期刊
VISION RESEARCH
卷 50, 期 4, 页码 375-390出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.visres.2009.08.027
关键词
Re-weighting; Hebbian learning; Stimulus enhancement; External noise exclusion; Mechanisms of perceptual learning
资金
- NEI NIH HHS [R01 EY017491-08, R01 EY017491] Funding Source: Medline
- NIMH NIH HHS [R01 MH061834, R01 MH061834-04] Funding Source: Medline
Using the external noise plus training paradigm, we have consistently found that two independent mechanisms, stimulus enhancement and external noise exclusion, support perceptual learning in a range of tasks. Here, we show that re-weighting of stable early sensory representations through Hebbian learning (Petrov et al., 2005, 2006) can generate performance patterns that parallel a large range of empirical data: (1) perceptual learning reduced contrast thresholds at all levels of external noise in peripheral orientation identification (Dosher & Lu, 1998, 1999), (2) training with low noise exemplars transferred to performance in high noise, while training with exemplars embedded in high external noise transferred little to performance in low noise (Dosher & Lu, 2005), and (3) pre-training in high external noise only reduced subsequent learning in high external noise, whereas pre-training in zero external noise left very little additional learning in all the external noise conditions (Lu et al., 2006). In the augmented Hebbian re-weighting model (AHRM), perceptual learning strengthens or maintains the connections between the most closely tuned visual channels and a learned categorization structure, while it prunes or reduces inputs from task-irrelevant channels. Reducing the weights on irrelevant channels reduces the contributions of external noise and additive internal noise. Manifestation of stimulus enhancement or external noise exclusion depends on the initial state of internal noise and connection weights in the beginning of a learning task. Both mechanisms reflect re-weighting of stable early sensory representations. (C) 2009 Elsevier Ltd. All rights reserved.
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