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Visual Perceptual Learning and its Specificity and Transfer: A New Perspective
Author(s) -
Cong Yu
Publication year - 2011
Publication title -
i-perception
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.64
H-Index - 26
ISSN - 2041-6695
DOI - 10.1068/ic406
Subject(s) - perceptual learning , perception , transfer of learning , perspective (graphical) , orientation (vector space) , computer science , visual cortex , visual perception , task (project management) , artificial intelligence , cognitive psychology , sensory system , psychology , cognitive science , neuroscience , mathematics , geometry , management , economics
Visual perceptual learning is known to be location and orientation specific, and is thus assumed to reflect the neuronal plasticity in the early visual cortex. However, in recent studies we created “Double training” and “TPE” procedures to demonstrate that these “fundamental” specificities of perceptual learning are in some sense artifacts and that learning can completely transfer to a new location or orientation. We proposed a rule-based learning theory to reinterpret perceptual learning and its specificity and transfer: A high-level decision unit learns the rules of performing a visual task through training. However, the learned rules cannot be applied to a new location or orientation automatically because the decision unit cannot functionally connect to new visual inputs with sufficient strength because these inputs are unattended or even suppressed during training. It is double training and TPE training that reactivate these new inputs, so that the functional connections can be strengthened to enable rule application and learning transfer. Currently we are investigating the properties of perceptual learning free from the bogus specificities, and the results provide some preliminary but very interesting insights into how training reshapes the functional connections between the high-level decision units and sensory inputs in the brain

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