Dynamic functional connectivity as a neural correlate of fatigue in multiple sclerosis

Functional connectivity changes in males with nicotine addiction: A triple network model study

BACKGROUND

Nicotine addiction (NA) is recognized as a significant neurobehavioral disorder that affects both individuals and society. It is suggested that alterations in functional network connectivity (FNC) within specific brain networks underlie its neurobiological basis.

METHODS

The default mode network (DMN), executive control network (ECN), and salience network (SN) are identified using data from the Human Connectome Project. The study includes 47 individuals with NA and 35 normal controls (NC), all of whom undergo resting-state fMRI alongside smoking-related clinical assessments. A sliding window analysis is employed to assess connectivity metrics, including static functional network connectivity (FNC), standard deviation (SD), and coefficient of variation (CV), to compare information integration between the groups. Participants with NA are classified based on longitudinal changes in Fagerström Test for Nicotine Dependence (FTND) scores over six years into three categories: addiction tendency (AT), withdrawal tendency (WT), and stable tendency (ST). Correlation analyses are conducted to explore relationships between FNC abnormalities and clinical assessments.

RESULTS

Individuals with NA exhibit reduced static FNC (p_FDR = 0.029) between the dorsal DMN and the right ECN, accompanied by increased SD (p_FDR = 0.029) and CV (p_FDR = 0.029). A significant increase in SD (p_FDR = 0.049) is also observed in the dorsal DMN and left ECN. Correlations indicate that the SD of the dorsal DMN and right ECN relates to the pharmacological dimension of the Russell Smoking Reasons Questionnaire (RRSQ) scale (r = 0.416, p_FDR = 0.044), while CV correlates with changes in the FTND over six years (r = -0.391, p_FDR = 0.044) and the pharmacological dimension of the RRSQ scale (r = 0.402, p_FDR = 0.044). Post-hoc subgroup analyses reveal that these FNC intensity changes are present among WT patients (p_FDR < 0.05).

CONCLUSIONS

Alterations in brain network function within the DMN and ECN are suggested to precede behavioral changes in NA. These findings are interpreted as potential neurobiological markers of nicotine addiction.

Multisensory mental imagery of fatigue in patients with multiple Sclerosis. Preliminary evidence from a fMRI study

Fatigue, defined as a subjective lack of physical and/or mental energy, is a clinical symptom highly characterizing multiple sclerosis (MS). The present study utilized a novel approach to the study of fatigue, examining first person-mental imagery of the symptom. Eighteen right-handed patients with MS (14F, 4 M, mean age 45.8 ± 8.15 years) were evaluated and were compared to nineteen healthy controls (10F, 9 M, mean age 43.15 ± 8.34 years) Patients were all in relapsing remitting form and no patient had presented relapses in the 6 months prior to inclusion in the study. We evaluated their behavioral performance and fMRI activations. We used an fMRI paradigm used to trigger first person-mental imagery of fatigue, through short sentences describing the principal manifestations of fatigue. 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. They made a vividness rating by pressing the corresponding button. Behaviorally, we found that patients' mean scores at the Multidimensional Fatigue Symptom Inventory for the general scale, physical scale, and mental scale were significantly higher than healthy controls (p = 0.05, p = 0.002, p = 0.006 respectively), but not for the emotional scale and for vigor scale (p = 0.207, n.s., p = 0.06, n.s.). In the imagery fMRI task, patients were significantly slower (mean reaction times and standard deviation: 2.24 s ± 0.33) than controls (mean reaction times and standard deviation: 1.918 s ± 0.455) for the SI task (Z=-2.058, p = 0.040), while no significant difference was found for the VI task. Regarding brain mapping, our main result is a group by task interaction. The SI task (vs. VI task) in healthy controls (relative to patients) increased activation in the left inferior parietal lobule. These preliminary results indicate that fatigue is related to dysfunctions in higher-order aspects of motor control, given the role of the posterior parietal lobe in motor planning and multisensory integration.

Disrupted hemodynamic response within dorsolateral prefrontal cortex during cognitive tasks among people with multiple sclerosis-related fatigue

INTRODUCTION

Mental fatigue is an early and enduring symptom in persons with autoimmune disease particularly multiple sclerosis (MS). Neuromodulation has emerged as a potential treatment although optimal cortical targets have yet to be determined. We aimed to examine cortical hemodynamic responses within bilateral dorsolateral prefrontal cortex (dlPFC) and frontopolar areas during single and dual cognitive tasks in persons with MS-related fatigue compared to matched controls.

METHODS

We recruited persons (15 MS and 12 age- and sex-matched controls) who did not have physical or cognitive impairment and were free from depressive symptoms. Functional near infrared spectroscopy (fNIRS) registered hemodynamic responses during the tasks. We calculated oxyhemoglobin peak, time-to-peak, coherence between channels (a potential marker of neurovascular coupling) and functional connectivity (z-score).

RESULTS

In MS, dlPFC demonstrated disrupted hemodynamic coherence during both single and dual tasks, as evidenced by non-significant and negative correlations between fNIRS channels. In MS, reduced coherence occurred in left dorsolateral PFC during the single task but occurred bilaterally as the task became more challenging. Functional connectivity was lower during dual compared to single tasks in the right dorsolateral PFC in both groups. Lower z-score was related to greater feelings of fatigue. Peak and time-to-peak hemodynamic response did not differ between groups or tasks.

CONCLUSIONS

Hemodynamic responses were inconsistent and disrupted in people with MS experiencing mental fatigue, which worsened as the task became more challenging. Our findings point to dlPFC, but not frontopolar areas, as a potential target for neuromodulation to treat cognitive fatigue.

Brain connectivity changes underlying depression and fatigue in relapsing-remitting multiple sclerosis: A systematic review

Multiple Sclerosis (MS) is an autoimmune disease affecting the central nervous system, characterised by neuroinflammation and neurodegeneration. Fatigue and depression are common, debilitating, and intertwined symptoms in people with relapsing-remitting MS (pwRRMS). An increased understanding of brain changes and mechanisms underlying fatigue and depression in RRMS could lead to more effective interventions and enhancement of quality of life. To elucidate the relationship between depression and fatigue and brain connectivity in pwRRMS we conducted a systematic review. Searched databases were PubMed, Web-of-Science and Scopus. Inclusion criteria were: studied participants with RRMS (n ≥ 20; ≥ 18 years old) and differentiated between MS subtypes; published between 2001-01-01 and 2023-01-18; used fatigue and depression assessments validated for MS; included brain structural, functional magnetic resonance imaging (fMRI) or diffusion MRI (dMRI). Sixty studies met the criteria: 18 dMRI (15 fatigue, 5 depression) and 22 fMRI (20 fatigue, 5 depression) studies. The literature was heterogeneous; half of studies reported no correlation between brain connectivity measures and fatigue or depression. Positive findings showed that abnormal cortico-limbic structural and functional connectivity was associated with depression. Fatigue was linked to connectivity measures in cortico-thalamic-basal-ganglial networks. Additionally, both depression and fatigue were related to altered cingulum structural connectivity, and functional connectivity involving thalamus, cerebellum, frontal lobe, ventral tegmental area, striatum, default mode and attention networks, and supramarginal, precentral, and postcentral gyri. Qualitative analysis suggests structural and functional connectivity changes, possibly due to axonal and/or myelin loss, in the cortico-thalamic-basal-ganglial and cortico-limbic network may underlie fatigue and depression in pwRRMS, respectively, but the overall results were inconclusive, possibly explained by heterogeneity and limited number of studies. This highlights the need for further studies including advanced MRI to detect more subtle brain changes in association with depression and fatigue. Future studies using optimised imaging protocols and validated depression and fatigue measures are required to clarify the substrates underlying these symptoms in pwRRMS.

Effect of Tai-chi on balance, mood, cognition, and quality of life in women with multiple sclerosis: A one-year prospective study

INTRODUCTION

One of the most debilitating problems encountered by people with multiple sclerosis (MS) is the loss of balance and coordination. Our study aimed to comprehensively evaluate the effectiveness of one year of Tai-chi exercise in patients with MS using both subjective and objective methods, including posturography.

METHODS

This was a single-group longitudinal one-year study performed from the 1st of January 2019 to the 1st of January 2020. The primary outcomes of interest were the Mini-Balance Evaluation Systems Test (Mini-BESTest) and static posturography measures as objective methods to detect subtle changes associated with postural control/balance impairment. Secondary outcomes were measures of depression, anxiety, cognitive performance, and quality of life. All objective and subjective parameters were assessed four times: at baseline, and after three, six and 12 months of regular Tai-chi training. The difference was calculated as a subtraction of baseline values from every timepoint value for each measurement. If the normality test was passed, parametric one-sample t-test was used, if failed, Wilcoxon signed ranks test was used to test the difference between the baseline and each timepoint. Alpha was set to 0.017 using Bonferroni correction for multiple comparisons.

RESULTS

Out of 25 patients with MS enrolled, 15 women with MS (mean age 44.27 years) were included for statistical analyses after completing the 12-month program. After 12 months, significant improvements were found in all objective balance and gait tests: Mini-BESTest (p<0.001), static posturography measures (total area of the centre of foot pressure - TA; p = 0.015), 25 Feet Walk Test (25FWT; p = 0.001), anxiety (Beck Anxiety Inventory - BAI; p = 0.005) and cognition tests (Paced Auditory Serial Addition Test - PASAT; p = 0.003). Measures of depression (Beck Depression Inventory - BDI; p = 0.071), cognition (Symbol Digit Modalities Test - SDMT; p = 0.079), and health-related quality of life (European Quality of Life 5-Dimensions Questionnaire - EQ-5D-5L; p = 0.095) showed a trend of improvement but were not significant, which could be the result of a small sample and increased bias due the type II error.

CONCLUSION

According to these preliminary results, this study indicates the possible beneficial effects of long-term Tai-chi training on patients with MS. Although these findings need to be confirmed by further studies with a larger sample of participants of both genders and require more rigorous randomized controlled trials (RCT) design, our findings support the recommendation of regular and long-term Tai-chi exercise in patients with MS.

CLINICALTRIALS

GOV IDENTIFIER (RETROSPECTIVELY REGISTERED)

NCT05474209.

Male and female are not the same: a multicenter study of static and dynamic functional connectivity in relapse-remitting multiple sclerosis in China

Background

Sex-related effects have been observed in relapsing-remitting multiple sclerosis (RRMS), but their impact on functional networks remains unclear.

Objective

To investigate the sex-related differences in connectivity strength and time variability within large-scale networks in RRMS.

Methods

This is a multi-center retrospective study. A total of 208 RRMS patients (135 females; 37.55 ± 11.47 years old) and 228 healthy controls (123 females; 36.94 ± 12.17 years old) were included. All participants underwent clinical and MRI assessments. Independent component analysis was used to extract resting-state networks (RSNs). We assessed the connectivity strength using spatial maps (SMs) and static functional network connectivity (sFNC), evaluated temporal properties and dynamic functional network connectivity (dFNC) patterns of RSNs using dFNC, and investigated their associations with structural damage or clinical variables.

Results

For static connectivity, only male RRMS patients displayed decreased SMs in the attention network and reduced sFNC between the sensorimotor network and visual or frontoparietal networks compared with healthy controls [P<0.05, false discovery rate (FDR) corrected]. For dynamic connectivity, three recurring states were identified for all participants: State 1 (sparse connected state; 42%), State 2 (middle-high connected state; 36%), and State 3 (high connected state; 16%). dFNC analyses suggested that altered temporal properties and dFNC patterns only occurred in females: female patients showed a higher fractional time (P<0.001) and more dwell time in State 1 (P<0.001) with higher transitions (P=0.004) compared with healthy females. Receiver operating characteristic curves revealed that the fraction time and mean dwell time of State 1 could significantly distinguish female patients from controls (area under the curve: 0.838-0.896). In addition, female patients with RRMS also mainly showed decreased dFNC in all states, particularly within cognitive networks such as the default mode, frontoparietal, and visual networks compared with healthy females (P < 0.05, FDR corrected).

Conclusion

Our results observed alterations in connectivity strength only in male patients and time variability in female patients, suggesting that sex-related effects may play an important role in the functional impairment and reorganization of RRMS.

Static and dynamic resting-state brain activity patterns of table tennis players in 7-Tesla MRI

Table tennis involves quick and accurate motor responses during training and competition. Multiple studies have reported considerably faster visuomotor responses and expertise-related intrinsic brain activity changes among table tennis players compared with matched controls. However, the underlying neural mechanisms remain unclear. Herein, we performed static and dynamic resting-state functional magnetic resonance imaging (rs-fMRI) analyses of 20 table tennis players and 21 control subjects using 7T ultra-high field imaging. We calculated the static and dynamic amplitude of low-frequency fluctuations (ALFF) of the two groups. The results revealed that table tennis players exhibited decreased static ALFF in the left inferior temporal gyrus (lITG) compared with the control group. Voxel-wised static functional connectivity (sFC) and dynamic functional connectivity (dFC) analyses using lITG as the seed region afforded complementary and overlapping results. The table tennis players exhibited decreased sFC in the right middle temporal gyrus and left inferior parietal gyrus. Conversely, they displayed increased dFC from the lITG to prefrontal cortex, particularly the left middle frontal gyrus, left superior frontal gyrus-medial, and left superior frontal gyrus-dorsolateral. These findings suggest that table tennis players demonstrate altered visuomotor transformation and executive function pathways. Both pathways involve the lITG, which is a vital node in the ventral visual stream. These static and dynamic analyses provide complementary and overlapping results, which may help us better understand the neural mechanisms underlying the changes in intrinsic brain activity and network organization induced by long-term table tennis skill training.

Altered static and dynamic indices of intrinsic brain activity in patients with subcortical ischemic vascular disease: a resting-state functional magnetic resonance imaging analysis

PURPOSE

To explore the static and dynamic characteristics of intrinsic brain activity (IBA) in subcortical ischemic vascular disease (SIVD) patients with or without cognitive impairment.

METHODS

In total, 90 participants were recruited, including 32 SIVD patients with cognitive impairment (SIVD-CI, N = 32), 26 SIVD patients with no cognitive impairment (SIVD-NCI, N = 26), and 32 healthy controls (HC, N = 32) matched for age, gender, and education. All subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning and neuropsychological tests. Amplitude of low-frequency fluctuation (ALFF) was calculated to reflect static alterations of regional IBA. Sliding window analysis was conducted in order to explore the dynamic characteristics.

RESULTS

Both SIVD-CI and SIVD-NCI group showed significantly decreased ALFF in left angular gyrus (ANG), whereas SIVD-CI group showed increased ALFF in right superior frontal gyrus (SFG), compared with HCs. Furthermore, SIVD-CI group showed significantly decreased ALFF dynamics (dALFF) in right precuneus (PreCu) and left dorsal anterior cingulate cortex (dACC), compared with HC and SIVD-NCI groups (Gaussian random field-corrected, voxel-level P < 0.001, cluster-level P < 0.05). No dynamic changes were detected between SIVD-NCI group and HC group. The mean ALFF value in left ANG of SIVD-CI group was correlated with the score of delayed memory scale.

CONCLUSION

ANG may be a vulnerable brain region in SIVD patients. Temporal dynamic analysis could serve as a sensitive and promising method to investigate IBA alterations in SIVD patients.

Resting-State Functional Connectivity in Relapsing-Remitting Multiple Sclerosis with Mild Disability: A Data-Driven, Whole-Brain Multivoxel Pattern Analysis Study

Background: Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. Objectives: The aim of the present study was to investigate RSFC differences between people with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). Methods: We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Results: Significant group differences were noted in RSFC in three clusters distributed in the following regions: anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. Conclusions: The network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. Impact statement This study investigated resting-state functional connectivity (RSFC) in relapsing-remitting multiple sclerosis (RRMS) people with mild disability (expanded disability status scale ≤4). Whole-brain connectome-wide multivoxel pattern analysis was used for assessing RSFC. Compared with healthy controls, we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS.

Increased flexibility of brain dynamics in patients with multiple sclerosis

Patients with multiple sclerosis consistently show widespread changes in functional connectivity. Yet, alterations are heterogeneous across studies, underscoring the complexity of functional reorganization in multiple sclerosis. Here, we aim to provide new insights by applying a time-resolved graph-analytical framework to identify a clinically relevant pattern of dynamic functional connectivity reconfigurations in multiple sclerosis. Resting-state data from 75 patients with multiple sclerosis (N = 75, female:male ratio of 3:2, median age: 42.0 ± 11.0 years, median disease duration: 6 ± 11.4 years) and 75 age- and sex-matched controls (N = 75, female:male ratio of 3:2, median age: 40.2 ± 11.8 years) were analysed using multilayer community detection. Local, resting-state functional system and global levels of dynamic functional connectivity reconfiguration were characterized using graph-theoretical measures including flexibility, promiscuity, cohesion, disjointedness and entropy. Moreover, we quantified hypo- and hyper-flexibility of brain regions and derived the flexibility reorganization index as a summary measure of whole-brain reorganization. Lastly, we explored the relationship between clinical disability and altered functional dynamics. Significant increases in global flexibility (t = 2.38, P_FDR = 0.024), promiscuity (t = 1.94, P_FDR = 0.038), entropy (t = 2.17, P_FDR = 0.027) and cohesion (t = 2.45, P_FDR = 0.024) were observed in patients and were driven by pericentral, limbic and subcortical regions. Importantly, these graph metrics were correlated with clinical disability such that greater reconfiguration dynamics tracked greater disability. Moreover, patients demonstrate a systematic shift in flexibility from sensorimotor areas to transmodal areas, with the most pronounced increases located in regions with generally low dynamics in controls. Together, these findings reveal a hyperflexible reorganization of brain activity in multiple sclerosis that clusters in pericentral, subcortical and limbic areas. This functional reorganization was linked to clinical disability, providing new evidence that alterations of multilayer temporal dynamics play a role in the manifestation of multiple sclerosis.

The role of basal ganglia network in neural plasticity in neuromyelitis optica spectrum disorder with myelitis

OBJECTIVES

To explore the alternation of the brain baseline activity in neuromyelitis optica spectrum disorder (NMOSD) patients after myelitis, and characterize the representation of the neural plasticity process.

METHODS

Clinical evaluation and resting-state fMRI were obtained from 20 NMOSD patients with myelitis and 20 healthy controls, matched in gender and age. Resting-state networks (RSNs) were identified through independent component analysis (ICA), and functional connectivity (FC) intra-RSNs and between region-of-interest (ROI) seed to whole-brain voxels were analyzed. Between-group comparisons and correlations with motor performance were also assessed.

RESULTS

A total of 14 main functional RSNs were identified. Group comparison of intra-network FCs revealed that FC strengths increased in basal ganglia network (BGN) and left frontoparietal network, decreased in sensorimotor network and default mode network in NMOSD. Better motor performance was found closely correlated with higher FC of BGN. Additionally, remarkably increased FC between caudate in BGN with cerebellum, frontal lobe and parietal lobe was discovered in further ROI-based whole-brain voxels FC analysis.

CONCLUSIONS

NMOSD patients presented wide brain resting-state functional connectivity alterations after myelitis, and BGN might be highly active in the process of neural plasticity in chronic stage of NMOSD. Besides, understanding neural plasticity representation, especially that in NMOSD patients after myelitis, might have important applications in monitoring and designing rehabilitative approaches.

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.

Suboptimal states and frontoparietal network-centered incomplete compensation revealed by dynamic functional network connectivity in patients with post-stroke cognitive impairment

Background

Neural reorganization occurs after a stroke, and dynamic functional network connectivity (dFNC) pattern is associated with cognition. We hypothesized that dFNC alterations resulted from neural reorganization in post-stroke cognitive impairment (PSCI) patients, and specific dFNC patterns characterized different pathological types of PSCI.

Methods

Resting-state fMRI data were collected from 16 PSCI patients with hemorrhagic stroke (hPSCI group), 21 PSCI patients with ischemic stroke (iPSCI group), and 21 healthy controls (HC). We performed the dFNC analysis for the dynamic connectivity states, together with their topological and temporal features.

Results

We identified 10 resting-state networks (RSNs), and the dFNCs could be clustered into four reoccurring states (modular, regional, sparse, and strong). Compared with HC, the hPSCI and iPSCI patients showed lower standard deviation (SD) and coefficient of variation (CV) in the regional and modular states, respectively (p &lt; 0.05). Reduced connectivities within the primary network (visual, auditory, and sensorimotor networks) and between the primary and high-order cognitive control domains were observed (p &lt; 0.01).

Conclusion

The transition trend to suboptimal states may play a compensatory role in patients with PSCI through redundancy networks. The reduced exploratory capacity (SD and CV) in different suboptimal states characterized cognitive impairment and pathological types of PSCI. The functional disconnection between the primary and high-order cognitive control network and the frontoparietal network centered (FPN-centered) incomplete compensation may be the pathological mechanism of PSCI. These results emphasize the flexibility of neural reorganization during self-repair.

Neural distinctiveness of fatigue and low sleep quality in multiple sclerosis

BACKGROUND AND PURPOSE

Fatigue and low sleep quality in multiple sclerosis (MS) are closely related symptoms. Here, the associations between the brain's functional connectivity (FC) and fatigue and low sleep quality were investigated to determine the degree of neural distinctiveness of these symptoms.

METHOD

A hundred and four patients with relapsing-remitting MS (age 38.9 ± 10.2 years, 66 females) completed the Modified Fatigue Impact Scale and the Pittsburgh Sleep Quality Index and underwent resting-state functional magnetic resonance imaging. FC was analyzed using independent-component analysis in sensorimotor, default-mode, fronto-parietal and basal-ganglia networks. Multiple linear regression models allowed us to test the association between FC and fatigue and sleep quality whilst controlling for one another as well as for demographic, disease-related and imaging variables.

RESULTS

Higher fatigue correlated with lower sleep quality (r = 0.54, p < 0.0001). Higher fatigue was associated with lower FC of the precentral gyrus in the sensorimotor network, the precuneus in the posterior default-mode network and the superior frontal gyrus in the left fronto-parietal network, independently of sleep quality. Lower sleep quality was associated with lower FC of the left intraparietal sulcus in the left fronto-parietal network, independently of fatigue. Specific associations were found between fatigue and the sensorimotor network's global FC and between low sleep quality and the left fronto-parietal network's global FC.

CONCLUSION

Despite the high correlation between fatigue and low sleep quality in the clinical picture, our findings clearly indicate that, on the neural level, fatigue and low sleep quality in MS are associated with decreased FC in distinct functional brain networks.

Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective

•

Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages.

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Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease.

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Collapse of long-range connections and impaired hub integration characterize MS network reorganization.

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Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity.

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New perspectives might be the use of multimodal MRI and artificial intelligence.

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

A more unstable resting-state functional network in cognitively declining multiple sclerosis

Cognitive impairment is common in people with multiple sclerosis and strongly affects their daily functioning. Reports have linked disturbed cognitive functioning in multiple sclerosis to changes in the organization of the functional network. In a healthy brain, communication between brain regions and which network a region belongs to is continuously and dynamically adapted to enable adequate cognitive function. However, this dynamic network adaptation has not been investigated in multiple sclerosis, and longitudinal network data remain particularly rare. Therefore, the aim of this study was to longitudinally identify patterns of dynamic network reconfigurations that are related to the worsening of cognitive decline in multiple sclerosis. Resting-state functional MRI and cognitive scores (expanded Brief Repeatable Battery of Neuropsychological tests) were acquired in 230 patients with multiple sclerosis and 59 matched healthy controls, at baseline (mean disease duration: 15 years) and at 5-year follow-up. A sliding-window approach was used for functional MRI analyses, where brain regions were dynamically assigned to one of seven literature-based subnetworks. Dynamic reconfigurations of subnetworks were characterized using measures of promiscuity (number of subnetworks switched to), flexibility (number of switches), cohesion (mutual switches) and disjointedness (independent switches). Cross-sectional differences between cognitive groups and longitudinal changes were assessed, as well as relations with structural damage and performance on specific cognitive domains. At baseline, 23% of patients were cognitively impaired (≥2/7 domains Z < −2) and 18% were mildly impaired (≥2/7 domains Z < −1.5). Longitudinally, 28% of patients declined over time (0.25 yearly change on ≥2/7 domains based on reliable change index). Cognitively impaired patients displayed more dynamic network reconfigurations across the whole brain compared with cognitively preserved patients and controls, i.e. showing higher promiscuity (P = 0.047), flexibility (P = 0.008) and cohesion (P = 0.008). Over time, cognitively declining patients showed a further increase in cohesion (P = 0.004), which was not seen in stable patients (P = 0.544). More cohesion was related to more severe structural damage (average r = 0.166, P = 0.015) and worse verbal memory (r = −0.156, P = 0.022), information processing speed (r = −0.202, P = 0.003) and working memory (r = −0.163, P = 0.017). Cognitively impaired multiple sclerosis patients exhibited a more unstable network reconfiguration compared to preserved patients, i.e. brain regions switched between subnetworks more often, which was related to structural damage. This shift to more unstable network reconfigurations was also demonstrated longitudinally in patients that showed cognitive decline only. These results indicate the potential relevance of a progressive destabilization of network topology for understanding cognitive decline in multiple sclerosis.

Development of functional connectivity within and among the resting-state networks in anesthetized rhesus monkeys

OBJECTIVE

The age-related changes in the resting-state networks (RSNs) exhibited temporally specific patterns in humans, and humans and rhesus monkeys have similar RSNs. We hypothesized that the RSNs in rhesus monkeys experienced similar developmental patterns as humans.

METHODS

We acquired resting-state fMRI data from 62 rhesus monkeys, which were divided into childhood, adolescence, and early adulthood groups. Group independent component analysis (ICA) was used to identify monkey RSNs. We detected the between-group differences in the RSNs and static, dynamic, and effective functional network connections (FNCs) using one-way variance analysis (ANOVA) and post-hoc analysis.

RESULTS

Eight rhesus RSNs were identified, including cerebellum (CN), left and right lateral visual (LVN and RVN), posterior default mode (pDMN), visuospatial (VSN), frontal (FN), salience (SN), and sensorimotor networks (SMN). In internal connections, the CN, SN, FN, and SMN mainly matured in early adulthood. The static FNCs associated with FN, SN, pDMN primarily experienced fast descending slow ascending type (U-shaped) developmental patterns for maturation, and the dynamic FNCs related to pDMN (RVN, CN, and SMN) and SMN (CN) were mature in early adulthood. The effective FNC results showed that the pDMN and VSN (stimulated), SN (inhibited), and FN (first inhibited then stimulated) chiefly matured in early adulthood.

CONCLUSION

We identified eight monkey RSNs, which exhibited similar development patterns as humans. All the RSNs and FNCs in monkeys were not widely changed but fine-tuned. Our study clarified that the progressive synchronization, exploration, and regulation of cognitive RSNs within the pDMN, FN, SN, and VSN denoted potential maturation of the RSNs throughout development. We confirmed the development patterns of RSNs and FNCs would support the use of monkeys as a best animal model for human brain function.

Altered anterior default mode network dynamics in progressive multiple sclerosis

BACKGROUND

Modifications in brain function remain relatively unexplored in progressive multiple sclerosis (PMS), despite their potential to provide new insights into the pathophysiology of the disease at this stage.

OBJECTIVES

To characterize the dynamics of functional networks at rest in patients with PMS, and the relation with clinical disability.

METHODS

Thirty-two patients with PMS underwent clinical and cognitive assessment. The dynamic properties of functional networks, retrieved from transient brain activity, were obtained from patients and 25 healthy controls (HCs). Sixteen HCs and 19 patients underwent a 1-year follow-up (FU) clinical and imaging assessment. Differences in the dynamic metrics between groups, their longitudinal changes, and the correlation with clinical disability were explored.

RESULTS

PMS patients, compared to HCs, showed a reduced dynamic functional activation of the anterior default mode network (aDMN) and a decrease in its opposite-signed co-activation with the executive control network (ECN), at baseline and FU. Processing speed and visuo-spatial memory negatively correlated to aDMN dynamic activity. The anti-couplings between aDMN and auditory/sensory-motor network, temporal-pole/amygdala, or salience networks were differently associated with separate cognitive domains.

CONCLUSION

Patients with PMS presented an altered aDMN functional recruitment and anti-correlation with ECN. The aDMN dynamic functional activity and interaction with other networks explained cognitive disability.