Noninvasive neural decoding of walking

描述(申请人提供)：该项目广泛的、长期的目标是开发新型非侵入性神经假体，用于恢复和/或康复脊髓损伤(SCI)、肌萎缩侧索硬化症(ALS)、皮质下中风或下肢截肢患者的两足运动。两足运动控制是脑机接口(BMI)领域的研究热点，脑机接口是一种利用神经活动控制假肢和步态康复的装置。由于运动障碍通常与脊髓损伤和神经退行性疾病有关，也有必要研究新的潜在治疗方法来恢复这些患者的步态控制。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还没有被证明。这个项目建立在我们实验室对运动的非侵入性神经解码的基础上，遵循一种原则性的、循序渐进的、实验和计算的方法来从头皮EEG中对人类两足运动进行神经解码，并开发用于步态康复的脑机接口。该项目的具体目标是：1)研究从头皮脑电获取的大脑活动中最能预测哪些步态参数；2)使用闭环BCI环境，纵向检查在适应虚拟皮质损伤或步态运动学虚拟扰动的过程中，步态皮质表征的变化。这将是首次对皮质网络如何适应健康受试者步态神经表征的变化进行时间分辨的研究，并可能对研究脑损伤或身体残疾后皮质的可塑性以及步态恢复的BMI的发展具有意义。这项研究对步态功能受损的患者具有临床意义，例如中风患者、帕金森病患者、脊髓损伤患者和下肢截肢者，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.