Modeling trial by trial and block feedback in perceptual learning

Liu, Jiajuan; Dosher, Barbara Anne; Lü, Zhong-Lin

doi:10.1016/j.visres.2014.01.001

Cited by 27 publications

(38 citation statements)

References 35 publications

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“…The Augmented Hebbian Reweighting Model (AHRM) accounts for several perceptual learning phenomena, including transfer across features and locations (Dosher et al, 2013; Liu, Dosher & Lu, 2014; Petrov, Dosher & Lu, 2005, 2006). Interestingly, model simulations for orientation training of Gabor stimuli suggested that learning increases the weight not only for the most diagnostic orientation channels but also for the target spatial-frequency bands (Petrov, Dosher & Lu, 2005, 2006).…”

Section: Discussionmentioning

confidence: 99%

Learning one task by interleaving practice with another task

2014

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Perceptual learning is a sustainable improvement in performance on a perceptual task following training. A hallmark of perceptual learning is task specificity – after participants have trained on and learned a particular task, learning rarely transfers to another task, even with identical stimuli. Accordingly, it is assumed that performing a task throughout training is a requirement for learning to occur on that specific task. Thus, interleaving training trials of a target task, with those of another task, should not improve performance on the target task. However, recent findings in audition show that interleaving two tasks during training can facilitate perceptual learning, even when the training on neither task yields learning on its own. Here we examined the role of cross-task training in the visual domain by training 4 groups of human observers for 3 consecutive days on an orientation comparison task (target task) and/or spatial-frequency comparison task (interleaving task). Interleaving small amounts of training on each task, which were ineffective alone, not only enabled learning on the target orientation task, as in audition, but also surpassed the learning attained by training on that task alone for the same total number of trials. This study illustrates that cross-task training in visual perceptual learning can be more effective than single-task training. The results reveal a comparable learning principle across modalities and demonstrate how to optimize training regimens to maximize perceptual learning.

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Section: Discussionmentioning

confidence: 99%

Learning one task by interleaving practice with another task

2014

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“…One possible reason for this lack of consensus is that feedback has largely been treated in a unitary fashion in most studies of perceptual learning. Specifically, traditional experimental procedures used to examine perceptual learning have relied on binary judgments, and have thus been restricted to manipulating feedback in a purely success-based fashion (see Liu, Dosher, & Lu, 2014 for model and review). By contrast, there is a long history of examining more graded forms of feedback in motor learning (Salmoni, Schmidt, & Walter, 1984).…”

Section: Introductionmentioning

confidence: 99%

Error-driven learning in statistical summary perception.

Fan

Turk‐Browne

Taylor

2016

Journal of Experimental Psychology: Human Perception and Perfor

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We often interact with multiple objects at once, such as when balancing food and beverages on a dining tray. The success of these interactions relies upon representing not only individual objects, but also statistical summary features of the group (e.g., center-of-mass). While previous research has established that humans can readily and accurately extract such statistical summary features, how this ability is acquired and refined through experience currently remains unaddressed. Here we ask if training and task feedback can improve summary perception. During training, participants practiced estimating the centroid (i.e., average location) of an array of objects on a touchscreen display. Before and after training, they completed a transfer test requiring perceptual discrimination of the centroid. Across four experiments, we manipulated the information in task feedback and how participants interacted with the objects during training. We found that vector error feedback, which conveys error both in terms of distance and direction, was the only form of feedback that improved perceptual discrimination of the centroid on the transfer test. Moreover, this form of feedback was effective only when coupled with reaching movements towards the visual objects. Taken together, these findings suggest that sensory-prediction error — signaling the mismatch between expected and actual consequences of an action — may play a previously unrecognized role in tuning perceptual representations.

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“…In this modeling study Liu, Dosher, and Lu (2014) extended their reweight model to account for the complex effects of feedback on perceptual learning (Herzog & Fahle, 1999; Liu, Lu, & Dosher, 2010; Seitz et al, 2006). They incorporated three major factors that facilitate perceptual learning: the external trial-by-trial feedback, the self-generated output as an internal feedback when no external feedback is available, and the adaptive criterion control based on the block feedback.…”

Section: Articles In This Special Issuementioning

confidence: 99%