机器学习解码体内单个神经元的语音大脑机器接口
Ariel Tankus1,2,3, Noam Rosenberg4, Oz Ben-Hamo4
1Functional Neurosurgery Unit, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel.
Journal of neural engineering
|April 22, 2024
概括
在 thalamus 中单个神经元的活动.
科学领域:
- 神经科学是一个神经科学.
- 生物医学工程 生物医学工程
背景情况:
- 胸膜中介核 (Vim) 发挥着运动控制的作用,并可能参与语言.
- 解码神经活动对于开发有效的脑机界面 (BMI) 至关重要.
研究的目的:
- 解码左侧单个神经元的发射模式与语音产生,感知和图像相关的Vim.
- 为了确定BMI中准确解读语音所需的Vim神经元的数量.
主要方法:
- 在八名神经外科患者中,从左侧的Vim中进行了手术内单个神经元记录.
- 利用基于稀疏分解的机器学习算法Spade解码器,分析语音任务期间的神经发射模式.
- 在语音产生,感知和母音声音的影像过程中记录的神经活动.
主要成果:
- 斯佩德解码器实现了高精度:100%的生产,96%的感知和92%的图像 (机会水平:20%).
- 解码精度显示与用于所有语音方面的神经元数量之间存在对数关系.
- 语音制作解码始终产生了比感知和图像更高的准确性.
结论:
- 左侧Vim中的单个神经元活动是与语音相关的BMI的有希望的输入来源.
- 了解解码精度所需的神经元数量对于计划BMI植入语言障碍患者至关重要.
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