The recent quantitative description of activity-dependent depression in the synaptic transmission between cortical neurons has lead to many interesting suggestions of possible computational implications. Based on a simple biological model, we have constructed an analog circuit that emulates the properties of short-term depressing synapses. The circuit comprises only seven transistors and two capacitors per synapse, and is able to reproduce computational features of depressing synapses such as the 1/F law, the detection of long intervals of presynaptic silence and the sensitivity to redistribution of presynaptic firing rates. It provides a useful basis for implementing neural networks with dynamical synapses.