摘要
神经元膜电位的放电活动是神经编码的基础。然而,目前对于神经元电活动对神经信息的编码方式,至今尚未形成一个完整的认识。传统的编码理论认为神经系统以离散的动作电位放电序列进行信息的表达和传递,主要研究动作电位的发放频率和放电活动的时间模式。基于该理论,对神经元放电序列所携带的信息已经出现了一些定量的计算方法,但这些方法还很难应用到大规模神经元网络的计算当中。本研究以神经元的膜电位为研究对象,展示了如何量化膜电位序列所携带的信息,并将该计算结果与传统放电序列方沣的计算结果进行了对比分析,其结果取得了很好的一致性。本研究为神经活动信息量的定量计算提供了一种新的思路和方法。
The firing activity of neuronal membrane potential is the basis of neural coding.However,to date,a complete understanding of the way by which neuronal electrical activity codes neural information has not yet been established.The traditional coding theory holds that the nervous system expresses and transfers information in discrete firing sequences of action potential,mainly studying the firing frequency of action potential and the time pattern of firing activity.Based on this theory,some quantitative calculation methods have been presented for the information carried by the neuronal spike trains,but these methods are still difficult to be applied in the calculation of large-scale neural networks.In the present study,the membrane potential of neurons was used as the study object.Analysis was performed regarding how to quantify the information carried by the membrane potential trains,and the calculation results were compared with results calculated by the traditional neuronal spike trains method,and good consistency was obtained.This study provided a new idea and method for the quantitative calculation of neural activity information.
作者
彭俊
王如彬
Peng Jun;Wang Rubin(Institute of Cognitive Neurodynamics,East China University of Science and Technology,Shanghai 200237,China)
出处
《动力学与控制学报》
2020年第1期24-32,共9页
Journal of Dynamics and Control
关键词
信息编码
膜电位序列
信息熵
神经网络
information coding
membrane potential trains
information entropy
neural network
