A NEW STATISTICAL-METHOD FOR IDENTIFYING INTERCONNECTIONS BETWEEN NEURONAL NETWORK ELEMENTS
A NEW STATISTICAL-METHOD FOR IDENTIFYING INTERCONNECTIONS BETWEEN NEURONAL NETWORK ELEMENTS
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DOI：
10.1007/bf00355752
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发表时间：
1985-01-01
影响因子：
1.9
通讯作者：
KRYUKOV, VI
中科院分区：
文献类型：
--
作者：
BORISYUK, GN;BORISYUK, RM;KRYUKOV, VI
提出了一种考虑神经元活动特性的点过程依赖性分析方法。对神经网络的仿真建模表明，连接权值的估计单调依赖于模型突触强度的值。与互相关相反，该方法允许非线性互连，并且不需要点过程是平稳的，也不需要样本很大。给出了该方法在神经生理数据分析中的应用实例。
A new method is proposed to analyse dependencies in point processes, which takes into account specific character of neuronal activity. Simulation modelling of neuronal network revealed that the estimated weight of connection depends monotonically on the value of the model synaptic strength. In contrast to the crosscorrelation, the method allows for nonlinear interconnections and does not require point processes to be stationary and samples to be large. Examples are presented of the method''s application to neurophysiological data analysis.