Comparative study on the information encoding mode of neuronal networks based on Hodgkin-Huxley model
Objective To propose two different types of information encoding methods for the information encoding mode of neuronal networks based on Hodgkin-Huxley(HH)model.Methods The biological neuronal networks with different topologies were built with numerical simulations using HH model and chemical synapses.The specificities of two information encoding methods,namely average frequency encoding and interspike interval encoding,under the stimulus of sinusoidal signals and random audio signals were investigated,and the information encoding mode of neuronal networks stimulated by different signals was also analyzed.Results The information encoding mode of the neuronal networks was correlated with the stimulus signal type.When being stimulated by a continuous periodic signal,the neuronal network would generate a discharge sequence with periodicity corresponding to the stimulus signal.When the stimulus signal was a random signal,the discharge rate of the neuronal network would change with the stimulus signal intensity,and the higher the stimulus signal intensity was,the higher the action potential discharge rate was.Under the same stimulus signal,the temporal structure of the neuronal network discharge sequence was affected by the topology of the neuronal network.Conclusion The information encoding mode of neuronal networks is correlated with the stimulus signal,and the temporal structure of the discharge sequence of neuronal networks with different topologies is different.Interspike interval encoding has higher accuracy and contains more information,and the combination with the average frequency encoding can effectively express the dynamic change of the information encoding mode of neuronal networks under the stimulus.
Hodgkin-Huxley modelneuronal networknumerical simulationaverage frequency encodinginterspike interval encoding
万方数据
维普
