人的左前中心神经元组合中的手势编码
Carlos E Vargas-Irwin1,2,3, Tommy Hosman4,5, Jacob T Gusman6,4,5,7
1Department of Neuroscience, Brown University, Providence, RI, USA. Carlos_Vargas_Irwin@Brown.edu.
Communications biology
|August 30, 2025
概括
研究人员解码了来自运动皮质的神经信号以控制手势. 这种脑电脑接口 (BCI) 技术对行动能力有限的人来说是有前途的,
科学领域:
- 神经科学
- 生物医学工程
- 康复技术
背景情况:
- 上肢的敏捷运动是由复杂的皮质活动模式控制的.
- 脑电脑接口 (BCI) 技术为行动能力有限的人提供了潜在的解决方案.
- 了解神经信号对于开发有效的BCI应用至关重要.
研究的目的:
- 调查与灵巧的手势相关的皮质活动模式.
- 评估用于各种手势命令的皮质内记录的可行性.
- 探索BCI在恢复上肢功能方面的潜力.
主要方法:
- 使用微电极阵列记录来自运动皮层组合的神经活动,
- 参与者试图执行48种不同的手势.
- 分析神经数据以识别与特定手势相关的模式.
主要成果:
- 在所有48个手势中实现了~70%的分类准确性.
- 在分类10种手势时达到~90%的准确性.
- 证明前中心环中的单个单元集体活动可以产生各种与手势相关的信号.
- 观察到每个参与者的独特神经潜伏空间组织.
结论:
- 单半球运动皮质活动具有产生各种手势相关信号的潜力.
- 这些发现支持用于皮质内BCI的直观和多样化的指令信号的开发.
- 这项研究可以显著地帮助行动能力有限的临床患者.
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