A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback.

ABSTRACT: Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how behaviorally relevant adaptive changes in complex networks of spiking neurons could be achieved in a self-organizing manner through local synaptic plasticity. However, the capabilities and limitations of this learning rule could so far only be tested through computer simulations. This article provides tools for an analytic treatment of reward-modulated STDP, which allows us to predict under which conditions reward-modulated STDP will achieve a desired learning effect. These analytical results imply that neurons can learn through reward-modulated STDP to classify not only spatial but also temporal firing patterns of presynaptic neurons. They also can learn

SUBMITTER: Legenstein R 

PROVIDER: S-EPMC2543108 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature