Cognitive Neurodynamics

, Volume 5, Issue 1, pp 31–43 | Cite as

Perceptual learning with perceptions

Research Article


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.


Perceptual learning Hebb Neurodynamical model Perception 



This work was supported by a grant from the German Federal Ministry of Education and Research (BMBF).

Supplementary material

11571_2010_9134_MOESM1_ESM.pdf (57 kb)
Supplementary material 1 (PDF 57 kb)


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Computational Intelligence and Machine Learning - CIML, Institute for BiophysicsUniversity of RegensburgRegensburgGermany
  2. 2.Theoretical and Computational Neuroscience, Unit for Brain and CognitionUniversitat Pompeu FabraBarcelonaSpain

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