Activity-driven Computational Strategies of a Dynamically Regulated Integrate-And-Fire Model Neuron

J Comput Neurosci. Nov-Dec 1999;7(3):247-54. 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