Post-stroke fatigue is associated with resting state posterior hypoactivity and prefrontal hyperactivity

Cotter, Georgia; Khlif, Mohamed Salah; Bird, Laura; Howard, Mark; Brodtmann, Amy; Egorova-Brumley, Natalia

doi:10.1177/17474930211048323

Cited by 16 publications

(21 citation statements)

References 49 publications

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“…A recent fMRI study indicated that PSF was associated with the posterior hypoactivity and prefrontal hyperactivity reflecting that dysfunction within fronto-striatal-thalamic and frontal-occipital networks may be involved in the occurrence of fatigue, which was partially consistent with our findings (Cotter et al, 2021 ). In addition, the prevalence of PSF in this study was 39.8% in the acute phase of stroke and 35.8% at the 6-month follow-up.…”

Section: Discussionsupporting

confidence: 92%

Association of Lesion Location and Fatigue Symptoms After Ischemic Stroke: A VLSM Study

Wang

Xiao

et al. 2022

Front. Aging Neurosci.

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Background:Poststroke fatigue (PSF) is a common symptom in stroke survivors, yet its anatomical mechanism is unclear. Our study was aimed to identify which brain lesions are related to the PSF in patients with acute stroke.MethodPatients with first-ever acute ischemic stroke consecutively admitted from the first affiliated hospital of the University of Science and Technology of China (USTC) between January 2017 and June 2020. Fatigue was scored using the Fatigue Severity Scale. All the participants were assessed by 3.0 T brain MRI including diffusion-weighted imaging. The infarct lesions were delineated manually and transformed into a standard template. Voxel-based lesion-symptom mapping (VLSM) was applied to investigate the association between lesion location and the occurrence and severity of fatigue. The same analyses were carried out by flipping the left-sided lesions. Multivariate logistic regressions were applied to verify the associations.ResultsOf the 361 patients with acute stroke, 142 (39.3%) patients were diagnosed with fatigue in the acute phase and 116 (35.8%) at 6 months after the index stroke. VLSM analysis indicated clusters in the right thalamus which was significantly associated with the occurrence and severity of PSF at 6-month follow-up. In contrast, no significant cluster was found in the acute phase of stroke. The flipped analysis did not alter the results. Multivariate logistic regression verified that lesion load in the right thalamus (OR 2.67, 95% CI 1.46–4.88) was an independent predictor of 6-month PSF.ConclusionOur findings indicated that lesions in the right thalamus increased the risk of fatigue symptoms 6 months poststroke.

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Section: Discussionsupporting

confidence: 92%

Association of Lesion Location and Fatigue Symptoms After Ischemic Stroke: A VLSM Study

Wang

Xiao

et al. 2022

Front. Aging Neurosci.

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“…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.…”

Section: Discussionmentioning

confidence: 99%

“…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.…”

Section: Discussionmentioning

confidence: 99%

“…In this study we provide first evidence for a common mechanism of pathological fatigue in two neurological conditions that present with fatigue as a significant symptom, stroke and MS. 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.…”

Section: Discussionmentioning

confidence: 99%

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

Doncker

Croce

et al. 2022

Preprint

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A common mechanism of altered sensory processing is the basis of chronic fatigue in neurological disorders. Here we test the hypothesis - Altered connectivity in sensory networks underlies chronic fatigue in stroke and multiple sclerosis. In 46 non-depressed, minimally impaired stroke survivors (n=29) and multiple sclerosis patients (n=17), median disease duration of 5 years, resting state neuronal activity was measured using 64-channel electroencephalography. Graph theory-based network analysis measure of functional connectivity (small-world index) was calculated in right and left motor (Brodmann areas 4, 6, 8, 9, 24 and 32) and somatosensory (Brodmann areas 1, 2, 3, 5, 7, 40 and 43) networks, in 5 frequency bands: delta, theta, alpha, beta and gamma. Fatigue was measured using Fatigue Severity Scale (Stroke) and modified Fatigue Impact Scale (MS), with scores of >4 (FSS) and >38 (mFIS), defined as high fatigue. Both stroke survivors and multiple sclerosis patients with high fatigue showed significantly more small-worldness in the right sensory networks in the beta band frequency. Additionally, only in stroke survivors with high fatigue, there was decreased small-worldness in the left motor network in the delta and theta bands. Altered sensory network connectivity is common to both stroke and MS fatigue, indicating impaired sensory processing as a disease-independent mechanism of chronic fatigue in neurological conditions. Furthermore, such difference in functional connectivity emerges in beta band activity, further strengthening the idea of altered sensorimotor processing as the basis of chronic neurological fatigue.

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“…Sixteen studies with 2755 participants tested the association between fatigue and lesion diameter or volume. 1,7,20,21,31,32,35,43,[44][45][46][47][48][49]52,53 None identified any significant associations (see Supplementary sTable 4).…”

Section: Lesion Volumementioning

confidence: 99%

Neuroimaging correlates of post-stroke fatigue: A systematic review and meta-analysis

Jolly,

Zainurin,

Mead

et al. 2023

International Journal of Stroke

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Background Fatigue is a common and disabling symptom following stroke, but its underlying mechanisms are unknown. Associations with a number of imaging features have been proposed. Aims We aimed to assess whether neuroimaging parameters could better inform our understanding of possible causes of post-stroke fatigue (PSF) through systematic review and meta-analysis. Methods Using a pre-defined protocol registered with PROSPERO (ID: CRD42022303168), we searched EMBASE, MEDLINE, PubMed and PsycInfo for studies assessing PSF and Computerised Tomography (CT)-, Magnetic Resonance (MR)-, Positron Emission Tomography (PET)- imaging or Diffusion Tensor Imaging (DTI). We extracted neuroimaging parameters and narratively analysed study results to assess any association to PSF. Where there were 3+ similar studies, we carried out a meta-analysis using inverse-variance random-effects model to estimate total association of each neuroimaging parameter on PSF. Risk of bias was assessed using the Newcastle and Ottawa Scale. Results We identified 46 studies ( N=6,543); in many studies associations with fatigue were secondary or sub-analyses (28.3%). Imaging parameters were assessed across 8 variables: lesion lateralisation, lesion location, lesion volume, brain atrophy, infarct number, cerebral microbleeds, white matter hyperintensities (WMH) and network measures. Most variables showed no conclusive evidence for any association with fatigue. Meta-analysis where possible showed no association of the following with PSF; left lesion lateralisation (OR: 0.88, 95% CI [0.64, 1. 22], ( p=0.45)), infratentorial lesion location (OR: 1.83, 95% CI [0.63, 5.32], ( p=0.27)) and WMH (OR: 1.21, 95% CI [0.84, 1.75], ( p=0.29)). Many studies assessed lesion location with mixed findings, only one used voxel-symptom lesion-mapping (VSLM). Some small studies suggested association between altered functional brain networks, namely frontal, fronto-striato-thalamic and sensory processing networks, with PSF. Conclusion There was little evidence for association between any neuroimaging parameters and PSF. Future studies should utilise advanced imaging techniques to fully understand the role of lesion location in PSF, whilst the role of altered brain networks in mediating PSF merits further research

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Post-stroke fatigue is associated with resting state posterior hypoactivity and prefrontal hyperactivity

Cited by 16 publications

References 49 publications

Association of Lesion Location and Fatigue Symptoms After Ischemic Stroke: A VLSM Study

Association of Lesion Location and Fatigue Symptoms After Ischemic Stroke: A VLSM Study

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

Neuroimaging correlates of post-stroke fatigue: A systematic review and meta-analysis

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