"Here we show that a purely Markovian integrate-and-fire (IF) model, with a noisy slow adaptation term, can generate interspike intervals (ISIs) that appear as having Long-range dependency (LRD). However a proper analysis shows that this is not the case asymptotically. For comparison, we also consider a new model of individual IF neuron with fractional (non-Markovian) noise. The correlations of its spike trains are studied and proven to have LRD, unlike classical IF models."
Cell Type(s): Abstract integrate-and-fire leaky neuron
Simulation Environment: Python
Implementer(s): Orio, Patricio [patricio.orio at uv.cl]; Richard, Alexandre
References:
Richard A, Orio P, Tanré E. (2018). An integrate-and-fire model to generate spike trains with long-range dependence Journal of Computational Neuroscience.