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Publication Detail
Neural effective connectivity explains subjective fatigue in stroke.
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Ondobaka S, De Doncker W, Ward N, Kuppuswamy A
  • Publication date:
    17/11/2021
  • Journal:
    Brain
  • Status:
    Published online
  • Country:
    England
  • PII:
    6430105
  • Language:
    eng
  • Keywords:
    dynamic causal modelling, inter-hemispheric inhibition, paired-pulse TMS, post-stroke fatigue
Abstract
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.
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