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Perceptual learning (PL) can significantly improve human performance in perceptual tasks primarily through template reweighting. Previous studies have documented how PL changes perceptual template in stimulus feature space. We investigated how PL reweights visual information in time. With a dynamic external noise paradigm and the elaborated perceptual template model (ePTM) analysis, we found that training with an orientation identification task in the zero external noise condition reduced contrast thresholds in both zero and high external noise conditions, whereas training in the high external noise condition only reduced contrast thresholds in high external noise conditions. The ePTM analysis showed that training in both zero and high external noise changed the overall amplitude, but not the shape of the temporal window of the perceptual template to exclude external noise across time, and training in zero external noise additionally reduced additive internal noise. Our results provided additional constraints for models of PL. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Experience or training can substantially improve perceptual performance through perceptual learning, and the extent and rate of these improvements may be affected by feedback. In this paper, we first developed a neural network model based on the integrated reweighting theory (Dosher et al., 2013) to account for perceptual learning and performance in n-alternative identification tasks and the dependence of learning on different forms of feedback. We then report an experiment comparing the effectiveness of response feedback (RF) versus accuracy feedback (AF) or no feedback (NF) (full versus partial versus no supervision) in learning a challenging eight-alternative visual orientation identification (8AFC) task. Although learning sometimes occurred in the absence of feedback (NF), RF had a clear advantage above AF or NF in this task. Using hybrid supervision learning rules, a new n-alternative identification integrated reweighting theory (I-IRT) explained both the differences in learning curves given different feedback and the dynamic changes in identification confusion data. This study shows that training with more informational feedback (RF) is more effective, though not necessary, in these challenging n-alternative tasks, a result that has implications for developing training paradigms in realistic tasks., Competing Interests: Declaration of Competing Interest Liu and Dosher have no competing interests. Lu owns intellectual property rights on qCSF, qPartialReport, and related technologies and has equity interest in Adaptive Sensory Technology, Inc.. (San Diego, CA) and Jiangsu Juehua Medical Technology Co., LTD (Jiangsu, China); these interests are not related to the current research., (Copyright © 2023. Published by Elsevier Ltd.)

Perceptual learning, the improvement of perceptual judgments with practice, occurs in many visual tasks. There are, however, relatively fewer studies examining perceptual learning in spatial frequency judgments. In addition, perceptual learning has generally been studied in two-alternative tasks, occasionally in n-alternative tasks, and infrequently in identification. Recently, perceptual learning was found in an orientation identification task (eight-alternatives) and was well accounted for by a new identification integrated reweighting theory (I-IRT) (Liu et al., submitted). Here, we examined perceptual learning in a similar eight-alternative spatial frequency absolute identification task in two different training protocols, finding learning in the majority but not all observers. We fit the I-IRT to the spatial frequency learning data and discuss possible model explanations for variations in learning.

Previous work has demonstrated that action video game training produces enhancements in a wide range of cognitive abilities. Here we evaluate a possible mechanism by which such breadth of enhancement could be attained: that action game training enhances learning rates in new tasks (i.e., "learning to learn"). In an initial controlled intervention study, we show that individuals who were trained on action video games subsequently exhibited faster learning in the two cognitive domains that we tested, perception and working memory, as compared to individuals who trained on non-action games. We further confirmed the causal effect of action video game play on learning ability in a pre-registered follow-up study that included a larger number of participants, blinding, and measurements of participant expectations. Together, this work highlights enhanced learning speed for novel tasks as a mechanism through which action video game interventions may broadly improve task performance in the cognitive domain., (© 2021. The Author(s).)

To characterize internal processes of an observer conducting perceptual tasks, we developed an observer model that combines the perceptual template model (PTM), the attention mechanisms in the PTM framework (Lu & Dosher, 1998), and uncertainty of signal detection theory (Green & Swets, 1966). The model was evaluated with a visual search experiment conducted in a range of external noise, signal contrast, and target-distractor similarity conditions. In each trial, eight Gabor patches were shown in each of two brief intervals, with one target at a different orientation from the distractors in one of the presentations. Subjects were precued to a subset of the stimuli (1, 2, 4, or 8) and asked to report (a) which interval contained the target and (b) where the target was. Individual roles of uncertainty and of attention in visual search were investigated by comparing models with and without an attention component. The results showed that decision uncertainty alone was sufficient to account for the set-size effect, even in conditions with high target-distractor similarity. Our theoretical model and empirical results provide a coherent picture regarding how visual information is selected and processed during feature search.

People routinely perform multiple visual judgments in the real world, yet, intermixing tasks or task variants during training can damage or even prevent learning. This paper explores why. We challenged theories of visual perceptual learning focused on plastic retuning of low-level retinotopic cortical representations by placing different task variants in different retinal locations, and tested theories of perceptual learning through reweighting (changes in readout) by varying task similarity. Discriminating different (but equivalent) and similar orientations in separate retinal locations interfered with learning, whereas training either with identical orientations or sufficiently different ones in different locations released rapid learning. This location crosstalk during learning renders it unlikely that the primary substrate of learning is retuning in early retinotopic visual areas; instead, learning likely involves reweighting from location-independent representations to a decision. We developed an Integrated Reweighting Theory (IRT), which has both V1-like location-specific representations and higher level (V4/IT or higher) location-invariant representations, and learns via reweighting the readout to decision, to predict the order of learning rates in different conditions. This model with suitable parameters successfully fit the behavioral data, as well as some microstructure of learning performance in a new trial-by-trial analysis.

Purpose: Aging affects a variety of visual functions. In this study, we aim to quantitatively investigate the temporal characteristics of visual processing in aging., Methods: Twelve younger (24.1 ± 1.6 years) and 12 older observers (58.4 ± 3.6 years) participated in the study. All participants had normal or corrected-to-normal vision. The contrast thresholds of the participants were measured using an orientation discrimination task with white external noise masks. The target-mask stimulus onset asynchronies were 16.7 ms, 33.4 ms, 50.0 ms, 83.4 ms, and ∞ (no external noise masks) in separate conditions. The signal stimulus was carefully chosen such that it was equally visible for the younger and older participants. An elaborated perceptual template model (ePTM) was fit to the data of each participant., Results: Without masks, there was no difference in contrast thresholds between the younger and older groups (P = 0.707). With masks, contrast thresholds in the older group elevated more than those in the younger group, and the pattern of threshold elevation differed in the two groups. The ePTM fitted the data well, with the older observers having lower template gains than the younger observers (P = 3.58 × 10-6). A further analysis of the weight parameters of the temporal window revealed that the older observers had a flatter temporal window than the younger observers (P = 0.025)., Conclusions: Age-related temporal processing deficits were found in older observers with normal contrast sensitivity to the signal stimuli. The deficits were accounted for by the inferior temporal processing window of the visual system in aging.

Perceptual sensitivity is usually estimated over trials and time intervals, which results in imprecise and biased estimates when it changes rapidly over time. We develop a novel procedure, the quick Change-Detection (qCD) method, to accurately, precisely, and efficiently assess the trial-by-trial time course of perceptual sensitivity change. Based on Bayesian adaptive testing, qCD selects the optimal stimulus, and updates, trial by trial, a joint probability distribution of the parameters that quantify perceptual sensitivity change over time. We demonstrate the utility of the method in measuring the time course of dark adaptation. Simulations showed that the accuracy and precision of the estimated dark adaptation curve after one qCD run (root mean squared error (RMSE): 0.002; the half width of the 68.2% credible interval (HWCI): 0.016; standard deviation (SD): 0.020; all in log 10 units) was higher than those obtained by ten runs of the quick Forced-Choice (qFC) procedure (RMSE: 0.020; HWCI: 0.032; SD: 0.031) and ten runs of a weighted up-down staircase procedure (RMSE: 0.026; SD: 0.031). Further, the dark adaptation curve obtained from one qCD run in a psychophysics experiment was highly consistent with the average of four qFC runs (RMSE = 0.076 log 10 units). Overall, qCD provides a procedure to characterize the detailed time course of perceptual sensitivity change in both basic research and clinical applications., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Intensive monocular perceptual learning can improve visual acuity, contrast sensitivity, and vernier acuity in the amblyopic eye in adults with amblyopia. It is however not clear how much monocular training can enhance binocular visual functions. In the current study, we aimed to evaluate effects of monocular training on a variety of binocular functions. Nineteen anisometropic amblyopes (18.5±1.26yrs, mean±s.e.) were trained in a grating contrast detection task near each individual's cutoff spatial frequency for 6-10days (630 trials/day). Visual acuity, stereoacuity, monocular and binocular contrast sensitivity functions (CSF), binocular phase combination and binocular rivalry were tested before and after training. Although monocular training can improve visual acuity and contrast sensitivity and eye dominance of the amblyopic eye, the magnitudes of improvements did not correlate with each other; the impact of monocular training on binocular phase combination was not significant. The results strongly suggest that structured monocular and binocular training is needed to fully recover deficient visual functions in anisometropic amblyopia., (Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Studies of perceptual learning have revealed a great deal of plasticity in adult humans. In this study, we systematically investigated the effects and mechanisms of several forms (trial-by-trial, block, and session rewards) and levels (no, low, high, subliminal) of monetary reward on the rate, magnitude, and generalizability of perceptual learning. We found that high monetary reward can greatly promote the rate and boost the magnitude of learning and enhance performance in untrained spatial frequencies and eye without changing interocular, interlocation, and interdirection transfer indices. High reward per se made unique contributions to the enhanced learning through improved internal noise reduction. Furthermore, the effects of high reward on perceptual learning occurred in a range of perceptual tasks. The results may have major implications for the understanding of the nature of the learning rule in perceptual learning and for the use of reward to enhance perceptual learning in practical applications.

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

The sense of vision allows us to discriminate fine details across a wide range of tasks. How to improve this perceptual skill, particularly within a short training session, is of substantial interest. Emerging evidence suggests that mixing easy trials can quickly improve performance in hard trials, but it is equivocal whether the improvement is short-lived or long-lasting, and additionally what accounts for this improvement. Here, by tracking objective performance (accuracy) and subjective experience (ratings of target visibility and choice confidence) over time and in a large sample of participants, we demonstrate the coexistence of transient and sustained effects of mixing easy trials, which differ markedly in their timescales, in their effects on subjective awareness, and in individual differences. In particular, whereas the transient effect was found to be ubiquitous and manifested similarly across objective and subjective measures, the sustained effect was limited to a subset of participants with weak convergence from objective and subjective measures. These results indicate that mixture of easy trials enables two distinct, co-existing forms of rapid perceptual improvements in hard trials, as mediated by robust priming and fragile learning. Placing constraints on theory of brain plasticity, this finding may also have implications for alleviating visual deficits.

The automaticity of phasic alertness is investigated using the attention network test. Results show that the cueing effect from the alerting cue-double cue-is strongly enhanced by the task relevance of visual cues, as determined by the informativeness of the orienting cue-single cue-that is being mixed (80 % vs. 50 % valid in predicting where the target will appear). Counterintuitively, the cueing effect from the alerting cue can be negatively affected by its visibility, such that masking the cue from awareness can reveal a cueing effect that is otherwise absent when the cue is visible. Evidently, then, top-down influences-in the form of contextual relevance and cue awareness-can have opposite influences on the cueing effect from the alerting cue. These findings lead us to the view that a visual cue can engage three components of attention-orienting, alerting, and inhibition-to determine the behavioral cueing effect. We propose that phasic alertness, particularly in the form of specific response readiness, is regulated by both internal, top-down expectation and external, bottom-up stimulus properties. In contrast to some existing views, we advance the perspective that phasic alertness is strongly tied to temporal orienting, attentional capture, and spatial orienting. Finally, we discuss how translating attention research to clinical applications would benefit from an improved ability to measure attention. To this end, controlling the degree of intraindividual variability in the attentional components and improving the precision of the measurement tools may prove vital.

Human training studies in the laboratory have demonstrated plasticity in brain systems and, in some cases, large improvements in perceptual performance, inspiring a quest to develop training apps and systems. We consider the next steps in the translation from the laboratory to the clinic and commerce., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Although numerous models describe the individual neural mechanisms that may be involved in the perception of visual motion, few of them have been constructed to take arbitrary stimuli and map them to a motion percept. Here, we propose an integrated dynamical motion model (IDM), which is sufficiently general to handle diverse moving stimuli, yet sufficiently precise to account for a wide-ranging set of empirical observations made on a family of random dot kinematograms. In particular, we constructed models of the cortical areas involved in motion detection, motion integration and perceptual decision. We analyzed their parameters through dynamical simulations and numerical continuation to constrain their proper ranges. Then, empirical data from a family of random dot kinematograms experiments with systematically varying direction distribution, presentation duration and stimulus size, were used to evaluate our model and estimate corresponding model parameters. The resulting model provides an excellent account of a demanding set of parametrically varied behavioral effects on motion perception, providing both quantitative and qualitative elements of evaluation., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

In this article we develop an extension to the signal detection theory framework to separately estimate internal noise arising from representational and decision processes. Our approach constrains signal detection theory models with decision noise by combining a multipass external noise paradigm with confidence rating responses. In a simulation study we present evidence that representation and decision noise can be separately estimated over a range of representative underlying representational and decision noise level configurations. These results also hold across a number of decision rules and show resilience to rule miss-specification. The new theoretical framework is applied to a visual detection confidence-rating task with 3 and 5 response categories. This study compliments and extends the recent efforts of researchers (Benjamin, Diaz, & Wee, 2009; Mueller & Weidemann, 2008; Rosner & Kochanski, 2009; Kellen, Klauer, & Singmann, 2012) to separate and quantify underlying sources of response variability in signal detection tasks., ((c) 2015 APA, all rights reserved).)

Comparing characteristics of learning in first- and second-order systems might inform us about different neural plasticity in the two systems. In the current study, we aim to determine the properties of perceptual learning in second-order contrast modulation detection in normal adults. We trained nine observers to detect second-order gratings at an envelope modulation spatial frequency of 8 cycles/° with their nondominant eyes. We found that, although training generated the largest improvements around the trained frequency, contrast sensitivity over a broad range of spatial frequencies also improved, with a 4.09-octave bandwidth of perceptual learning, exhibiting specificity to the trained spatial frequency as well as a relatively large degree of generalization. The improvements in the modulation sensitivity function (MSF) were not significantly different between the trained and untrained eyes. Furthermore, training did not significantly change subjects' ability in detecting first-order gratings. Our results suggest that perceptual learning in second-order detection might occur at the postchannel level in binocular neurons, possibly through reducing the internal noise of the visual system., (© 2015 ARVO.)

Visual performance is jointly determined by the quality of optical transmission of the eye and neural processing in the visual system. An open question is: Can effects of optical defects be compensated by perceptual learning in neural processing? To address this question, we conducted a perceptual learning study on 23 observers with myopic vision, targeting high frequency deficits by training them in a monocular grating detection task in the non-dominant eye near their individual cutoff spatial frequencies. The contrast sensitivity function and visual acuity in both eyes (without optical correction) were assessed for all the observers in the training group before and after training, and for all the observers in the control group twice with a 10-day interval between the tests. In addition, the threshold versus external noise contrast function was measured for five observers in the training group before and after training. We found that (a) training significantly improved contrast sensitivity at the trained spatial frequency, visual acuity, and contrast sensitivity over a wide range of spatial frequencies in both eyes; (b) training did not lead to any significant refractive changes; (c) the mechanism of improvements was a combination of internal additive noise reduction and external noise exclusion; and (d) the improvements in visual acuity and contrast sensitivity were almost fully retained for at least four months in the three observers tested. These results suggest that perceptual learning may provide a potential noninvasive procedure to compensate for optical defects in mild to modest myopia.

Using an asymmetrical set of vernier stimuli (-15″, -10″, -5″, +10″, +15″) together with reverse feedback on the small subthreshold offset stimulus (-5″) induces response bias in performance (Aberg & Herzog, 2012; Herzog, Eward, Hermens, & Fahle, 2006; Herzog & Fahle, 1999). These conditions are of interest for testing models of perceptual learning because the world does not always present balanced stimulus frequencies or accurate feedback. Here we provide a comprehensive model for the complex set of asymmetric training results using the augmented Hebbian reweighting model (Liu, Dosher, & Lu, 2014; Petrov, Dosher, & Lu, 2005, 2006) and the multilocation integrated reweighting theory (Dosher, Jeter, Liu, & Lu, 2013). The augmented Hebbian learning algorithm incorporates trial-by-trial feedback, when present, as another input to the decision unit and uses the observer's internal response to update the weights otherwise; block feedback alters the weights on bias correction (Liu et al., 2014). Asymmetric training with reversed feedback incorporates biases into the weights between representation and decision. The model correctly predicts the basic induction effect, its dependence on trial-by-trial feedback, and the specificity of bias to stimulus orientation and spatial location, extending the range of augmented Hebbian reweighting accounts of perceptual learning.

The contrast sensitivity function (CSF), a measure of visual sensitivity to a wide range of spatial frequencies, has been widely used as the gain profile of the front-end filter of the visual system to predict how we perceive spatial patterns. However, the CSF itself is determined by the gain profile and other processing inefficiencies of the visual system; it may be problematic to use the CSF as the gain profile in observer models. Here, we applied the external noise paradigm and the perceptual template model (PTM) to characterize several major properties of the visual system. With the external noise normalized gain profile, nonlinearity, and internal additive and multiplicative noises, the PTM accounted for 92.8% of the variance in the experiment data measured in a wide range of conditions and revealed the major processing components that determine the CSF. Unlike the CSF, the external noise normalized gain profile of the visual system is relatively flat across a wide range of spatial frequencies. The results may have major implications for understanding normal and abnormal spatial vision., (© 2014 ARVO.)

Attention precues improve the performance of perceptual tasks in many but not all circumstances. These spatial attention effects may depend upon display set size or workload, and have been variously attributed to external noise filtering, stimulus enhancement, contrast gain, or response gain, or to uncertainty or other decision effects. In this study, we document systematically different effects of spatial attention in low- and high-precision judgments, with and without external noise, and in different set sizes in order to contribute to the development of a taxonomy of spatial attention. An elaborated perceptual template model (ePTM) provides an integrated account of a complex set of effects of spatial attention with just two attention factors: a set-size dependent exclusion or filtering of external noise and a narrowing of the perceptual template to focus on the signal stimulus. These results are related to the previous literature by classifying the judgment precision and presence of external noise masks in those experiments, suggesting a taxonomy of spatially cued attention in discrimination accuracy.

Feedback has been shown to play a complex role in visual perceptual learning. It is necessary for performance improvement in some conditions while not others. Different forms of feedback, such as trial-by-trial feedback or block feedback, may both facilitate learning, but with different mechanisms. False feedback can abolish learning. We account for all these results with the Augmented Hebbian Reweight Model (AHRM). Specifically, three major factors in the model advance performance improvement: the external trial-by-trial feedback when available, the self-generated output as an internal feedback when no external feedback is available, and the adaptive criterion control based on the block feedback. Through simulating a comprehensive feedback study (Herzog & Fahle, 1997), we show that the model predictions account for the pattern of learning in seven major feedback conditions. The AHRM can fully explain the complex empirical results on the role of feedback in visual perceptual learning., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Purpose: Amblyopia is a developmental disorder that results in both monocular and binocular deficits. Although traditional treatment in clinical practice (i.e., refractive correction, or occlusion by patching and penalization of the fellow eye) is effective in restoring monocular visual acuity, there is little information on how binocular function, especially stereopsis, responds to traditional amblyopia treatment. We aim to evaluate the effects of perceptual learning on stereopsis in observers with amblyopia in the current study., Methods: Eleven observers (21.1 ± 5.1 years, six females) with anisometropic or ametropic amblyopia were trained to judge depth in 10 to 13 sessions. Red-green glasses were used to present three different texture anaglyphs with different disparities but a fixed exposure duration. Stereoacuity was assessed with the Fly Stereo Acuity Test and visual acuity was assessed with the Chinese Tumbling E Chart before and after training., Results: Averaged across observers, training significantly reduced disparity threshold from 776.7″ to 490.4″ (P < 0.01) and improved stereoacuity from 200.3″ to 81.6″ (P < 0.01). Interestingly, visual acuity also significantly improved from 0.44 to 0.35 logMAR (approximately 0.9 lines, P < 0.05) in the amblyopic eye after training. Moreover, the learning effects in two of the three retested observers were largely retained over a 5-month period., Conclusions: Perceptual learning is effective in improving stereo vision in observers with amblyopia. These results, together with previous evidence, suggest that structured monocular and binocular training might be necessary to fully recover degraded visual functions in amblyopia. Chinese Abstract.

Brightness illusions demonstrate that an object's perceived brightness depends on its visual context, leading to theoretical explanations ranging from simple lateral inhibition to those based on the influence of knowledge of and experience with the world. We measure the relative brightness of mid-luminance test disks embedded in gray-scale images, and show that rankings of test disk brightness are independent of viewing distance, implying that the rankings depend on the physical object size, not the size of disks subtended on the retina. A single filter that removes low spatial frequency content, adjusted to the diameters of the test disks, can account for the relative brightness of the disks. We note that the removal of low spatial frequency content is a principle common to many different approaches to brightness/lightness phenomena; furthermore, object-size representations--as opposed to retinal-size representations--inherently remove low spatial frequency content, therefore, any process that creates object representations should also produce brightness illusions.

Improvements in performance on visual tasks due to practice are often specific to a retinal position or stimulus feature. Many researchers suggest that specific perceptual learning alters selective retinotopic representations in early visual analysis. However, transfer is almost always practically advantageous, and it does occur. If perceptual learning alters location-specific representations, how does it transfer to new locations? An integrated reweighting theory explains transfer over retinal locations by incorporating higher level location-independent representations into a multilevel learning system. Location transfer is mediated through location-independent representations, whereas stimulus feature transfer is determined by stimulus similarity at both location-specific and location-independent levels. Transfer to new locations/positions differs fundamentally from transfer to new stimuli. After substantial initial training on an orientation discrimination task, switches to a new location or position are compared with switches to new orientations in the same position, or switches of both. Position switches led to the highest degree of transfer, whereas orientation switches led to the highest levels of specificity. A computational model of integrated reweighting is developed and tested that incorporates the details of the stimuli and the experiment. Transfer to an identical orientation task in a new position is mediated via more broadly tuned location-invariant representations, whereas changing orientation in the same position invokes interference or independent learning of the new orientations at both levels, reflecting stimulus dissimilarity. Consistent with single-cell recording studies, perceptual learning alters the weighting of both early and midlevel representations of the visual system.

Perceptual learning, even when it exhibits significant specificity to basic stimulus features such as retinal location or spatial frequency, may cause discrimination performance to improve either through enhancement of early sensory representations or through selective re-weighting of connections from the sensory representations to specific responses, or both. For most experiments in the literature, the two forms of plasticity make similar predictions (Dosher & Lu, 2009; Petrov, Dosher, & Lu, 2005). The strongest test of the two hypotheses must use training and transfer tasks that rely on the same sensory representation with different task-dependent decision structures. If training changes sensory representations, transfer (or interference) must occur since the (changed) sensory representations are common. If instead training re-weights a separate set of task connections to decision, then performance in the two tasks may still be independent. Here, we performed a co-learning analysis of two perceptual learning tasks based on identical input stimuli, following a very interesting study of Fahle and Morgan (1996) who used nearly identical input stimuli (a three dot pattern) in training bisection and vernier tasks. Two important modifications were made: (1) identical input stimuli were used in the two tasks, and (2) subjects practiced both tasks in multiple alternating blocks (800 trials/block). Two groups of subjects with counter-balanced order of training participated in the experiments. We found significant and independent learning of the two tasks. The pattern of results is consistent with the reweighting hypothesis of perceptual learning., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

In this study, we investigated whether mixing easy and difficult trials can lead to learning in the difficult conditions. We hypothesized that while feedback is necessary for significant learning in training regimes consisting solely of low training accuracy trials, training mixtures with sufficient proportions of high accuracy training trials would lead to significant learning without feedback. Thirty-six subjects were divided into one experimental group in which trials with high training accuracy were mixed with those with low training accuracy and no feedback, and five control groups in which high and low accuracy training were mixed in the presence of feedback; high and high training accuracy were mixed or low and low training accuracy were mixed with and without feedback trials. Contrast threshold improved significantly in the low accuracy condition in the presence of high training accuracy trials (the high-low mixture group) in the absence of feedback, although no significant learning was found in the low accuracy condition in the group with the low-low mixture without feedback. Moreover, the magnitude of improvement in low accuracy trials without feedback in the high-low training mixture is comparable to that in the high accuracy training without feedback condition and those obtained in the presence of trial-by-trial external feedback. The results are both qualitatively and quantitatively consistent with the predictions of the Augmented Hebbian Re-Weighting model. We conclude that mixed training at high and low accuracy levels can lead to perceptual learning at low training accuracy levels without feedback., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Extensive training on simple tasks such as fine orientation discrimination results in large improvements in performance, a form of learning known as perceptual learning. Previous models have argued that perceptual learning is due to either sharpening and amplification of tuning curves in early visual areas or to improved probabilistic inference in later visual areas (at the decision stage). However, early theories are inconsistent with the conclusions of psychophysical experiments manipulating external noise, whereas late theories cannot explain the changes in neural responses that have been reported in cortical areas V1 and V4. Here we show that we can capture both the neurophysiological and behavioral aspects of perceptual learning by altering only the feedforward connectivity in a recurrent network of spiking neurons so as to improve probabilistic inference in early visual areas. The resulting network shows modest changes in tuning curves, in line with neurophysiological reports, along with a marked reduction in the amplitude of pairwise noise correlations.

Perceptual learning refers to the phenomenon that practice or training in perceptual tasks often substantially improves perceptual performance. Often exhibiting stimulus or task specificities, perceptual learning differs from learning in the cognitive or motor domains. Research on perceptual learning reveals important plasticity in adult perceptual systems, and as well as the limitations in the information processing of the human observer. In this article, we review the behavioral results, mechanisms, physiological basis, computational models, and applications of visual perceptual learning., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Perceptual learning often shows substantial and long-lasting changes in the ability to classify relevant perceptual stimuli due to practice. Specificity to trained stimuli and tasks is a key characteristic of visual perceptual learning, but little is known about whether specificity depends upon the extent of initial training. Using an orientation discrimination task, we demonstrate that specificity follows after extensive training, while the earliest stages of perceptual learning exhibit substantial transfer to a new location and an opposite orientation. Brief training shows the best performance at the point of transfer. These results for orientation-location transfer have both theoretical and practical implications for understanding perceptual expertise., (Copyright 2010 Elsevier Ltd. All rights reserved.)

Feedback plays an interesting role in perceptual learning. The complex pattern of empirical results concerning the role of feedback in perceptual learning rules out both a pure supervised mode and a pure unsupervised mode of learning and leads some researchers to the proposal that feedback may change the learning rate through top-down control but does not act as a teaching signal in perceptual learning (M. H. Herzog & M. Fahle, 1998). In this study, we tested the predictions of an augmented Hebbian reweighting model (AHRM) of perceptual learning (A. Petrov, B. A. Dosher, & Z.-L. Lu, 2005), in which feedback influences the effective rate of learning by serving as an additional input and not as a direct teaching signal. We investigated the interactions between feedback and training accuracy in a Gabor orientation identification task over six training days. The accelerated stochastic approximation method was used to track threshold contrasts at particular performance accuracy levels throughout training. Subjects were divided into 4 groups: high training accuracy (85% correct) with and without feedback, and low training accuracy (65%) with and without feedback. Contrast thresholds improved in the high training accuracy condition, independent of the feedback condition. However, thresholds improved in the low training accuracy condition only in the presence of feedback but not in the absence of feedback. The results are both qualitatively and quantitatively consistent with the predictions of the augmented Hebbian learning model and are not consistent with pure supervised error correction or pure Hebbian learning models.

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., (Copyright 2009 Elsevier Ltd. All rights reserved.)

Existing observer models developed for studies with the external noise paradigm are strictly applicable only to target detection or identification/discrimination of orthogonal target(s). We elaborated the perceptual template model (PTM) to account for contrast thresholds in identifying nonorthogonal targets. Full contrast psychometric functions were measured in an orientation identification task with four orientation differences across a wide range of external noise levels. We showed that observer performance can be modeled by the elaborated PTM with two templates that correspond to the two stimulus categories. Sampling efficiencies of the human observers were also estimated. The elaborated PTM provides a theoretical framework for characterizing joint feature and contrast sensitivity of human observers.

Perceptual learning, the improvement in performance with practice, reflects plasticity in the adult visual system. We challenge a standard claim that specificity of perceptual learning depends on task difficulty during training, instead showing that specificity, or conversely transfer, is primarily controlled by the precision demands (i.e., orientation difference) of the transfer task. Thus, for an orientation discrimination task, transfer of performance improvement is observed in low-precision transfer tasks, while specificity of performance improvement is observed in high-precision transfer tasks, regardless of the precision of initial training. The nature of specificity places important constraints on mechanisms of transfer in visual learning. These results contribute to understanding generalization of practiced improvements that may be key to the development of expertise and for applications in remediation.

A fundamental question about human perception is how the speech perceiving brain combines auditory and visual phonetic stimulus information. We assumed that perceivers learn the normal relationship between acoustic and optical signals. We hypothesized that when the normal relationship is perturbed by mismatching the acoustic and optical signals, cortical areas responsible for audiovisual stimulus integration respond as a function of the magnitude of the mismatch. To test this hypothesis, in a previous study, we developed quantitative measures of acoustic-optical speech stimulus incongruity that correlate with perceptual measures. In the current study, we presented low incongruity (LI, matched), medium incongruity (MI, moderately mismatched), and high incongruity (HI, highly mismatched) audiovisual nonsense syllable stimuli during fMRI scanning. Perceptual responses differed as a function of the incongruity level, and BOLD measures were found to vary regionally and quantitatively with perceptual and quantitative incongruity levels. Each increase in the level of incongruity resulted in an increase in overall levels of cortical activity and in additional activations. However, the only cortical region that demonstrated differential sensitivity to the three stimulus incongruity levels (HI>MI>LI) was a subarea of the left supramarginal gyrus (SMG). The left SMG might support a fine-grained analysis of the relationship between audiovisual phonetic input in comparison with stored knowledge, as hypothesized here. The methods here show that quantitative manipulation of stimulus incongruity is a new and powerful tool for disclosing the system that processes audiovisual speech stimuli.

Recent studies have demonstrated that training adult amblyopes in simple visual tasks leads to significant improvements of their spatial vision. One critical question is: How much can training with one particular stimulus and task generalize to other stimuli and tasks? In this study, we estimated the bandwidth of perceptual learning in teenage and adult observers with anisometropic amblyopia and compared it to that of normal observers. We measured and compared contrast sensitivity functions-i.e., sensitivity to sine-wave gratings of various spatial frequencies-before and after training at a single spatial frequency in teenagers and adults with and without amblyopia. We found that the bandwidth of perceptual learning in the amblyopic visual system is much broader than that of the normal visual system. The broader bandwidth, suggesting more plasticity and wider generalization in the amblyopic visual system, provides a strong empirical and theoretical basis for perceptual learning as a potential treatment for amblyopia.

The role of feedback in perceptual learning is probed in an orientation discrimination experiment under destabilizing non-stationary conditions, and explored in a neural-network model. Experimentally, perceptual learning was examined with periodic alteration of a strong external noise context. The speed of learning, the performance loss at each change in external noise context (switch cost), and the asymptotic accuracy d' without feedback were very similar or identical to those with feedback. However, lack of feedback led to higher decision bias (error responses matching the external noise context). In the model, the stimulus representations are constant, whereas the read-out connections to a decision unit learn by a Hebbian plasticity rule that may be augmented by additional feedback input and criterion control of decision bias.

We combined the external noise paradigm, the Perceptual Template Model approach, and transfer tests to investigate the mechanisms and eye-specificity of perceptual learning of Gabor orientation in visual periphery. Coupled with a fixation task, discriminating a 5 from an S in a rapid small character string at fixation, contrast thresholds were estimated for each of eight external noise levels at two performance criteria using 3/1 and 2/1 staircases. Perceptual learning in one eye was measured over 10 practice sessions, followed by five sessions of practice in the new eye to assess transfer. We found that monocular learning improved performance (reduced contrast thresholds) with virtually equal magnitude across a wide range of external noise levels with no significant change in central task performance. Based on measurements of learning effects at two performance criterion levels, we identified a mixture of stimulus enhancement and external noise exclusion as the mechanism of perceptual learning underlying the observed improvements. Perceptual learning in the trained eye generalized completely to the untrained eye. We related the transfer patterns to known physiology and psychophysics on orientation direction coding.

We evaluated signal-noise discrimination in children with and without dyslexia, using magnocellular and parvocellular visual stimuli presented either with or without high noise. Dyslexic children had elevated contrast thresholds when stimuli of either type were presented in high noise, but performed as well as non-dyslexic children when either type was displayed without noise. Our findings suggest that deficits in noise exclusion, not magnocellular processing, contribute to the etiology of dyslexia.

Human operators develop expertise in perceptual tasks by practice or perceptual learning. For noisy displays, practice improves performance by learned external-noise filtering. For clear displays, practice improves performance by improved amplification or enhancement of the stimulus. Can these two mechanisms of perceptual improvement be trained separately? In an orientation task, we found that training with clear displays generalized to performance in noisy displays, but we did not find the reverse to be true. In noisy displays, the noise in the stimulus limits performance. In clear displays, performance is limited by noisiness of internal representations and processes. Our results suggest that training in one display condition optimizes the limiting factor(s) in performance in that condition and that noise filtering is also improved by exposure to the stimulus in clear displays. The asymmetric pattern of transfer implies the existence of two independent mechanisms of perceptual learning, which may reflect channel re-weighting in adult visual system. These results also suggest that training operators with clear stimuli may suffice to improve performance in a range of clear and noisy environments by simultaneous learning by two mechanisms.

One primary function of spatial attention is to exclude external noise [e.g., Psychol. Sci. 11(2) (2000) 139], especially in the region of the target stimulus [J. Vis. 2(4) (2000) 312]. What is not known is the spatial profile of external noise exclusion in the vicinity of the target and how this depends upon attention. The spatial region around an oriented Gabor target was segmented into four concentric rings (R1-R4). Psychometric functions were measured for orientation discrimination with external random Gaussian noise in all combinations of rings (e.g., R1 alone; R1+R2; etc.). Regions with larger impact on performance are weighted more heavily in the perceptual template. In an orientation discrimination task in periphery the effective noise regions aligned closely with the high contrast regions of the target Gabor, with attention reducing the effective noise across the spatial template. The combined effects of external noise regions were well-modeled by a (non-linear) perceptual template model (PTM) [Vis. Res. 38(9) (1998) 1183]. In another experiment in attended fovea, the results were similar to those in periphery, but exhibited additional ability to selectively weight clear spatial regions.

External noise presented in temporal contiguity with a target impairs perceptual performance, reflecting the temporal tuning of the perceptual template. Deriving the temporal characteristics of the perceptual template, however, requires an observer model that segregates the impact of non-linearities and intrinsic inefficiencies of the observer in order to account for the impact of external noise in various temporal configurations. In Experiment 1, we showed that the perceptual template model successfully accounts for temporal masking functions in foveal Gabor orientation identification masked by external noise with a wide range of temporal configurations, and estimates the temporal characteristics of the perceptual template. In Experiment 2, we extended the paradigm and the model to compare the temporal tuning characteristics of the perceptual template in central pre- and simultaneous cuing of endogenous spatial attention in a Gabor orientation identification task in visual periphery. We found that endogenous spatial attention excludes external noise by both sharpening the temporal window of the perceptual template and (mostly) reducing the impact of external noise uniformly across the entire temporal window.

What is learned during perceptual learning? We address this question by analyzing how perceptual inefficiencies improve over the course of perceptual learning (Dosher & Lu, 1998). Systematic measurements of human performance as a function of both the amount of external noise added to the signal stimulus and the length of training received by the observers enable us to track changes of the characteristics of the perceptual system (e.g., internal noise[s] and efficiency of the perceptual template) as perceptual learning progresses, and, therefore, identifies the mechanism(s) underlying the observed performance improvements. Two different observer models, the linear amplifier model (LAM) and the perceptual template model (PTM), however, have led to two very different theories of learning mechanisms. Here we demonstrate the failure of an LAM-based prediction - that the magnitude of learning-induced threshold reduction in high external noise must be less or equal to that in low external noise. In Experiment 1, perceptual learning of Gabor orientation identification in fovea showed substantial performance improvements only in high external noise but not in zero or low noise. The LAM-based model was "forced" to account for the data with a combination of improved calculation efficiency and (paradoxical) compensatory increases of the equivalent internal noise. Based on the PTM framework, we conclude that perceptual learning in this task involved learning how to better exclude external noise, reflecting retuning of the perceptual template. The data provide the first empirical demonstration of an isolable mechanism of perceptual learning. This learning completely transferred to a different visual scale in a second experiment.

The difficulty of visual search may depend on assignment of the same visual elements as targets and distractors-search asymmetry. Easy C-in-O searches and difficult O-in-C searches are often associated with parallel and serial search, respectively. Here, the time course of visual search was measured for both tasks with speed-accuracy methods. The time courses of the 2 tasks were similar and independent of display size. New probabilistic parallel and serial search models and sophisticated-guessing variants made predictions about time course and accuracy of visual search. The probabilistic parallel model provided an excellent account of the data, but the serial model did not. Asymptotic search accuracies and display size effects were consistent with a signal-detection analysis, with lower variance encoding of Cs than Os. In the absence of eye movements, asymmetric visual search, long considered an example of serial deployment of covert attention, is qualitatively and quantitatively consistent with parallel search processes., (((c) 2004 APA, all rights reserved))

A technique by Rogers-Ramachandran and Ramachandran [Vis. Res. 38 (1998) 71-77] was adapted to evaluate magnocellular (M) and parvocellular (P) visual processing efficiency, with identical task structure, in normal and dyslexic children. A battery of phonological, orthographic and cognitive tasks was administered to assess reading ability and component reading skills in both groups. For the visual processing experiment, children identified shapes created by patterns of dots flickering in counter-phase. The dots were black and white in the M condition, versus isoluminant red and green in the P condition. A staircase procedure determined the children's threshold flicker rate for shape identification. Dyslexics displayed selectively slower visual processing in the M condition but not in the P condition. Across all subjects, performance in the M condition was correlated with measures of orthographic skill, consistent with previous findings linking M processing and orthographic skill. Within the dyslexic group, processing in the M condition was negatively correlated with level of phonological awareness. The results are not consistent with the argument that dyslexics with phonological impairments suffer from deficits across all sensory modalities, as those children with the poorest phonological awareness displayed magnocellular processing well within the normal range.