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 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.

Electroencephalography-derived functional connectivity in sensorimotor networks in Stroke and Multiple Sclerosis Fatigue

“…Both in post-stroke and MS fatigue, there are several reports of altered resting state connectivity 14,54–58 . In stroke, suggestions of parietal hypoconnectivity and frontal hyper connectivity 58 with reversed inter-hemispheric balance of connectivity 14 , are implicated in manifestation of fatigue. In MS, changes in default mode network 56 and involvement of striatal circuits involved in movement, sensation and motivation 55 have all been implicated in development of fatigue.…”

“…Both in post-stroke and MS fatigue, there are several reports of altered resting state connectivity 14,[54][55][56][57][58] . In stroke, suggestions of parietal hypoconnectivity and frontal hyper connectivity 58 with reversed inter-hemispheric balance of connectivity 14 , are implicated in manifestation of fatigue.…”

Fatigue in perinatal stroke is associated with resting-state functional connectivity

“…In a preliminary analysis of this data 35 , we performed both ROI-to-ROI and seed to voxel analysis in eight predetermined ROI's within the sensorimotor network. However, based on feedback to this preprinted analysis, and subsequent experimental and theoretical advances in the study of fatigue 15,21,22 , we decided to adopt a data-driven analysis plan to reduce possible bias in seed selection. Individuals with perinatal stroke often have widespread morphological and functional differences in brain structure and development ( 46 for a review).…”

“…The exteroceptive and proprioceptive predictive coding account of fatigue predicts that in addition to the insula, networks comprised of sensorimotor, visual, and attentional hubs also contribute to fatigue 15 . There is emerging evidence from resting-state functional magnetic resonance imaging studies that connectivity between these areas is associated with fatigue perception [20][21][22] . Proprioception is impaired in individuals with perinatal stroke and is shown to be related to connectivity of sensory networks 23,24 , supporting that the connectivity in these networks may contribute to fatigue.…”

Fatigue in perinatal stroke is associated with resting-state functional connectivity

“…The exteroceptive and proprioceptive predictive coding account of fatigue predicts that in addition to the insula, networks comprised of sensorimotor, visual, and attentional hubs also contribute to fatigue 15 . There is emerging evidence from resting-state functional magnetic resonance imaging studies that connectivity between these areas is associated with fatigue perception [20][21][22] .…”