Noninvasive neural decoding of walking

描述（由申请人提供）：该项目的广泛、长期目标是开发新型无创神经假肢，用于脊髓损伤（SCI）、肌萎缩侧索硬化症（ALS）、皮质下中风或下肢截肢患者的双足运动恢复和/或康复。双足运动的控制是脑机接口（BMIs）领域的一个重要研究方向，即利用神经活动控制假肢和步态康复的设备。由于运动缺陷通常与脊髓损伤和神经退行性疾病相关，因此还需要研究新的潜在疗法来恢复这类患者的步态控制。虽然在猴子和人类的研究中已经证明了上肢BMI的可行性，但人类两足运动的神经解码尚未得到证实。该项目建立在我们实验室非侵入性运动神经解码的基础上，遵循原则性的、循序渐进的、实验性的和计算性的方法，从头皮脑电图中解码人类两足运动的神经，并开发用于步态康复的脑机接口。该项目的具体目的是：1)研究从头皮脑电图获得的大脑活动中最能预测哪些步态参数；2)利用闭环脑机接口（BCI）环境，纵向研究步态皮层表征在适应虚拟皮质损伤或虚拟步态运动学扰动过程中的变化。这将是首次对健康受试者的皮质网络如何适应步态神经表征的变化进行时间解决的研究，并可能对研究脑损伤或身体残疾后的皮质可塑性以及开发用于步态恢复的bmi具有指导意义。这项研究对步态功能受损的患者具有临床意义，如中风患者、帕金森病、脊髓损伤和下肢截肢者，因为bmi有朝一日可能有助于恢复步态功能。

DESCRIPTION (provided by applicant): The broad, long-term goal of this project is to develop novel noninvasive neuroprosthetics for restoration and/or rehabilitation of bipedal locomotion in patients with spinal cord injury (SCI), amyotrophic lateral sclerosis (ALS), subcortical stroke or lower limb amputations. The control of bipedal locomotion is of great interest to the fields of brain machine interfaces (BMIs), i.e. devices that utilize neural activity to control limb prosthesis and gait rehabilitation. Since locomotion deficits are commonly associated with SCI and neurodegenerative diseases, there is also a need to investigate new potential therapies to restore gait control in such patients. While the feasibility of a BMI for upper limbs has been demonstrated in studies in monkeys and humans, neural decoding of bipedal locomotion in humans has not yet been demonstrated. This project builds upon findings from non-invasive neural decoding of movements in our laboratory, and follows a principled, step-by-step, experimental and computational approach to neural decoding of human bipedal locomotion from scalp EEG and the development of brain-computer interfaces for gait rehabilitation. The specific aims of this project are: 1) to investigate what gait parameters are best predicted from brain activity acquired with scalp EEG; 2) to examine longitudinally the changes in the cortical representation of gait during adaptation to virtual cortical lesions or virtual perturbations of gait kinematics using a closed-loop BCI environment. This will be the first time-resolved examination of how cortical networks may adapt to changes in the neural representation of gait in healthy subjects, and may have implications for studying cortical plasticity after brain injury or physical disability, and for the development of BMIs for gait restoration. This research is clinically significant to patients with impaired gait function, as in the case of stroke patients, Parkinson's disease, SCI and lower-limb amputees, as BMIs may one day help restore gait function.