ArticleFrontiers in behavioral neuroscience2022
Signal Detection Theory as a Novel Tool to Understand Cognitive Fatigue in Individuals With Multiple Sclerosis.
Article in Frontiers in behavioral neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Towards a domain-general mechanistic model of fatigue: application to Functional Neurological Disorder.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Review
- The critical role of the basal ganglia in post-stroke fatigue: A pilot study.Neuroimage. Reports · 2026Article
- The differential effect of chronological age and brain age on cognitive fatigue: new metrics, new insights.Journal of neurology · 2026Article
- Evaluating the effects of brain injury, disease and tasks on cognitive fatigue.Scientific reports · 2023Article
- Avoidance-motivational intensity modulated the effect of negative emotion on working memory.Royal Society open science · 2023Article
- Associations of White Matter and Basal Ganglia Microstructure to Cognitive Fatigue Rate in Multiple Sclerosis.Frontiers in neurology · 2022Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
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Abstract
Multiple Sclerosis (MS) affects 2.8 million persons worldwide. One of the most persistent, pervasive, and debilitating symptoms of MS is cognitive fatigue. While this has been known for over a century, cognitive fatigue has been difficult to study because patients' subjective (self-reported) cognitive fatigue has consistently failed to correlate with more objective measures, such as reaction time (RT) and accuracy. Here, we investigated whether more nuanced metrics of performance, specifically the metrics of Signal Detection Theory (SDT), would show a relationship to cognitive fatigue even if RT and accuracy did not. We also measured brain activation to see whether SDT metrics were related to activation in brain areas that have been shown to be sensitive to cognitive fatigue. Fifty participants (30 MS, 20 controls) took part in this study and cognitive fatigue was induced using four blocks of a demanding working memory paradigm. Participants reported their fatigue before and after each block, and their performance was used to calculate SDT metrics (Perceptual Certainty and Criterion) and RT and accuracy. The results showed that the SDT metric of Criterion (i.e., response bias) was positively correlated with subjective cognitive fatigue. Moreover, the activation in brain areas previously shown to be related to cognitive fatigue, such as the striatum, was also related to Criterion. These results suggest that the metrics of SDT may represent a novel tool with which to study cognitive fatigue in MS and other neurological populations. These results hold promise for characterizing cognitive fatigue in MS and developing effective interventions in the future.
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