Time course of visual extrapolation accuracy

Lyon, Don R.; Waag, Wayne L.

doi:10.1016/0001-6918(95)98945-z

Cited by 56 publications

(60 citation statements)

References 14 publications

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“…For example, to use CME, a temporal process would seem necessary to update the object's extrapolated position (and corresponding imagery) at each point in time until it reaches the end point. Alternatively, observers may compute the object's hidden time (TTC) from the ratio of exposed distance to hidden distance and the duration of the object's visible motion; the clock would count the latter duration and the hidden time (Rosenbaum, 1975; see also Lyon & Waag, 1995). Lyon and Waag (1995) classified hypotheses about the mechanisms that underlie the ability to extrapolate motion as either tracking hypotheses or timing hypotheses.…”

Section: Cognitive Motion Extrapolation and Cognitive Clocking In Prementioning

confidence: 99%

“…Alternatively, observers may compute the object's hidden time (TTC) from the ratio of exposed distance to hidden distance and the duration of the object's visible motion; the clock would count the latter duration and the hidden time (Rosenbaum, 1975; see also Lyon & Waag, 1995). Lyon and Waag (1995) classified hypotheses about the mechanisms that underlie the ability to extrapolate motion as either tracking hypotheses or timing hypotheses. Timing hypotheses involve a central timing mechanism that clocks the object's visible motion; this elapsed time is the basis for how long the observer waits before responding.…”

Section: Cognitive Motion Extrapolation and Cognitive Clocking In Prementioning

confidence: 99%

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Cognitive motion extrapolation and cognitive clocking in prediction motion tasks.

DeLucia¹,

Liddell²

1998

Journal of Experimental Psychology: Human Perception and Perfor

106

141

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An interruption paradigm was used to measure judgments that rely on cognitive extrapolation of approach and lateral motion. In some conditions the pattern of errors was consistent with that obtained with time-to-contact (TIC) judgments measured with a prediction motion (I'M) task. Also, the slope of the relationship between estimated and actual TTC in judgments of approaching objects decreased when visual information about the environment between the observer and the display was minimized. Moreover, the accuracy of relative duration judgments of visual (but not auditory) stimuli decreased when a PM task was performed concurrently. Results are consistent with the notion that PM tasks involve cognitive motion extrapolation rather than solely a clocking process that counts down TIC.

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Section: Cognitive Motion Extrapolation and Cognitive Clocking In Prementioning

confidence: 99%

Section: Cognitive Motion Extrapolation and Cognitive Clocking In Prementioning

confidence: 99%

Cognitive motion extrapolation and cognitive clocking in prediction motion tasks.

DeLucia¹,

Liddell²

1998

Journal of Experimental Psychology: Human Perception and Perfor

106

141

View full text Add to dashboard Cite

show abstract

“…1a). Another variant requires the participant to judge whether the target reappeared from occlusion too early or too late (Bennett & Benguigui, 2013;DeLucia & Liddell, 1998;Jonikaitis, Deubel, & de'Sperati, 2009;Lyon & Waag, 1995;O'Reilly, Mesulam, & Nobre, 2008). This is sometimes called an 'interruption paradigm' (see Fig.…”

mentioning

confidence: 99%

The common rate control account of prediction motion

Makin

2017

Psychon Bull Rev

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In prediction-motion (PM) tasks, people judge the current position of an occluded moving object. People can also judge the current number on an occluded digital counter or the current colour of an occluded colour-change display. These abilities imply that we can run mental simulations at a chosen speed, even without feedback from the senses. There is increasing evidence that the brain has a common rate control module for pacing all such dynamic mental simulations. The common rate control account of PM has more explanatory power than alternative accounts which emphasise the role of mental imagery or the oculomotor system. Finally, neuroimaging work suggests that the common rate controller is a part of a core timing network that incorporates basal ganglia circuitry.

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“…The fact that stimulus history biases perceptual judgments is well-known. Broadly speaking, it appears in two ways-biases to (or away from) the mean of a stimulus distribution (1)(2)(3)(4)(5)(6)(7)(8)(9), referred to as central-tendency biases, and biases to (or away from) recently observed stimuli (10)(11)(12)(13)(14)(15)(16), referred to as n − 1 biases.…”

mentioning

confidence: 99%

“…We tested this prediction for perceptual estimates of object speed used to plan hand movements to intercept a moving object (6,(14)(15)(16). Most previous studies of perceptual biases have used some form of perceptual report of the stimulus dimension of interest.…”

mentioning

confidence: 99%

The brain uses adaptive internal models of scene statistics for sensorimotor estimation and planning

Kwon

Knill

2013

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

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Because of uncertainty and noise, the brain should use accurate internal models of the statistics of objects in scenes to interpret sensory signals. Moreover, the brain should adapt its internal models to the statistics within local stimulus contexts. Consider the problem of hitting a baseball. The impoverished nature of the visual information available makes it imperative that batters use knowledge of the temporal statistics and history of previous pitches to accurately estimate pitch speed. Using a laboratory analog of hitting a baseball, we tested the hypothesis that the brain uses adaptive internal models of the statistics of object speeds to plan hand movements to intercept moving objects. We fit Bayesian observer models to subjects' performance to estimate the statistical environments in which subjects' performance would be ideal and compared the estimated statistics with the true statistics of stimuli in an experiment. A first experiment showed that subjects accurately estimated and used the variance of object speeds in a stimulus set to time hitting behavior but also showed serial biases that are suboptimal for stimuli that were uncorrelated over time. A second experiment showed that the strength of the serial biases depended on the temporal correlations within a stimulus set, even when the biases were estimated from uncorrelated stimulus pairs subsampled from the larger set. Taken together, the results show that subjects adapted their internal models of the variance and covariance of object speeds within a stimulus set to plan interceptive movements but retained a bias to positive correlations.Bayesian inference | motion perception | statistical learning | sequential effects

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Time course of visual extrapolation accuracy

Cited by 56 publications

References 14 publications

Cognitive motion extrapolation and cognitive clocking in prediction motion tasks.

Cognitive motion extrapolation and cognitive clocking in prediction motion tasks.

The common rate control account of prediction motion

The brain uses adaptive internal models of scene statistics for sensorimotor estimation and planning

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