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Mechanisms of perceptual learning
Open accessAbstract
Systematic measurements of perceptual learning were performed in the presence of external or stimulus noise. In the new external noise method (Dosher, B, & Lu, Z.-L. (1997). Investigative Ophthalmology and Visual Science, 38, S687; Lu, Z.-L., & Dosher, B. (1998). Vision Research, 38, 1183-1198), increasing amounts of external noise (white Gaussian random noise) is added to the visual stimulus in order to identify mechanisms of perceptual learning. Performance improved (threshold contrast was reduced) over days of practice on a peripheral orientation discrimination task--labelling Gabor patches as tilted slightly to the right or left. Practice improvements were largely specific to the trained quadrant of the display. Performance improved at all levels of external noise. The external noise method and perceptual template model (PTM) of the observer identifies the mechanism(s) of performance improvements as due to stimulus enhancement, external noise exclusion, or internal noise suppression. The external noise method was further extended by measuring thresholds at two threshold performance levels, allowing identification of mixtures in the PTM model. Perceptual learning over 8-10 days improved the filtering or exclusion of external noise by a factor of two or more, and improved suppression of additive internal noise--equivalent to stimulus enhancement--by 50% or more. Coupled improvements in external noise exclusion and stimulus enhancement in the PTM model may reflect channel weighting. Perceptual learning may not reflect neural plasticity at the level of basic visual channels, nor cognitive adjustments of strategy, but rather plasticity at an intermediate level of weighting inputs to decision.
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“provides additional evidence that the stimulus specificity of perceptual learning does not necessarily imply changes in primary sensory cortex3, 4.”
From Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area (2008) · cites this paper as [4]
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“These results support the intriguing possibility that associative and perceptual learning might share common mechanisms4, 43.”
From Neural correlates of perceptual learning in a sensory-motor, but not a sensory, cortical area (2008) · cites this paper as [4]
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Metadata
- Authors
- Dosher, B. A., & Lu, Z.-L.
- Affiliations
- University of California, Irvine (US)
- University of Southern California (US)
- Corresponding author
- Dosher, Barbara Anne
- ORCID
- Lu, Zhong-Lin
- Venue
- Vision Research
- Publisher
- Elsevier BV
- Published
- 1999-10
- Volume
- 39
- Issue
- 19
- Pages
- 3197-3221
- ISSN
- 0042-6989 (ISSN-L)
- OpenAlex
- W2113860392
- Cited by
- 394
- References
- 82
- Citations by year
- 2026: 13 · 2025: 7 · 2024: 10 · 2023: 11 · 2022: 9 · 2021: 12 · 2020: 13 · 2019: 10 · 2018: 14 · 2017: 13 · 2016: 13 · 2015: 17 · 2014: 22 · 2013: 19 · 2012: 18
- FWCI
- 4.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Vision Research (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Air Force
- Air Force Office of Scientific Research
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- perceptual learning, orientation discrimination, Gabor patches, peripheral vision, perceptual template model, stimulus enhancement, channel weighting, contrast threshold, neuroplasticity
- MeSH terms
- Discrimination, Psychological, Humans, Learning, Models, Psychological, Perception, Psychophysics, Signal Detection, Psychological
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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