Task precision at transfer determines specificity of perceptual learning

Jeter, Pamela E.; Dosher, Barbara Anne; Petrov, Alexander; Lü, Zhong-Lin

doi:10.1167/9.3.1

Cited by 211 publications

(222 citation statements)

References 36 publications

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“…All reweighting models assume training improved readout of visual inputs from a specific population of neurons, which also predicts orientation and location specificities, but not transfer. The transfer results also run counter to the recent claim that orientation specificity results from response reweighting within the same orientation channel (Jeter et al, 2009). Again, within-channel reweighting would not predict complete transfer of learning to a new orientation.…”

Section: Discussioncontrasting

confidence: 99%

Rule-Based Learning Explains Visual Perceptual Learning and Its Specificity and Transfer

Zhang¹,

Zhang²,

Xiao³

et al. 2010

J. Neurosci.

215

259

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Visual perceptual learning models, as constrained by orientation and location specificities, propose that learning either reflects changes in V1 neuronal tuning or reweighting specific V1 inputs in either the visual cortex or higher areas. Here we demonstrate that, with a training-plus-exposure procedure, in which observers are trained at one orientation and either simultaneously or subsequently passively exposed to a second transfer orientation, perceptual learning can completely transfer to the second orientation in tasks known to be orientation-specific. However, transfer fails if exposure precedes the training. These results challenge the existing specific perceptual learning models by suggesting a more general perceptual learning process. We propose a rule-based learning model to explain perceptual learning and its specificity and transfer. In this model, a decision unit in high-level brain areas learns the rules of reweighting the V1 inputs through training. However, these rules cannot be applied to a new orientation/location because the decision unit cannot functionally connect to the new V1 inputs that are unattended or even suppressed after training at a different orientation/location, which leads to specificity. Repeated orientation exposure or location training reactivates these inputs to establish the functional connections and enable the transfer of learning.

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Section: Discussioncontrasting

confidence: 99%

Rule-Based Learning Explains Visual Perceptual Learning and Its Specificity and Transfer

Zhang¹,

Zhang²,

Xiao³

et al. 2010

J. Neurosci.

215

259

View full text Add to dashboard Cite

show abstract

“…The majority of the literature to date has treated the enhanced performance seen as a result of action video game experience as an example of direct transfer of learning-in other words, the skills and knowledge acquired during action video game play result in immediate benefits to performance when exposed to a new task. However, we have recently suggested (28) Fig. 2.…”

Section: Resultsmentioning

confidence: 99%

“…Ten AVGPs and 10 NVPGs underwent eight sessions (across 2 d) of a Gabor orientation identification task (28), which was slightly different from that used in experiments 1 and 2 (Fig. 5A).…”

Section: Resultsmentioning

confidence: 99%

Action video game play facilitates the development of better perceptual templates

Bejjanki

Zhang

et al. 2014

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

166

141

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The field of perceptual learning has identified changes in perceptual templates as a powerful mechanism mediating the learning of statistical regularities in our environment. By measuring thresholdvs.-contrast curves using an orientation identification task under varying levels of external noise, the perceptual template model (PTM) allows one to disentangle various sources of signal-to-noise changes that can alter performance. We use the PTM approach to elucidate the mechanism that underlies the wide range of improvements noted after action video game play. We show that action video game players make use of improved perceptual templates compared with nonvideo game players, and we confirm a causal role for action video game play in inducing such improvements through a 50-h training study. Then, by adapting a recent neural model to this task, we demonstrate how such improved perceptual templates can arise from reweighting the connectivity between visual areas. Finally, we establish that action gamers do not enter the perceptual task with improved perceptual templates. Instead, although performance in action gamers is initially indistinguishable from that of nongamers, action gamers more rapidly learn the proper template as they experience the task. Taken together, our results establish for the first time to our knowledge the development of enhanced perceptual templates following action game play. Because such an improvement can facilitate the inference of the proper generative model for the task at hand, unlike perceptual learning that is quite specific, it thus elucidates a general learning mechanism that can account for the various behavioral benefits noted after action game play.action video games | perceptual templates | external noise method | learning | probabilistic inference P laying action video games substantially improves performance in a range of attentional, perceptual, and cognitive tasks. In the case of attention, playing action video games has been shown to result in a variety of enhancements, such as a faster visual search rate, a reduction in the size of the attentional blink, better change detection, and an increase in the number of items that can be simultaneously tracked (1-3). These changes in attentional control are also accompanied by enhanced performance in visual tasks such as crowding acuity (4), backward masking (5), and contrast sensitivity (6), as well as by improved performance in high-level cognitive tasks such as mental rotation (7) and multitasking (8, 9). Such benefits even seem to carry over to real-world domains, because pilots and laparoscopic surgeons have been shown to outperform their peers after fast-paced, action-packed video game training (10-12). Together, these results suggest that action game play, unlike perceptual learning, which is usually specific to the learned task (13), may act to increase signal-to-noise ratio and facilitate improved distractor exclusion during perceptual processing (14), which is notable because such changes hold the potential to affect, for ...

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“…To measure the time course of the training effect (learning curve), discrimination thresholds from 25 QUEST staircases in a daily training session were averaged and plotted as a function of training day. Learning curves were fitted with a power function (Jeter et al 2009). …”

Section: Trainmentioning

confidence: 99%

Learning to Discriminate Face Views

Chen

Weng

et al. 2010

Journal of Neurophysiology

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. Although perceptual learning of simple visual features has been studied extensively and intensively for many years, we still know little about the mechanisms of perceptual learning of complex object recognition. In a series of seven experiments, human perceptual learning in discrimination of in-depth orientation of face view was studied using psychophysical methods. We trained subjects to discriminate face orientations around a face view (i.e., 30°) over eight daily sessions, which resulted in a significant improvement in sensitivity to the face view orientation. This improved sensitivity was highly specific to the trained orientation and persisted up to 6 mo. Different from perceptual learning of simple visual features, this orientation-specific learning effect could completely transfer across changes in face size, visual field, and face identity. A complete transfer also occurred between two partial face images that were mutually exclusive but constituted a complete face. However, the transfer of the learning effect between upright and inverted faces and between a face and a paperclip object was very weak. These results shed light on the mechanisms of the perceptual learning of face view discrimination. They suggest that the visual system had learned how to compute face orientation from face configural information more accurately and that a large amount of plastic changes took place at a level of higher visual processing where size-, location-, and identity-invariant face views are represented.

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Task precision at transfer determines specificity of perceptual learning

Cited by 211 publications

References 36 publications

Rule-Based Learning Explains Visual Perceptual Learning and Its Specificity and Transfer

Rule-Based Learning Explains Visual Perceptual Learning and Its Specificity and Transfer

Action video game play facilitates the development of better perceptual templates

Learning to Discriminate Face Views

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