 |
| Volume 4, Number 3, Article 4, Pages 169-182 |
doi:10.1167/4.3.4 |
http://journalofvision.org/4/3/4/ |
ISSN 1534-7362 |
Perceptual learning in contrast discrimination and the (minimal) role of context
Cong Yu |
School of Optometry, University of California, Berkeley, CA, USA, & Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China |
|
Stanley A. Klein |
School of Optometry and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA |
|
Dennis M. Levi |
School of Optometry and Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA |
|
Abstract
Unlike most visual tasks, contrast discrimination has been reported to
be unchanged by practice (Dorais & Sagi, 1997;
Adini, Sagi, & Tsodyks, 2002),
unless practice is undertaken in the presence of flankers (context-enabled
learning, Adini et al., 2002).
Here we show that under experimental conditions nearly identical to those in the
no-flanker practice experiment of Adini et al. ( 2002),
practice significantly improved contrast discrimination. Moreover, in a separate
experiment, we found that practice without flankers can improve contrast
discrimination to a level only reached with flankers in Adini et al. ( 2002),
but further practice with flankers produces no further improvement of contrast
discrimination. These results call into question whether the “context-enabled
learning” proposed by Adini et al. ( 2002)
is different from regular contrast learning without flankers. In separate
experiments, we found that contrast learning is tuned to spatial frequency,
orientation, retinal location, and, unexpectedly, contrast. We also replicated
Sagi, Adini, Tsodyks, and Wilkonsky’s ( 2003)
more recent finding that no regular contrast learning occurs if reference
contrasts are randomly interleaved (contrast roving), and further demonstrated
that flankers have no effect on contrast learning under contrast roving, another
piece of evidence equating “context-enabled learning” to regular contrast
learning. The contrast specificity of learning and the lack of learning under
contrast roving provide new evidence in favor of a multiple contrast-selective
channels model of contrast discrimination, and against saturating transducer
models and multiplicative noise models.
|
|