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Kyle McDermott, Pascal Mamassian; A unifying mechanism underlying adaptation and perceptual learning. Journal of Vision 2014;14(10):402. doi: https://doi.org/10.1167/14.10.402.
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© ARVO (1962-2015); The Authors (2016-present)
Repeated stimulus presentations can lead to dramatic changes in the perception of subsequent stimuli. Two such phenomena are biased perception (after-effects) due to adaptation and increased sensitivity due to perceptual learning. Here we study the interaction of these two phenomena and present a model accounting for both. Observers were asked to indicate whether the direction of motion of a briefly presented field of random dots was to the left or right of a cued direction. Stimuli were presented by method of constant stimuli with directions of motion chosen from a non-uniform distribution designed to induce a bias. This was achieved by manipulating the frequency with which different directions of motion were presented: for both the left and right halves of the stimulus distribution the left end of the range was shown few times and the right end of the range was shown many times. Observers trained on this task for an hour a day for five consecutive days. The data reveal both a bias in perceived direction of motion due to adaptation and a reduction in discrimination threshold due to learning. Both phenomena asymptotically approach some maximum magnitude both within and across days with some of the effects carrying over from one day to the next. These results are consistent with a model based on a process where stimuli induce slight changes in the tuning of neural populations coding for motion direction, namely in the width of the tuning functions and their preferred directions. Such alterations of these tuning functions are in line with physiological measurements and similar models have been used to explain various phenomena associated with long-term exposure to the image statistics of natural scenes (e.g. Girshick, Landy & Simoncelli, 2011, Nature Neuroscience).
Meeting abstract presented at VSS 2014
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