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

Anna Maria Sobczak; Bartosz Bohaterewicz; Anna Ceglarek; Aleksandra Zyrkowska; Magdalena Fafrowicz; Agnieszka Slowik; Marcin Wnuk; Monika Marona; Klaudia Nowak; Kamila Zur-Wyrozumska; Tadeusz Marek

doi:10.3389/fnhum.2022.852981

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

Front Hum Neurosci. 2022 May 10:16:852981. doi: 10.3389/fnhum.2022.852981. eCollection 2022.

Authors

Anna Maria Sobczak¹, Bartosz Bohaterewicz^{1

2}, Anna Ceglarek¹, Aleksandra Zyrkowska¹, Magdalena Fafrowicz¹, Agnieszka Slowik^{3

4}, Marcin Wnuk^{3

4}, Monika Marona^{3

4}, Klaudia Nowak^{3

4}, Kamila Zur-Wyrozumska^{5

6}, Tadeusz Marek¹

Affiliations

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.
³ Department of Neurology, Jagiellonian University Collegium Medicum, Kraków, Poland.
⁴ Department of Neurology, University Hospital in Krakow, Kraków, Poland.
⁵ Department of Medical Education, Jagiellonian University Medical College, Kraków, Poland.
⁶ Department of Neurology, 5th Military Hospital, Kraków, Poland.

Abstract

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.

Keywords: ALFF/fALFF; fatigue; functional network (FN); multiple sclerosis (MS); resting-state fMRI (rs-fMRI).