Demonstration of cue recruitment: Change in visual appearance by means of Pavlovian conditioning

Hu, Qi; Saunders, Jeffrey A.; Stone, Rebecca; Backus, Benjamin T.

doi:10.1073/pnas.0506728103

Cited by 100 publications

(180 citation statements)

References 66 publications

(51 reference statements)

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“…These results suggest that sensory variables are not directly accessible in learning; learning processes may use these inputs only through constancy-based representations. Although it remains possible that more extended training might lead to some learning, the lack of improvement in the sensory conditions across the entire session contrasts with many results showing that PL effects begin to appear early in training (12,13). Moreover, our design used the same sensory relations in conditions that were unlearnable (in the uncorrelated conditions) as the basis of constancy in the correlated conditions.…”

Section: Resultsmentioning

confidence: 90%

“…In contrast, the identical sensory invariants were readily discoverable when they correlated with a perceptual classification (e.g., when equal retinal sizes correlated with equal perceived sizes). PL effects in learnable situations are normally largest in the earliest trials and conspicuously evident over the first few hundred trials (12,13). One concern we had was that learning could have been occurring gradually in the cases where no reliable indications of performance improvement were observed.…”

Section: Resultsmentioning

confidence: 99%

“…It is also apparent, however, that learning involves interactions of lower processing levels with higher perceptual representations (11)(12)(13). Corresponding neurophysiological evidence suggests that higher cortical areas have important functional significance in PL and that the locus of neural modification for PL related to a single task depends on characteristics of the stimuli (14).…”

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confidence: 99%

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Perceptual learning depends on perceptual constancy

Garrigan

Kellman

2008

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

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Perceptual learning refers to experience-induced improvements in the pick-up of information. Perceptual constancy describes the fact that, despite variable sensory input, perceptual representations typically correspond to stable properties of objects. Here, we show evidence of a strong link between perceptual learning and perceptual constancy: Perceptual learning depends on constancybased perceptual representations. Perceptual learning may involve changes in early sensory analyzers, but such changes may in general be constrained by categorical distinctions among the high-level perceptual representations to which they contribute. Using established relations of perceptual constancy and sensory inputs, we tested the ability to discover regularities in tasks that dissociated perceptual and sensory invariants. We found that human subjects could learn to classify based on a perceptual invariant that depended on an underlying sensory invariant but could not learn the identical sensory invariant when it did not correlate with a perceptual invariant. These results suggest that constancy-based representations, known to be important for thought and action, also guide learning and plasticity.abstract ͉ representation C lassical theories and contemporary computational accounts of sensation and perception distinguish between variables encoded in early sensory analysis and higher level representations of objects, scenes, and events. Whereas early analyzers involve relatively local responses to energy, perceptual representations most often correspond to stable properties of material objects. Object properties persist across changes in the energy reaching the senses, so that comprehending the world requires perceptual constancy-attainment of relatively constant perceptual descriptions despite variation in the sensory inputs used to compute them. A common example is constancy of size: Under a variety of conditions, an object's perceived size does not vary as the observer's viewing distance changes, even though such changes alter the projected (retinal) size. Similarly, an object's surface lightness (shade of gray) does not appear to change when an object is viewed outside in sunshine or indoors, despite changes of more than three orders of magnitude in

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Section: Resultsmentioning

confidence: 90%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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Perceptual learning depends on perceptual constancy

Garrigan

Kellman

2008

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

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“…Increased symbol identity errors under conditions of compromised visual encoding may be related to "cue recruitment," in which an uninformative visual cue (e.g., presentation position on a computer screen) can be trained in order to disambiguate a bistable figure (e.g., a Necker cube; Qi, Saunders, Stone, & Backus, 2006). In our case, spacing, a formally uninformative cue to symbol identity, was being used as if it were predictive.…”

Section: Discussionmentioning

confidence: 99%

Persistent perceptual grouping effects in the evaluation of simple arithmetic expressions

Rivera

Garrigan

2016

Mem Cogn

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Landy and Goldstone (2007a demonstrated that an explicit rule, operator precedence for simple arithmetic expressions, is enforced in part by perceptual processes like unit formation and attention. When perceptual grouping competes with operator precedence, errors increase. We replicated this result (Exp. 1) and investigated whether perceptual grouping effects persist when the visual stimulus is presented briefly and then masked (Exp. 2) and when verbal recoding is encouraged through vocal expression (Exp. 3). We found that perceptual-grouping effects persisted in the masking condition, suggesting that the mental representations of arithmetic expressions retain visuospatial characteristics. Similarly, verbalization of the expressions did not eliminate perceptualgrouping effects, suggesting that participants were not verbally recoding. In sum, the persistent effects of unit formation and spatial attention emphasize the importance of perceptual processing in the development of human expertise in this domain.

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“…If perception is a function of both the sensory input and internal states, then-because states can vary both across individual observers and over time-the presence of an internal state would manifest itself as potentially large individual differences in the perception of the same stimulus and in coherent temporal variations of perception of the same stimulus over time in a single observer. It is known that visual functions can be modulated (2) on brief time scales by priming (3)(4)(5)(6), aftereffects (7)(8)(9), and sequence effects (10)(11)(12)(13) [and sometimes on larger time scales as well (14)]; can undergo visible short-term fluctuations in the presence of multistable stimuli (15)(16)(17)(18)(19)(20); and can undergo long-term or permanent changes in their structure through learning (21)(22)(23)(24). Despite these examples, little is known about internal states of the visual system.…”

mentioning

confidence: 99%

Persistent states in vision break universality and time invariance

Wexler

Duyck

Mamassian

2015

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

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Studies of perception usually emphasize processes that are largely universal across observers and-except for short-term fluctuationsstationary over time. Here we test the universality and stationarity assumptions with two families of ambiguous visual stimuli. Each stimulus can be perceived in two different ways, parameterized by two opposite directions from a continuous circular variable. A large-sample study showed that almost all observers have preferred directions or biases, with directions lying within 90 degrees of the bias direction nearly always perceived and opposite directions almost never perceived. The biases differ dramatically from one observer to the next, and although nearly every bias direction occurs in the population, the population distributions of the biases are nonuniform, featuring asymmetric peaks in the cardinal directions. The biases for the two families of stimuli are independent and have distinct population distributions. Following external perturbations and spontaneous fluctuations, the biases decay over tens of seconds toward their initial values. Persistent changes in the biases are found on time scales of several minutes to 1 hour. On scales of days to months, the biases undergo a variety of dynamical processes such as drifts, jumps, and oscillations. The global statistics of a majority of these long-term time series are well modeled as random walk processes. The measurable fluctuations of these hitherto unknown degrees of freedom show that the assumptions of universality and stationarity in perception may be unwarranted and that models of perception must include both directly observable variables as well as covert, persistent states.T he neural networks underlying visual perception are complex systems and, as such, undoubtedly have internal states. The formal notion of "state" can be defined as the minimal set of variables that, together with the input to a system and the fixed processing mechanisms, allows one to predict the system's output (1). If perception is a function of both the sensory input and internal states, then-because states can vary both across individual observers and over time-the presence of an internal state would manifest itself as potentially large individual differences in the perception of the same stimulus and in coherent temporal variations of perception of the same stimulus over time in a single observer. It is known that visual functions can be modulated (2) on brief time scales by priming (3-6), aftereffects (7-9), and sequence effects (10-13) [and sometimes on larger time scales as well (14)]; can undergo visible short-term fluctuations in the presence of multistable stimuli (15-20); and can undergo long-term or permanent changes in their structure through learning (21-24). Despite these examples, little is known about internal states of the visual system. In terms of underlying mechanisms, the internal state is represented naturally in recurrent but not in feed-forward neural networks (25, 26).Here we measure patterns of biases in two families of vis...

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Demonstration of cue recruitment: Change in visual appearance by means of Pavlovian conditioning

Abstract: classical conditioning ͉ perceptual learning ͉ bistable perception

Cited by 100 publications

References 66 publications

Perceptual learning depends on perceptual constancy

Perceptual learning depends on perceptual constancy

Persistent perceptual grouping effects in the evaluation of simple arithmetic expressions

Persistent states in vision break universality and time invariance

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