Dynamics of Activity in Biology-Oriented Neural Network Models: Stability at Low Firing Rates
作者： Michael Erb , Ad Aertsen
DOI: 10.1007/978-3-642-49967-8_14
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摘要: We investigated the dynamics of activity in feedback neural network models at low firing rates. The networks were designed to capture typical features real cortical networks. Stability analysis linearized model and simulations different degrees complexity show that stability is only obtained for very fast sufficiently strong inhibition; otherwise develops into synchronous oscillations with frequency amplitude governed predominantly by inhibition parameters, but largely independent (1) architecture (uniform, random or structured), (2) spiking analog nature activity, and, albeit a lesser extent, (3) linear nonlinear threshold function. Provided connectivity rich structured, spike exhibits which resemble those observed physiological recordings from various areas: cell assembly behaviour different, simultaneous correlation (event coherence rate coherence).
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