Circuit Model of Short-Term Synaptic Dynamics

Liu, Shih-Chii, Boegershausen, Malte, Suter, Pascal

Neural Information Processing Systems 

We describe a model of short-term synaptic depression that is derived from a silicon circuit implementation. The dynamics of this circuit model are similar to the dynamics of some present theoretical models of shortterm depressionexcept that the recovery dynamics of the variable describing thedepression is nonlinear and it also depends on the presynaptic frequency. The equations describing the steady-state and transient responses ofthis synaptic model fit the experimental results obtained from a fabricated silicon network consisting of leaky integrate-and-fire neurons anddifferent types of synapses. We also show experimental data demonstrating the possible computational roles of depression. One possible roleof 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.

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