Spike-driven synaptic plasticity for learning correlated patterns of mean firing rates

Abstract

Long term synaptic changes induced by neural spike activity are believed to underlie learning and memory. Spike-driven long-term synaptic plasticity has been investigated in simplified situations in which the patterns of mean rates to be encoded were statistically independent. An additional regulatory mechanism is required to extend the learning capability to more complex and natural stimuli. This mechanism can be provided by those effects of the action potentials that are believed to be responsible for spike-timing dependent plasticity. These effects, when combined with the dependence of synaptic plasticity on the post-synaptic depolarization, produce the non-monotonic learning rule needed for storing correlated patterns of mean rates.