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We investigate the detectability of weak electric field in a noisy neural network based on Izhikevich neuron model systematically. The neural network is composed of excitatory and inhibitory neurons with similar ratio as that in the mammalian neocortex, and the axonal conduction delays between neurons are also considered. It is found that the noise intensity can modulate the detectability of weak...
Recent studies have suggested that endogenous electric fields can not only be considered as an observation window of neural activities but also form a feedback on membranes of adjacent cells which implies it may play an important role in network dynamic behaviors. However, the role of endogenous field feedback in the detectability of external weak signal is still unknown. In this study, we introduced...
In this paper, we investigate the effects of the network amplification on stochastic resonance in a randomly connected neural network. The network consists of excitatory and inhibitory neurons with similar ratio as that in the mammalian neocortex and the axonal conduction delays between neurons are also considered. Numerical results elucidate that the resonance in the neural network is just the expression...
How much influence could noise take in FHN neuron which is exposed to a weak periodic signal is deeply affected by its bifurcation parameter. By a series of simulations, the authors derive the effective region of the bifurcation parameter, in which system could be influenced by noise apparently. Ulteriorly, it is divided into three part, namely, suprathreshold, subthreshold and canard effective region...
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