Using multi-neuron population recordings for neural prosthetics
Using multi-neuron population recordings for neural prosthetics
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DOI：
10.1038/nn1234
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发表时间：
2004-05-01
影响因子：
25
通讯作者：
Chapin, JK
中科院分区：
文献类型：
--
作者：
Chapin, JK
经典的单神经元记录方法导致了神经编码的“神经元中心”概念，而最近的多神经元种群记录激发了神经系统中分布式处理的“种群中心”概念。由于大多数新皮质神经元对信息进行粗略编码，感觉或运动处理往往广泛分布在神经元群中。因此，神经群体功能的动态波动涉及神经活动整体模式的微妙变化。通过对神经种群编码的数学分析，可以从运动皮层的神经元种群记录中提取“运动信号”，然后可以实时使用这些信号直接控制机器人手臂的运动。这项技术为神经控制的假肢装置的发展提供了希望，并提供了信息如何在几个大脑区域之间分布的见解。
Classical single-neuron recording methods led to 'neuron-centric' concepts of neural coding, whereas more recent multi-neuron population recordings have inspired 'population-centric' concepts of distributed processing in neural systems. Because most neocortical neurons code information coarsely, sensory or motor processing tends to be widely distributed across neuronal populations. Dynamic fluctuations in neural population functions thus involve subtle changes in the overall pattern of neural activity. Mathematical analysis of neural population codes allows extraction of 'motor signals' from neuronal population recordings in the motor cortices, which can then be used in real-time to directly control movement of a robot arm. This technique holds promise for the development of neurally controlled prosthetic devices and provides insights into how information is distributed across several brain regions.