Influence of Motor and Cognitive Tasks on Time Estimation.

clock speed cognitive load cognitive–motor interaction duration estimation time perception walking

Journal

Brain sciences
ISSN: 2076-3425
Titre abrégé: Brain Sci
Pays: Switzerland
ID NLM: 101598646

Informations de publication

Date de publication:
18 Mar 2022
Historique:
received: 12 01 2022
revised: 18 02 2022
accepted: 17 03 2022
entrez: 25 3 2022
pubmed: 26 3 2022
medline: 26 3 2022
Statut: epublish

Résumé

The passing of time can be precisely measured by using clocks, whereas humans' estimation of temporal durations is influenced by many physical, cognitive and contextual factors, which distort our internal clock. Although it has been shown that temporal estimation accuracy is impaired by non-temporal tasks performed at the same time, no studies have investigated how concurrent cognitive and motor tasks interfere with time estimation. Moreover, most experiments only tested time intervals of a few seconds. In the present study, participants were asked to perform cognitive tasks of different difficulties (look, read, solve simple and hard mathematical operations) and estimate durations of up to two minutes, while walking or sitting. The results show that if observers pay attention only to time without performing any other mental task, they tend to overestimate the durations. Meanwhile, the more difficult the concurrent task, the more they tend to underestimate the time. These distortions are even more pronounced when observers are walking. Estimation biases and uncertainties change differently with durations depending on the task, consistent with a fixed relative uncertainty. Our findings show that cognitive and motor systems interact non-linearly and interfere with time perception processes, suggesting that they all compete for the same resources.

Identifiants

pubmed: 35326362
pii: brainsci12030404
doi: 10.3390/brainsci12030404
pmc: PMC8946194
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : European Union's Horizon 2020 research and innovation program
ID : 832813

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Auteurs

Serena Castellotti (S)

Department of Neurofarba, University of Florence, 1035 Florence, Italy.

Ottavia D'Agostino (O)

Department of Neurofarba, University of Florence, 1035 Florence, Italy.

Alessandra Biondi (A)

Department of Neurofarba, University of Florence, 1035 Florence, Italy.

Luigi Pignatiello (L)

Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy.

Maria Michela Del Viva (MM)

Department of Neurofarba, University of Florence, 1035 Florence, Italy.

Classifications MeSH