Effect of the chaotic signal on the firing frequency of Morris-Lecar neurons

Abstract

Inverse Chaotic Resonance (ICR) is a phenomenon in the excitable neuronal system where neurons reduce or stop firing at a specific intensity of the chaotic signal. This study investigates the impact of chaotic signals on the firing frequency of Morris-Lecar (ML) neurons, and the ICR phenomenon has been explored in single ML neurons and within a scale-free network topology. The results demonstrate that chaotic signals induce significant changes in the mean firing frequency of ML neurons. Firstly, there is a controllability and potential biological mechanism of neurons during information encoding. Secondly, chaotic signals have demonstrated the presence of ICR in both single neurons and neuronal networks. ICR is highly sensitive to chaotic current intensity (especially for epsilon=0-1.5) and can be modulated by chaotic current. The ICR phenomenon results in a 96% decrease in the mean firing frequency of the ML Type-I neurons; that is, the ICR characteristic exhibits a bandstop filter-like behavior and stops the signals. The partial ICR occurs at two different current values, denoted as I-0, in both Type-II and Type-III neurons, and the mean firing frequency of neurons decreases by approximately 33%. This partial decrease enables the transmission of signals below certain frequencies in Type-II and Type-III neurons, resembling a bandpass filter. The chaotic activity effect is also investigated in a scale-free network topology. For the coupling strength (g=0.3) value, ICR in the network appears to be more prominent than in single-neuron models. At high coupling strength (g>0.6) values, the rhythmic firing behavior of the neurons in the network is proportionally impaired. The clarity of the ICR mechanism, which exhibits filter-like behavior, may play a crucial role in eliminating undesirable signals in the nervous system.