Neural effective connectivity explains subjective fatigue in stroke

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 as to 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' MRI and single- and paired-pulse transcranial magnetic stimulation. In the first session of Experiment 1, we assessed resting motor thresholds-a typical measure of cortical excitability-by applying transcranial magnetic stimulation to the primary motor cortex (M1) and measuring motor-evoked potentials in the hand affected by stroke. In the second session, we measured their brain activity with resting-state MRI to assess effective connectivity interactions at rest. In Experiment 2 we examined effective inter-hemispheric connectivity in an independent sample of patients using paired-pulse transcranial magnetic stimulation. We also assessed the levels of non-exercise induced, persistent fatigue using Fatigue Severity Scale (FSS-7), a self-report questionnaire that has been widely applied and validated across different conditions. We used spectral dynamic causal modelling in Experiment 1 and paired-pulse transcranial magnetic stimulation in Experiment 2 to characterize how neuronal effective connectivity relates to self-reported post-stroke fatigue. In a multiple regression analysis, we used the balance in inhibitory connectivity between homologue regions in M1 as the main predictor, and have included lesioned hemisphere, resting motor threshold 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 = 7.56 × 10-5, confidence interval: 0.921 to 2.127) and in Experiment 2 (β = 0.541, P = 0.049, confidence interval: 0.002 to 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.

Keywords: dynamic causal modelling; inter-hemispheric inhibition; paired-pulse TMS; poststroke fatigue.