Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time

Sensory stimulation can systematically bias the perceived passage of time [1–5], but why and how this happens is mysterious. In this report, we provide evidence that such biases may ultimately derive from an innate and adaptive use of stochastically evolving dynamic stimuli to help refine estimates...

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Main Authors: Ahrens, Misha B., Sahani, Maneesh
Format: Online
Language:English
Published: Cell Press 2011
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3094759/
id pubmed-3094759
recordtype oai_dc
spelling pubmed-30947592011-07-12 Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time Ahrens, Misha B. Sahani, Maneesh Report Sensory stimulation can systematically bias the perceived passage of time [1–5], but why and how this happens is mysterious. In this report, we provide evidence that such biases may ultimately derive from an innate and adaptive use of stochastically evolving dynamic stimuli to help refine estimates derived from internal timekeeping mechanisms [6–15]. A simplified statistical model based on probabilistic expectations of stimulus change derived from the second-order temporal statistics of the natural environment [16, 17] makes three predictions. First, random noise-like stimuli whose statistics violate natural expectations should induce timing bias. Second, a previously unexplored obverse of this effect is that similar noise stimuli with natural statistics should reduce the variability of timing estimates. Finally, this reduction in variability should scale with the interval being timed, so as to preserve the overall Weber law of interval timing. All three predictions are borne out experimentally. Thus, in the context of our novel theoretical framework, these results suggest that observers routinely rely on sensory input to augment their sense of the passage of time, through a process of Bayesian inference based on expectations of change in the natural environment. Cell Press 2011-02-08 /pmc/articles/PMC3094759/ /pubmed/21256018 http://dx.doi.org/10.1016/j.cub.2010.12.043 Text en © 2011 ELL & Excerpta Medica. https://creativecommons.org/licenses/by/3.0/ Open Access under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/) license
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Ahrens, Misha B.
Sahani, Maneesh
spellingShingle Ahrens, Misha B.
Sahani, Maneesh
Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time
author_facet Ahrens, Misha B.
Sahani, Maneesh
author_sort Ahrens, Misha B.
title Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time
title_short Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time
title_full Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time
title_fullStr Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time
title_full_unstemmed Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time
title_sort observers exploit stochastic models of sensory change to help judge the passage of time
description Sensory stimulation can systematically bias the perceived passage of time [1–5], but why and how this happens is mysterious. In this report, we provide evidence that such biases may ultimately derive from an innate and adaptive use of stochastically evolving dynamic stimuli to help refine estimates derived from internal timekeeping mechanisms [6–15]. A simplified statistical model based on probabilistic expectations of stimulus change derived from the second-order temporal statistics of the natural environment [16, 17] makes three predictions. First, random noise-like stimuli whose statistics violate natural expectations should induce timing bias. Second, a previously unexplored obverse of this effect is that similar noise stimuli with natural statistics should reduce the variability of timing estimates. Finally, this reduction in variability should scale with the interval being timed, so as to preserve the overall Weber law of interval timing. All three predictions are borne out experimentally. Thus, in the context of our novel theoretical framework, these results suggest that observers routinely rely on sensory input to augment their sense of the passage of time, through a process of Bayesian inference based on expectations of change in the natural environment.
publisher Cell Press
publishDate 2011
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3094759/
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