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Using Signal Detection Theory to Better Understand Cognitive Fatigue
When we are fatigued, we feel that our performance is worse than when we are fresh. Yet, for over 100 years, researchers have been unable to identify an objective, behavioral measure that covaries with the subjective experience of fatigue. Previous work suggests that the metrics of signal detection...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7844088/ https://www.ncbi.nlm.nih.gov/pubmed/33519595 http://dx.doi.org/10.3389/fpsyg.2020.579188 |
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author | Wylie, Glenn R. Yao, Bing Sandry, Joshua DeLuca, John |
author_facet | Wylie, Glenn R. Yao, Bing Sandry, Joshua DeLuca, John |
author_sort | Wylie, Glenn R. |
collection | PubMed |
description | When we are fatigued, we feel that our performance is worse than when we are fresh. Yet, for over 100 years, researchers have been unable to identify an objective, behavioral measure that covaries with the subjective experience of fatigue. Previous work suggests that the metrics of signal detection theory (SDT)—response bias (criterion) and perceptual certainty (d’)—may change as a function of fatigue, but no work has yet been done to examine whether these metrics covary with fatigue. Here, we investigated cognitive fatigue using SDT. We induced fatigue through repetitive performance of the n-back working memory task, while functional magnetic resonance imaging (fMRI) data was acquired. We also assessed cognitive fatigue at intervals throughout. This enabled us to assess not only whether criterion and d’ covary with cognitive fatigue but also whether similar patterns of brain activation underlie cognitive fatigue and SDT measures. Our results show that both criterion and d’ were correlated with changes in cognitive fatigue: as fatigue increased, subjects became more conservative in their response bias and their perceptual certainty declined. Furthermore, activation in the striatum of the basal ganglia was also related to cognitive fatigue, criterion, and d’. These results suggest that SDT measures represent an objective measure of cognitive fatigue. Additionally, the overlap and difference in the fMRI results between cognitive fatigue and SDT measures indicate that these measures are related while also separate. In sum, we show the relevance of SDT measures in the understanding of fatigue, thus providing researchers with a new set of tools with which to better understand the nature and consequences of cognitive fatigue. |
format | Online Article Text |
id | pubmed-7844088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78440882021-01-30 Using Signal Detection Theory to Better Understand Cognitive Fatigue Wylie, Glenn R. Yao, Bing Sandry, Joshua DeLuca, John Front Psychol Psychology When we are fatigued, we feel that our performance is worse than when we are fresh. Yet, for over 100 years, researchers have been unable to identify an objective, behavioral measure that covaries with the subjective experience of fatigue. Previous work suggests that the metrics of signal detection theory (SDT)—response bias (criterion) and perceptual certainty (d’)—may change as a function of fatigue, but no work has yet been done to examine whether these metrics covary with fatigue. Here, we investigated cognitive fatigue using SDT. We induced fatigue through repetitive performance of the n-back working memory task, while functional magnetic resonance imaging (fMRI) data was acquired. We also assessed cognitive fatigue at intervals throughout. This enabled us to assess not only whether criterion and d’ covary with cognitive fatigue but also whether similar patterns of brain activation underlie cognitive fatigue and SDT measures. Our results show that both criterion and d’ were correlated with changes in cognitive fatigue: as fatigue increased, subjects became more conservative in their response bias and their perceptual certainty declined. Furthermore, activation in the striatum of the basal ganglia was also related to cognitive fatigue, criterion, and d’. These results suggest that SDT measures represent an objective measure of cognitive fatigue. Additionally, the overlap and difference in the fMRI results between cognitive fatigue and SDT measures indicate that these measures are related while also separate. In sum, we show the relevance of SDT measures in the understanding of fatigue, thus providing researchers with a new set of tools with which to better understand the nature and consequences of cognitive fatigue. Frontiers Media S.A. 2021-01-15 /pmc/articles/PMC7844088/ /pubmed/33519595 http://dx.doi.org/10.3389/fpsyg.2020.579188 Text en Copyright © 2021 Wylie, Yao, Sandry and DeLuca. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Wylie, Glenn R. Yao, Bing Sandry, Joshua DeLuca, John Using Signal Detection Theory to Better Understand Cognitive Fatigue |
title | Using Signal Detection Theory to Better Understand Cognitive Fatigue |
title_full | Using Signal Detection Theory to Better Understand Cognitive Fatigue |
title_fullStr | Using Signal Detection Theory to Better Understand Cognitive Fatigue |
title_full_unstemmed | Using Signal Detection Theory to Better Understand Cognitive Fatigue |
title_short | Using Signal Detection Theory to Better Understand Cognitive Fatigue |
title_sort | using signal detection theory to better understand cognitive fatigue |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7844088/ https://www.ncbi.nlm.nih.gov/pubmed/33519595 http://dx.doi.org/10.3389/fpsyg.2020.579188 |
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