Shih-Chii Liu, Malte Boegershausen, Pascal Suter
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 short- term depression except that the recovery dynamics of the variable de- scribing the depression is nonlinear and it also depends on the presynap- tic frequency. The equations describing the steady-state and transient re- sponses of this synaptic model ﬁt the experimental results obtained from a fabricated silicon network consisting of leaky integrate-and-ﬁre neu- rons and different types of synapses. We also show experimental data demonstrating the possible computational roles of depression. One pos- sible 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 rest- ing potential.