Learning to generalize stimulus-specific learning across contexts | Zendy

Ali Hashemi | Zendy; Matthew V. Pachai | Zendy; Allison B. Sekuler | Zendy; Patrick Bennett | Zendy

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Learning to generalize stimulus-specific learning across contexts

Author(s) -

Ali Hashemi,

Matthew V. Pachai,

Allison B. Sekuler,

Patrick Bennett

Publication year - 2016

Publication title -

journal of vision

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.126

H-Index - 113

ISSN - 1534-7362

DOI - 10.1167/16.12.1110

Subject(s) - stimulus (psychology) , perceptual learning , perception , psychology , artificial intelligence , stimulus generalization , cognitive psychology , discrimination learning , communication , pattern recognition (psychology) , computer science , neuroscience

Perceptual Learning (PL) in a texture identification task reflects observers becoming more sensitive to diagnostic stimulus components, and the learned components vary across observers1. Discrimination of a particular orientation component is difficult when   orthogonal, uninformative orientation components (i.e., context) are visible2. Learning to discriminate particular orientation components in a texture   identification task is highly specific to the context presented during training3. Can we reduce the influence of context on learning to discriminate   particular orientation components in a texture identification task? Learning to generalize stimulus-specific learning across contexts Ali Hashemi1, Matthew V. Pachai2, Allison B. Sekuler1, and Patrick J. Bennett1 1Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, Canada  2Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne

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