基于活体神经元的自发电机
Svetlana A Gerasimova1, Anna Beltyukova1, Anastasia Fedulina1
1Department of Control Theory and System Dynamics, Neurotechnology Department, National Research Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia.
Sensors (Basel, Switzerland)
|August 26, 2023
概括
这项研究引入了一种混合系统,将生物和人工神经元合并在一起. 这种新型电路控制神经信号,同步人工和活神经元活动,用于神经形态应用.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
- 生物电子学 生物电子学
背景情况:
- 整合生物和人工神经系统对于推进神经形态计算至关重要.
- 现有的混合系统在实现无信号集成和控制方面经常面临挑战.
研究的目的:
- 开发和演示一种新的闭环系统,用于统一生物和人工神经元.
- 建立一个双向接口来控制生物神经元信号,使用人工组件.
主要方法:
- 基于FitzHugh-Nagumo模型的电子电路被用于人工神经元模拟.
- 该系统利用急性海马区老鼠大脑切片来容纳生物神经元.
- 来自生物神经元的局部场势调节了电子电路的状态,反之亦然.
主要成果:
- 混合系统成功地将生物和人工神经元集成到一个统一的振荡电路中.
- 活着的神经元活动触发了FitzHugh-Nagumo电路的振荡.
- 人工电路的尖峰与生物神经元尖峰同步,证明了有效的控制.
结论:
- 开发的混合电生物自发电机有效控制生物神经元信号.
- 该系统为各种需要集成神经处理的神经形态应用提供了一个有前途的平台.
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