Advances in visual perceptual learning and plasticity

Sasaki, Yuka; Náñez, José E.; Watanabe, Takeo

doi:10.1038/nrn2737

Cited by 375 publications

(356 citation statements)

References 122 publications

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“…Individuals also differ in their ability to improve with training (2-6), i.e., perceptual learning (7,8). Initial performance and rate of learning tend to be inversely related (3,9).…”

mentioning

confidence: 99%

Individual variability in functional connectivity predicts performance of a perceptual task

Baldassarre

Lewis

Committeri

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

247

177

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People differ in their ability to perform novel perceptual tasks, both during initial exposure and in the rate of improvement with practice. It is also known that regions of the brain recruited by particular tasks change their activity during learning. Here we investigate neural signals predictive of individual variability in performance. We used resting-state functional MRI to assess functional connectivity before training on a novel visual discrimination task. Subsequent task performance was related to functional connectivity measures within portions of visual cortex and between visual cortex and prefrontal association areas. Our results indicate that individual differences in performing novel perceptual tasks can be related to individual differences in spontaneous cortical activity

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“…Individuals also differ in their ability to improve with training (2-6), i.e., perceptual learning (7,8). Initial performance and rate of learning tend to be inversely related (3,9).…”

mentioning

confidence: 99%

Individual variability in functional connectivity predicts performance of a perceptual task

Baldassarre

Lewis

Committeri

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

247

177

View full text Add to dashboard Cite

show abstract

“…Reward anticipation boosts incoming sensory signals related to the presented cue, irrespective of whether the perceived stimulus features are task-relevant (Sasaki et al, 2010;Seitz and Watanabe, 2005). Hence, reward affects attention, leading to an increase in correct selection of the reward-associated target amongst other items in the environment and reduced response latency.…”

Section: Reward Captures Attentionmentioning

confidence: 99%

Influence of reward motivation on human declarative memory

Miendlarzewska

Bavelier

Schwartz

2016

Neuroscience & Biobehavioral Reviews

149

134

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a b s t r a c tMotivational relevance can prioritize information for memory encoding and consolidation based on reward value. In this review, we pinpoint the possible psychological and neural mechanisms by which reward promotes learning, from guiding attention to enhancing memory consolidation. We then discuss how reward value can spill-over from one conditioned stimulus to a non-conditioned stimulus. Such generalization can occur across perceptually similar items or through more complex relations, such as associative or logical inferences. Existing evidence suggests that the neurotransmitter dopamine boosts the formation of declarative memory for rewarded information and may also control the generalization of reward values. In particular, temporally-correlated activity in the hippocampus and in regions of the dopaminergic circuit may mediate value-based decisions and facilitate cross-item integration. Given the importance of generalization in learning, our review points to the need to study not only how reward affects later memory but how learned reward values may generalize to related representations and ultimately alter memory structure.

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“…Neural plasticity involves structural and functional changes, arising from the formation of new synapses and dendrites that carry information throughout the brain [1]. Once learning has occurred, the neural changes temporarily exist in a fragile state until stabilized, allowing for longlasting improvements of the learned skill, even without additional practice [2,3]. This stabilization process, otherwise known as consolidation, involves the transfer of these changes from short-term into long-term forms of memory.…”

Section: Introductionmentioning

confidence: 99%

When more equals less: overtraining inhibits perceptual learning owing to lack of wakeful consolidation

Ashley

Pearson

2012

Proc. R. Soc. B.

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Performance on perceptual tasks usually improves with training. However, too much consecutive training can be detrimental. Repeated within-day testing or overtraining demonstrates the detrimental effects this has on perceptual learning. Consolidation of learnt information during sleep has the power to prevent such deficits in learning. However, little is known regarding the role of wakeful consolidation in preventing the effects of overtraining. Here, we report that perceptual deterioration may result from the disruption of early wakeful consolidation processes. Three groups were tested on day 1 and again 24 h later, on a motion discrimination task. Participants who had a 1 h break between the two training sessions on the first day displayed improved accuracy on the second day (i.e. learning). Subjects who only completed the first training session on day 1 also exhibited learning. However, individuals who completed two blocks without a break ('overtraining') showed no improvement in accuracy on day 2. Interestingly, changes in reaction times were not susceptible to the effects of overtraining, but instead speeded up as a function of total performed trials. These data suggest that effects of overtraining might be due to disruption of wakeful consolidation processes.

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Advances in visual perceptual learning and plasticity

Cited by 375 publications

References 122 publications

Individual variability in functional connectivity predicts performance of a perceptual task

Individual variability in functional connectivity predicts performance of a perceptual task

Influence of reward motivation on human declarative memory

When more equals less: overtraining inhibits perceptual learning owing to lack of wakeful consolidation

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