Persistent fatigue in post-acute COVID syndrome is associated with altered T1 MRI texture in subcortical structures: a preliminary investigation.

Post-acute COVID syndrome (PACS) is a global health concern and is often associated with debilitating symptoms. Post-COVID fatigue is a particularly frequent and troubling issue, and its underlying mechanisms remain incompletely understood. One potential contributor is micropathological injury of subcortical and brainstem structures, as has been identified in other patient populations. Texture-based analysis (TA) may be used to measure such changes in anatomical MRI data. The present study develops a methodology of voxel-wise TA mapping in subcortical and brainstem regions, which is then applied to T1-weighted MRI data from a cohort of 48 individuals who had PACS (32 with and 16 without ongoing fatigue symptoms) and 15 controls who had cold and flu-like symptoms but tested negative for COVID-19. Both groups were assessed an average of 4-5 months post-infection. There were no significant differences between PACS and control groups, but significant differences were observed within the PACS groups, between those with and without fatigue symptoms. This included reduced texture energy and increased entropy, along with reduced texture correlation, cluster shade and profile in the putamen, pallidum, thalamus and brainstem. These findings provide new insights into the neurophysiological mechanisms that underlie PACS, with altered tissue texture as a potential biomarker of this debilitating condition.

Structural MRI measures are associated with fatigue severity and persistence in a large, real-world cohort of people with multiple sclerosis.

BACKGROUND: Results of research on radiological hallmarks of multiple sclerosis (MS) fatigue have been conflicting. OBJECTIVE: To investigate the associations of lesion and brain compartment volumes with fatigue severity and persistence in people with multiple sclerosis (PwMS). METHODS: The Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) network collects standardized data during routine care of PwMS from 10 healthcare institutions. Magnetic resonance imaging (MRI) predictors included baseline brain parenchymal (BPF) and gray matter fractions (GMF) and T2 lesion volume (T2LV). The Quality of Life in Neurological Disorders (Neuro-QOL) fatigue subscore was analyzed linearly and categorically using T-score cutpoints, with a period of elevated symptoms defined as T-score ⩾ mean + 0.5 SD over follow-up. RESULTS: At baseline, of 4012 participants (average age: 45.6 ± 11.8 years; 73% female; 31% progressive MS), 2058 (51%) had no fatigue, 629 (16%) had mild fatigue, and 1325 (33%) had moderate-to-severe fatigue. One SD greater baseline BPF and GMF were associated with 0.83 (p < 0.001) and 0.38 (p = 0.02) lower values in the baseline Neuro-QOL fatigue T-score. A 1 SD lower log of total T2LV was associated with a 0.49 (p < 0.001) lower baseline fatigue T-score. Higher BPF and lower T2LV at baseline were associated with lower odds of subsequent periods of elevated fatigue. CONCLUSION: Baseline lesion burden and lower generalized whole-brain volumes were associated with MS fatigue in cross-sectional and longitudinal analyses in a large, real-world cohort of PwMS.

Thalamic nuclei volume partially mediates the effects of aerobic capacity on fatigue in people with multiple sclerosis.

BACKGROUND: Fatigue is frequent in people with multiple sclerosis (pwMS) impacting physical and cognitive functions. Lower aerobic capacity and regional thalamic volume may be involved in the pathophysiology of fatigue in pwMS. OBJECTIVES: To identify associations between thalamic nuclei volumes, aerobic capacity and fatigue and to investigate whether the influence of aerobic capacity on fatigue in pwMS is mediated by thalamic integrity. METHODS: Eighty-three pwMS underwent a clinical evaluation with assessment of fatigue (Modified Fatigue Impact Scale [MFIS]), including physical (pMFIS) and cognitive (cMFIS) components, and peak of oxygen uptake (VO2peak). PwMS and 63 sex- and age-matched healthy controls (HC) underwent a 3 T brain MRI to quantify volume of the whole thalamus and its nuclei. RESULTS: Compared to HC, pwMS showed higher global MFIS, pMFIS and cMFIS scores, and lower VO2peak and thalamic volumes (p < 0.001). In pwMS, higher VO2peak was significantly associated with lower MFIS and pMFIS scores (r value = - 0.326 and - 0.356; pFDR ≤ 0.046) and higher laterodorsal thalamic nucleus (Dor) cluster volume (r value = 0.300; pFDR = 0.047). Moreover, lower Dor thalamic cluster volume was significantly associated with higher MFIS, pMFIS and cMFIS scores (r value range = - 0.305; - 0.293; pFDR ≤ 0.049). The volume of Dor thalamic cluster partially mediated the positive effects of VO2peak on both MFIS and cMFIS, with relative indirect effects of 21% and 32% respectively. No mediation was found for pMFIS. CONCLUSIONS: Higher VO2peak is associated with lower fatigue in pwMS, likely acting on Dor thalamic cluster volume integrity. Such an effect might be different according to the type of fatigue (cognitive or physical).

Altered functional connectivity in patients with post-stroke fatigue: A resting-state fMRI study.

BACKGROUND: Post-stroke fatigue (PSF) was a common complication after stroke. This study aimed to explore the neuroimaging mechanism of PSF, which was rarely studied. METHODS: Patients with the first episode of ischemic stroke were recruited from the First Affiliated Hospital of Wenzhou Medical University between March 2021 and December 2022. The fatigue severity scale (FSS) was used to assess fatigue symptoms. PSF was diagnosed by a neurologist based on the FSS score and PSF diagnostic criteria. All the patients were scanned by resting-state functional MRI (rs-fMRI). Precuneus, the posterior node of default-mode network (pDMN), was related to fatigue. Therefore, imaging data were further analyzed by the seed-based resting-state functional connectivity (FC) approach, with the left (PCUN.L) and right precuneus (PCUN.R) being the seeds. RESULTS: A total of 70 patients with acute ischemic stroke were finally recruited, comprising 40 patients with PSF and 30 patients without PSF. Both the PCUN.L and PCUN.R seeds (pDMN) exhibited decreased FC with the prefrontal lobes located at the anterior part of DMN (aDMN), and the FC values were negatively correlated with FSS scores (both p < 0.001). These two seeds also exhibited increased FC with the right insula, and the FC values were positively correlated with FSS scores (both p < 0.05). CONCLUSION: The abnormal FC between the aDMN and pDMN was associated with PSF. Besides, the insula, related to interoception, might also play an important role in PSF.

Functional connectome hierarchy of thalamus impacts fatigue in acute stroke patients.

This study aimed to explore the topographic features of thalamic subregions, functional connectomes and hierarchical organizations between thalamus and cortex in poststroke fatigue patients. We consecutively recruited 121 acute ischemic stroke patients (mean age: 59 years) and 46 healthy controls matched for age, sex, and educational level. The mean age was 59 years (range 19-80) and 38% of acute stroke patients were females. Resting-state functional and structural magnetic resonance imaging were conducted on all participants. The fatigue symptoms were measured using the Fatigue Severity Scale. The thalamic functional subdivisions corresponding to the canonical functional network were defined using the winner-take-all parcellation method. Thalamic functional gradients were derived using the diffusion embedding analysis. The results suggested abnormal functional connectivity of thalamic subregions primarily located in the temporal lobe, posterior cingulate gyrus, parietal lobe, and precuneus. The thalamus showed a gradual increase from the medial to the lateral in all groups, but the right thalamus shifted more laterally in poststroke fatigue patients than in non- poststroke fatigue patients. Poststroke fatigue patients also had higher gradient scores in the somatomotor network and the right medial prefrontal and premotor thalamic regions, but lower values in the right lateral prefrontal thalamus. The findings suggested that poststroke fatigue patients had altered functional connectivity and thalamocortical hierarchical organizations, providing new insights into the neural mechanisms of the thalamus.

Functional connectivity modifications in monoaminergic circuits occur in fatigued MS patients treated with fampridine and amantadine.

BACKGROUND: Monoaminergic network dysfunction may have a role in multiple sclerosis (MS) fatigue pathogenesis. OBJECTIVE: To investigate modifications of fatigue severity and resting state (RS) functional connectivity (FC) in monoaminergic networks of 45 fatigued MS patients after different symptomatic treatments. METHODS: Patients were randomly, blindly assigned to fampridine (n = 15), amantadine (n = 15) or placebo (n = 15) treatment and underwent clinical and 3T-MRI evaluations at baseline (t0) and week 4 (w4), i.e. after four weeks of treatment. Fifteen healthy controls (HC) were enrolled. Dopamine-, noradrenaline- and serotonin-related RS FC was assessed by PET-guided constrained independent component analysis. RESULTS: At t0, MS patients showed widespread monoamine-related RS FC abnormalities. At w4, fatigue scores decreased in all groups (p = range < 0.001-0.002). Concomitantly, fampridine and amantadine patients showed increased insular RS FC in dopamine-related and noradrenaline-related networks (p < 0.001, uncorrected). Amantadine patients also showed increased RS FC of anterior cingulate cortex in dopamine-related and noradrenaline-related networks (p < 0.001, uncorrected). Placebo patients showed increased precuneus/middle cingulate RS FC in the noradrenaline-related network (p < 0.001, uncorrected). In fampridine and placebo patients, just tendencies towards correlations between RS FC and fatigue modifications were found. CONCLUSIONS: In MS patients, specific RS FC modifications in PET-guided monoaminergic networks were observed, concomitantly with fatigue improvements following treatment. TRIAL REGISTRATION NUMBER: EudraCT 2010-023678-38.

Reduced clinical connectome fingerprinting in multiple sclerosis predicts fatigue severity.

BACKGROUND: Brain connectome fingerprinting is progressively gaining ground in the field of brain network analysis. It represents a valid approach in assessing the subject-specific connectivity and, according to recent studies, in predicting clinical impairment in some neurodegenerative diseases. Nevertheless, its performance, and clinical utility, in the Multiple Sclerosis (MS) field has not yet been investigated. METHODS: We conducted the Clinical Connectome Fingerprint (CCF) analysis on source-reconstructed magnetoencephalography signals in a cohort of 50 subjects: twenty-five MS patients and twenty-five healthy controls. RESULTS: All the parameters of identifiability, in the alpha band, were reduced in patients as compared to controls. These results implied a lower similarity between functional connectomes (FCs) of the same patient and a reduced homogeneity among FCs in the MS group. We also demonstrated that in MS patients, reduced identifiability was able to predict, fatigue level (assessed by the Fatigue Severity Scale). CONCLUSION: These results confirm the clinical usefulness of the CCF in both identifying MS patients and predicting clinical impairment. We hope that the present study provides future prospects for treatment personalization on the basis of individual brain connectome.

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

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 predefined protocol registered with PROSPERO (ID: CRD42022303168), we searched EMBASE, MEDLINE, PubMed, and PsycInfo for studies assessing PSF and computerized tomography (CT), magnetic resonance (MR), positron emission tomography (PET) imaging, or diffusion tensor imaging (DTI). We extracted neuroimaging parameters and narratively analyzed study results to assess any association with PSF. Where there were 3+ similar studies, we carried out a meta-analysis using inverse-variance random-effects model to estimate the total association of each neuroimaging parameter on PSF. The risk of bias was assessed using the Newcastle and Ottawa Scale. RESULTS: We identified 46 studies (N = 6543); in many studies, associations with fatigue were secondary or subanalyses (28.3%). Imaging parameters were assessed across eight variables: lesion lateralization, lesion location, lesion volume, brain atrophy, infarct number, cerebral microbleeds, white matter hyperintensities (WMHs), 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 lateralization (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 an association between altered functional brain networks, namely frontal, fronto-striato-thalamic, and sensory processing networks, with PSF. CONCLUSION: There was little evidence for the association between any neuroimaging parameters and PSF. Future studies should utilize advanced imaging techniques to fully understand the role of lesion location in PSF, while the role of altered brain networks in mediating PSF merits further research.

Thalamic network under wakefulness after sleep onset and its coupling with daytime fatigue in insomnia disorder: An EEG-fMRI study.

BACKGROUND: Fatigue is the most common daytime impairment of insomnia disorder (ID). Thalamus is acknowledged as the key brain region closely associated with fatigue. However, the thalamus-based neurobiological mechanisms of fatigue in patients with ID remain unknown. METHODS: Forty-two ID patients and twenty-eight well-matched healthy controls (HCs) underwent simultaneous electroencephalography--functional magnetic resonance imaging. We calculated the functional connectivity (FC) between the thalamic seed and each voxel across the whole brain in two conditions of wakefulness--after sleep onset (WASO) and before sleep onset. A linear mixed effect model was used to determine the condition effect of the thalamic FC. The correlation between daytime fatigue and the thalamic connectivity was explored. RESULTS: After sleep onset, the connectivity with the bilateral thalamus was increased in the cerebellar and cortical regions. Compared with HCs, ID patients showed significantly lower FC between left thalamus and left cerebellum under the WASO condition. Furthermore, thalamic connectivity with cerebellum under the WASO condition was negatively correlated with Fatigue Severity Scale scores in the pooled sample. CONCLUSIONS: These findings contribute to an emerging framework that reveals the link between insomnia-related daytime fatigue and the altered thalamic network after sleep onset, further highlighting the possibility that this neural pathway is a therapeutic target for meaningfully mitigating fatigue.

Aberrant voxel-based degree centrality and functional connectivity in Parkinson's disease patients with fatigue.

AIMS: The study aimed to investigate alterations in the inherent connectivity pattern of global functional networks in Parkinson's disease (PD) patients with fatigue. METHODS: Eighteen PD patients with fatigue (PD-F), 20 PD patients without fatigue (PD-NF), and 23 healthy controls (HCs) were recruited and analyzed by the voxel-wise degree centrality (DC) and the seed-based functional connectivity (FC) analysis. Meanwhile, the surface-based morphometry (SBM) analysis was also commanded to explore the structural alternations among groups. RESULTS: PD-F patients displayed reduced DC values in the left postcentral gyrus relative to PD-NF and HCs groups, while increased DC values in the bilateral precuneus compared to HCs. Simultaneously, altered DC value in the left postcentral gyrus negatively corresponded to the mean fatigue severity scale (FSS) in PD-F patients. Additionally, the receiver operating characteristic (ROC) curves uncovered that the reduced DC value of the left postcentral gyrus could discriminate PD-F from PD-NF and HCs groups. Our FC analysis further revealed that altered FC was located predominantly in the sensorimotor network in the PD-F group. Moreover, we discovered no statistically significant differences between the three groups concerning cortical thickness. CONCLUSION: Our findings indicated that the altered functional connectivity in the sensorimotor network centering on the left postcentral gyrus and the bilateral precuneus might be the potential pathogenesis of PD with fatigue.

Disruptions in Structural and Functional Connectivity Relate to Poststroke Fatigue.

Introduction: Poststroke fatigue (PSF) is a disabling condition with unclear etiology. The brain lesion is thought to be an important causal factor in PSF, although focal lesion characteristics such as size and location have not proven to be predictive. Given that the stroke lesion results not only in focal tissue death but also in widespread changes in brain networks that are structurally and functionally connected to damaged tissue, we hypothesized that PSF relates to disruptions in structural and functional connectivity. Materials and Methods: Twelve patients who incurred an ischemic stroke in the middle cerebral artery (MCA) territory 1-3 years prior, and currently experiencing a range of fatigue severity, were enrolled. The patients underwent structural and resting-state functional magnetic resonance imaging (MRI). The structural MRI data were used to measure structural disconnection of gray matter resulting from lesion to white matter pathways. The functional MRI data were used to measure network functional connectivity. Results: The patients showed structural disconnection in varying cortical and subcortical regions. Fatigue severity correlated significantly with structural disconnection of several frontal cortex regions in the ipsilesional (IL) and contralesional hemispheres. Fatigue-related structural disconnection was most severe in the IL rostral middle frontal cortex. Greater structural disconnection of a subset of fatigue-related frontal cortex regions, including the IL rostral middle frontal cortex, trended toward correlating significantly with greater loss in functional connectivity. Among identified fatigue-related frontal cortex regions, only the IL rostral middle frontal cortex showed loss in functional connectivity correlating significantly with fatigue severity. Conclusion: Our results provide evidence that loss in structural and functional connectivity of bihemispheric frontal cortex regions plays a role in PSF after MCA stroke, with connectivity disruptions of the IL rostral middle frontal cortex having a central role. Impact statement Poststroke fatigue (PSF) is a common disabling condition with unclear etiology. We hypothesized that PSF relates to disruptions in structural and functional connectivity secondary to the focal lesion. Using structural and resting-state functional connectivity magnetic resonance imaging (MRI) in patients with chronic middle cerebral artery (MCA) stroke, we found frontal cortex regions in the ipsilesional (IL) and contralesional hemispheres with greater structural disconnection correlating with greater fatigue. Among these fatigue-related cortices, the IL rostral middle frontal cortex showed loss in functional connectivity correlating with fatigue. These findings suggest that disruptions in structural and functional connectivity play a role in PSF after MCA stroke.

MRI Assessment of Cerebral Blood Flow in Nonhospitalized Adults Who Self-Isolated Due to COVID-19.

BACKGROUND: Neurological symptoms associated with coronavirus disease 2019 (COVID-19), such as fatigue and smell/taste changes, persist beyond infection. However, little is known of brain physiology in the post-COVID-19 timeframe. PURPOSE: To determine whether adults who experienced flu-like symptoms due to COVID-19 would exhibit cerebral blood flow (CBF) alterations in the weeks/months beyond infection, relative to controls who experienced flu-like symptoms but tested negative for COVID-19. STUDY TYPE: Prospective observational. POPULATION: A total of 39 adults who previously self-isolated at home due to COVID-19 (41.9 ± 12.6 years of age, 59% female, 116.5 ± 62.2 days since positive diagnosis) and 11 controls who experienced flu-like symptoms but had a negative COVID-19 diagnosis (41.5 ± 13.4 years of age, 55% female, 112.1 ± 59.5 since negative diagnosis). FIELD STRENGTH AND SEQUENCES: A 3.0 T; T1-weighted magnetization-prepared rapid gradient and echo-planar turbo gradient-spin echo arterial spin labeling sequences. ASSESSMENT: Arterial spin labeling was used to estimate CBF. A self-reported questionnaire assessed symptoms, including ongoing fatigue. CBF was compared between COVID-19 and control groups and between those with (n = 11) and without self-reported ongoing fatigue (n = 28) within the COVID-19 group. STATISTICAL TESTS: Between-group and within-group comparisons of CBF were performed in a voxel-wise manner, controlling for age and sex, at a family-wise error rate of 0.05. RESULTS: Relative to controls, the COVID-19 group exhibited significantly decreased CBF in subcortical regions including the thalamus, orbitofrontal cortex, and basal ganglia (maximum cluster size = 6012 voxels and maximum t-statistic = 5.21). Within the COVID-19 group, significant CBF differences in occipital and parietal regions were observed between those with and without self-reported on-going fatigue. DATA CONCLUSION: These cross-sectional data revealed regional CBF decreases in the COVID-19 group, suggesting the relevance of brain physiology in the post-COVID-19 timeframe. This research may help elucidate the heterogeneous symptoms of the post-COVID-19 condition. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 3.

Evaluation of the relationship between the morphometric structure of the pituitary gland and fatigue in patients with multiple sclerosis.

BACKGROUND: The correlation between fatigue and disability in multiple sclerosis (MS) with the hypothalamus-pituitary-adrenal axis is known. This study aimed to investigate the relationship between the morphometric dimensions of the pituitary gland with fatigue and disability. METHOD: This research, designed as a prospective and case-control study, included 85 MS patients and 45 healthy controls. The disability was evaluated using the expanded disability rating scale (EDSS), while fatigue was determined using the fatigue severity scale (FSS) and the neurological fatigue index (NFI-MS). The morphometric structure of the pituitary gland was measured using a coronal, T2-weighted, turbo-spin-echo sequence of magnetic resonance imaging. RESULTS: FSS and NFI-MS scores were higher in MS patients than in the control group (p = 0.001). Patients with a progressive and moderate-to-severe disability had a higher FSS score (p = 0.015; p = 0.002, respectively). A positive correlation was determined between disease duration, attack frequency, and EDSS and physical fatigue subscale score (p = 0.001; r = 0.383; 0.373; 0.545, respectively). The height and width of the pituitary gland were higher in MS patients (p = 0.021; p = 0.001, respectively). Pituitary gland height was higher in fatigued patients (p = 0.041). A low-positive correlation was determined between the number of attacks and the height of the pituitary gland (p = 0.027, r = 0.231). CONCLUSION: The difference in the dimensions of the pituitary gland in MS patients, especially in the fatigued group, supports the relationship of fatigue with morphometric features as well as the hypothalamus-pituitary-adrenal axis.

Assessment of cognitive function, structural brain changes and fatigue 6 months after treatment of neuroborreliosis.

BACKGROUND: Complete recovery after adequately treated neuroborreliosis is common, but studies report that some patients experience persistent symptoms like self-reported cognitive problems and fatigue. Persisting symptoms are often termed post-Lyme disease syndrome, of which etiology is not clearly understood. The aim of this study was to investigate cognitive function, possible structural changes in brain regions and level of fatigue. We have not found previous studies on neuroborreliosis that use standardized neuropsychological tests and MRI with advanced image processing to investigate if there are subtle regional changes in cortical thickness and brain volumes after treatment. METHODS: We examined 68 patients treated for neuroborreliosis 6 months earlier and 66 healthy controls, with a comprehensive neuropsychological test protocol, quantitative structural MRI analysis of the brain and Fatigue Severity Scale. RESULTS: We found no differences between the groups in either cognitive function, cortical thickness or brain volumes. The patients had higher score on Fatigue Severity Scale 3.8 vs. 2.9 (p = 0.001), and more patients (25.4%) than controls (5%) had severe fatigue (p = 0.002), but neither mean score nor proportion of patients with severe fatigue differed from findings in the general Norwegian population. CONCLUSION: The prognosis regarding cognitive function, brain MRI findings and fatigue after adequately treated neuroborreliosis is favorable.

Brain morphometry changes with fatigue severity in fibromyalgia.

OBJECTIVES: This study investigated brain morphometry changes associated with fatigue severity in fibromyalgia (FM). METHODS: Clinical profiles and brain-MRI data were collected in patients with FM. Patients were divided into three groups based on their fatigue severity. Using voxel-based morphometry analysis and trend analysis, neural substrates showing volumetric changes associated with fatigue severity across the three groups were identified. Their seed-to-voxel structural covariance (SC) networks with the whole brain were studied in distribution and strength. RESULTS: Among the 138 enrolled patients with FM, 23, 57, and 58 were categorised into the mild, moderate, and severe fatigue groups, respectively. The number of musculoskeletal pain regions and intensity of pain were not associated with fatigue severity, but somatic symptoms and psychiatric distress, including waking unrefreshed, depression, and anxiety, were associated with fatigue severity. After adjusting for anxiety and depression, decreased bilateral thalamic volumes were associated with higher fatigue severity. The SC distributions of the thalamic seed were more widespread to the frontal, parietal, subcortical, and limbic regions in patients with higher fatigue severity. In addition, increased right inferior temporal cortex volumes were associated with higher fatigue severity. The SC distributions of the right inferior temporal seed were more over the temporal cortex and the SC strengths of the seed were higher with the bilateral occipital cortex in patients with higher fatigue severity. CONCLUSIONS: The thalamus and the right inferior temporal cortex are implicated in the manifestation of fatigue severity in FM. Future therapeutic strategies targeting these regions are worthy of investigation.

Resting-state fMRI study on drug-naïve early-stage patients with Parkinson's disease and with fatigue.

INTRODUCTION: Fatigue is one of the most common and debilitating non-motor symptoms in patients with Parkinson's disease (PD), which could manifest during the early stage of the disease and persist through the disease course. However, the treatment options for fatigue remain limited for patients with PD. METHODS: Using seed-based resting-state functional magnetic resonance imaging, we explored the fatigue-related functional deficiencies in the anterior caudate nucleus, anterior putamen, and posterior putamen in a cohort of early-stage drug-naïve patients with PD. Thirty-eight patients with PD, 19 with and 19 without fatigue, and 31 matched healthy controls were selected. The fatigue status was defined based on the score obtained from the fatigue severity scale (FSS). RESULTS: Patients with PD with fatigue exhibited a decreased connectivity in the cerebellar-striatal, cortico-striatal, and mesolimbic-striatal loops. No increased functional connectivity was observed. The abnormal connections of the dorsal striatum subdivisions overlapped to extensive brain regions, including the cerebellum, inferior frontal gyrus, inferior temporal gyrus, lingual gyrus, rolandic operculum, insular, and hippocampus. CONCLUSIONS: Our findings revealed that the widespread functional deficiency in the striatal-cerebellar-cerebral cortical network may be critical to the pathology underlying fatigue in the early-stage PD. The key feature of fatigue-related connectivity was observed between the caudate nucleus and the cerebellum, which could serve as a potential biomarker or treatment target for fatigue in early-stage patients with PD in future studies.

Functional connectivity dynamics reflect disability and multi-domain clinical impairment in patients with relapsing-remitting multiple sclerosis.

BACKGROUND & AIM: Multiple sclerosis (MS) is an autoimmune disease of the central nervous system associated with deficits in cognitive and motor functioning. While structural brain changes such as demyelination are an early hallmark of the disease, a characteristic profile of functional brain alterations in early MS is lacking. Functional neuroimaging studies at various disease stages have revealed complex and heterogeneous patterns of aberrant functional connectivity (FC) in MS, with previous studies largely being limited to a static account of FC. Thus, it remains unclear how time-resolved FC relates to variance in clinical disability status in early MS. We here aimed to characterize brain network organization in early MS patients with time-resolved FC analysis and to explore the relationship between disability status, multi-domain clinical outcomes and altered network dynamics. METHODS: Resting-state functional MRI (rs-fMRI) data were acquired from 101 MS patients and 101 age- and sex-matched healthy controls (HC). Based on the Expanded Disability Status Score (EDSS), patients were split into two sub-groups: patients without clinical disability (EDSS ≤ 1, n = 36) and patients with mild to moderate levels of disability (EDSS ≥ 2, n = 39). Five dynamic FC states were extracted from whole-brain rs-fMRI data. Group differences in static and dynamic FC strength, across-state overall connectivity, dwell time, transition frequency, modularity, and global connectivity were assessed. Patients' impairment was quantified as custom clinical outcome z-scores (higher: worse) for the domains depressive symptoms, fatigue, motor, vision, cognition, total brain atrophy, and lesion load. Correlation analyses between functional measures and clinical outcomes were performed with Spearman partial correlation analyses controlling for age. RESULTS: Patients with mild to moderate levels of disability exhibited a more widespread spatiotemporal pattern of altered FC and spent more time in a high-connectivity, low-occurrence state compared to patients without disability and HCs. Worse symptoms in all clinical outcome domains were positively associated with EDSS scores. Furthermore, depressive symptom severity was positively related to functional dynamics as measured by state-specific global connectivity and default mode network connectivity with attention networks, while fatigue and motor impairment were related to reduced frontoparietal network connectivity with the basal ganglia. CONCLUSIONS: Despite comparably low impairment levels in early MS, we identified distinct connectivity alterations between patients with mild to moderate disability and those without disability, and these changes were sensitive to clinical outcomes in multiple domains. Furthermore, time-resolved analysis uncovered alterations in network dynamics and clinical correlations that remained undetected with conventional static analyses, showing that accounting for temporal dynamics helps disentangle the relationship between functional alterations, disability status, and symptoms in early MS.

Multisensory mental imagery of fatigue: Evidence from an fMRI study.

Functional imaging experimental designs measuring fatigue, defined as a subjective lack of physical and/or mental energy characterizing a wide range of neurologic conditions, are still under development. Nineteen right-handed healthy subjects (9 M and 10 F, mean age 43.15 ± 8.34 years) were evaluated by means of functional magnetic resonance imaging (fMRI), asking them to perform explicit, first-person, mental imagery of fatigue-related multisensory sensations. Short sentences designed to assess the principal manifestations of fatigue from the Multidimensional Fatigue Symptom Inventory were presented. Participants were asked to imagine the corresponding sensations (Sensory Imagery, SI). As a control, they had to imagine the visual scenes (Visual Imagery, VI) described in short phrases. The SI task (vs. VI task) differentially activated three areas: (i) the precuneus, which is involved in first-person perspective taking; (ii) the left superior temporal sulcus, which is a multisensory integration area; and (iii) the left inferior frontal gyrus, known to be involved in mental imagery network. The SI fMRI task can be used to measure processing involved in mental imagery of fatigue-related multisensory sensations.

Structural Basal Ganglia Correlates of Subjective Fatigue in Middle-Aged and Older Adults.

OBJECTIVE: Fatigue is among the most common complaints in community-dwelling older adults, yet its etiology is poorly understood. Based on models implicating frontostriatal pathways in fatigue pathogenesis, we hypothesized that smaller basal ganglia volume would be associated with higher levels of subjective fatigue and reduced set-shifting in middle-aged and older adults without dementia or other neurologic conditions. METHODS: Forty-eight non-demented middle-aged and older adults (Mage = 68.1, SD = 9.4; MMMSE = 27.3, SD = 1.9) completed the Fatigue Symptom Inventory, set-shifting measures, and structural MRI as part of a clinical evaluation for subjective cognitive complaints. Associations were examined cross-sectionally. RESULTS: Linear regression analyses showed that smaller normalized basal ganglia volumes were associated with more severe fatigue (ß = -.29, P = .041) and poorer Trail Making Test B-A (TMT B-A) performance (ß = .30, P = .033) controlling for depression, sleep quality, vascular risk factors, and global cognitive status. Putamen emerged as a key structure linked with both fatigue (r = -.43, P = .003) and TMT B-A (ß = .35, P = .021). The link between total basal ganglia volume and reduced TMT B-A was particularly strong in clinically fatigued patients. CONCLUSION: This study is among the first to show that reduced basal ganglia volume is an important neurostructural correlate of subjective fatigue in physically able middle-aged and older adults without neurological conditions. Findings suggest that fatigue and rapid set-shifting deficits may share common neural underpinnings involving the basal ganglia, and provide a framework for studying the neuropathogenesis and treatment of subjective fatigue.

Subcortical Volumes as Early Predictors of Fatigue in Multiple Sclerosis.

OBJECTIVE: Fatigue is a frequent and severe symptom in multiple sclerosis (MS), but its pathophysiological origin remains incompletely understood. We aimed to examine the predictive value of subcortical gray matter volumes for fatigue severity at disease onset and after 4 years by applying structural equation modeling (SEM). METHODS: This multicenter cohort study included 601 treatment-naive patients with MS after the first demyelinating event. All patients underwent a standardized 3T magnetic resonance imaging (MRI) protocol. A subgroup of 230 patients with available clinical follow-up data after 4 years was also analyzed. Associations of subcortical volumes (included into SEM) with MS-related fatigue were studied regarding their predictive value. In addition, subcortical regions that have a central role in the brain network (hubs) were determined through structural covariance network (SCN) analysis. RESULTS: Predictive causal modeling identified volumes of the caudate (s [standardized path coefficient] = 0.763, p = 0.003 [left]; s = 0.755, p = 0.006 [right]), putamen (s = 0.614, p = 0.002 [left]; s = 0.606, p = 0.003 [right]) and pallidum (s = 0.606, p = 0.012 [left]; s = 0.606, p = 0.012 [right]) as prognostic factors for fatigue severity in the cross-sectional cohort. Moreover, the volume of the pons was additionally predictive for fatigue severity in the longitudinal cohort (s = 0.605, p = 0.013). In the SCN analysis, network hubs in patients with fatigue worsening were detected in the putamen (p = 0.008 [left]; p = 0.007 [right]) and pons (p = 0.0001). INTERPRETATION: We unveiled predictive associations of specific subcortical gray matter volumes with fatigue in an early and initially untreated MS cohort. The colocalization of these subcortical structures with network hubs suggests an early role of these brain regions in terms of fatigue evolution. ANN NEUROL 2022;91:192-202.