Summary: The study reveals an association between signal detection theory, brain activation patterns, and subjective state fatigue. In people with multiple sclerosis, greater effects of stress are observed.
source: Kessler Foundation
Using signal-detection theory, Kessler Foundation researchers advance their understanding of the mechanisms of cognitive fatigue in a recent neuroimaging study that compared participants with multiple sclerosis and controls.
The researchers found an association between measures of signal-detection theory, subjective “state” fatigue, and brain activation patterns in both groups.
The MS group showed greater effects of fatigue as indicated by patterns of bias in their response.
These results have been reported in Frontiers in behavioral neuroscience. The authors are Christina Almeida Flores Roman, Ph.D., John DeLuca, Ph.D., Ping Yao, Ph.D., Helen M. Genova, Ph.D., and Glenn Wiley, D.
Because subjective feelings of cognitive fatigue fail to correlate with objective measures of performance, researchers sought to identify an objective behavioral measure that correlates with subjective experience of fatigue.
Previous research at the Kessler Foundation has shown that measures of signal detection (perceptual certainty and response bias) are associated with changes in cognitive fatigue as well as activation in the basal ganglia striatum — an area of the brain previously identified by Kessler researchers as sensitive to changes in cognitive fatigue.
They continued their investigation in this study of MS, which is often complicated by symptoms of fatigue, including cognitive fatigue.
The study was conducted at the Rocco Ortensio Center for Neuroimaging at the Kessler Foundation, which is dedicated solely to rehabilitation research.
The researchers used a demanding working memory model to induce cognitive fatigue in 50 participants, 30 of whom had MS and 20 controls.
All participants underwent structural and functional magnetic resonance imaging (fMRI) and assessed using the Visual Analog Fatigue Scale (VAS-F) at baseline and after each task block.
“We showed that response bias was associated with subjective state fatigue in MS,” said lead author Dr. Roman, a postdoctoral fellow in the National MS Society at the Kessler Foundation.
“This reinforces our previous finding of the same relationship in controls and provides additional support for the signal detection theory scale as an objective measure of cognitive fatigue.”
Cognitive fatigue is a feature of many neurodegenerative conditions, including MS, according to Dr. Wylie, director of the Ortenzio Center.
“By building on this promising avenue of research, we are laying the foundation for a new set of tools,” he explained, “which will help us develop effective interventions to treat this disabling condition in a wide range of individuals and mitigate its impact on their daily functioning, employment and quality of life.”
Financing: New Jersey Committee for Brain Injury Research (10.05.BIR1) and the National Multiple Sclerosis Society (RG 4232A1/1)
About this research on multiple sclerosis news
author: Carolan Murphy
source: Kessler Foundation
Contact: Carolan Murphy – The Kessler Foundation
picture: The image is in the public domain
original search: open access.
“Signal detection theory as a new tool for understanding cognitive fatigue in individuals with multiple sclerosis” by Glenn Wiley et al. Frontiers in behavioral neuroscience
Signal detection theory as a new tool for understanding cognitive fatigue in individuals with multiple sclerosis
Multiple sclerosis (MS) affects 2.8 million people worldwide. Cognitive exhaustion is one of the most persistent, widespread, and debilitating symptoms of multiple sclerosis.
While this has been known for over a century, cognitive fatigue has been difficult to study because patients’ subjective (self-reported) cognitive fatigue consistently fails to correlate with more objective measures, such as reaction time (RT) and accuracy.
Here, we investigated whether more accurate measures of performance, specifically measures of Signal Detection Theory (SDT), would show a relationship with cognitive fatigue even if there was no relationship with RT and accuracy. We also measured brain activation to see if measures of SDT are related to activation in brain regions 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 the demanding working memory model. Participants reported their stress before and after each block, and their performance was used to calculate measures of SDT (perceptual certainty and norm), RT and accuracy.
The results showed that the SDT scale of the criterion (ie, response bias) was positively associated with subjective cognitive burnout. Furthermore, activation in brain regions previously shown to be associated with cognitive fatigue, such as the striatum, was also associated with criterion.
These results suggest that SDT measures may represent a new tool for studying cognitive fatigue in MS and other neurodegenerative groups.
These results hold promise for characterizing cognitive fatigue in MS and developing effective interventions in the future.