Activity in sparsely connected excitatory neural networks: effect of connectivity

被引:35
|
作者
Pham, J
Pakdaman, K
Champagnat, J
Vibert, JF
机构
[1] Univ Paris 06, Fac Med St Antoine, ISARS, INSERM,U444, F-75571 Paris 12, France
[2] Osaka Univ, Fac Engn Sci, Dept Biophys Engn, Osaka, Japan
[3] Inst Alfred Fessard, Gif Sur Yvette, France
关键词
neural network model; excitatory connections; spontaneous activity; noise; rhythm generation;
D O I
10.1016/S0893-6080(97)00153-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Nucleus Tractus Solitarius (NTS) of the brainstem contains a neural circuit with only excitatory connections displaying a spontaneous activity involved in the control of respiration. A model of a network with random connections is presented and is used to investigate a possible mechanism of spontaneous activity generation consisting of the amplification of a low-background activity by the excitatory connections. First, the steady states of the network model and its ability to amplify the activity are studied. Then, a low-background activity is introduced, and dynamics of simulated networks are examined. Low-tonic, slow-phasic and fast-tonic activities are successively observed when the mean number K of connections per neuron increases. The transition between the two first types of activity is progressive whereas the transition from slow-phasic to fast-tonic activity is sharp. Simulation results show that activities of low frequency can be obtained with the proposed mechanism of spontaneous activity generation only if the network connectivity is low. (C) 1998 Elsevier Science Ltd. All rights reserved.
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页码:415 / 434
页数:20
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