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the environment are represented. Hence initial learning stages involve understanding global aspects of the task. Subsequent practice may yield better perceptual resolution as a consequence of accessing lower-level information via the feedback connections going from high to low levels. Accessing the relevant low-level representations requires a backward search during which informative input populations of neurons in the low level are allocated. Hence, subsequent learning and its specificity reflect the resolution of lower levels. RHT thus proposes that initial performance is limited by the high-level resolution whereas post-training performance is limited by the resolution at low levels. Since high-level representations of different individuals differ due to their prior experience, their initial learning patterns may differ. Several imaging studies are in line with this interpretation, finding that initial performance is correlated with average (BOLD) responses at higher-level areas whereas subsequent performance is more correlated with activity at lower-level areas. RHT proposes that modifications at low levels will occur only when the backward search (from high to low levels of processing) is successful. Such success requires that the backward search will "know" which neurons in the lower level are informative. This "knowledge" is gained by training repeatedly on a limited set of stimuli, such that the same lower-level neuronal populations are informative during several trials. Recent studies found that mixing a broad range of stimuli may also yield effective learning if these stimuli are clearly perceived as different, or are explicitly tagged as different. These findings further support the requirement for top-down guidance in order to obtain effective learning.
1028:. Traditional explanations attribute this expertise to some holistic, somewhat specialized, mechanisms. Perhaps such quick identifications are achieved by more specific and complex perceptual detectors which gradually "chunk" (i.e., unitize) features that tend to concur, making it easier to pull a whole set of information. Whether any concurrence of features can gradually be chunked with practice or chunking can only be obtained with some pre-disposition (e.g. faces, phonological categories) is an open question. Current findings suggest that such expertise is correlated with a significant increase in the cortical volume involved in these processes. Thus, we all have somewhat specialized face areas, which may reveal an innate property, but we also develop somewhat specialized areas for written words as opposed to single letters or strings of letter-like symbols. Moreover, special experts in a given domain have larger cortical areas involved in that domain. Thus, expert musicians have larger auditory areas. These observations are in line with traditional theories of enrichment proposing that improved performance involves an increase in cortical representation. For this expertise, basic categorical identification may be based on enriched and detailed representations, located to some extent in specialized brain areas.
880:, attributed it to higher-level categorization mechanisms whereby initially blurred differences are gradually associated with distinctively different labels. The work focused on basic sensory discrimination, however, suggests that the effects of perceptual learning are specific to changes in low-levels of the sensory nervous system (i.e., primary sensory cortices). More recently, research suggest that perceptual learning processes are multilevel and flexible. This cycles back to the earlier Gibsonian view that low-level learning effects are modulated by high-level factors, and suggests that improvement in information extraction may not involve only low-level sensory coding but also apprehension of relatively abstract structure and relations in time and space.
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domain, learners' pattern recognition, classification abilities, and their abilities to map across multiple representations. As a result of practice with mapping across transformations (e.g., algebra, fractions) and across multiple representations (e.g., graphs, equations, and word problems), students show dramatic gains in their structure recognition in fraction learning and algebra. They also demonstrated that when students practice classifying algebraic transformations using PLMs, the results show remarkable improvements in fluency at algebra problem solving. These results suggests that perceptual learning can offer a needed complement to conceptual and procedural instructions in the classroom.
1065:. He found that when a stimulus (e.g. sound) is immediately followed by food several times, the mere presentation of this stimulus would subsequently elicit saliva in a dog's mouth. He further found that when he used a differential protocol, by consistently presenting food after one stimulus while not presenting food after another stimulus, dogs were quickly conditioned to selectively salivate in response to the rewarded one. He then asked whether this protocol could be used to increase perceptual discrimination, by differentially rewarding two very similar stimuli (e.g. tones with similar frequency). However, he found that differential conditioning was not effective.
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cingulate, the prefrontal cortex and the associative striatum, including the head of the caudate. The second is a basal ganglia-mediated implicit system that uses procedural learning, requires a dopamine reward signal and is mediated primarily by the sensorimotor striatum" The studies showed that there was significant involvement of the striatum and less involvement of the medial temporal lobes in category learning. In people who have striatal damage, the need to ignore irrelevant information is more predictive of a rule-based category learning deficit. Whereas, the complexity of the rule is predictive of an information integration category learning deficit.
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later session. With appropriate practice, visual search can become automatic and very efficient, such that observers do not need more time to search when there are more items present on the search field. Tactile perceptual learning has been demonstrated on spatial acuity tasks such as tactile grating orientation discrimination, and on vibrotactile perceptual tasks such as frequency discrimination; tactile learning on these tasks has been found to transfer from trained to untrained fingers. Practice with
Braille reading and daily reliance on the sense of touch may underlie the enhancement in tactile spatial acuity of blind compared to sighted individuals.
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of skills were upgraded in video game players, including "improved hand-eye coordination, increased processing in the periphery, enhanced mental rotation skills, greater divided attention abilities, and faster reaction times, to name a few". An important characteristic is the functional increase in the size of the effective visual field (within which viewers can identify objects), which is trained in action games and transfers to new settings. Whether learning of simple discriminations, which are trained in separation, transfers to new stimulus contexts (e.g. complex stimulus conditions) is still an open question.
842:, a noted learning theorist, trained human participants to learn to categorize deformed Chinese characters into categories. For each category, he used 6 instances that shared some invariant structural property. People learned to associate a sound as the name of each category, and more importantly, they were able to classify novel characters accurately. This ability to extract invariances from instances and apply them to classify new instances marked this study as a perceptual learning experiment. It was not until 1969, however, that
833:, Just Noticeable Difference) decreases dramatically with practice, and that this improvement is at least partially retained on subsequent days. Moreover, this improvement is at least partially specific to the trained skin area. A particularly dramatic improvement was found for skin positions at which initial discrimination was very crude (e.g. on the back), though training could not bring the JND of initially crude areas down to that of initially accurate ones (e.g. finger tips).
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that stimulus and important task events or upon stimulus reward contingencies. It has thus been suggested that learning (of task irrelevant stimuli) is contingent upon spatially diffusive learning signals. Similar effects, but upon a shorter time scale, have been found for memory processes and in some cases is called attentional boosting. Thus, when an important (alerting) event occurs, learning may also affect concurrent, non-attended and non-salient stimuli.
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differently-oriented line segments could generalize to positions at which the target was never presented. In human vision, not enough receptive field modification has been found in early visual areas to explain perceptual learning. Training that produces large behavioral changes such as improvements in discrimination does not produce changes in receptive fields. In studies where changes have been found, the changes are too small to explain changes in behavior.
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one's ability to identify both as belonging to the same category. A specific difference between them could be considered 'signal' in the first case and 'noise' in the second case. Thus, as we adapt to tasks and environments, we pay increasingly more attention to the perceptual features that are relevant and important for the task at hand, and at the same time, less attention to the irrelevant features. This mechanism is called attentional weighting.
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encodings at the lowest level do not change. Rather, changes that occur in perceptual learning arise from changes in higher-level, abstract representations of the relevant stimuli. Because specificity can come from differentially selecting information, this "selective reweighting theory" allows for learning of complex, abstract representation. This corresponds to Gibson's earlier account of perceptual learning as selection and
872:) sensory areas are also modified. Research in this period centered on basic sensory discriminations, where remarkable improvements were found on almost any sensory task through discrimination practice. Following training, subjects were tested with novel conditions and learning transfer was assessed. This work departed from earlier work on perceptual learning, which spanned different tasks and levels.
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develop stereotypes because they are less knowledgeable. Perceptual learning is a more in-depth relationship between experience and perception. Different perceptions of the same sensory input may arise in individuals with different experiences or training. This leads to important issues about the ontology of sensory experience, the relationship between cognition and perception.
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1185:. For example, the perceptual expertise of a baseball player at bat can detect early in the ball's flight whether the pitcher threw a curveball. However, the perceptual differentiation of the feel of swinging the bat in various ways may also have been involved in learning the motor commands that produce the required swing.
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information. Experts extract larger "chunks" of information and discover high-order relations and structures in their domains of expertise that are invisible to novices. Fluency effects involve changes in the ease of extraction. Not only can experts process high-order information, they do so with great speed and low
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is the acquisition of skill for practical purposes. Thus it is important to understand whether training for increased resolution in lab conditions induces a general upgrade which transfers to other environmental contexts, or results from mechanisms which are context specific. Improving complex skills
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In speech phonemes, observers who listen to a continuum of equally spaced consonant-vowel syllables going from /be/ to /de/ are much quicker to indicate that two syllables are different when they belonged to different phonemic categories than when they were two variants of the same phoneme, even when
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Infants, when different sounds belong to the same phonetic category in their native language, tend to lose sensitivity to differences between speech sounds by 10 months of age. They learn to pay attention to salient differences between native phonetic categories, and ignore the less language-relevant
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Multiple different category learning systems may mediate the learning of different category structures. "Two systems that have received support are a frontal-based explicit system that uses logical reasoning, depends on working memory and executive attention, and is mediated primarily by the anterior
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skills in a general way, which transfers to new visual contexts. In 2010, Achtman, Green, and
Bavelier reviewed the research on video games to train visual skills. They cite a previous review by Green & Bavelier (2006) on using video games to enhance perceptual and cognitive abilities. A variety
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These studies showed that the dynamics of learning depend on the training protocol, rather than on the total amount of practice. Moreover, it seems that the strategy implicitly chosen for learning is highly sensitive to the choice of the first few trials during which the system tries to identify the
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The
Reverse Hierarchy Theory (RHT), proposed by Ahissar & Hochstein, aims to link between learning dynamics and specificity and the underlying neuronal sites. RHT proposes that naïve performance is based on responses at high-level cortical areas, where crude, categorical level representations of
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and defined the modern field of perceptual learning. She established the study of perceptual learning as an inquiry into the behavior and mechanism of perceptual change. By the mid-1970s, however, this area was in a state of dormancy due to a shift in focus to perceptual and cognitive development in
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As our perceptual system adapts to the natural world, we become better at discriminating between different stimuli when they belong to different categories than when they belong to the same category. We also tend to become less sensitive to the differences between two instances of the same category.
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and colleagues showed that perceptual learning can be systematically produced and accelerated using specific, computer-based technology. Their approach to perceptual learning methods take the form of perceptual learning modules (PLMs): sets of short, interactive trials that develop, in a particular
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and V2 cells) that initially encode the stimulus. For example, individual cells could adapt to become more sensitive to important features, effectively recruiting more cells for a particular purpose, making some cells more specifically tuned for the task at hand. Evidence for receptive field change
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condition may be considered noise in another. For example, when presented with two similar stimuli, one might endeavor to study the differences between their representations in order to improve one's ability to discriminate between them, or one may instead concentrate on the similarities to improve
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The prevalent idiom that “practice makes perfect” captures the essence of the ability to reach impressive perceptual expertise. This has been demonstrated for centuries and through extensive amounts of practice in skills such as wine tasting, fabric evaluation, or musical preference. The first
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ones. In chess, expert chess players encode larger chunks of positions and relations on the board and require fewer exposures to fully recreate a chess board. This is not due to their possessing superior visual skill, but rather to their advanced extraction of structural patterns specific to chess.
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It can be fairly easy to confuse category learning and perceptual learning. Category learning is "an assumed fixed, pre-established perceptual representation to describe the objects to be categorized." Category learning is built upon perceptual learning because you are showing a distinction of what
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Other examples of perceptual learning in the natural world include the ability to distinguish between relative pitches in music, identify tumors in x-rays, sort day-old chicks by gender, taste the subtle differences between beers or wines, identify faces as belonging to different races, detect the
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with visual search show that experience leads to great gains in sensitivity and speed. In one study by Karni and Sagi, the time it took for subjects to search for an oblique line among a field of horizontal lines was found to improve dramatically, from about 200ms in one session to about 50ms in a
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methods to basic and complex skills use training situations in which the learner receives many short classification trials. Tallal, Merzenich and their colleagues have successfully adapted auditory discrimination paradigms to address speech and language difficulties. They reported improvements in
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However, recent studies suggest that perceptual learning occurs without selective attention. Studies of such task-irrelevant perceptual learning (TIPL) show that the degree of TIPL is similar to that found through direct training procedures. TIPL for a stimulus depends on the relationship between
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An example of this is money. Every day we look at money and we can look at it and know what it is but when you are asked to find the correct coin in similar coins that have slight differences we may have a problem finding the difference. This is because we see it every day but we are not directly
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Despite the marked perceptual learning demonstrated in different sensory systems and under varied training paradigms, it is clear that perceptual learning must face certain unsurpassable limits imposed by the physical characteristics of the sensory system. For instance, in tactile spatial acuity
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of more difficult cases. By recording ERPs from human adults, Ding and
Colleagues investigated the influence of task difficulty on the brain mechanisms of visual perceptual learning. Results showed that difficult task training affected earlier visual processing stage and broader visual cortical
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Pavlov's studies were followed by many training studies which found that an effective way to increase perceptual resolution is to begin with a large difference along the required dimension and gradually proceed to small differences along this dimension. This easy-to-difficult transfer was termed
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may be explained in terms of the selection of which analyzers best perform the classification, even in simple discrimination tasks. They explain that the some part of the neural system responsible for particular decisions have specificity, while low-level perceptual units do not. In their model,
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Perceptual learning is prevalent and occurs continuously in everyday life. "Experience shapes the way people see and hear." Experience provides the sensory input to our perceptions as well as knowledge about identities. When people are less knowledgeable about different races and cultures people
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tasks are specific to the trained stimuli or tasks. Sireteanu and
Rettenback discussed discrimination learning effects that generalize across eyes, retinal locations and tasks. Ahissar and Hochstein used visual search to show that learning to detect a single line element hidden in an array of
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Perceptual learning effects can be organized into two broad categories: discovery effects and fluency effects. Discovery effects involve some change in the bases of response such as in selecting new information relevant for the task, amplifying relevant information or suppressing irrelevant
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Since the mid-1980s, there has been a new wave of interest in perceptual learning due to findings of cortical plasticity at the lowest sensory levels of sensory systems. Our increased understanding of the physiology and anatomy of our cortical systems has been used to connect the behavioral
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Wise, J., Kubose, T., Chang, N., Russell, A., & Kellman, P. (1999). Perceptual learning modules in mathematics and science instruction. Artificial intelligence in education: open learning environments: new computational technologies to support learning, exploration and collaboration,
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varies from one participant to another. Perceptual learning occurs not only within the first training session but also between sessions. Fast learning (i.e., within-first-session learning) and slow learning (i.e., between-session learning) involves different changes in the human adult
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Goldstone, R. L., Steyvers, M., Spencer-Smith, J. & Kersten, A. (2000). Interaction between perceptual and conceptual learning. In E. Diettrich & A. B. Markman (Eds). Cognitive
Dynamics: Conceptual Change in Humans and Machines (pp. 191-228). Lawrence Erlbaum and
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infancy. Much of the scientific community tended to underestimate the impact of learning compared with innate mechanisms. Thus, most of this research focused on characterizing basic perceptual capacities of young infants rather than on perceptual learning processes.
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evidence suggests that training for refined discrimination along basic dimensions (e.g. frequency in the auditory modality) also increases the representation of the trained parameters, though in these cases the increase may mainly involve lower-level sensory areas.
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documented report, dating to the mid-19th century, is the earliest example of tactile training aimed at decreasing the minimal distance at which individuals can discriminate whether one or two points on their skin have been touched. It was found that this distance (
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When a woman has a baby, shortly after the baby's birth she will be able to decipher the difference in her baby's cry. This is because she is becoming more sensitive to the differences. She can tell what cry is because they are hungry, need to be changed, etc.
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trying to find a difference. Learning to perceive differences and similarities among stimuli based on exposure to the stimuli. A study conducted by Gibson's in 1955 illustrates how exposure to stimuli can affect how well we learn details for different stimuli.
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Practice with comparison and contrast of instances that belong to the same or different categories allow for the pick-up of the distinguishing features—features that are important for the classification task—and the filter of the irrelevant features.
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In many cases, perceptual learning does not require feedback (whether or not the classification is correct). Other studies suggest that block feedback (feedback only after a block of trials) produces more learning effects than no feedback at all.
916:, 1890) asserted that "My experience is what I agree to attend to. Only those items which I notice shape my mind - without selective interest, experience is an utter chaos.". His view was extreme, yet its gist was largely supported by subsequent
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processes (i.e., language) and interacts with other kinds of learning to produce perceptual expertise. Underlying perceptual learning are changes in the neural circuitry. The ability for perceptual learning is retained throughout life.
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features that distinguish familiar faces, discriminate between two bird species ("great blue crown heron" and "chipping sparrow"), and attend selectively to the hue, saturation and brightness values that comprise a color definition.
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A question still debated today is to what extent improvements from perceptual learning stems from peripheral modifications compared with improvement in higher-level readout stages. Early interpretations, such as that suggested by
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In complex perceptual learning tasks (e.g., sorting of newborn chicks by sex, playing chess), experts are often unable to explain what stimulus relationships they are using in classification. However, in less complex perceptual
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Similar results have also been replicated in other domains with PLMs, including anatomic recognition in medical and surgical training, reading instrumental flight displays, and apprehending molecular structures in chemistry.
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is typically gained by training under complex simulation conditions rather than one component at a time. Recent lab-based training protocols with complex action computer games have shown that such practice indeed modifies
901:. Discovery and fluency effects work together so that as the discovery structures becomes more automatic, attentional resources are conserved for discovery of new relations and for high-level thinking and problem-solving.
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Merzenich MM, Kaas JH, Wall JT, Sur M, Nelson RJ, Felleman DJ (1983). "Progression of change following median nerve section in the cortical representation of the hand in areas 3b and 1 in adult owl and squirrel monkeys".
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Active classification effort and attention are often necessary to produce perceptual learning effects. However, in some cases, mere exposure to certain stimulus variations can produce improved discriminations.
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devoted a section in his
Principles of Psychology (1890/1950) to "the improvement in discrimination by practice". He noted examples and emphasized the importance of perceptual learning for expertise. In 1918,
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language learning-impaired children using specially enhanced and extended speech signals. The results applied not only to auditory discrimination performance but speech and language comprehension as well.
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that perceptual representations at sensory areas of the cortex are substantially modified during a short ("critical") period immediately following birth. Merzenich, Kaas and colleagues showed that though
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Green, C.S., & Bavelier, D.. (2006) The
Cognitive Neuroscience of Video Games. In: Messaris P, Humphrey L, editors. Digital Media: Transformations in Human Communication. New York: Peter Lang
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Guerlain, S.; La
Follette, M.; Mersch, T.C.; Mitchell, B.A.; Poole, G.R.; Calland, J.F.; et al. (2004). "Improving surgical pattern recognition through repetitive viewing of video clips".
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tends to occur with perceptual learning. As we learn to distinguish between an array of wine flavors, we also develop a wide range of vocabularies to describe the intricacy of each flavor.
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Kellman, P.J.; Massey, C.M.; Roth, Z.; Burke, T.; Zucker, J.; Saw, A.; et al. (2008). "Perceptual learning and the technology of expertise: Studies in fraction learning and algebra".
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Within the past decade, researchers have sought a more unified understanding of perceptual learning and worked to apply these principles to improve perceptual learning in applied domains.
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is diminished, it is not eliminated when the critical period ends. Thus, when the external pattern of stimulation is substantially modified, neuronal representations in lower-level (e.g.
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is always implicit. Changes in sensitivity that arise are often not conscious and do not involve conscious procedures, but perceptual information can be mapped onto various responses.
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the objects are. Perceptual learning is defined as a "change in perception as a product of experience, and has reviewed evidence demonstrating that discrimination between other words
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tasks, observers judge whether one line is displaced above or below a second line. Untrained observers are often already very good with this task, but after training, observers'
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Merzenich; Jenkins, W.M.; Johnstone, P.; Schreiner, C.; Miller, S.; Tallal, P. (1996). "Temporal processing deficits of language impaired children ameliorated by training".
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Castel, A.D.; Pratt, J.; Drummond, E. (2005). "The effects of action video game experience on the time course of inhibition of return and the efficiency of visual search".
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Greenfield, P.M.; DeWinstanley, P.; Kilpatrick, H.; Kaye, D. (1994). "Action video games and informal education: effects on strategies for dividing visual attention".
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Burns, E.M.; Ward, W.D. (1978). "Categorical perception - phenomenon or epiphenomenon: Evidence from experiments in the per- ception of melodic musical intervals".
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Kellman, P.J.; Kaiser, M.K. (1994). "Extracting object motion during observer motion: Combining constraints from optic flow and binocular disparity".
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Biederman, I.; Shiffrar, M. M. (1987). "Sexing day- old chicks: a case study and expert systems analysis of a difficult perceptual-learning task".
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has been shown to improve as much as 6 fold. Similar improvements have been found for visual motion discrimination and orientation sensitivity. In
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Liberman, A.M.; Harris, K.S.; Hoffman, H.S.; Griffith, B.C. (1957). "The discrimination of speech sounds within and across phonemes boundaries".
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Griffith, J.L.; Voloschin, P.; Gibb, G.D.; Bailey, J.R. (1983). "Differences in eye-hand motor coordination of video-game users and non-users".
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Extensive practice reading in
English leads to extraction and rapid processing of the structural regularities of English spelling patterns. The
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that sound similar to their native language. They now can tell the difference whereas in category learning they are trying to separate the two.
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tasks, experiments suggest that the extent of learning is limited by fingertip surface area, which may constrain the underlying density of
3378:"Learning pop-out detection: The spread of attention and learning in feature search: effects of target distribution and task difficulty"
1093:, inducing improvement, and fatigue, which hampers performance. Current studies suggest that sleep contributes to improved and durable
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Schneider, W.; Shiffrin, R.M. (1977). "Controlled and automatic human information processing: I. Detection, search, and attention".
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from one another or categorizations of spatial and temporal patterns relevant to real-world expertise. Examples of this may include
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Wang, Y.; Song, Y.; Qu, Z.; Ding, Y.L. (2010). "Task difficulty modulates electrophysiological correlates of perceptual learning".
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Tallal, P.; Merzenich, M.; Miller, S.; Jenkins, W. (1998). "Language learning impairment: Integrating research and remediation".
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Fahle, M.; Edelman, S. (1993). "Long-term learning in vernier acuity: Effects of stimulus orientation, range and of feedback".
3280:"Plasticity in the frequency representation of primary auditory cortex following discrimination training in adult owl monkeys"
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Laboratory studies reported many examples of dramatic improvements in sensitivities from appropriately structured perceptual
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Wheeler, D. D. (1970). Processes in the visual recognition of words (Doctoral dissertation, University of Michigan, 1970)"
1784:"A Physical Constraint on Perceptual Learning: Tactile Spatial Acuity Improves with Training to a Limit Set by Finger Size"
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2521:"Dimensional interactions and the structure of psychological space: the representation of hue, saturation, and brightness"
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Petrov, A. A.; Dosher, B. A.; Lu, Z.-L. (2005). "The Dynamics of Perceptual Learning: An Incremental Reweighting Model".
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4249:"Perceptual Learning Modules in Mathematics: Enhancing Students' Pattern Recognition, Structure Extraction, and Fluency"
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Werker, J.F.; Lalonde, C.E. (1988). "Cross-language speech perception: initial capabilities and developmental change".
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are experts. We are all very sophisticated, but not infallible at scene identification, face identification and speech
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Ghose, G.M.; Yang, T.; Maunsell, J.H. (2002). "Physiological correlates of perceptual learning in monkey v1 and v2".
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Qu, Z. Song; Ding, Y. (2010). "ERP evidence for distinct mechanisms of fast and slow visual perceptual learning".
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Tanaka, J.; Taylor, M. (1991). "Object categories and expertise: Is the basic level in the eye of the beholder?".
3029:"The Attentional Boost Effect: Transient increases in attention to one task enhance performance in a second task"
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O'Toole, A. J.; Peterson, J.; Deffenbacher, K.A. (1996). "An "other-race effect" for categorizing faces by sex".
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Peron, R.M.; Allen, G.L. (1988). "Attempts to train novices for beer flavor discrimination: a matter of taste".
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Myles-Worsley, M.; Johnston, W.A.; Simon, M.A. (1988). "The influence of expertise on X-ray image processing".
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tasks, observers are asked to find a target object hidden among distractors or in noise. Studies of perceptual
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In many domains of expertise in the real world, perceptual learning interacts with other forms of learning.
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Herzog, M.H.; Fahle, M. (1998). "Modeling perceptual learning: Difficulties and how they can be overcome".
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Gibson, Eleanor (1969) Principles of Perceptual Learning and Development. New York: Appleton-Century-Crofts
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Vogels, R; Orban, GA (1985). "The effect of practice on the oblique effect in line orientation judgments".
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of distinguishing features. Selection may be the unifying principles of perceptual learning at all levels.
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takes place during practice sessions or in between, for example, during subsequent sleep. The dynamics of
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1105:(rapid eye movement) stages of sleep may contribute to this process, via not-yet-understood mechanisms.
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Reicher, G.M. (1969). "Perceptual recognition as a function of meaningfulness of stimulus material".
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are hard to evaluate since the directly measured parameter is performance, which is affected by both
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Seitz; Watanabe (2005). "A unified model of task-irrelevant and task-relevant perceptual learning".
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Ball, K; Sekuler, R (1982). "A specific and enduring improvement in visual motion discrimination".
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3753:"Improvement in line orientation discrimination is retinally local but dependent on cognitive set"
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M. Ahissar; S. Hochstein (2004). "The reverse hierarchy theory of visual perceptual learning".
1980:"Tactile spatial acuity enhancement in blindness: evidence for experience-dependent mechanisms"
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demonstrates this—people are often much faster at recognizing words than individual letters.
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improvement to the underlying cortical areas. This trend began with earlier findings of
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tasks, people can point out what information they're using to make classifications.
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2904:
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physical differences were equated between each pair of syllables.
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1833:"Tactile learning is task specific but transfers between fingers"
1243:
Like experimental procedures, other attempts to apply perceptual
797:. Categorical perception effects do not transfer across domains.
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3701:"Visual discrimination learning requires sleep after training"
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Leonards, U.; Rettenback, R.; Nase, G.; Sireteanu, R. (2002).
2594:. Vol. I. New York: Dover Publications Inc. p. 509.
2056:. The Oxford handbook of philosophy of perception. p. 1.
2031:. Handbook of categorization in cognitive science. p. 1.
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effects can be preserved for a long term over several months.
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3329:"Perceptual learning of highly demanding visual search tasks"
1181:
Similarly, perceptual learning also interacts flexibly with
1054:
The impact of training protocol and the dynamics of learning
1125:
easy examples first may lead to better transfer and better
1041:
In 2005, Petrov, Dosher and Lu pointed out that perceptual
3278:
Recanzone, G.H.; Schreiner, C.E.; Merzenich, M.M. (1993).
1777:
1775:
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has been found using single-cell recording techniques in
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1882:"Learning of tactile frequency discrimination in humans"
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The Neuropsychology of Perceptual Category Learning
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2079:Wiley Interdisciplinary Reviews: Cognitive Science
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3127:
3125:
1230:An important potential application of perceptual
1782:Wong, M.; Peters, R. M.; Goldreich, D. (2013).
771:Neuropsychology of perceptual category learning
3932:"Video games as a tool to train visual skills"
1931:"The topography of tactile learning in humans"
1335:
1333:
1331:
1329:
793:These effects are described as the result of
601:
8:
1929:Harris, JA; Harris, IM; Diamond, ME (2001).
1439:Human Perceptual Learning and Categorization
1381:
1379:
1342:Stevens' Handbook of Experimental Psychology
978:effects are specific to the trained task or
701:. There might be a discussion about this on
4360:Journal of the Optical Society of America A
4107:Journal of Applied Developmental Psychology
974:discriminations often show that perceptual
1256:In educational domains, recent efforts by
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3854:International Journal of Psychophysiology
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3644:"Perceptual learning and human expertise"
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1464:Journal of the Optical Society of America
721:Learn how and when to remove this message
666:Category learning vs. perceptual learning
2888:"Is subliminal learning really passive?"
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2583:
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1325:
23:
3197:10.1016/j.neuropsychologia.2010.01.008
2656:
2646:
1020:In some complex perceptual tasks, all
995:in both tactile and auditory domains.
643:pieces, and knowing whether or not an
3642:Kellman, P. J.; Garrigan, P. (2009).
3027:Swallow, KM; Jiang, YV (April 2010).
2219:Dissertation Abstracts Internationals
1170:Declarative & procedural learning
927:Indeed, a relevant signal in a given
7:
1252:Technologies for perceptual learning
1165:Relations to other forms of learning
3376:Ahissar, M.; Hochstein, S. (2000).
2617:. Vol. XXVIII. pp. 1–86.
1134:Active classification and attention
631:skills such as differentiating two
4213:Scandinavian Journal of Psychology
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3296:10.1523/JNEUROSCI.13-01-00087.1993
2233:Journal of Experimental Psychology
2185:Journal of Experimental Psychology
1947:10.1523/JNEUROSCI.21-03-01056.2001
1831:Sathian, K; Zangaladze, A (1997).
940:Time course of perceptual learning
14:
1130:regions than easy task training.
1016:Enrichment versus differentiation
4265:10.1111/j.1756-8765.2009.01053.x
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678:
575:
31:
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3866:10.1016/j.ijpsycho.2009.11.006
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2721:. The MIT Press (2002: p. xiv)
1996:10.1523/jneurosci.6461-10.2011
1837:Perception & Psychophysics
1800:10.1523/JNEUROSCI.0514-13.2013
1505:Saarinen, J; Levi, DM (1995).
1081:Several studies asked whether
1069:"transfer along a continuum".
944:The time course of perceptual
1:
3395:10.1016/s0042-6989(00)00002-x
3346:10.1016/s0042-6989(02)00134-7
2935:Seitz, Kim; Watanabe (2009).
2393:10.1080/00221309.1988.9710577
2381:Journal of General Psychology
1650:Shiu, LP; Pashler, H (1992).
892:Discovery and fluency effects
318:Industrial and organizational
4146:10.1016/j.actpsy.2005.02.004
4119:10.1016/0193-3973(94)90008-6
4078:Applied Cognitive Psychology
3517:Trends in Cognitive Sciences
3249:10.1016/0042-6989(93)90094-d
2986:Trends in Cognitive Sciences
2953:10.1016/j.neuron.2009.01.016
2855:10.1016/j.visres.2009.08.003
2689:10.1016/0306-4522(83)90208-7
2592:The principles of psychology
2570:Leipzig Ber Math-Phys Classe
2525:Perception and Psychophysics
2498:10.1016/0010-0285(91)90016-H
2170:10.1016/0010-0285(73)90004-2
1713:10.1016/0042-6989(85)90140-3
1524:10.1016/0042-6989(94)00141-8
998:However, not all perceptual
966:Receptive field modification
742:Basic sensory discrimination
473:Human factors and ergonomics
4253:Topics in Cognitive Science
4181:10.1126/science.271.5245.77
4041:10.1037/0096-1523.32.6.1465
3982:Perceptual and Motor Skills
3668:10.1016/j.plrev.2008.12.001
2757:10.1037/0033-295X.112.4.715
2428:10.1037/0033-2909.100.2.139
1226:Improving perceptual skills
846:published her seminal book
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4310:10.1075/p&c.16.2.07kel
4298:Pragmatics & Cognition
3936:Restor Neurol Neuroscience
3529:10.1016/j.tics.2004.08.011
3482:Journal of Neurophysiology
2998:10.1016/j.tics.2005.05.010
2366:10.1037/0278-7393.13.4.640
2331:10.1037/0278-7393.14.3.553
2134:10.1037/0012-1649.24.5.672
2052:Goldstone, Robert (2015).
1350:10.1002/0471214426.pas0307
4337:10.1109/tsmca.2004.836793
3994:10.2466/pms.1983.57.1.155
3572:10.1016/j.bbr.2008.02.015
639:, seeing relations among
248:Applied behavior analysis
4226:10.1111/1467-9450.393079
2886:Seitz; Watanabe (2003).
2837:Seitz; Watanabe (2009).
2615:Psychological monographs
2122:Developmental Psychology
2027:Roeder, Jessica (2017).
1756:10.1037/0033-295X.84.1.1
1437:Carvalho, Paulo (2017).
1007:Reverse hierarchy theory
914:Principles of Psychology
4372:10.1364/JOSAA.12.000623
3648:Physics of Life Reviews
3284:Journal of Neuroscience
1984:Journal of Neuroscience
1935:Journal of Neuroscience
1788:Journal of Neuroscience
1629:10.1126/science.7134968
1576:10.1126/science.1589770
1109:Comparison and contrast
1077:Consolidation and sleep
961:Explanations and models
810:word superiority effect
438:Behavioral neuroscience
93:Behavioral neuroscience
3889:Biological Cybernetics
2416:Psychological Bulletin
1484:10.1364/JOSA.68.000450
1295:Educational psychology
1280:Categorical perception
795:categorical perception
488:Psychology of religion
428:Behavioral engineering
112:Cognitive neuroscience
78:Affective neuroscience
3901:10.1007/s004220050418
3494:10.1152/jn.00690.2001
2623:10.2105/ajph.10.7.583
1290:Cognitive development
1176:Declarative knowledge
1037:Selective reweighting
905:The role of attention
647:image shows a tumor.
582:Psychology portal
4432:Sources of knowledge
3606:Psychological Review
2745:Psychological Review
2486:Cognitive Psychology
2158:Cognitive Psychology
1744:Psychological Review
1197:is often said to be
1183:procedural knowledge
986:of the cells (e.g.,
780:In the natural world
691:confusing or unclear
4417:Behavioral concepts
3705:Nature Neuroscience
3660:2009PhLRv...6...53K
3443:2001Natur.412..549S
3146:1993Natur.365..250K
2800:2001Natur.413..844W
2719:Perceptual Learning
2288:1978ASAJ...63..456B
2054:Perceptual Learning
1886:Human Brain Mapping
1621:1982Sci...218..697B
1568:1992Sci...256.1018P
1476:1978JOSA...68..450W
1400:1993Natur.365..250K
1315:Pattern recognition
699:clarify the article
621:Perceptual learning
433:Behavioral genetics
348:Occupational health
88:Behavioral genetics
19:Part of a series on
3770:10.3758/bf03206720
3388:(10–12): 1349–64.
2538:10.3758/BF03207885
2276:J. Acoust. Soc. Am
1850:10.3758/bf03206854
1669:10.3758/BF03206720
1656:Percept Psychophys
970:Research on basic
651:Sensory modalities
550:Schools of thought
388:Sport and exercise
234:Applied psychology
4134:Acta Psychologica
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2590:James, W (1890).
2063:978-0-19-960047-2
2038:978-0-08-101107-2
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1305:Implicit learning
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1189:Implicit learning
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4438:
4437:
4436:
4407:
4406:
4405:
4399:
4395:
4357:
4356:
4352:
4322:
4321:
4317:
4295:
4294:
4290:
4246:
4245:
4241:
4209:
4208:
4204:
4175:(5245): 77–81.
4166:
4165:
4161:
4131:
4130:
4126:
4104:
4103:
4099:
4091:10.1002/acp.759
4071:
4070:
4066:
4022:
4021:
4017:
3979:
3978:
3974:
3969:
3965:
3929:
3928:
3924:
3886:
3885:
3881:
3851:
3850:
3846:
3808:
3807:
3803:
3798:
3794:
3750:
3749:
3742:
3698:
3697:
3693:
3641:
3640:
3633:
3603:
3602:
3595:
3560:Behav Brain Res
3557:
3556:
3552:
3514:
3513:
3509:
3479:
3478:
3474:
3424:
3423:
3419:
3382:Vision Research
3375:
3374:
3370:
3333:Vision Research
3326:
3325:
3321:
3277:
3276:
3272:
3237:Vision Research
3234:
3233:
3229:
3224:
3220:
3182:
3181:
3177:
3131:
3130:
3123:
3075:
3074:
3070:
3026:
3025:
3021:
2983:
2982:
2978:
2934:
2933:
2929:
2905:10.1038/422036a
2885:
2884:
2880:
2843:Vision Research
2836:
2835:
2831:
2785:
2784:
2780:
2742:
2741:
2732:
2716:
2712:
2673:
2672:
2668:
2655:
2645:
2612:
2611:
2607:
2589:
2588:
2581:
2567:
2566:
2562:
2518:
2517:
2513:
2483:
2482:
2478:
2455:10.1068/p250669
2440:
2439:
2435:
2413:
2412:
2408:
2378:
2377:
2373:
2351:
2350:
2346:
2316:
2315:
2311:
2273:
2272:
2268:
2230:
2229:
2225:
2216:
2212:
2182:
2181:
2177:
2155:
2154:
2150:
2145:
2141:
2119:
2118:
2114:
2076:
2075:
2071:
2064:
2051:
2050:
2046:
2039:
2026:
2025:
2021:
1990:(19): 7028–37.
1977:
1976:
1972:
1928:
1927:
1923:
1879:
1878:
1874:
1830:
1829:
1825:
1781:
1780:
1771:
1741:
1740:
1736:
1698:
1697:
1693:
1649:
1648:
1644:
1606:
1605:
1601:
1553:
1552:
1548:
1511:Vision Research
1504:
1503:
1499:
1461:
1460:
1456:
1449:
1436:
1435:
1431:
1385:
1384:
1377:
1371:
1367:
1360:
1339:
1338:
1327:
1323:
1310:Neuroplasticity
1271:
1254:
1228:
1223:
1191:
1172:
1167:
1154:
1145:
1136:
1120:
1118:Task difficulty
1111:
1079:
1073:relevant cues.
1056:
1039:
1018:
1009:
968:
963:
942:
907:
894:
889:
887:Characteristics
866:neuroplasticity
826:
782:
773:
744:
739:
727:
716:
710:
707:
696:
683:
679:
668:
614:
576:
574:
567:
566:
565:
564:
540:Psychotherapies
508:
498:
497:
418:
410:
409:
408:
407:
236:
226:
225:
224:
223:
184:Neuropsychology
66:
12:
11:
5:
4445:
4443:
4435:
4434:
4429:
4424:
4419:
4409:
4408:
4404:
4403:
4393:
4350:
4331:(6): 699–707.
4315:
4304:(2): 356–405.
4288:
4239:
4220:(3): 197–199.
4202:
4159:
4140:(2): 217–230.
4124:
4097:
4064:
4015:
3988:(1): 155–158.
3972:
3963:
3922:
3895:(2): 107–117.
3879:
3860:(3): 234–240.
3844:
3801:
3792:
3763:(5): 582–588.
3740:
3691:
3631:
3593:
3566:(1): 137–142.
3550:
3523:(10): 457–64.
3507:
3488:(4): 1867–88.
3472:
3417:
3368:
3319:
3270:
3243:(3): 397–412.
3227:
3218:
3175:
3121:
3091:10.1.1.24.8668
3084:(4): 1105–24.
3068:
3019:
2992:(7): 329–334.
2976:
2927:
2878:
2829:
2778:
2751:(4): 715–743.
2730:
2710:
2666:
2657:|journal=
2605:
2579:
2560:
2531:(5): 494–507.
2511:
2476:
2433:
2406:
2387:(4): 403–418.
2371:
2344:
2309:
2266:
2239:(5): 358–368.
2223:
2210:
2191:(2): 275–280.
2175:
2148:
2139:
2112:
2091:10.1002/wcs.26
2069:
2062:
2044:
2037:
2019:
1970:
1941:(3): 1056–61.
1921:
1872:
1823:
1769:
1734:
1691:
1662:(5): 582–588.
1642:
1599:
1546:
1517:(4): 519–527.
1497:
1470:(4): 450–455.
1454:
1447:
1429:
1375:
1365:
1358:
1324:
1322:
1319:
1318:
1317:
1312:
1307:
1302:
1297:
1292:
1287:
1282:
1277:
1270:
1267:
1258:Philip Kellman
1253:
1250:
1227:
1224:
1222:
1219:
1190:
1187:
1171:
1168:
1166:
1163:
1153:
1150:
1144:
1141:
1135:
1132:
1119:
1116:
1110:
1107:
1078:
1075:
1055:
1052:
1038:
1035:
1017:
1014:
1008:
1005:
967:
964:
962:
959:
941:
938:
906:
903:
893:
890:
888:
885:
844:Eleanor Gibson
825:
822:
781:
778:
772:
769:
752:Vernier acuity
743:
740:
738:
735:
729:
728:
686:
684:
677:
667:
664:
616:
615:
613:
612:
605:
598:
590:
587:
586:
585:
584:
569:
568:
563:
562:
557:
552:
547:
542:
537:
532:
527:
522:
517:
511:
510:
509:
504:
503:
500:
499:
496:
495:
490:
485:
480:
475:
470:
465:
460:
455:
450:
445:
440:
435:
430:
425:
419:
416:
415:
412:
411:
406:
405:
400:
395:
390:
385:
380:
375:
370:
365:
360:
355:
350:
345:
340:
335:
330:
325:
320:
315:
310:
305:
300:
295:
290:
285:
280:
275:
270:
265:
260:
255:
250:
245:
239:
238:
237:
232:
231:
228:
227:
222:
221:
216:
211:
206:
201:
196:
191:
186:
181:
176:
171:
166:
161:
156:
151:
146:
141:
136:
131:
129:Cross-cultural
126:
121:
120:
119:
109:
100:
95:
90:
85:
80:
75:
69:
68:
67:
62:
61:
58:
57:
56:
55:
50:
45:
37:
36:
28:
27:
21:
20:
13:
10:
9:
6:
4:
3:
2:
4444:
4433:
4430:
4428:
4425:
4423:
4420:
4418:
4415:
4414:
4412:
4397:
4394:
4389:
4385:
4381:
4377:
4373:
4369:
4365:
4361:
4354:
4351:
4346:
4342:
4338:
4334:
4330:
4326:
4319:
4316:
4311:
4307:
4303:
4299:
4292:
4289:
4284:
4280:
4275:
4270:
4266:
4262:
4258:
4254:
4250:
4243:
4240:
4235:
4231:
4227:
4223:
4219:
4215:
4214:
4206:
4203:
4198:
4194:
4190:
4186:
4182:
4178:
4174:
4170:
4163:
4160:
4155:
4151:
4147:
4143:
4139:
4135:
4128:
4125:
4120:
4116:
4112:
4108:
4101:
4098:
4092:
4087:
4083:
4079:
4075:
4068:
4065:
4060:
4056:
4051:
4046:
4042:
4038:
4034:
4030:
4026:
4019:
4016:
4011:
4007:
4003:
3999:
3995:
3991:
3987:
3983:
3976:
3973:
3967:
3964:
3959:
3955:
3950:
3945:
3941:
3937:
3933:
3926:
3923:
3918:
3914:
3910:
3906:
3902:
3898:
3894:
3890:
3883:
3880:
3875:
3871:
3867:
3863:
3859:
3855:
3848:
3845:
3840:
3836:
3832:
3828:
3824:
3820:
3816:
3812:
3805:
3802:
3796:
3793:
3788:
3784:
3780:
3776:
3771:
3766:
3762:
3758:
3754:
3747:
3745:
3741:
3736:
3732:
3728:
3724:
3719:
3718:10.1038/81756
3714:
3710:
3706:
3702:
3695:
3692:
3687:
3683:
3678:
3673:
3669:
3665:
3661:
3657:
3653:
3649:
3645:
3638:
3636:
3632:
3627:
3623:
3619:
3615:
3611:
3607:
3600:
3598:
3594:
3589:
3585:
3581:
3577:
3573:
3569:
3565:
3561:
3554:
3551:
3546:
3542:
3538:
3534:
3530:
3526:
3522:
3518:
3511:
3508:
3503:
3499:
3495:
3491:
3487:
3483:
3476:
3473:
3468:
3464:
3460:
3456:
3452:
3448:
3444:
3440:
3436:
3432:
3428:
3421:
3418:
3413:
3409:
3405:
3401:
3396:
3391:
3387:
3383:
3379:
3372:
3369:
3364:
3360:
3356:
3352:
3347:
3342:
3338:
3334:
3330:
3323:
3320:
3315:
3311:
3306:
3301:
3297:
3293:
3290:(1): 87–103.
3289:
3285:
3281:
3274:
3271:
3266:
3262:
3258:
3254:
3250:
3246:
3242:
3238:
3231:
3228:
3222:
3219:
3214:
3210:
3206:
3202:
3198:
3194:
3190:
3186:
3179:
3176:
3171:
3167:
3163:
3159:
3155:
3151:
3147:
3143:
3139:
3135:
3128:
3126:
3122:
3117:
3113:
3109:
3105:
3101:
3097:
3092:
3087:
3083:
3079:
3072:
3069:
3064:
3060:
3055:
3050:
3046:
3042:
3039:(1): 118–32.
3038:
3034:
3030:
3023:
3020:
3015:
3011:
3007:
3003:
2999:
2995:
2991:
2987:
2980:
2977:
2972:
2968:
2963:
2958:
2954:
2950:
2946:
2942:
2938:
2931:
2928:
2923:
2919:
2915:
2911:
2906:
2901:
2897:
2893:
2889:
2882:
2879:
2874:
2870:
2865:
2860:
2856:
2852:
2848:
2844:
2840:
2833:
2830:
2825:
2821:
2817:
2813:
2809:
2805:
2801:
2797:
2793:
2789:
2782:
2779:
2774:
2770:
2766:
2762:
2758:
2754:
2750:
2746:
2739:
2737:
2735:
2731:
2728:
2724:
2720:
2714:
2711:
2706:
2702:
2698:
2694:
2690:
2686:
2683:(3): 639–65.
2682:
2678:
2670:
2667:
2662:
2650:
2642:
2638:
2633:
2628:
2624:
2620:
2616:
2609:
2606:
2601:
2597:
2593:
2586:
2584:
2580:
2575:
2571:
2564:
2561:
2556:
2552:
2548:
2544:
2539:
2534:
2530:
2526:
2522:
2515:
2512:
2507:
2503:
2499:
2495:
2492:(3): 457–82.
2491:
2487:
2480:
2477:
2472:
2468:
2464:
2460:
2456:
2452:
2449:(6): 669–76.
2448:
2444:
2437:
2434:
2429:
2425:
2422:(2): 139–56.
2421:
2417:
2410:
2407:
2402:
2398:
2394:
2390:
2386:
2382:
2375:
2372:
2367:
2363:
2360:(4): 640–45.
2359:
2355:
2348:
2345:
2340:
2336:
2332:
2328:
2325:(3): 553–57.
2324:
2320:
2313:
2310:
2305:
2301:
2297:
2293:
2289:
2285:
2282:(2): 456–68.
2281:
2277:
2270:
2267:
2262:
2258:
2254:
2250:
2246:
2242:
2238:
2234:
2227:
2224:
2220:
2214:
2211:
2206:
2202:
2198:
2194:
2190:
2186:
2179:
2176:
2171:
2167:
2163:
2159:
2152:
2149:
2143:
2140:
2135:
2131:
2128:(5): 672–83.
2127:
2123:
2116:
2113:
2108:
2104:
2100:
2096:
2092:
2088:
2084:
2080:
2073:
2070:
2065:
2059:
2055:
2048:
2045:
2040:
2034:
2030:
2023:
2020:
2015:
2011:
2006:
2001:
1997:
1993:
1989:
1985:
1981:
1974:
1971:
1966:
1962:
1957:
1952:
1948:
1944:
1940:
1936:
1932:
1925:
1922:
1917:
1913:
1908:
1903:
1899:
1895:
1892:(4): 260–71.
1891:
1887:
1883:
1876:
1873:
1868:
1864:
1860:
1856:
1851:
1846:
1843:(1): 119–28.
1842:
1838:
1834:
1827:
1824:
1819:
1815:
1810:
1805:
1801:
1797:
1793:
1789:
1785:
1778:
1776:
1774:
1770:
1765:
1761:
1757:
1753:
1749:
1745:
1738:
1735:
1730:
1726:
1722:
1718:
1714:
1710:
1706:
1702:
1695:
1692:
1687:
1683:
1679:
1675:
1670:
1665:
1661:
1657:
1653:
1646:
1643:
1638:
1634:
1630:
1626:
1622:
1618:
1614:
1610:
1603:
1600:
1595:
1591:
1586:
1581:
1577:
1573:
1569:
1565:
1561:
1557:
1550:
1547:
1542:
1538:
1534:
1530:
1525:
1520:
1516:
1512:
1508:
1501:
1498:
1493:
1489:
1485:
1481:
1477:
1473:
1469:
1465:
1458:
1455:
1450:
1444:
1440:
1433:
1430:
1425:
1421:
1417:
1413:
1409:
1405:
1401:
1397:
1393:
1389:
1382:
1380:
1376:
1369:
1366:
1361:
1355:
1351:
1347:
1343:
1336:
1334:
1332:
1330:
1326:
1320:
1316:
1313:
1311:
1308:
1306:
1303:
1301:
1300:Eureka effect
1298:
1296:
1293:
1291:
1288:
1286:
1283:
1281:
1278:
1276:
1273:
1272:
1268:
1266:
1262:
1259:
1251:
1249:
1246:
1241:
1238:
1233:
1225:
1220:
1218:
1216:
1210:
1208:
1204:
1200:
1196:
1188:
1186:
1184:
1179:
1177:
1169:
1164:
1162:
1160:
1151:
1149:
1142:
1140:
1133:
1131:
1128:
1124:
1117:
1115:
1108:
1106:
1104:
1100:
1096:
1092:
1088:
1084:
1076:
1074:
1070:
1066:
1064:
1060:
1053:
1051:
1049:
1044:
1036:
1034:
1031:
1030:Physiological
1027:
1023:
1015:
1013:
1006:
1004:
1001:
996:
994:
989:
985:
981:
977:
973:
965:
960:
958:
956:
952:
947:
939:
937:
933:
930:
925:
923:
922:physiological
919:
915:
911:
910:William James
904:
902:
900:
891:
886:
884:
881:
879:
878:William James
873:
871:
867:
862:
858:
852:
849:
845:
841:
840:Clark L. Hull
836:
835:William James
832:
824:Brief history
823:
821:
817:
813:
811:
806:
802:
798:
796:
790:
786:
779:
777:
770:
768:
765:
761:
760:visual search
757:
753:
749:
741:
736:
734:
725:
722:
714:
704:
703:the talk page
700:
694:
692:
687:This article
685:
676:
675:
672:
665:
663:
660:
656:
652:
648:
646:
642:
638:
634:
633:musical tones
630:
626:
622:
611:
606:
604:
599:
597:
592:
591:
589:
588:
583:
573:
572:
571:
570:
561:
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556:
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551:
548:
546:
543:
541:
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536:
535:Psychologists
533:
531:
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525:Organizations
523:
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494:
493:Psychometrics
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669:
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619:
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174:Mathematical
169:Intelligence
159:Experimental
154:Evolutionary
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4113:: 105–123.
1750:(1): 1–66.
1585:1721.1/6585
1193:Perceptual
1061:discovered
1059:Ivan Pavlov
520:Disciplines
393:Suicidology
288:Educational
243:Anomalistic
219:Theoretical
194:Personality
124:Comparative
107:Cognitivism
98:Behaviorism
4427:Perception
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1701:Vision Res
1373:Associates
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918:behavioral
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278:Counseling
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1818:23719803
1764:26558224
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1541:14458537
1269:See also
1245:learning
1232:learning
1215:learning
1207:learning
1203:learning
1199:implicit
1195:learning
1143:Feedback
1127:learning
1123:Learning
1095:learning
1091:learning
1087:learning
1083:learning
1048:learning
1043:learning
1000:learning
993:primates
980:stimulus
976:learning
955:learning
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748:learning
737:Examples
625:learning
555:Timeline
468:Feelings
463:Emotions
423:Behavior
417:Concepts
378:Religion
363:Positive
353:Pastoral
338:Military
303:Forensic
298:Feminist
283:Critical
273:Consumer
263:Coaching
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134:Cultural
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637:reading
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1152:Limits
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655:visual
560:Topics
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308:Health
214:Social
117:Social
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