Using Signal Detection Theory to Better Understand Cognitive Fatigue.

Glenn R Wylie,Joshua Sandry,Bing Yao,John Deluca

doi:10.3389/fpsyg.2020.579188

Abstract

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.

Highlights

Fatigue resulting from cognitive work is a common experience, caused by tasks that require care and skill such as air traffic control (Orasanu et al, 2012; Kuo et al, 2017) or driving (Matthews and Desmond, 2002)
Fatigue has been linked to decrements in perceptual sensitivity [i.e., a reduced ability to distinguish stimuli requiring a response from stimuli that do not require a response]—or d’, a measure derived from signal detection theory (SDT) (Green and Swets, 1966; Lynn and Barrett, 2014)—in the human factors literature (Matthews and Desmond, 2002), which may be linked to well-documented decrements in d’ associated with vigilance tasks (See et al, 1995)
The volumetric data was correlated with the average of the fatigue and SDT measures, which were averaged across task and run

Summary

Introduction

Fatigue resulting from cognitive work (cognitive fatigue) is a common experience, caused by tasks that require care and skill such as air traffic control (Orasanu et al, 2012; Kuo et al, 2017) or driving (Matthews and Desmond, 2002). We feel that performance should decline as cognitive fatigue increases, yet a large body of research shows that this is not the case Fatigue has been linked to decrements in perceptual sensitivity [i.e., a reduced ability to distinguish stimuli requiring a response (targets) from stimuli that do not require a response (non-targets)]—or d’, a measure derived from signal detection theory (SDT) (Green and Swets, 1966; Lynn and Barrett, 2014)—in the human factors literature (Matthews and Desmond, 2002), which may be linked to well-documented decrements in d’ associated with vigilance tasks (See et al, 1995). While simple RT and accuracy correlate poorly with fatigue, the tools of SDT (and perceptual sensitivity in particular) may provide better objective indices of fatigue. Showing a correlation of this sort between d’ and fatigue would provide researchers with a powerful tool to better understand fatigue

Methods

Results

Discussion

Conclusion