Transient Sequences in a Network of Excitatory Coupled Morris-Lecar Neurons
We propose a model of neural network demonstrating variety of sequential activity modes. Unlike the previously known models of transient dynamics, in the present model transient sequential modes are formed by means of dynamical bifurcations and not directly related to the existence of heteroclinic channels. It is shown that network being initially at rest generates a sequence of metastable oscillatory states of activity in response to an external stimulus. We study the influence of the parameters characterized the initial times of synaptic activation processes caused by input information signals on the network dynamics. Numerical simulation of the model has shown, that these parameters determine not only the structure of the set of oscillatory metastable states and the sequence of transitions between them, but also the temporal characteristics of the transition sequences such as the time duration of the oscillatory metastable states.
Keywordsneural network transient dynamics oscillatory metastable states dynamical bifurcation
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