Change In Response Time of Neuronal Populations With Noise, Synaptical Interactions and Stimulus Frequency

Neurons which are the fundamental elements of the nervous system, encode the information about stimulus they received from the external world by sensory system into action potential (spike) sequences before transmitting to the brain. In this study, a neuron population is modeled in mathematical manner and then first spike appearance time in a spike train is examined against changes in the characteristics of the periodic forcing. We also examine the effect of noise which stems from the biophysical structure of neurons and the effect of synaptic coupling which is the consequence of synaptic interaction of neurons with each other in the population to the appearance time of first spikes. The obtained results show that the mean response time of the population decreases with the increasing frequency. When the intensity of inherent noise in the neuronal environment increased, it shows a decreasing effect on the mean response only for low frequency range of the stimulus. Although the synaptic interaction coefficient does not affect substantially the mean response time of the population, it was shown that it is the fundamental parameter controlling the standard deviation of the response time.