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Michael H. Herzog - One of the best experts on this subject based on the ideXlab platform.
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What is new in Perceptual Learning
Journal of vision, 2017Co-Authors: Michael H. Herzog, Aline F. Cretenoud, Lukasz GrzeczkowskiAbstract:What is new in Perceptual Learning? In the early days of research, specificity was the hallmark of Perceptual Learning; that is, improvements following training were limited to the trained stimulus features. For example, training with a stimulus improves performance for this stimulus but not for the same stimulus when rotated by 908 (Ball & Sekuler, 1987; Spang, Grimsen, Herzog, & Fahle, 2010). Because of this specificity, Learning was thought to be mediated by neural changes at the early stages of vision. In the last decade, many procedures were discovered in which transfer occurs from trained to untrained conditions under certain conditions. The location of Learning is now often thought to occur in higher stage of vision and decision-making. This special issue shows how the field has progressed along these lines.
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Linking Perceptual Learning with identical stimuli to imagery Perceptual Learning
Journal of vision, 2015Co-Authors: Lukasz Grzeczkowski, Elisa M. Tartaglia, Fred W. Mast, Michael H. HerzogAbstract:Perceptual Learning is usually thought to be exclusively driven by the stimuli presented during training (and the underlying synaptic Learning rules). In some way, we are slaves of our visual experiences. However, Learning can occur even when no stimuli are presented at all. For example, Gabor contrast detection improves when only a blank screen is presented and observers are asked to imagine Gabor patches. Likewise, performance improves when observers are asked to imagine the nonexisting central line of a bisection stimulus to be offset either to the right or left. Hence, performance can improve without stimulus presentation. As shown in the auditory domain, performance can also improve when the very same stimulus is presented in all Learning trials and observers were asked to discriminate differences which do not exist (observers were not told about the set up). Classic models of Perceptual Learning cannot handle these situations since they need proper stimulus presentation, i.e., variance in the stimuli, such as a left versus right offset in the bisection stimulus. Here, we show that Perceptual Learning with identical stimuli occurs in the visual domain, too. Second, we linked the two paradigms by telling observers that only the very same bisection stimulus was presented in all trials and asked them to imagine the central line to be offset either to the left or right. As in imagery Learning, performance improved.
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Perceptual Learning With Only One Stimulus
2014Co-Authors: Lukasz Grzeczkowski, Elisa M. Tartaglia, Fred W. Mast, Michael H. HerzogAbstract:Perceptual Learning is Learning to see. For example in a bisection task, three parallel lines are presented with the central line slightly offset towards the right or the left outer line. Participants indicate the offset direction. Training gradually improves performance. Models of Perceptual Learning explain Learning by synaptic changes determined by the Learning algorithm and the stimulus presentation. In these models, Learning cannot occur when the very same stimulus is presented in all training trials. Here we show that, surprisingly, humans can improve performance in such "impossible" conditions. We trained observers with a line bisection task where the central line was always exactly in the middle for all 4160 training trials. Participants were not told about the “zero offset” and were instructed to indicate the offset direction as in a normal bisection task. Surprisingly, performance improved with gains similar to "normal" bisection experiments where both the left and right offset are presented. These results cannot be explained by most of current models of Perceptual Learning and reproduce previous studies in the auditory domain (Amitay, Irwin & Moore 2006). We suggest that Perceptual Learning occurs by mental imagery in accordance with previous results (Tartaglia, Bamert, Mast & Herzog, 2009, 2012).
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No stress with Perceptual Learning
F1000Research, 2013Co-Authors: Aaron Clarke, Kristoffer Carl Aberg, Carmen Sandi, Michael H. HerzogAbstract:While stress has been shown to affect higher-level cognitive Learning (such as Learning to remember pictures of different emotional salience), it does not affect Perceptual Learning.
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Perceptual Learning, Roving, and Synaptic Drift
Journal of Vision, 2012Co-Authors: Michael H. Herzog, Aaron ClarkeAbstract:Perceptual Learning improves with most basic stimuli. Interestingly, performance does not improve when stimuli of two types are randomly presented during training (roving). For example, there is no Perceptual Learning when left or right bisection stimuli with outer line distances of 20’ and 30’ are presented randomly interleaved from trial to trial. How can roving be explained? Perceptual Learning is reward-based Learning. A recent mathematical analysis showed that any reward-based Learning system suffers from synaptic drift, which makes Learning impossible, when two tasks are learned and the mean rewards of the tasks are not identical. Hence, we propose that Perceptual Learning fails in roving conditions because of the different rewards for the two roved tasks. The unsupervised bias hypothesis makes the surprising prediction that Perceptual Learning should also fail when an easy and a hard task are roved because of their different rewards. To test this prediction, we presented bisection stimuli with outer-line-distances of either 20’ or 30’. In both tasks, observers judged whether the central vertical line was closer to the left- or right-outer line. Task difficulty was adjusted by manipulating the center line’s offset. Easy and difficult discriminations corresponded to 70 and 87 percent correct respectively. As predicted, subjects failed to learn in this roving task for both bisection-stimulus types. Hence, an easy undemanding task can block Perceptual Learning of another task.
Barbara Anne Dosher - One of the best experts on this subject based on the ideXlab platform.
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Visual Perceptual Learning and Models
Annual review of vision science, 2017Co-Authors: Barbara Anne DosherAbstract: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.
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Visual Perceptual Learning
Neurobiology of learning and memory, 2010Co-Authors: Tianmiao Hua, Chang-bing Huang, Yifeng Zhou, Barbara Anne DosherAbstract: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.
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Specificity of Perceptual Learning increases with increased training.
Vision research, 2010Co-Authors: Pamela E. Jeter, Barbara Anne Dosher, Shiau-hua LiuAbstract: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.
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Category and Perceptual Learning in Subjects with Treated Wilson's Disease
PloS one, 2010Co-Authors: Xiaoping Wang, Barbara Anne Dosher, Jiang-ning Zhou, Daren Zhang, Yifeng ZhouAbstract:To explore the relationship between category and Perceptual Learning, we examined both category and Perceptual Learning in patients with treated Wilson's disease (WD), whose basal ganglia, known to be important in category Learning, were damaged by the disease. We measured their Learning rate and accuracy in rule-based and information-integration category Learning, and magnitudes of Perceptual Learning in a wide range of external noise conditions, and compared the results with those of normal controls. The WD subjects exhibited deficits in both forms of category Learning and in Perceptual Learning in high external noise. However, their Perceptual Learning in low external noise was relatively spared. There was no significant correlation between the two forms of category Learning, nor between Perceptual Learning in low external noise and either form of category Learning. Perceptual Learning in high external noise was, however, significantly correlated with information-integration but not with rule-based category Learning. The results suggest that there may be a strong link between information-integration category Learning and Perceptual Learning in high external noise. Damage to brain structures that are important for information-integration category Learning may lead to poor Perceptual Learning in high external noise, yet spare Perceptual Learning in low external noise. Perceptual Learning in high and low external noise conditions may involve separate neural substrates.
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Perceptual Learning and attention: Reduction of object attention limitations with practice
Vision research, 2009Co-Authors: Barbara Anne Dosher, Songmei HanAbstract:Perceptual Learning has widely been claimed to be attention driven; attention assists in choosing the relevant sensory information and attention may be necessary in many cases for Learning. In this paper, we focus on the interaction of Perceptual Learning and attention – that Perceptual Learning can reduce or eliminate the limitations of attention, or, correspondingly, that Perceptual Learning depends on the attention condition. Object attention is a robust limit on performance. Two attributes of a single attended object may be reported without loss, while the same two attributes of different objects can exhibit a substantial dual-report deficit due to the sharing of attention between objects. The current experiments document that this fundamental dual-object report deficit can be reduced, or eliminated, through Perceptual Learning that is partially specific to retinal location. This suggests that alternative routes established by practice may reduce the competition between objects for processing resources.
Elisa M. Tartaglia - One of the best experts on this subject based on the ideXlab platform.
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Linking Perceptual Learning with identical stimuli to imagery Perceptual Learning
Journal of vision, 2015Co-Authors: Lukasz Grzeczkowski, Elisa M. Tartaglia, Fred W. Mast, Michael H. HerzogAbstract:Perceptual Learning is usually thought to be exclusively driven by the stimuli presented during training (and the underlying synaptic Learning rules). In some way, we are slaves of our visual experiences. However, Learning can occur even when no stimuli are presented at all. For example, Gabor contrast detection improves when only a blank screen is presented and observers are asked to imagine Gabor patches. Likewise, performance improves when observers are asked to imagine the nonexisting central line of a bisection stimulus to be offset either to the right or left. Hence, performance can improve without stimulus presentation. As shown in the auditory domain, performance can also improve when the very same stimulus is presented in all Learning trials and observers were asked to discriminate differences which do not exist (observers were not told about the set up). Classic models of Perceptual Learning cannot handle these situations since they need proper stimulus presentation, i.e., variance in the stimuli, such as a left versus right offset in the bisection stimulus. Here, we show that Perceptual Learning with identical stimuli occurs in the visual domain, too. Second, we linked the two paradigms by telling observers that only the very same bisection stimulus was presented in all trials and asked them to imagine the central line to be offset either to the left or right. As in imagery Learning, performance improved.
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Perceptual Learning With Indiscriminable Stimuli
Journal of Vision, 2014Co-Authors: Lukasz Grzeczkowski, Elisa M. Tartaglia, Fred W. MastAbstract:Perceptual Learning is Learning to perceive. For example, in a bisection task three parallel lines are presented. The central line is slightly offset towards the right or the left outer line. Observers indicate the offset direction. Training greatly improves performance. In models of Perceptual Learning, Learning occurs by synaptic changes determined by the Learning algorithm and the stimulus presentation. None of the models can learn when the very same stimulus is presented during training. Here we show that, surprisingly, humans can improve performance in such "impossible" conditions. We trained observers with a line bisection task where the central line was always exactly in the middle, i.e., the stimulus was the same in all 4160 trials. Participants were not told about the zero offset and were instructed to indicate the offset direction as in a normal bisection task. Surprisingly, performance improved with gains similar to "normal" bisection experiments where both the left and right offset are presented. These results cannot be explained by most of current models of Perceptual Learning and reproduce previous studies in the auditory domain (Amitay, Irwin & Moore 2006). We suggest that Learning occurs by mental imagery in accordance with previous results (Tartaglia, Bamert, Mast & Herzog, 2009, 2012).
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Perceptual Learning With Only One Stimulus
2014Co-Authors: Lukasz Grzeczkowski, Elisa M. Tartaglia, Fred W. Mast, Michael H. HerzogAbstract:Perceptual Learning is Learning to see. For example in a bisection task, three parallel lines are presented with the central line slightly offset towards the right or the left outer line. Participants indicate the offset direction. Training gradually improves performance. Models of Perceptual Learning explain Learning by synaptic changes determined by the Learning algorithm and the stimulus presentation. In these models, Learning cannot occur when the very same stimulus is presented in all training trials. Here we show that, surprisingly, humans can improve performance in such "impossible" conditions. We trained observers with a line bisection task where the central line was always exactly in the middle for all 4160 training trials. Participants were not told about the “zero offset” and were instructed to indicate the offset direction as in a normal bisection task. Surprisingly, performance improved with gains similar to "normal" bisection experiments where both the left and right offset are presented. These results cannot be explained by most of current models of Perceptual Learning and reproduce previous studies in the auditory domain (Amitay, Irwin & Moore 2006). We suggest that Perceptual Learning occurs by mental imagery in accordance with previous results (Tartaglia, Bamert, Mast & Herzog, 2009, 2012).
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Perceptual Learning by mental imagery
Journal of Vision, 2010Co-Authors: Michael H. Herzog, Elisa M. Tartaglia, Laura Bamert, Fred W. MastAbstract:In a bisection discrimination task, two vertical outer lines delineate an interval which is bisected by a centre line. Observers indicate whether this centre line is closer to the left or right outer line. Performance in this task improves strongly with training. This Perceptual Learning is usually assumed to be caused by synaptic changes which are mainly driven by the presentation of the stimuli. Here, we show that Perceptual Learning can also occur in the absence of physical stimulation via mental imagery. We presented only the two outer lines of the bisection stimulus and asked observers to imagine the centre line to be closer to the left or right outer line. Surprisingly, performance improved. Control experiments show that this improvement cannot be explained by unspecific aspects, such as adaptation to the experimental conditions. Hence, Perceptual Learning can occur without proper physical stimulation, driven by mental imagery
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Human Perceptual Learning by Mental Imagery
Current biology : CB, 2009Co-Authors: Elisa M. Tartaglia, Laura Bamert, Fred W. Mast, Michael H. HerzogAbstract:Perceptual Learning is Learning to perceive. For example, a radiologist is able to easily identify anomalies in medical images only after extended training. Theoretical and psychophysical studies [1-12] suggest that such improvements of performance are accomplished by neural synaptic changes driven by the repetitive presentation of stimuli. Here, we demonstrate that an equally reliable improvement can also occur in the absence of physical stimulation. Imagining the crucial part of a bisection stimulus was sufficient for successful Perceptual Learning. Hence, the neural processes underlying Perceptual Learning, which are usually assumed to be primarily dependent on stimulus processing, can be equally based on mentally generated signals.
Fred W. Mast - One of the best experts on this subject based on the ideXlab platform.
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Linking Perceptual Learning with identical stimuli to imagery Perceptual Learning
Journal of vision, 2015Co-Authors: Lukasz Grzeczkowski, Elisa M. Tartaglia, Fred W. Mast, Michael H. HerzogAbstract:Perceptual Learning is usually thought to be exclusively driven by the stimuli presented during training (and the underlying synaptic Learning rules). In some way, we are slaves of our visual experiences. However, Learning can occur even when no stimuli are presented at all. For example, Gabor contrast detection improves when only a blank screen is presented and observers are asked to imagine Gabor patches. Likewise, performance improves when observers are asked to imagine the nonexisting central line of a bisection stimulus to be offset either to the right or left. Hence, performance can improve without stimulus presentation. As shown in the auditory domain, performance can also improve when the very same stimulus is presented in all Learning trials and observers were asked to discriminate differences which do not exist (observers were not told about the set up). Classic models of Perceptual Learning cannot handle these situations since they need proper stimulus presentation, i.e., variance in the stimuli, such as a left versus right offset in the bisection stimulus. Here, we show that Perceptual Learning with identical stimuli occurs in the visual domain, too. Second, we linked the two paradigms by telling observers that only the very same bisection stimulus was presented in all trials and asked them to imagine the central line to be offset either to the left or right. As in imagery Learning, performance improved.
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Perceptual Learning With Indiscriminable Stimuli
Journal of Vision, 2014Co-Authors: Lukasz Grzeczkowski, Elisa M. Tartaglia, Fred W. MastAbstract:Perceptual Learning is Learning to perceive. For example, in a bisection task three parallel lines are presented. The central line is slightly offset towards the right or the left outer line. Observers indicate the offset direction. Training greatly improves performance. In models of Perceptual Learning, Learning occurs by synaptic changes determined by the Learning algorithm and the stimulus presentation. None of the models can learn when the very same stimulus is presented during training. Here we show that, surprisingly, humans can improve performance in such "impossible" conditions. We trained observers with a line bisection task where the central line was always exactly in the middle, i.e., the stimulus was the same in all 4160 trials. Participants were not told about the zero offset and were instructed to indicate the offset direction as in a normal bisection task. Surprisingly, performance improved with gains similar to "normal" bisection experiments where both the left and right offset are presented. These results cannot be explained by most of current models of Perceptual Learning and reproduce previous studies in the auditory domain (Amitay, Irwin & Moore 2006). We suggest that Learning occurs by mental imagery in accordance with previous results (Tartaglia, Bamert, Mast & Herzog, 2009, 2012).
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Perceptual Learning With Only One Stimulus
2014Co-Authors: Lukasz Grzeczkowski, Elisa M. Tartaglia, Fred W. Mast, Michael H. HerzogAbstract:Perceptual Learning is Learning to see. For example in a bisection task, three parallel lines are presented with the central line slightly offset towards the right or the left outer line. Participants indicate the offset direction. Training gradually improves performance. Models of Perceptual Learning explain Learning by synaptic changes determined by the Learning algorithm and the stimulus presentation. In these models, Learning cannot occur when the very same stimulus is presented in all training trials. Here we show that, surprisingly, humans can improve performance in such "impossible" conditions. We trained observers with a line bisection task where the central line was always exactly in the middle for all 4160 training trials. Participants were not told about the “zero offset” and were instructed to indicate the offset direction as in a normal bisection task. Surprisingly, performance improved with gains similar to "normal" bisection experiments where both the left and right offset are presented. These results cannot be explained by most of current models of Perceptual Learning and reproduce previous studies in the auditory domain (Amitay, Irwin & Moore 2006). We suggest that Perceptual Learning occurs by mental imagery in accordance with previous results (Tartaglia, Bamert, Mast & Herzog, 2009, 2012).
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Perceptual Learning by mental imagery
Journal of Vision, 2010Co-Authors: Michael H. Herzog, Elisa M. Tartaglia, Laura Bamert, Fred W. MastAbstract:In a bisection discrimination task, two vertical outer lines delineate an interval which is bisected by a centre line. Observers indicate whether this centre line is closer to the left or right outer line. Performance in this task improves strongly with training. This Perceptual Learning is usually assumed to be caused by synaptic changes which are mainly driven by the presentation of the stimuli. Here, we show that Perceptual Learning can also occur in the absence of physical stimulation via mental imagery. We presented only the two outer lines of the bisection stimulus and asked observers to imagine the centre line to be closer to the left or right outer line. Surprisingly, performance improved. Control experiments show that this improvement cannot be explained by unspecific aspects, such as adaptation to the experimental conditions. Hence, Perceptual Learning can occur without proper physical stimulation, driven by mental imagery
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Human Perceptual Learning by Mental Imagery
Current biology : CB, 2009Co-Authors: Elisa M. Tartaglia, Laura Bamert, Fred W. Mast, Michael H. HerzogAbstract:Perceptual Learning is Learning to perceive. For example, a radiologist is able to easily identify anomalies in medical images only after extended training. Theoretical and psychophysical studies [1-12] suggest that such improvements of performance are accomplished by neural synaptic changes driven by the repetitive presentation of stimuli. Here, we demonstrate that an equally reliable improvement can also occur in the absence of physical stimulation. Imagining the crucial part of a bisection stimulus was sufficient for successful Perceptual Learning. Hence, the neural processes underlying Perceptual Learning, which are usually assumed to be primarily dependent on stimulus processing, can be equally based on mentally generated signals.
I. P. L. Mclaren - One of the best experts on this subject based on the ideXlab platform.
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Special issue on recent advances in Perceptual Learning.
Journal of experimental psychology. Animal learning and cognition, 2021Co-Authors: Andrew R. Delamater, Ciro Civile, I. P. L. MclarenAbstract:This is an introduction to the special issue "Perceptual Learning." This collection of studies reflects some of the interesting new discoveries being made in the study of Perceptual Learning. Although much headway has been made toward understanding the basic phenomena, this collection of studies makes clear that there is much that remains to be understood. The study of Perceptual Learning continues to be a fruitful area of research, and it is our hope that this collection, like the Exeter workshop that it was based on, will continue to inspire future research efforts. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Switching off Perceptual Learning: Anodal transcranial direct current stimulation (tDCS) at Fp3 eliminates Perceptual Learning in humans.
Journal of experimental psychology. Animal learning and cognition, 2016Co-Authors: Ciro Civile, Frederick Verbruggen, Rossy Mclaren, Di Zhao, I. P. L. MclarenAbstract:Perceptual Learning can be acquired as a result of experience with stimuli that would otherwise be difficult to tell apart, and is often explained in terms of the modulation of feature salience by an error signal based on how well that feature can be predicted by the others that make up the stimulus. In this article we show that anodal transcranial Direct Current Stimulation (tDCS) at Fp3 directly influences this modulation process so as to eliminate and possibly reverse Perceptual Learning. In 2 experiments, anodal stimulation disrupted Perceptual Learning (indexed by an inversion effect) compared with sham (Experiment 1) or cathodal (Experiment 2) stimulation. Our findings can be interpreted as showing that anodal tDCS severely reduced or even abolished the modulation of salience based on error, greatly increasing generalization between stimuli. This result supports accounts of Perceptual Learning based on variations in salience as a consequence of pre-exposure, and opens up the possibility of controlling this phenomenon. (PsycINFO Database Record
