Document Detail


Functional requirements for reward-modulated spike-timing-dependent plasticity.
MedLine Citation:
PMID:  20926659     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.
Authors:
Nicolas Frémaux; Henning Sprekeler; Wulfram Gerstner
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  The Journal of neuroscience : the official journal of the Society for Neuroscience     Volume:  30     ISSN:  1529-2401     ISO Abbreviation:  J. Neurosci.     Publication Date:  2010 Oct 
Date Detail:
Created Date:  2010-10-07     Completed Date:  2010-10-29     Revised Date:  2014-03-25    
Medline Journal Info:
Nlm Unique ID:  8102140     Medline TA:  J Neurosci     Country:  United States    
Other Details:
Languages:  eng     Pagination:  13326-37     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Action Potentials / physiology*
Animals
Brain / physiology
Computer Simulation
Conditioning, Operant / physiology
Learning / physiology
Long-Term Potentiation / physiology*
Models, Neurological*
Neuronal Plasticity / physiology*
Neurons / physiology*
Reaction Time / physiology
Reward*
Synapses / physiology
Synaptic Potentials / physiology
Synaptic Transmission / physiology

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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