Poststroke fatigue is a debilitating symptom and is poorly understood. Here we summarise molecular, behavioural and neurophysiological changes related to poststroke fatigue and put forward potential theories for mechanistic understanding of poststroke fatigue.

Background Fatigue is one of the most commonly reported symptoms post-stroke, which has a severe impact on the quality of life. Post-stroke fatigue is associated with reduced motor cortical excitability, specifically of the affected hemisphere. Objective The aim of this exploratory study was to assess whether fatigue symptoms can be reduced by increasing cortical excitability using anodal transcranial direct current stimulation (tDCS). Methods In this sham-controlled, double-blind intervention study, tDCS was applied bilaterally over the primary motor cortex in a single session in thirty stroke survivors with high severity of fatigue. A questionnaire-based measure of trait fatigue (primary outcome) was obtained before, after a week and 5 weeks post stimulation. Secondary outcome measures of state fatigue, motor cortex neurophysiology and perceived effort were also assessed pre, immediately post, a week and 5 weeks post stimulation. Results Anodal tDCS significantly improved fatigue symptoms a week after real stimulation when compared to sham stimulation. There was also a significant change in motor cortex neurophysiology of the affected hemisphere and perceived effort, a week after stimulation. The degree of improvement in fatigue was associated with baseline anxiety levels. Conclusion A single session of anodal tDCS improves fatigue symptoms with the effect lasting up to a week post stimulation. tDCS may therefore be a useful tool for managing fatigue symptoms post-stroke. Trial registration NCT04634864 Date of registration 17/11/2020–“retrospectively registered”.

Persistent fatigue is a major debilitating symptom in many psychiatric and neurological conditions, including stroke. Post-stroke fatigue has been linked to low corticomotor excitability. Yet, it remains elusive what the neuronal mechanisms are that underlie motor cortex excitability and chronic persistence of fatigue. In this cross-sectional observational study, in two experiments we examined a total of 59 non-depressed stroke survivors with minimal motoric and cognitive impairments using ‘resting state’ magnetic resonance imaging (rs-fMRI), single-pulse and paired-pulse transcranial magnetic stimulation (pp-TMS). In the first session of Experiment 1, we assessed resting motor thresholds (RMTs) - a typical measure of cortical excitability—by applying TMS to the primary motor cortex (M1) and measuring motor-evoked potential in the hand affected by stroke. In the second session, we measured their brain activity with rs-fMRI to assess effective connectivity interactions at rest. In Experiment 2 we examined effective inter-hemispheric connectivity in an independent sample of patients using pp-TMS. We also assessed the levels of non-exercise induced, persistent fatigue using Fatigue Severity Scale (FSS-7), a self-report questionnaire which has been widely applied and validated across different conditions. We employed spectral dynamic causal modelling (sp-DCM) in Experiment 1 and pp-TMS in Experiment 2 to characterise how neuronal effective connectivity relates to self-reported post-stroke fatigue. In a multiple regression we used the balance in inhibitory connectivity between homologue regions in M1 as the main predictor, and have included lesioned hemisphere, RMT and levels of depression as additional predictors. Our novel index of inter-hemispheric inhibition balance was a significant predictor of post-stroke fatigue in Experiment 1 (β  =  1.524, p = 7.56e−05, CI[0.921, 2.127]) and in Experiment 2 (β  =  0.541, p = 0.049, CI[0.002, 1.080]). In experiment 2, depression scores and corticospinal excitability, a measure associated with subjective fatigue, also significantly accounted for variability in fatigue. We suggest that the balance in inter-hemispheric inhibitory effects between primary motor regions can explain subjective post-stroke fatigue. Findings provide novel insights into neural mechanisms that underlie persistent fatigue.

ObjectiveTo test the hypothesis—post-stroke fatigue, a chronic, pathologic fatigue condition, is driven by altered effort perception.ParticipantsFifty-eight non-depressed, mildly impaired stroke survivors with varying severity of fatigue completed the study.Main outcome measuresSelf-reported fatigue (trait and state), perceived effort—PE (explicit and implicit) and motor performance was measured in a handgrip task. Trait fatigue was measured using Fatigue Severity Scale-7 and Neurologic Fatigue Index. State fatigue was measured using a visual analogue scale (VAS). Length of hold at target force, overshoot above target force and force variability in handgrip task were measures of motor performance. PE was measured using a VAS (explicit PE) and line length estimation, a novel implicit measure of PE.ResultsRegression analysis showed 11.6% of variance in trait fatigue was explained by implicit PE (R = 0.34; p = 0.012). Greater fatigue related to longer length of hold at target force (R = 0.421; p < 0.001). A backward regression showed length of hold explained explicit PE in the 20% force condition (R = 0.306; p = 0.021) and length of hold and overshoot above target force, explained explicit PE in the 40% (R = 0.399; p = 0.014 & 0.004) force condition. In the 60% force condition, greater explicit PE was explained by higher force variability (R = 0.315; p = 0.017). None of the correlations were significant for state fatigue.ConclusionTrait fatigue, but not state fatigue, correlating with measures of perceived effort and motor performance may suggest that altered perception may lead to high fatigue mediated by changes in motor performance. This novel finding furthers our mechanistic understanding of post-stroke fatigue.

Highlights Higher the fatigue, lesser the inhibition in movement preparation in stroke survivors. Higher the fatigue, lesser the pre-movement facilitation and slower the reaction times. Poor excitability modulation supports sensory attenuation model of fatigue.