Suppr超能文献

人类左中央前回神经元群中的手势编码

Gesture encoding in human left precentral gyrus neuronal ensembles.

作者信息

Vargas-Irwin Carlos E, Hosman Tommy, Gusman Jacob T, Pun Tsam Kiu, Simeral John D, Singer-Clark Tyler, Kapitonava Anastasia, Nicolas Claire, Shah Nishal P, Avansino Donald T, Kamdar Foram, Williams Ziv M, Henderson Jaimie M, Hochberg Leigh R

机构信息

Department of Neuroscience, Brown University, Providence, RI, USA.

Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, RI, USA.

出版信息

Commun Biol. 2025 Aug 30;8(1):1315. doi: 10.1038/s42003-025-08557-z.

Abstract

Understanding the cortical activity patterns driving dexterous upper limb motion has the potential to benefit a broad clinical population living with limited mobility through the development of novel brain-computer interface (BCI) technology. The present study examines the activity of ensembles of motor cortical neurons recorded using microelectrode arrays in the dominant hemisphere of two BrainGate clinical trial participants with cervical spinal cord injury as they attempted to perform a set of 48 different hand gestures. Although each participant displayed a unique organization of their respective neural latent spaces, it was possible to achieve classification accuracies of ~70% for all 48 gestures (and ~90% for sets of 10). Our results show that single-unit ensemble activity recorded in a single hemisphere of human precentral gyrus has the potential to generate a wide range of gesture-related signals across both hands, providing an intuitive and diverse set of potential command signals for intracortical BCI use.

摘要

通过开发新型脑机接口(BCI)技术,了解驱动灵巧上肢运动的皮层活动模式,有望使广大行动不便的临床患者受益。本研究检测了两名参加BrainGate临床试验的颈脊髓损伤患者优势半球中,使用微电极阵列记录的运动皮层神经元集群的活动,他们试图做出一组48种不同的手势。尽管每个参与者各自的神经潜在空间呈现出独特的组织方式,但对于所有48种手势都能达到约70%的分类准确率(对于10种手势的集合,准确率约为90%)。我们的结果表明,在人类中央前回的单个半球中记录的单单元集群活动,有可能产生与双手相关的广泛手势信号,为皮层内BCI的使用提供了一组直观且多样的潜在命令信号。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验