Brain Under Fatigue - Can Perceived Fatigability in Multiple Sclerosis Be Seen on the Level of Functional Brain Network Architecture?

Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural underpinnings of physical and mental fatigue in MS are still vague. The aim of our study was to investigate the functional architecture of resting-state...

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Published inFrontiers in human neuroscience Vol. 16; p. 852981
Main Authors Sobczak, Anna Maria, Bohaterewicz, Bartosz, Ceglarek, Anna, Zyrkowska, Aleksandra, Fafrowicz, Magdalena, Slowik, Agnieszka, Wnuk, Marcin, Marona, Monika, Nowak, Klaudia, Zur-Wyrozumska, Kamila, Marek, Tadeusz
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Research Foundation 10.05.2022
Frontiers Media S.A
Subjects
ALFF/fALFF
Brain architecture
Brain research
Fatigue
Frontal gyrus
functional network (FN)
Human Neuroscience
Immune system
Multiple sclerosis
multiple sclerosis (MS)
Neural networks
Neuroimaging
Pain perception
Questionnaires
resting-state fMRI (rs-fMRI)
Sensorimotor system
multiple sclerosis (MS)
functional network (FN)
ALFF/fALFF
fatigue
resting-state fMRI (rs-fMRI)
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Abstract Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural underpinnings of physical and mental fatigue in MS are still vague. The aim of our study was to investigate the functional architecture of resting-state networks associated with fatigue in patients with MS. The sum of 107 high-functioning patients underwent a resting-state scanning session and filled out the 9-item Fatigue Severity Scale (FSS). Based on the FSS score, we identified patients with different levels of fatigue using the cluster analysis. The low-fatigue group consisted of = 53 subjects, while the high-fatigue group = 48. The neuroimaging data were analyzed in terms of functional connectivity (FC) between various resting-state networks as well as amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuations (fALFF). Two-sample -test revealed between-group differences in FC of posterior salience network (SN). No differences occurred in default mode network (DMN) and sensorimotor network (SMN). Moreover, differences in fALFF were shown in the right middle frontal gyrus and right superior frontal gyrus, however, no ALFF differences took place. Current study revealed significant functional network (FN) architecture between-group differences associated with fatigue. Present results suggest the higher level of fatigue is related to deficits in awareness as well as higher interoceptive awareness and nociception.
AbstractList Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural underpinnings of physical and mental fatigue in MS are still vague. The aim of our study was to investigate the functional architecture of resting-state networks associated with fatigue in patients with MS. The sum of 107 high-functioning patients underwent a resting-state scanning session and filled out the 9-item Fatigue Severity Scale (FSS). Based on the FSS score, we identified patients with different levels of fatigue using the cluster analysis. The low-fatigue group consisted of = 53 subjects, while the high-fatigue group = 48. The neuroimaging data were analyzed in terms of functional connectivity (FC) between various resting-state networks as well as amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuations (fALFF). Two-sample -test revealed between-group differences in FC of posterior salience network (SN). No differences occurred in default mode network (DMN) and sensorimotor network (SMN). Moreover, differences in fALFF were shown in the right middle frontal gyrus and right superior frontal gyrus, however, no ALFF differences took place. Current study revealed significant functional network (FN) architecture between-group differences associated with fatigue. Present results suggest the higher level of fatigue is related to deficits in awareness as well as higher interoceptive awareness and nociception.
Background: Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural underpinnings of physical and mental fatigue in MS are still vague. The aim of our study was to investigate the functional architecture of resting-state networks associated with fatigue in patients with multiple sclerosis. Methods: The sum of 107 high-functioning patients underwent a resting-state scanning session and filled out the 9-item Fatigue Severity Scale. Based on the FSS score, we identified patients with different levels of fatigue using the cluster analysis. The low-fatigue group consisted of n=53 subjects, while the high-fatigue group n=48. The neuroimaging data were analyzed in terms of Functional Connectivity between various resting-state networks as well as Amplitude of Low-Frequency Fluctuation and Fractional ALFF. Results: Two-sample t-test revealed between-group differences in FC of posterior Salience Network. No differences occurred in Default Mode Network and Sensorimotor Network. Moreover, differences in fALFF were shown in the right middle frontal gyrus and right superior frontal gyrus, however, no ALFF differences took place. Conclusions: Current study revealed significant functional network architecture between-group differences associated with fatigue. Present results suggest the higher level of fatigue is related to deficits in awareness as well as higher interoceptive awareness and nociception.
BackgroundFatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural underpinnings of physical and mental fatigue in MS are still vague. The aim of our study was to investigate the functional architecture of resting-state networks associated with fatigue in patients with MS. MethodsThe sum of 107 high-functioning patients underwent a resting-state scanning session and filled out the 9-item Fatigue Severity Scale (FSS). Based on the FSS score, we identified patients with different levels of fatigue using the cluster analysis. The low-fatigue group consisted of n = 53 subjects, while the high-fatigue group n = 48. The neuroimaging data were analyzed in terms of functional connectivity (FC) between various resting-state networks as well as amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuations (fALFF). ResultsTwo-sample t-test revealed between-group differences in FC of posterior salience network (SN). No differences occurred in default mode network (DMN) and sensorimotor network (SMN). Moreover, differences in fALFF were shown in the right middle frontal gyrus and right superior frontal gyrus, however, no ALFF differences took place. ConclusionCurrent study revealed significant functional network (FN) architecture between-group differences associated with fatigue. Present results suggest the higher level of fatigue is related to deficits in awareness as well as higher interoceptive awareness and nociception.
Background Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural underpinnings of physical and mental fatigue in MS are still vague. The aim of our study was to investigate the functional architecture of resting-state networks associated with fatigue in patients with MS. Methods The sum of 107 high-functioning patients underwent a resting-state scanning session and filled out the 9-item Fatigue Severity Scale (FSS). Based on the FSS score, we identified patients with different levels of fatigue using the cluster analysis. The low-fatigue group consisted of n = 53 subjects, while the high-fatigue group n = 48. The neuroimaging data were analyzed in terms of functional connectivity (FC) between various resting-state networks as well as amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuations (fALFF). Results Two-sample t -test revealed between-group differences in FC of posterior salience network (SN). No differences occurred in default mode network (DMN) and sensorimotor network (SMN). Moreover, differences in fALFF were shown in the right middle frontal gyrus and right superior frontal gyrus, however, no ALFF differences took place. Conclusion Current study revealed significant functional network (FN) architecture between-group differences associated with fatigue. Present results suggest the higher level of fatigue is related to deficits in awareness as well as higher interoceptive awareness and nociception.
Author Wnuk, Marcin
Slowik, Agnieszka
Fafrowicz, Magdalena
Nowak, Klaudia
Marona, Monika
Zyrkowska, Aleksandra
Marek, Tadeusz
Ceglarek, Anna
Sobczak, Anna Maria
Zur-Wyrozumska, Kamila
Bohaterewicz, Bartosz
AuthorAffiliation 1 Department of Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Jagiellonian University , Kraków , Poland
2 Department of Psychology of Individual Differences, Psychological Diagnosis, and Psychometrics, Institute of Psychology, University of Social Sciences and Humanities , Warsaw , Poland
6 Department of Neurology, 5th Military Hospital , Kraków , Poland
4 Department of Neurology, University Hospital in Krakow , Kraków , Poland
5 Department of Medical Education, Jagiellonian University Medical College , Kraków , Poland
3 Department of Neurology, Jagiellonian University Collegium Medicum , Kraków , Poland
AuthorAffiliation_xml – name: 4 Department of Neurology, University Hospital in Krakow , Kraków , Poland
– name: 5 Department of Medical Education, Jagiellonian University Medical College , Kraków , Poland
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– name: 1 Department of Cognitive Neuroscience and Neuroergonomics, Institute of Applied Psychology, Jagiellonian University , Kraków , Poland
– name: 2 Department of Psychology of Individual Differences, Psychological Diagnosis, and Psychometrics, Institute of Psychology, University of Social Sciences and Humanities , Warsaw , Poland
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/35620154$$D View this record in MEDLINE/PubMed
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Copyright Copyright © 2022 Sobczak, Bohaterewicz, Ceglarek, Zyrkowska, Fafrowicz, Slowik, Wnuk, Marona, Nowak, Zur-Wyrozumska and Marek.
2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright © 2022 Sobczak, Bohaterewicz, Ceglarek, Zyrkowska, Fafrowicz, Slowik, Wnuk, Marona, Nowak, Zur-Wyrozumska and Marek. 2022 Sobczak, Bohaterewicz, Ceglarek, Zyrkowska, Fafrowicz, Slowik, Wnuk, Marona, Nowak, Zur-Wyrozumska and Marek
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Keywords multiple sclerosis (MS)
functional network (FN)
ALFF/fALFF
fatigue
resting-state fMRI (rs-fMRI)
Language English
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Edited by: Cornelia Laule, University of British Columbia, Canada
Reviewed by: Thorsten Rudroff, The University of Iowa, United States; Panagiotis G. Simos, University of Crete, Greece
This article was submitted to Brain Health and Clinical Neuroscience, a section of the journal Frontiers in Human Neuroscience
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Snippet Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural...
Background Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural...
Background: Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural...
BackgroundFatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural...
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SubjectTerms ALFF/fALFF
Brain architecture
Brain research
Fatigue
Frontal gyrus
functional network (FN)
Human Neuroscience
Immune system
Multiple sclerosis
multiple sclerosis (MS)
Neural networks
Neuroimaging
Pain perception
Questionnaires
resting-state fMRI (rs-fMRI)
Sensorimotor system
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Title Brain Under Fatigue - Can Perceived Fatigability in Multiple Sclerosis Be Seen on the Level of Functional Brain Network Architecture?
URI https://www.ncbi.nlm.nih.gov/pubmed/35620154
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https://search.proquest.com/docview/2691055853
https://pubmed.ncbi.nlm.nih.gov/PMC9128356
https://doaj.org/article/27d53e71e4ae4f739bc9a30c68ac7b59
Volume 16
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