Modeling short-term synaptic depression in silicon.

Abstract:

:We describe a model of short-term synaptic depression that is derived from a circuit implementation. The dynamics of this circuit model is similar to the dynamics of some theoretical models of short-term depression except that the recovery dynamics of the variable describing the depression is nonlinear and it also depends on the presynaptic frequency. The equations describing the steady-state and transient responses of this synaptic model are compared to the experimental results obtained from a fabricated silicon network consisting of leaky integrate-and-fire neurons and different types of short-term dynamic synapses. We also show experimental data demonstrating the possible computational roles of depression. One possible role of a depressing synapse is that the input can quickly bring the neuron up to threshold when the membrane potential is close to the resting potential.

journal_name

Neural Comput

journal_title

Neural computation

authors

Boegerhausen M,Suter P,Liu SC

doi

10.1162/089976603762552942

subject

Has Abstract

pub_date

2003-02-01 00:00:00

pages

331-48

issue

2

eissn

0899-7667

issn

1530-888X

journal_volume

15

pub_type

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