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Recent experiments have shown that neocortical synapses exhibit both short-term plasticity and spike-timing dependent long-term plasticity. It has been suggested that changes in short-term plasticity are mediated by a redistribution of synaptic efficacy. Here we propose a simple model of the interaction between spike-timing dependent plasticity and short-term plasticity. We show that the model captures the synaptic behavior seen in experiments on redistribution of synaptic efficacy. Results from our simulations suggest that spike-timing dependent redistribution of synaptic efficacy offers neocortical neurons a potentially powerful mechanism for learning spatiotemporal patterns in the input stream.

The standard cortical model assumes that the meaning of a neuron's signal is contained in its firing rate. While that model has been used to interpret a voluminous amount of experimental data, it does not address the question of timing, or how recipient neurons can decode this signal in time to predict behavioral results. We propose a model based on coincident firing of large groups of neurons. We show using an example of predictive coding, how the cortex can support vast amounts of non-interfering parallel computation.