What matters in neuronal locking?

被引:161
作者
Gerstner, W [1 ]
vanHemmen, JL [1 ]
Cowan, JD [1 ]
机构
[1] UNIV CHICAGO,DEPT MATH,CHICAGO,IL 60637
关键词
D O I
10.1162/neco.1996.8.8.1653
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Exploiting local stability, we show what neuronal characteristics are essential to ensure that coherent oscillations are asymptotically stable in a spatially homogeneous network of spiking neurons. Under standard conditions, a necessary and, in the limit of a large number of interacting neighbors, also sufficient condition is that the postsynaptic potential is increasing in time as the neurons fire. If the postsynaptic potential is decreasing, oscillations are bound to be unstable. This is a kind of locking theorem and boils down to a subtle interplay of axonal delays, postsynaptic potentials, and refractory behavior. The theorem also allows for mixtures of excitatory and inhibitory interactions. On the basis of the locking theorem, we present a simple geometric method to verify the existence and local stability of a coherent oscillation.
引用
收藏
页码:1653 / 1676
页数:24
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