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In this paper,we study how information transmission delays affect the spiking behavior of electrically coupled stochastic Hodgkin-Huxley (HH) neurons on Newman-Watts networks.It is found that the spiking behavior becomes the most regular at an optimal time delay,indicating the occurrence of delay-induced coherence resonance-like (CR-like) behavior.Interestingly,there are different CR-like types,depending on the membrane patch size of the neuron.For a smaller patch size,only single CR-like behavior occurs;while for a larger patch size,coherence bi-resonance-like (CBR) behavior appears.These findings show that the delay-induced CR-like behavior is closely related to the channel noise strength,and the coupled neurons may exhibit different spiking behaviors under the interplay of the channel noise and time delay.Therefore,the channel noise should be taken into account in the study of time delay-related spiking activity in stochastic HH neurons.This work provides new insight into the role of channel noise and information transmission delays in realistic neural systems.
In this paper, we study how information transmission delays affect the spiking behavior of electrically coupled stochastic Hodgkin-Huxley (HH) neurons on Newman-Watts networks. It is found that the spiking behavior becomes the most regular at an optimal time delay, indicating the occurrence of delay-induced coherence resonance-like (CR-like) behavior.Interestingly, there are different CR-like types, depending on the membrane patch size of the neuron. For a smaller patch size, only single CR-like behavior occurrence; while for a larger patch size, coherence bi-resonance-like (CBR) behavior appears. These findings show that the delay-induced CR-like behavior is closely related to the channel noise strength, and the coupled neurons may exhibit different spiking behaviors under the interplay of the channel noise and time delay.Therefore, the channel noise should be taken into account in the study of time delay-related spiking activity in stochastic HH neurons. this work provides new insight into the role o f channel noise and information transmission delays in realistic neural systems.