Activity-driven computational strategies of a dynamically regulated integrate-and-fire model neuron

M Giugliano; M Bove; M Grattarola

doi:10.1023/a:1008979302515

Activity-driven computational strategies of a dynamically regulated integrate-and-fire model neuron

J Comput Neurosci. 1999 Nov-Dec;7(3):247-54. doi: 10.1023/a:1008979302515.

Authors

M Giugliano¹, M Bove, M Grattarola

Affiliation

¹ Department of Biophysical and Electronic Engineering, University of Genoa, Italy.

PMID: 10596836
DOI: 10.1023/a:1008979302515

Abstract

Activity-dependent slow biochemical regulation processes, affecting intrinsic properties of a neuron, might play an important role in determining information processing strategies in the nervous system. We introduce second-order biochemical phenomena into a linear leaky integrate-and-fire model neuron together with a detailed kinetic description for synaptic signal transduction. In this framework, we investigate the membrane intrinsic electrical properties differentiation, showing the appearance of activity-dependent shifts between integration and temporal coincidence detection operating mode, for the single unit of a network.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Action Potentials / physiology*
Models, Neurological
Neurons / physiology*
Nonlinear Dynamics
Signal Transduction / physiology
Synapses / physiology