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      A Bayesian Model of Perceived Head-Centered Velocity during Smooth Pursuit Eye Movement

      brief-report
      1 , , 1 , 2
      Current Biology
      Cell Press
      SYSNEURO

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          Summary

          During smooth pursuit eye movement, observers often misperceive velocity. Pursued stimuli appear slower (Aubert-Fleishl phenomenon [ 1, 2]), stationary objects appear to move (Filehne illusion [ 3]), the perceived direction of moving objects is distorted (trajectory misperception [ 4]), and self-motion veers away from its true path (e.g., the slalom illusion [ 5]). Each illusion demonstrates that eye speed is underestimated with respect to image speed, a finding that has been taken as evidence of early sensory signals that differ in accuracy [ 4, 6–11]. Here we present an alternative Bayesian account, based on the idea that perceptual estimates are increasingly influenced by prior expectations as signals become more uncertain [ 12–15]. We show that the speeds of pursued stimuli are more difficult to discriminate than fixated stimuli. Observers are therefore less certain about motion signals encoding the speed of pursued stimuli, a finding we use to quantify the Aubert-Fleischl phenomenon based on the assumption that the prior for motion is centered on zero [ 16–20]. In doing so, we reveal an important property currently overlooked by Bayesian models of motion perception. Two Bayes estimates are needed at a relatively early stage in processing, one for pursued targets and one for image motion.

          Highlights

          ► Pursuit-based velocity illusions can be explained by Bayesian inference ► Speed discrimination is worse when stimuli are pursued by eye ► Separate (and early) Bayes estimates are needed for pursued targets and image motion

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          Most cited references41

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          Noise characteristics and prior expectations in human visual speed perception.

          Human visual speed perception is qualitatively consistent with a Bayesian observer that optimally combines noisy measurements with a prior preference for lower speeds. Quantitative validation of this model, however, is difficult because the precise noise characteristics and prior expectations are unknown. Here, we present an augmented observer model that accounts for the variability of subjective responses in a speed discrimination task. This allowed us to infer the shape of the prior probability as well as the internal noise characteristics directly from psychophysical data. For all subjects, we found that the fitted model provides an accurate description of the data across a wide range of stimulus parameters. The inferred prior distribution shows significantly heavier tails than a Gaussian, and the amplitude of the internal noise is approximately proportional to stimulus speed and depends inversely on stimulus contrast. The framework is general and should prove applicable to other experiments and perceptual modalities.
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            Motion illusions as optimal percepts.

            The pattern of local image velocities on the retina encodes important environmental information. Although humans are generally able to extract this information, they can easily be deceived into seeing incorrect velocities. We show that these 'illusions' arise naturally in a system that attempts to estimate local image velocity. We formulated a model of visual motion perception using standard estimation theory, under the assumptions that (i) there is noise in the initial measurements and (ii) slower motions are more likely to occur than faster ones. We found that specific instantiation of such a velocity estimator can account for a wide variety of psychophysical phenomena.
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              Relations between the central Nervous System and the peripheral organs

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                Author and article information

                Journal
                Curr Biol
                Curr. Biol
                Current Biology
                Cell Press
                0960-9822
                1879-0445
                27 April 2010
                27 April 2010
                : 20
                : 8-6
                : 757-762
                Affiliations
                [1 ]School of Psychology, Cardiff University, Tower Building, Park Place, Cardiff CF10 3AT, UK
                [2 ]School of Psychological Sciences, University of Manchester, Zochonis Building, Brunswick Street, Manchester M13 9PL, UK
                Author notes
                []Corresponding author freemant@ 123456cardiff.ac.uk
                Article
                CURBIO7975
                10.1016/j.cub.2010.02.059
                2861164
                20399096
                add35a3e-8527-42f2-a4a8-ef2ca46e13a3
                © 2010 ELL & Excerpta Medica.

                This document may be redistributed and reused, subject to certain conditions.

                History
                : 9 October 2009
                : 18 February 2010
                : 18 February 2010
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                Life sciences
                sysneuro
                Life sciences
                sysneuro

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