Temporal complexity measure of reaction time series: Operational versus event time.
detrended fluctuation analysis
reaction time series
temporal complexity
time-stress
Journal
Brain and behavior
ISSN: 2162-3279
Titre abrégé: Brain Behav
Pays: United States
ID NLM: 101570837
Informations de publication
Date de publication:
07 2023
07 2023
Historique:
revised:
30
04
2023
received:
22
11
2022
accepted:
03
05
2023
medline:
14
7
2023
pubmed:
24
5
2023
entrez:
24
5
2023
Statut:
ppublish
Résumé
Detrended fluctuation analysis (DFA) is a well-established method to evaluate scaling indices of time series, which categorize the dynamics of complex systems. In the literature, DFA has been used to study the fluctuations of reaction time Y(n) time series, where n is the trial number. Herein we propose treating each reaction time as a duration time that changes the representation from operational (trial number) time n to event (temporal) time t, or X(t). The DFA algorithm was then applied to the X(t) time series to evaluate scaling indices. The dataset analyzed is based on a Go-NoGo shooting task that was performed by 30 participants under low and high time-stress conditions in each of six repeated sessions over a 3-week period. This new perspective leads to quantitatively better results in (1) differentiating scaling indices between low versus high time-stress conditions and (2) predicting task performance outcomes. We show that by changing from operational time to event time, the DFA allows discrimination of time-stress conditions and predicts performance outcomes.
Identifiants
pubmed: 37221980
doi: 10.1002/brb3.3069
pmc: PMC10338792
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
e3069Informations de copyright
© 2023 The Authors. Brain and Behavior published by Wiley Periodicals LLC.
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