIRS as a tool to assess command-driven brain activity in patients with severe brain injuries to infer residual awareness. In this study, time-resolved (TR) fNIRS, a variant of fNIRS with enhanced sensitivity to the brain, was used to assess brain function in patients with prolonged disorders of consciousness (DOC). A portable system was developed in-house, and patients were assessed in their homes or long-term care facilities across London and the Greater Toronto Area, Canada. Five DOC patients and one locked-in patient were recruited in this study, and motor imagery was used to elicit command-driven brain activity. TR-fNIRS data were analyzed using the general linear modelling (GLM) approach, as well as with basic machine learning. Three patients showed activity with GLM, four with machine learning, and two with both techniques. Interestingly, the two patients that showed activity by both approaches also had detectable motor imagery activity by functional magnetic resonance imaging. These promising preliminary results highlight the potential of TR fNIRS as a tool to probe consciousness and map brain activity at the bedside.
机译:功能近红外光谱(FNIR)是一种新兴光学技术,可用于监测床侧的大脑功能。最近,利用FNIR作为评估严重脑损伤患者的命令驱动的大脑活动以推断剩余意识的工具。在该研究中,使用时间分辨(TR)FNIR,用于对大脑敏感性增强的FNIR的变体,用于评估患者患者的脑功能,延长意识(DOC)。在内部开发了一个便携式系统,患者在伦敦和加拿大大多雅地区的家庭或长期护理设施中进行评估。在本研究中招募了五名Doc患者和一个锁定的患者,并使用汽车图像引发指挥驱动的大脑活动。使用一般线性建模(GLM)方法以及基本机器学习分析TR-FNIRS数据。三名患者展示了GLM,四个带机器学习的活动,两种技术都有两种技术。有趣的是,通过两种方法显示活动的两名患者通过功能磁共振成像也具有可检测的电动机图像活动。这些有前途的初步结果突出了TR FNIR作为探测意识的工具的潜力,并在床边映射脑活动。

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