September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Time compression, but not dilation, in slowly moving stimuli
Author Affiliations
  • Saya Kashiwakura
    Department of Integrated Sciences, The University of Tokyo
  • Isamu Motoyoshi
    Department of Life Sciences, The University of Tokyo
Journal of Vision August 2017, Vol.17, 187. doi:10.1167/17.10.187
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      Saya Kashiwakura, Isamu Motoyoshi; Time compression, but not dilation, in slowly moving stimuli. Journal of Vision 2017;17(10):187. doi: 10.1167/17.10.187.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

A number of psychophysical studies have shown that a moving visual stimulus is perceived to last longer than a stationary stimulus. In contrast, here we report a case in which the perceived duration of a moving stimulus is shorter than that of a stationary stimulus. In our procedure, observers viewed a natural movie (i.e., a running horse) that was presented at a particular speed (0.0, 0.25, or 1.9 relative to the original speed) for a particular duration (0.5, 1.1, or 1.6 sec), and indicated whether its duration appeared longer or shorter than that of the comparison movie presented at the original speed. We found that the duration of the movie with a slow speed (i.e., 0.25 speed) was perceived to be shorter than that of a static image (i.e., 0.0 speed), especially when the physical duration of the stimulus was longer than 1.1 sec. The perceived duration of a fast movie was longer than that of a static image as consistent with previous studies. Similar patterns of the results were obtained when we employed artificial stimuli such as drifting gratings, and when we measured the perceived duration by manual reproduction. These results are inconsistent with the fundamental assumption of time perception that the subjective experience of time passage depends on the number of changes or events. We discuss potential factors that may account for this paradoxical effect.

Meeting abstract presented at VSS 2017

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