Abstract: The study reveals an association between signal detection theory, brain activation patterns, and subjective fatigue. In those with multiple sclerosis, greater effects of fatigue were observed.
Source: Kessler Foundation
Using signal detection theory, Kessler Foundation researchers improved their understanding of the mechanisms of cognitive fatigue in a recent neuroimaging study comparing participants with multiple sclerosis (MS) and controls.
The researchers found an association between signal detection theory metrics, subjective “state” fatigue, and brain activation patterns in both groups.
The MS group showed greater effects of fatigue as evidenced by their response bias patterns.
These findings were reported in Frontiers in Behavioral Neuroscience. The authors are Cristina Almeida Flores Román, PhD, John DeLuca, PhD, Bing Yao, PhD, Helen M. Genova, PhD and Glenn Wylie, DPhil, of the Kessler Foundation.
Because subjective feelings of cognitive fatigue do not correlate with objective measures of performance, researchers have attempted to identify an objective measure of behavior that would incubate with the subjective experience of fatigue.
Preliminary research at the Kessler Foundation showed that signal detection metrics (perceptual certainty and response bias) correlated with changes in cognitive fatigue as well as activation in the striatum of the basal ganglia, an area of the brain. which Kessler researchers had previously identified as sensitive to change. in cognitive fatigue.
They continued their research in this study of MS, which is often complicated by symptoms of fatigue, including cognitive fatigue.
The study was conducted at the Rocco Ortenzio Neuroimaging Center of the Kessler Foundation, which is dedicated exclusively to research in rehabilitation.
The researchers used a demanding working memory paradigm to induce cognitive fatigue in 50 participants, 30 with MS, and 20 controls.
All participants underwent a structural and functional MRI (fMRI) and were assessed using the visual analog fatigue scale (VAS-F) at baseline and after each block of tasks.
Because subjective feelings of cognitive fatigue do not correlate with objective measures of performance, researchers have attempted to identify an objective measure of behavior that would incubate with the subjective experience of fatigue. The image is in the public domain
“We have shown that the response bias was related to fatigue of the subjective state of MS,” said lead author Dr. Román, postdoctoral fellow of the National MS Society at the Kessler Foundation.
“This reinforces our previous finding of the same relationship in controls and provides additional support for this metric of signal detection theory 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.
“Based on this promising line of research, we are laying the groundwork for a new set of tools,” he explained, “that will help us develop effective interventions to address this disabling condition in a wide range of individuals and to improve its impact on their daily functioning, employment and quality of life ”.
Funding: New Jersey Commission on Brain Injury Research (10.005.BIR1) and the National Multiple Sclerosis Society (RG 4232A1 / 1)
About this research news on multiple sclerosis
Author: Carolann MurphySource: Kessler FoundationContact: Carolann Murphy – Kessler FoundationImage: Image is in the public domain
Original search: open access. “The theory of signal detection as a new tool for understanding cognitive fatigue in people with multiple sclerosis” by Glenn Wylie et al. Frontiers in behavioral neuroscience
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Summary
Signal detection theory as a new tool to understand cognitive fatigue in individuals with multiple sclerosis
Multiple sclerosis (MS) affects 2.8 million people worldwide. One of the most persistent, widespread, and debilitating symptoms of MS is cognitive fatigue.
Although this has been known for more than a century, cognitive fatigue has been difficult to study because patients’ subjective (self-reported) cognitive fatigue has not been consistently correlated with more objective measures, such as reaction (RT) and accuracy.
Here, we investigated whether more nuanced performance metrics, specifically signal detection theory (SDT) metrics, would show a relationship to cognitive fatigue, even if RT and accuracy did not. We also measured brain activation to see if 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) participated 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 (perceptual certainty and judgment) and RT metrics and accuracy.
The results showed that Criterion’s SDT metric (i.e., response bias) was positively correlated with subjective cognitive fatigue. In addition, activation in brain areas previously shown to be related to cognitive fatigue, such as striatum, was also related to Criterion.
These results suggest that SDT metrics may represent a new tool with which to study cognitive fatigue in MS and other neurological populations.
These results are promising for characterizing cognitive fatigue in MS and developing effective interventions in the future.