Perceptual learning: Functions, mechanisms, and applications

Lü, Zhong-Lin; Yu, Cong; Watanabe, Takeo; Sagi, Dov; Levi, Dennis M.

doi:10.1016/j.visres.2010.01.010

Cited by 17 publications

(16 citation statements)

References 40 publications

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“…Perceptual learning usually produces improvements in discrimination with long-term training on a perceptual judgment (Lu, Yu, Watanabe, Sagi, & Levi, 2009) whereas adaptation is typically characterized as a more immediate loss in sensitivity when we are exposed to a stimulus. Learning might thus be distinguished from adaptation because it primarily reflects changes in performance rather than appearance, facilitation rather than suppression, a longer time course (Teich & Qian, 2003), and changes in how the visual system interprets the available neural signals rather than in the strength of those signals (Series, Stocker, & Simoncelli, 2009).…”

Section: Adaptation and Visual Plasticitymentioning

confidence: 99%

“…This is in contrast to studies of other forms of short-term visual plasticity such as perceptual learning. Interest in perceptual learning has exploded over the last decade, with much of this recent effort directed at elucidating the conditions under which learning occurs and the mechanisms mediating it (Lu et al, 2009; Sagi, in press; Sasaki, Nanez, & Watanabe, 2010). Analyses drawn from this work have been successfully applied to dissecting the processes of adaptation (e.g., Dao, Lu, & Dosher, 2006), but more often adaptation has remained the scalpel.…”

Section: Adaptation As a Toolmentioning

confidence: 99%

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Adaptation and visual coding

2011

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Visual coding is a highly dynamic process and continuously adapting to the current viewing context. The perceptual changes that result from adaptation to recently viewed stimuli remain a powerful and popular tool for analyzing sensory mechanisms and plasticity. Over the last decade, the footprints of this adaptation have been tracked to both higher and lower levels of the visual pathway and over a wider range of timescales, revealing that visual processing is much more adaptable than previously thought. This work has also revealed that the pattern of aftereffects is similar across many stimulus dimensions, pointing to common coding principles in which adaptation plays a central role. However, why visual coding adapts has yet to be fully answered.

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Section: Adaptation and Visual Plasticitymentioning

confidence: 99%

Section: Adaptation As a Toolmentioning

confidence: 99%

Adaptation and visual coding

2011

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“…This perceptual learning occurs in all sensory modalities (Fahle & Poggio, 2002) and is of great theoretical interest (Lu, Yu, Watanabe, Sagi, & Levi, 2009) and practical importance (Polat, 2009). However, its mechanisms are still poorly understood.…”

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confidence: 99%

Dissociable perceptual-learning mechanisms revealed by diffusion-model analysis

2011

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Performance on perceptual tasks improves with practice. Most theories address only accuracy data and tacitly assume that perceptual learning is a monolithic phenomenon. The present study pioneers the use of response time distributions in perceptual learning research. The 27 observers practiced a visual motion-direction discrimination task with filtered-noise textures for four sessions with feedback. Session 5 tested whether the learning effects transferred to the orthogonal direction. The diffusion model (Ratcliff, Psychological Review, 85, 59-108, 1978) achieved good fits to the individual response time distributions from each session and identified two distinct learning mechanisms with markedly different specificities. A stimulus-specific increase in the drift-rate parameter indicated improved sensory input to the decision process, and a stimulus-general decrease in nondecision time variability suggested improved timing of the decision process onset relative to stimulus onset (which was preceded by a beep). A traditional d' analysis would miss the latter effect, but the diffusion-model analysis identified it in the response time data.

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“…Even so, attention is considered a gate for perceptual learning (Ahissar & Hochstein, 2004; Lu, Yu, Sagi, Watanabe, & Levi, 2010; Roelfsema, van Ooyen, & Watanabe, 2010; Tsushima & Watanabe, 2009). On the one hand, some studies suggest that top-down attention is necessary for learning.…”

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Exogenous Attention Enables Perceptual Learning

Szpiro

Carrasco

2015

Psychol Sci

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Practice can improve visual perception, and these improvements are considered to be a form of brain plasticity. Training-induced learning is time-consuming and requires hundreds of trials across multiple days. The process of learning acquisition is understudied. Can learning acquisition be potentiated by manipulating visual attentional cues? We developed a protocol in which we used task-irrelevant cues for between-groups manipulation of attention during training. We found that training with exogenous attention can enable the acquisition of learning. Remarkably, this learning was maintained even when observers were subsequently tested under neutral conditions, which indicates that a change in perception was involved. Our study is the first to isolate the effects of exogenous attention and to demonstrate its efficacy to enable learning. We propose that exogenous attention boosts perceptual learning by enhancing stimulus encoding.

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Perceptual learning: Functions, mechanisms, and applications

Cited by 17 publications

References 40 publications

Adaptation and visual coding

Adaptation and visual coding

Dissociable perceptual-learning mechanisms revealed by diffusion-model analysis

Exogenous Attention Enables Perceptual Learning

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