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We study the chaotic resonance phenomenon whereby the response of a neuron to a weak signal is amplified with the help of chaotic current stemming from background activity in the brain. This resonance behavior exhibits a bell-shaped curve in terms of detection quality due to increasing chaotic current intensity. Recent experimental studies have shown that astrocytes, which are the most abundant types of glial cells, may be responsible for the regulation of electrophysiological events in neuronal medium. Hence, we consider here a realistic neuronal system which is constituted by a bipartite network consisting of an excitable neuron and an astrocyte. Our analysis reveals that signal detection quality can be greatly enhanced with the astrocyte contribution obtained by appropriate neuronal and astrocytic cell dynamics. We find that depolarization-induced astrocytic glutamate release is able to improve chaotic resonance performance considerably in the presence of an adequately strong interaction between the astrocyte and the excitable neuron receiving a weak signal with a relatively higher frequency. We also show that a moderate production rate of gliotransmitters is required for the astrocyte to affect resonance performance of the neuron. Except for those conditions where the facilitating effect of astrocyte is observed, it can also reduce signal detection performance in the neuron. Furthermore, we demonstrated that intrinsic neuronal excitability is regulated by the astrocyte, via a comparison of resonance behaviors under effects of bias and astrocytic current separately. Taken together, our findings provide a novel insight into the functioning of astrocyte-neuron circuits, in particular the encoding weak signals via chaotic resonance, and suggest that astrocytes play a key role in intrinsic regulation and selectivity in neuronal information processing. • Astrocyte expands the frequency range of which chaotic resonance emerges • Moderate levels of production rate affect resonance performance of the neuron • Neuronal excitability is regulated by crosstalk with astrocyte • Mean astrocytic current is in a close relationship with the firing rate of the neuron [ABSTRACT FROM AUTHOR]

The signal detection ability of nervous system is highly associated with nonlinear and collective behaviors in neuronal medium. Neuronal noise, which occurs as natural endogenous fluctuations in brain activity, is the most salient factor influencing this ability. Experimental and theoretical research suggests that noise is beneficial, not detrimental, for regular functioning of nervous system. In this regard, there is a general agreement that noise at an adequate intensity can engage rhythmic activity in brain and noise-induced oscillations enhances performance of the weak signal processing, especially when frequency of the signal is around that of the noise-induced rhythmic oscillation. This behavior in biological neural systems is explained by the notion of "stochastic resonance". Another factor that plays a key role in regulating neuronal behaviors, including motor and cognitive tasks by maintaining signaling between cells, is characteristics of synapses different in structure and functioning. Here, we study stochastic resonance in Hodgkin–Huxley neuron that has a peculiar synaptic connection called autapse, known as a biophysical feedback mechanism, under presynaptic noise originating from superposition of inhibitory and excitatory Poisson bombardment. Our results show that, under certain conditions, autapse dynamics are able to improve the weak signal detection performance of Hodgkin–Huxley neuron via stochastic resonance. This study provides novel insights into functional role of autapse in neural information processing by revealing a biophysical aspect of stochastic resonance with numerical computations. • We investigate stochastic resonance in neuron that has an autapse under Poisson input • Autapse dynamics are able to improve weak signal detection performance of neuron • Provide novel insights into functional role of autapse in neural signal processing [ABSTRACT FROM AUTHOR]