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. 2021 Jan 15:11:579188.
doi: 10.3389/fpsyg.2020.579188. eCollection 2020.

Using Signal Detection Theory to Better Understand Cognitive Fatigue

Affiliations

Using Signal Detection Theory to Better Understand Cognitive Fatigue

Glenn R Wylie et al. Front Psychol. .

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.

Keywords: cognitive fatigue; fMRI; signal detection theory; striatum; working memory.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Bias (response criterion) as a function of cognitive fatigue (VAS-F). As cognitive fatigue increased, subjects increased their response criterion. For ease of interpretation, the “raw,” un-transformed VAS-F scores are shown in the plot. VAS-F, visual analog scale of fatigue.
FIGURE 2
FIGURE 2
Perceptual certainty (d’) as a function of cognitive fatigue (VAS-F). As cognitive fatigue increased, subjects’ perceptual certainty decreased. For ease of interpretation, the “raw,” un-transformed VAS-F scores are shown in the plot. VAS-F, visual analog scale of fatigue.
FIGURE 3
FIGURE 3
The main effect of fatigue (VAS-F) and criterion in the caudate nucleus of the basal ganglia. Because this was within our region of interest, the cluster level threshold was k ≥ 3 voxels. The location of the local maxima of activation is shown in the panels on the left. For the main effect of VAS-F, the location was −7, 9, 14 (X Y Z); for the main effect of criterion, the location was 14, 19, −2 (X Y Z). The panels on the right show the relationship between brain activation and VAS-F (top) and criterion (bottom). For ease of interpretation, the “raw,” un-transformed VAS-F scores are shown in the plot. VAS-F, visual analog scale of fatigue.
FIGURE 4
FIGURE 4
The interaction of task and fatigue (VAS-F) in the insula. The location of this interaction is shown by the green arrow (local maxima X Y Z: -34, 26, 6). Because this was not within our region of interest, the cluster level threshold was k ≥ 13 voxels. The pattern of the interaction was similar in the superior frontal/orbital gyrus (the location of which can be seen in the left panel). For ease of interpretation, the “raw,” un-transformed VAS-F scores are shown in the plot. VAS-F, visual analog scale of fatigue.
FIGURE 5
FIGURE 5
The task × criterion interaction (left column) and task × d’ interaction (right column) in the supplementary motor area (SMA) (top row local maxima; X Y Z: −7, 2, 62) and in the superior parietal lobule (bottom row local maxima; X Y Z: −20, 63, 50). In both rows, the location of the interaction is shown by the red arrow. Because this was not within our region of interest, the cluster level threshold was k ≥ 13 voxels.

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