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.

Activity-driven computational strategies of a dynamically regulated integrate-and-fire model neuron / Giugliano, M.; Bove, M.; Grattarola, M.. - In: JOURNAL OF COMPUTATIONAL NEUROSCIENCE. - ISSN 0929-5313. - 7:3(1999), pp. 247-254. [10.1023/A:1008979302515]

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

Giugliano, M.;
1999-01-01

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.
1999
7
3
247
254
https://doi.org/10.1023/A:1008979302515
Giugliano, M.; Bove, M.; Grattarola, M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/98423
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