在刺激工件的存在下进行尖端分类:一种动态控制系统的方法
Mohammad Shokri1, Alex R Gogliettino2,3, Paweł Hottowy4
1Delft Center for Systems and Control, Delft University of Technology, Delft 2628 CN, The Netherlands.
Journal of neural engineering
|January 25, 2024
概括
这项研究提出了一种新的动态控制系统,用于区分双向神经接口中的神经尖峰与刺激工件. 该方法准确地识别神经活动,即使有显著的电干扰,提高信号清晰度.
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
- 信号处理 信号处理
背景情况:
- 双向神经接口通过记录唤起的神经反应来实现精确的校准.
- 刺激器件经常掩盖真正的神经信号,这构成了重大挑战.
研究的目的:
- 引入一种新的动态控制系统,用于检测和破译电气唤起的神经活动.
- 为了克服电工件对神经信号的掩盖效应.
主要方法:
- 利用神经活动和电器工件的独特时空模式来区分神经尖峰.
- 开发不同的动态模型,用于刺激器件和单个神经元.
- 通过分析刺激后的多电极电压反应来估计神经元活动.
主要成果:
- 该方法成功地将唤起的神经与灵长类视网膜录音中的刺激工件分开.
- 该方法产生的激活曲线与手动尖峰分类非常相匹配.
- 估计的刺激值显示出高可靠性,与手动分析有很强的相关性 (R2=0.951,R2=0.944).
结论:
- 开发的技术有效地区分使用时空传播模式唤起的神经尖峰与刺激工件.
- 这种方法对实时闭环刺激系统和先进的多通道刺激策略有很大的希望.
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