Modeling perceptual learning: Why mice do not play backgammon

Elisa M. Tartaglia; Kristoffer C. Aberg; Michael H. Herzog

doi:10.1556/lp.1.2009.1.12

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Learning & Perception

Volume/Issue:: Volume 1: Issue 1

Modeling perceptual learning: Why mice do not play backgammon

Authors:

Elisa M. Tartaglia

Elisa M. Tartaglia Laboratory of Psychophysics, Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland

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Kristoffer C. Aberg

Kristoffer C. Aberg Laboratory of Psychophysics, Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland

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Michael H. Herzog

Michael H. Herzog Laboratory of Psychophysics, Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland

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Pages:: 155–163

Online Publication Date:: 01 Jun 2009

Publication Date:: 01 Jun 2009

Article Category:: Journal Article

DOI:: https://doi.org/10.1556/lp.1.2009.1.12

Keywords:: neural networks; feedback; attention

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Abstract

Perceptual learning is often considered one of the simplest and basic forms of learning in general. Accordingly, it is usually modeled with simple and basic neural networks which show good results in grasping the empirical data. Simple meets simple. Complex forms of perception and learning are, then, thought to rely on these simple networks. Here, we will argue that the simplicity is in fact the Achilles heel of models of perceptual learning. We propose, instead, that perceptual learning of simple stimuli cannot be modeled with simple networks. We will review some of the empirical results yielding to this conclusion.

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Learning & Perception

Print ISSN:: 1789-3186

Online ISSN:: 2060-9175

Learning & Perception
Language	English
Size
Year of Foundation	2009
Publication Programme	ceased
Volumes per Year
Issues per Year
Publisher	Akadémiai Kiadó
Publisher's Address	H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible Publisher	Chief Executive Officer, Akadémiai Kiadó
ISSN	1789-3186 (Print)
ISSN	2060-9175 (Online)