Larger visual changes compress time: The inverted effect of asemantic visual features on interval time perception.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2022
Historique:
received: 16 02 2021
accepted: 04 03 2022
entrez: 22 3 2022
pubmed: 23 3 2022
medline: 6 5 2022
Statut: epublish

Résumé

Time perception is fluid and affected by manipulations to visual inputs. Previous literature shows that changes to low-level visual properties alter time judgments at the millisecond-level. At longer intervals, in the span of seconds and minutes, high-level cognitive effects (e.g., emotions, memories) elicited by visual inputs affect time perception, but these effects are confounded with semantic information in these inputs, and are therefore challenging to measure and control. In this work, we investigate the effect of asemantic visual properties (pure visual features devoid of emotional or semantic value) on interval time perception. Our experiments were conducted with binary and production tasks in both conventional and head-mounted displays, testing the effects of four different visual features (spatial luminance contrast, temporal frequency, field of view, and visual complexity). Our results reveal a consistent pattern: larger visual changes all shorten perceived time in intervals of up to 3min, remarkably contrary to their effect on millisecond-level perception. Our findings may help alter participants' time perception, which can have broad real-world implications.

Identifiants

pubmed: 35316292
doi: 10.1371/journal.pone.0265591
pii: PONE-D-21-05078
pmc: PMC8939824
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0265591

Déclaration de conflit d'intérêts

Some of the authors (LH, ZB, QS) of this manuscript were employed by Adobe, Inc. or Adobe Research during this project. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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Auteurs

Sandra Malpica (S)

Universidad de Zaragoza, Zaragoza, Spain.

Belen Masia (B)

Universidad de Zaragoza, Zaragoza, Spain.

Laura Herman (L)

Adobe, Inc., Mountain View, CA, United States of America.

Gordon Wetzstein (G)

Department of Electrical Engineering, Stanford University, Stanford, CA, United States of America.

David M Eagleman (DM)

Department of Psychiatry, Stanford University School of Medicine, Stanford, CA, United States of America.

Diego Gutierrez (D)

Universidad de Zaragoza, Zaragoza, Spain.

Zoya Bylinskii (Z)

Adobe, Inc., Mountain View, CA, United States of America.

Qi Sun (Q)

Adobe, Inc., Mountain View, CA, United States of America.
New York University, New York, NY, United States of America.

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Classifications MeSH