Correlated input spike trains and their effects on the response of the leaky integrate-and-fire neuron
Correlation of neuronal activities is widely observed in the central nervous system and is likely to play a key role in its functioning. It is, thus, essential to understand the effects of correlated synaptic input on the response of neurons. Here, we model neuronal input as correlated Poisson processes, and assess their impact on the leaky integrate-and-fire neuron. We found that neuronal output firing rate typically is a non-monotonic function of the input correlation, and propose that the response of neurons is critically dependent on the input ensemble statistics.
correlation integrate-and-fire input statistics neural coding