Activity-driven computational strategies of a dynamically regulated integrate-and-fire model neuron.
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.
Giugliano
M
M
Department of Biophysical and Electronic Engineering, University of Genoa, Italy.
Bove
M
M
Grattarola
M
M
D000200:Action Potentials / Q000502:physiology*; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D015398:Signal Transduction / Q000502:physiology; D013569:Synapses / Q000502:physiology