Filtering properties of Hodgkin-Huxley neuron on different time-scale signals

Neurons can be excited and inhibited by filtered signals. The filtering properties of neural networks have a huge impact on memory, learning, and disease. In this paper, the frequency selection of Hodgkin-Huxley (HH) neuron in response to band-pass filtered signals is investigated. It is found that the neuronal filtering property depends on the locking relationship between the band-pass filtered signal's center frequency and the neuronal natural frequency. The natural firing frequency is a combination of the fundamental component and the various level harmonic components. The response of the neuron to the band-pass filtered signal is related to the amplitude of the harmonic components. Neuron responds better to the low-frequency filtered signals than the high-frequency filtered signals because of the reduction in the harmonic component amplitude. The filtering ability of the neuron can be modulated by the excitation level, and is stronger around the excitation threshold. Our results might provide novel insights into the filtering properties of neural networks and guide the construction of artificial neural networks.(c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This paper investigates the frequency selection and filtering properties of neurons in response to band-pass filtered signals. It is found that the filtering property of neurons depends on the locking relationship between the signal frequency and the neuronal natural frequency. Neurons respond better to low-frequency signals due to the reduction in the amplitude of harmonic components. Additionally, the filtering ability of neurons can be modulated by the excitation level.