Dataset Information
Perceptual learning with perceptions.
Ontology highlight
ABSTRACT: Unlabelled
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 discrimination after damage to primary visual cortex as recently reported (Huxlin et al. in J Neurosci 29:3981-3991, 2009) and at least indicate that perceptual learning might only occur when accompanied by conscious percepts.Electronic supplementary material
The online version of this article (doi:10.1007/s11571-010-9134-9) contains supplementary material, which is available to authorized users.
SUBMITTER: Stemme A
PROVIDER: S-EPMC3045502 | biostudies-literature | 2011 Mar
REPOSITORIES: biostudies-literature
Publications
Perceptual learning with perceptions.
Cognitive neurodynamics 20101001 1
<h4>Unlabelled</h4>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 pro ...[more]