Cargando…
Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For?
Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810256/ https://www.ncbi.nlm.nih.gov/pubmed/36618326 http://dx.doi.org/10.1007/s42113-022-00162-1 |
_version_ | 1784863274458677248 |
---|---|
author | Perquin, Marlou Nadine van Vugt, Marieke K. Hedge, Craig Bompas, Aline |
author_facet | Perquin, Marlou Nadine van Vugt, Marieke K. Hedge, Craig Bompas, Aline |
author_sort | Perquin, Marlou Nadine |
collection | PubMed |
description | Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here, we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures — to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: (1) task performance assessed from the same data, (2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and (3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (d) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42113-022-00162-1. |
format | Online Article Text |
id | pubmed-9810256 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-98102562023-01-04 Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? Perquin, Marlou Nadine van Vugt, Marieke K. Hedge, Craig Bompas, Aline Comput Brain Behav Original Paper Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here, we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures — to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: (1) task performance assessed from the same data, (2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and (3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (d) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42113-022-00162-1. Springer International Publishing 2023-01-03 /pmc/articles/PMC9810256/ /pubmed/36618326 http://dx.doi.org/10.1007/s42113-022-00162-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Perquin, Marlou Nadine van Vugt, Marieke K. Hedge, Craig Bompas, Aline Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? |
title | Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? |
title_full | Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? |
title_fullStr | Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? |
title_full_unstemmed | Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? |
title_short | Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For? |
title_sort | temporal structure in sensorimotor variability: a stable trait, but what for? |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810256/ https://www.ncbi.nlm.nih.gov/pubmed/36618326 http://dx.doi.org/10.1007/s42113-022-00162-1 |
work_keys_str_mv | AT perquinmarlounadine temporalstructureinsensorimotorvariabilityastabletraitbutwhatfor AT vanvugtmariekek temporalstructureinsensorimotorvariabilityastabletraitbutwhatfor AT hedgecraig temporalstructureinsensorimotorvariabilityastabletraitbutwhatfor AT bompasaline temporalstructureinsensorimotorvariabilityastabletraitbutwhatfor |