亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Neural decoding of gait phase information during motor imagery and improvement of the decoding accuracy by concurrent action observation

作者
Hikaru Yokoyama,Naotsugu Kaneko,Katsumi Watanabe,Kimitaka Nakazawa
出处
期刊: [Cold Spring Harbor Laboratory]
被引量:1
标识
DOI:10.1101/2020.08.19.258210
摘要

Abstract Brain decoding of motor imagery (MI) is crucial for the control of neuroprosthesis, and it provides insights into the underlying neural mechanisms. Walking consists of stance and swing phases, which are associated with different biomechanical and neural control features. However, previous studies on the decoding of the MI of walking focused on the classification of more simple information (e.g., walk and rest). Here, we investigated the feasibility of electroencephalogram (EEG) decoding of the two gait phases during the MI of walking and whether the combined use of MI and action observation (AO) would improve decoding accuracy. We demonstrated that the stance and swing phases could be decoded from EEGs during AO or MI alone. Additionally, the combined use of MI and AO improved decoding accuracy. The decoding models indicated that the improved decoding accuracy following the combined use of MI and AO was facilitated by the additional information resulting from the concurrent cortical activations by multiple regions associated with MI and AO. This study is the first to show that decoding the stance versus swing phases during MI is feasible. The current findings provide fundamental knowledge for neuroprosthetic design and gait rehabilitation, and they expand our understanding of the neural activity underlying AO, MI, and AO+MI of walking. Significance Statement Brain decoding of detailed gait-related information during motor imagery (MI) is important for brain-computer interfaces (BCIs) for gait rehabilitation. However, previous knowledge on decoding the motor imagery of gait is limited to simple information (e.g., the classification of “walking” and “rest”). Here, we demonstrated the feasibility of EEG decoding of the two gait phases during MI. We also demonstrated that the combined use of MI and action observation (AO) improves decoding accuracy, which is facilitated by the concurrent and synergistic involvement of the cortical activations by multiple regions for MI and AO. These findings extend the current understanding of neural activity and the combined effects of AO and MI and provide a basis for developing effective techniques for walking rehabilitation.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
花海发布了新的文献求助10
刚刚
6秒前
桓桓的桓桓完成签到,获得积分10
10秒前
科研通AI6.4应助花海采纳,获得10
10秒前
桥西小河完成签到 ,获得积分10
11秒前
14秒前
会撒娇的乌冬面完成签到 ,获得积分10
16秒前
忘忧Aquarius完成签到,获得积分0
16秒前
17秒前
Kao应助科研通管家采纳,获得10
22秒前
Kao应助科研通管家采纳,获得10
22秒前
FeelingUnreal完成签到,获得积分10
35秒前
GHOSTagw完成签到,获得积分10
38秒前
49秒前
50秒前
55秒前
55秒前
1分钟前
1分钟前
1分钟前
慕青应助轻松的斑马采纳,获得10
1分钟前
伶俐的一斩完成签到,获得积分10
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
花海发布了新的文献求助10
1分钟前
无情的聪健应助秦长春采纳,获得20
1分钟前
科研通AI6.4应助花海采纳,获得30
1分钟前
灯火阑珊完成签到 ,获得积分10
1分钟前
默默的以柳完成签到,获得积分10
1分钟前
2分钟前
2分钟前
2分钟前
江誌濤发布了新的文献求助10
2分钟前
Una完成签到,获得积分10
2分钟前
2分钟前
2分钟前
灵巧的幼萱完成签到,获得积分10
2分钟前
zkk发布了新的文献求助10
2分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Introducing the Learning Sciences 600
Resiliency Scale for Adolescents--Chinese Version 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7323597
求助须知:如何正确求助?哪些是违规求助? 8938947
关于积分的说明 18952061
捐赠科研通 6980770
什么是DOI,文献DOI怎么找? 3215275
关于科研通互助平台的介绍 2382675
邀请新用户注册赠送积分活动 2194516