Cortical neurons are typically driven by thousands of synaptic inputs. The arrival of a spike
from one input may or may not be correlated with the arrival of other spikes from different …

To understand the interspike interval (ISI) variability displayed by visual cortical neurons
(Softky & Koch, 1993), it is critical to examine the dynamics of their neuronal integration, as …

We propose a biophysical mechanism for the high interspike interval variability observed in
cortical spike trains. The key lies in the nonlinear dynamics of cortical spike generation …

Neurons are sensitive to correlations among synaptic inputs. However, analytical models
that explicitly include correlations are hard to solve analytically, so their influence on a …

A model for coding of odor intensity in the first two neuronal layers of olfactory systems is
proposed. First, the occupation and activation by odorant molecules of receptor proteins of …

Using Stein's model with and without reversal potentials, we investigated the mechanism of
production of spike trains with a CV (ISI)(standard deviation/mean interspike interval) greater …

The temporal patterns of action potentials fired by a two-point stochastic neuron model were
investigated. In this model the membrane potential of the dendritic compartment follows the …

We present a comparison of the intrinsic saturation of firing frequency in four simple neural
models: leaky integrate-and-fire model, leaky integrate-and-fire model with reversal …

We introduce a stochastic spike train analysis method called joint interspike interval
difference (JISID) analysis. By design, this method detects changes in firing interspike …

The goal of systems neurophysiology is to understand the neural mecha-nisms underlying
behavior. Traditional approaches toward this goal have involved anatomical and …