Perfect Integrate and fire with noisy adaptation or fractional noise (Richard et al 2018)

"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]; Richard, Alexandre


Richard A, Orio P, Tanré E. (2018). An integrate-and-fire model to generate spike trains with long-range dependence Journal of Computational Neuroscience.

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