Dynamical behaviors of periodically forced Hindmarsh-Rose neural model: The role of excitability and 'intrinsic' stochastic resonance

Abstract

In the presence/absence of external noise, dynamical behaviors of periodically forced neural systems and firing modes of interspike interval (ISI) are investigated by employing the Hindmarsh-Rose model. In the biologically relevant range of the forcing frequency, the interplay among the intrinsic oscillation, the forcing oscillation, and the noise leads to three kinds of firing modes: multi-modal firing, bi-modal firing, and intrinsic oscillation, in terms of which we can roughly classify the relevant experimental observations on the periodically forced sensory neural systems through their dynamical status. The resonant feature of subthreshold intrinsic oscillations shown in the ISI, the output signal-to-noise ratio, and the mean firing rate, appears to be an indication of stochastic resonance (SR) without external noise, or the 'intrinsic' SR. In the multi-modal firing region where SR leads to the skipping phenomenon, based on the 'intrinsic' SR, a possible explanation of a specific ISIH observed in experiments is given. Moreover, a neural system can tune itself to be chaotic to encode the weak signal, rather than relying only on the external noise.