The stochastic Leaky Integrate-and-Fire (LIF) model is revisited adopting a fractional derivative instead of the classical one and a correlated input in place of the usual white noise. The aim is to include in the neuronal model some physiological evidences such as correlated inputs, codified input currents and different time-scales. Fractional integrals of Gauss-Markov processes are considered to investigate the proposed model. Two specific examples are given. Simulations of paths and histograms of first passage times are provided for a specific case.
On the Integration of Fractional Neuronal Dynamics Driven by Correlated Processes / Pirozzi, Enrica. - 12013:(2020), pp. 211-219. (Intervento presentato al convegno 17th International Conference on Computer Aided Systems Theory, EUROCAST 2019 tenutosi a Las Palmas, Spain nel 17-22 February 2019) [10.1007/978-3-030-45093-9_26].
On the Integration of Fractional Neuronal Dynamics Driven by Correlated Processes
Pirozzi Enrica
2020
Abstract
The stochastic Leaky Integrate-and-Fire (LIF) model is revisited adopting a fractional derivative instead of the classical one and a correlated input in place of the usual white noise. The aim is to include in the neuronal model some physiological evidences such as correlated inputs, codified input currents and different time-scales. Fractional integrals of Gauss-Markov processes are considered to investigate the proposed model. Two specific examples are given. Simulations of paths and histograms of first passage times are provided for a specific case.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
