Biophysical mechanism of signal encoding in an auditory neuron

Auditory system in animals can capture external sound signals, which can be converted into biophysical electric signals, and then the auditory neurons are activated to generate kinds of firing patterns. Bats can detect signals with ultrahigh frequency while human auditory system is sensitive to sound and voice within the frequency range 20 to 20,000 Hertz. In this paper, a piezoelectric neuron is proposed to investigate the physical mechanism for selection of frequency and filtering in auditory wave, and filtering wave function is designed to simulate the mode selection in the electrical activities of auditory neuron. Sound signals with multiple frequencies are imposed to drive the auditory neuron and mode selection is analyzed in detail. A decay factor is introduced to control the wave filter and frequency selection, and the amplitude is decreased sharply within transient period when the frequency is beyond or below the threshold. Furthermore, additive noise is accompanied by the sound signals and the mode selection is investigated by taming the noise intensity carefully. It is found that intermediate noise intensity can enhance nonlinear resonance and the auditory wave is encoded to induce regularity in the neural activities. The results can be helpful for further designing smart sensor and wave filter in signal processing, and the biophysical mechanism for signal processing in auditory system is clarified.

Automated summary

The study investigates how the auditory system in animals captures external sound signals and proposes a piezoelectric neuron to study the physical mechanism of frequency selection and filtering. The addition of noise can enhance nonlinear resonance, and mode selection is studied by carefully controlling the noise intensity.