Perceptual learning with perceptions.

ABSTRACT:

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In this work we present an approach to understand neuronal mechanisms underlying perceptual learning. Experimental results achieved with stimulus patterns of coherently moving dots are considered to build a simple neuronal model. The design of the model is made transparent and underlying behavioral assumptions made explicit. The key aspect of the suggested neuronal model is the learning algorithm used: We evaluated an implementation of Hebbian learning and are thus able to provide a straight-forward model capable to explain the neuronal dynamics underlying perceptual learning. Moreover, the simulation results suggest a very simple explanation for the aspect of "sub-threshold" learning (Watanabe et al. in Nature 413:844-884, 2001) as well as the relearning of motion discr

SUBMITTER: Stemme A 

PROVIDER: S-EPMC3045502 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature