Multiple sclerosis and related disorders · 2019
Capturing fatigue parameters: The impact of vagal processing in multiple sclerosis related cognitive fatigue.
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Sander Carina, Modes Fenja, Schlake Hans-Peter, Eling Paul, Hildebrandt Helmut
Аннотация
BACKGROUND: Causes of fatigue in Multiple Sclerosis remain elusive. Recently, we developed a model linking cognitive fatigue to inflammatory processes based on a neuroinflammatory reflex-arc instantiated by the vagus nerve. The relation between experienced autonomic dysfunctions, based on vagal processing, and cognitive fatigue is well-known, but an examination of the association of objectively measured vagal activity and cognitive fatigue is missing. An attempt was made to collect behavioral and physiological evidence that can be associated with experienced autonomic dysfunctions and fatigue in Multiple Sclerosis patients.
METHODS: Behavioral performance (response bias) and autonomic functioning (Heart rate variability and Skin conductance level) during an acoustic vigilance task were investigated in 53 Multiple Sclerosis patients. We assessed trait fatigue (independent from task), and time-on-task related increase of fatigue. Regression analysis was used to predict the fatigue status with physiological and behavioral scores.
RESULTS: Response bias, indicating a reduced responsiveness, and high and very low frequency components of Heart rate variability, indicating an increased parasympathetic activity, contribute to the regression of trait fatigue. Reduced Heart rate variability (SDNN) and increased parasympathetic activity (pNN50) remained in the regression model predicting time-on-task fatigue.
CONCLUSION: Cognitive fatigue in MS is related to parasympathetic activity and reduced responsiveness, supporting our model representing fatigue as inflammatory processes in the brain. Standardized subjective and objective autonomous dysfunction measures might be considered as additional assessments in MS.
METHODS: Behavioral performance (response bias) and autonomic functioning (Heart rate variability and Skin conductance level) during an acoustic vigilance task were investigated in 53 Multiple Sclerosis patients. We assessed trait fatigue (independent from task), and time-on-task related increase of fatigue. Regression analysis was used to predict the fatigue status with physiological and behavioral scores.
RESULTS: Response bias, indicating a reduced responsiveness, and high and very low frequency components of Heart rate variability, indicating an increased parasympathetic activity, contribute to the regression of trait fatigue. Reduced Heart rate variability (SDNN) and increased parasympathetic activity (pNN50) remained in the regression model predicting time-on-task fatigue.
CONCLUSION: Cognitive fatigue in MS is related to parasympathetic activity and reduced responsiveness, supporting our model representing fatigue as inflammatory processes in the brain. Standardized subjective and objective autonomous dysfunction measures might be considered as additional assessments in MS.