Frontiers in Behavioral Neuroscience (Mar 2022)
Signal Detection Theory as a Novel Tool to Understand Cognitive Fatigue in Individuals With Multiple Sclerosis
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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