Introduction: Identifying the potential firing patterns following different brain regions under normal and abnormal conditions increases our understanding of events at the level of neural interactions in the brain. Furthermore, it is important to be capable of modeling the potential neural activities to build precise artificial neural networks. The Izhikevich model is one of the simplest biolog...

a two-variable integrate and fire model is presented to study the role of transient outward potassium currents in producing temporal aspects of dorsal cochlear nucleus (dcn) pyramidal cells with different profiles namely the chopper, the pauser and the buildup. this conductance based model is a reduced version of km-lif model (meng & rinzel, 2010) which captures qualitative firing features of a...

A simple extension of standard neural network models is introduced which provides a model for neural computations that involve both firing rates and firing correlations. Such an extension appears to be useful since it has been shown that firing correlations play a significant computational role in many biological neural systems. Standard neural network models are only suitable for describing ne...

Neural spike trains present analytical challenges due to their noisy, spiking nature. Many studies of neuroscientific and neural prosthetic importance rely on a smoothed, denoised estimate of a spike train's underlying firing rate. Numerous methods for estimating neural firing rates have been developed in recent years, but to date no systematic comparison has been made between them. In this stu...

Hypothetical neural codes underlying the sensation of tactile roughness were investigated in a combined psychophysical and neurophysiological study. The stimulus set consisted of plastic surfaces embossed with dot arrays of varying dot diameter and center-to-center spacing. Human subjects explored each surface with the pad of the index finger and reported their subjective sense of roughness mag...