Information processing speed in multiple sclerosis: Relevance of default mode network dynamics

Self-reported cognitive function mediates the relationship between employment status and cognitive functioning in persons with multiple sclerosis

BACKGROUND

Cognitive impairment (CI) is common in people with MS (PwMS). Evidence is lacking for the self-reported CI's mediation effect on employment status and objective cognitive performance. Self-reported CI was found to be unreliable and seemed to be more associated with depression rather than formal cognitive performance. We hypothesized that the link between subjective and objective assessments of cognitive functions, mood, and employment status may be more complex in PwMS than previously reported.

OBJECTIVE

The aims of this study are the following: (Romero-Pinel et al., 2022) to determine whether employment status could affect performance in cognitive function testing and (Rao et al., 1991) whether their relationship may be mediated by self-reported CI; and (Deluca et al., 2013) to determine whether self-reported depression interacts with self-reported CI in influencing performance in various cognitive domains in PwMS.

METHODOLOGY

A retrospective study was performed involving PwMS who completed the self-report Multiple Sclerosis Neuropsychological Questionnaire (MSNQ), Hospital Anxiety and Depression Scale-depression scale (HADS-D), Minimal Assessment of Cognitive Function in MS (MACFIMS) and had data regarding employment status. Included PwMS were classified as employed or unemployed. A structural equation modeling (SEM) approach was taken due to the advantage of examining multiple cognitive outcomes simultaneously while accounting for shared associations. First, a latent factor of memory and executive functioning modeled the error-free associations between both factors and a processing speed task (SDMT). Next, the model tested for the indirect effect of self-reported cognition (MSNQ) on employment status differences in each outcome (memory, speed, and executive functioning). Finally, we tested interactions between MSNQ and HADS-D on each of the outcomes.

RESULTS

We included 590 PwMS: 72.5% female, mean age 44.2 years (SD = 10.5), mean disease duration 8.6 years (SD 9.0). The majority (n = 455, 77.1%) had relapsing MS; 357 (60.5%) were employed. About half (n = 301, 51%) did not report CI on the MSNQ; of those, 213 (70.8%) were employed. The mean MSNQ for employed PwMS was 24.5 (SD = 10.7) and 29.8 (SD = 11.2) for unemployed PwMS. Employed PwMS had significantly better memory (β = .16, p < .05), executive functioning (β = .25, p < .05), and processing speed (β = .22, p < .05). MSNQ partially indirectly mediated the effect of employment status on memory (Δβ = .03, p < .05) and executive functioning (Δβ = .03, p < .05) and processing speed (Δβ = .04, p < .05), indicating that self-report CI partially explains the influence of employment status on these cognitive domains. The association between MSNQ with both memory and executive functioning was moderated by depression, meaning that in PwMS with high HADS-D scores, MSNQ was more strongly related to worse memory and executive functioning. The final model was an acceptable fit to the data (χ2(87) = 465.07, p < .05; CFI = .90, RMSEA = .08, 90% CI [.06, .09], SRMR = .05) explaining 41.20%, 38.50% and 33.40% of the variability in memory, executive functioning, and processing speed, respectively.

CONCLUSION

Self-reported CI partially explains the associations between employment status and objective cognitive assessment in PwMS. Depression may moderate the relationship between self-reported cognitive assessment and objective cognitive performance. Thus, employment status and mood may guide the interpretation of self-reported CI.

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).

Functional gradients reveal cortical hierarchy changes in multiple sclerosis

Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting-state functional MRI (rs-fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs-fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual-to-sensorimotor) and a secondary (sensory-to-transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory-transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated (ρ = 0.30 $$ \rho =0.30 $$ , p < .005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network-level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold-out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs-fMRI studies across different MS populations.

Auditory attention measured by EEG in neurological populations: systematic review of literature and meta-analysis

Sensorimotor synchronization strategies have been frequently used for gait rehabilitation in different neurological populations. Despite these positive effects on gait, attentional processes required to dynamically attend to the auditory stimuli needs elaboration. Here, we investigate auditory attention in neurological populations compared to healthy controls quantified by EEG recordings. Literature was systematically searched in databases PubMed and Web of Science. Inclusion criteria were investigation of auditory attention quantified by EEG recordings in neurological populations in cross-sectional studies. In total, 35 studies were included, including participants with Parkinson's disease (PD), stroke, Traumatic Brain Injury (TBI), Multiple Sclerosis (MS), Amyotrophic Lateral Sclerosis (ALS). A meta-analysis was performed on P3 amplitude and latency separately to look at the differences between neurological populations and healthy controls in terms of P3 amplitude and latency. Overall, neurological populations showed impairments in auditory processing in terms of magnitude and delay compared to healthy controls. Consideration of individual auditory processes and thereafter selecting and/or designing the auditory structure during sensorimotor synchronization paradigms in neurological physical rehabilitation is recommended.

Larger lesion volume in people with multiple sclerosis is associated with increased transition energies between brain states and decreased entropy of brain activity

Quantifying the relationship between the brain's functional activity patterns and its structural backbone is crucial when relating the severity of brain pathology to disability in multiple sclerosis (MS). Network control theory (NCT) characterizes the brain's energetic landscape using the structural connectome and patterns of brain activity over time. We applied NCT to investigate brain-state dynamics and energy landscapes in controls and people with MS (pwMS). We also computed entropy of brain activity and investigated its association with the dynamic landscape's transition energy and lesion volume. Brain states were identified by clustering regional brain activity vectors, and NCT was applied to compute the energy required to transition between these brain states. We found that entropy was negatively correlated with lesion volume and transition energy, and that larger transition energies were associated with pwMS with disability. This work supports the notion that shifts in the pattern of brain activity in pwMS without disability results in decreased transition energies compared to controls, but, as this shift evolves over the disease, transition energies increase beyond controls and disability occurs. Our results provide the first evidence in pwMS that larger lesion volumes result in greater transition energy between brain states and decreased entropy of brain activity.

Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice

MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.

Relationship between subjective report and objective assessment of neurocognitive functioning in persons with multiple sclerosis

OBJECTIVE

Persons with multiple sclerosis (PwMS) are at increased risk for cognitive dysfunction. Considering the impact and potential ramifications of cognitive dysfunction, it is important that cognition is routinely assessed in PwMS. Thus, it is also important to identify a screener that is accurate and sensitive to MS-related cognitive difficulties, which can inform decisions for more resource-intensive neuropsychological testing. However, research focused on available self-report screeners has been mixed, such as with the Multiple Sclerosis Neuropsychological Screening Questionnaire (MSNQ). This study aims to clarify the relationship between subjective and objective assessment of cognitive functioning in MS by examining domain-specific performance and intraindividual variability (IIV).

METHODS

87 PwMS (F = 65, M = 22) completed a comprehensive neuropsychological battery which included self- and informant-report measures of neurocognitive functioning. Scores were examined in relation to mean performance on five domains of cognitive functioning and two measures of IIV.

RESULTS

The MSNQ-Self was inversely associated with executive function, verbal memory, and visual memory; it was not associated with IIV. The MSNQ-Informant was inversely associated with executive function and verbal memory, and positively associated with one measure of IIV. The MSNQ-Self showed a correlation of moderate effect size with depression (r = .39) while the MSNQ-Informant did not.

CONCLUSIONS

Results suggest that the MSNQ-Self and MSNQ-Informant show similar utility. Our findings also suggest that domains of executive function and memory may be most salient, thus more reflected in subjective reports of cognitive functioning. Future work should further examine the impact of mood disturbance with cognitive performance and IIV.

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.

•

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

•

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

•

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

•

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.

Aberrant Cross-Tissue Functional Connectivity in Alzheimer’s Disease: Static, Dynamic, and Directional Properties

Background: BOLD signals in the gray matter (GM) and white matter (WM) are tightly coupled. However, our understanding of the cross-tissue functional network in Alzheimer’s disease (AD) is limited. Objective: We investigated the changes of cross-tissue functional connectivity (FC) metrics for the GM regions susceptible to AD damage. Methods: For each GM region in the default mode (DMN) and limbic networks, we obtained its low-order static FC with any WM region, and the high-order static FC between any two WM regions based on their FC pattern similarity with multiple GM regions. The dynamic and directional properties of cross-tissue FC were then acquired, specifically for the regional pairs whose low- or high-order static FCs showed significant differences between AD and normal control (NC). Moreover, these cross-tissue FC metrics were correlated with voxel-based GM volumes and MMSE in all participants. Results: Compared to NC, AD patients showed decreased low-order static FCs between the intra-hemispheric GM-WM pairs (right ITG-right fornix; left MoFG-left posterior corona radiata), and increased low-order static, dynamic, and directional FCs between the inter-hemispheric GM-WM pairs (right MTG-left superior/posterior corona radiata). The high-order static and directional FCs between the left cingulate bundle-left tapetum were increased in AD, based on their FCs with the GMs of DMN. Those decreased and increased cross-tissue FC metrics in AD had opposite correlations with memory-related GM volumes and MMSE (positive for the decreased and negative for the increased). Conclusion: Cross-tissue FC metrics showed opposite changes in AD, possibly as useful neuroimaging biomarkers to reflect neurodegenerative and compensatory mechanisms.

Italian translation and validation of fatigue symptoms and impacts questionnaire in relapsing multiple sclerosis (FSIQ-RMS)

BACKGROUND

Fatigue is a disabling symptom of multiple sclerosis (MS) and impacts on daily life. The Fatigue Symptoms and Impacts Questionnaire-Relapsing Multiple Sclerosis (FSIQ-RMS) is a new 20-item tool that investigates the aspects of fatigue in MS. It concerns motor, cognitive, social, and emotional aspects of fatigue. We aim at validating the Italian version of FSIQ-RMS in an Italian population of MS patients and demonstrate its reliability and construct validity.

METHODS

We included patients with diagnosis of MS, age between 18 and 70 years with ability to participate in a 90-min interview. Each patient completed the Italian version of FSIQ-RMS and Fatigue Severity Scale (FSS) at the same time. Construct validity was explored by the exploratory factor analysis; reliability was assessed with Cronbach's alpha; and test-retest stability was examined through intraclass correlation coefficient (ICC). Concurrent validity was calculated using Pearson's correlation.

RESULTS

We enrolled 171 patients (126 female and 45 male), 83% with relapsing MS (RMS), and 17% with secondary progressive MS (SPMS). Italian FSIQ-RMS showed a Cronbach's alpha of 0.92; ICC was 0.96. Pearson's correlation coefficient between FSIQ-RMS and FSS total score was statistically significant (p < 0.01); FSIQ-RMS inversely correlated also with BMI and positively with EDSS.

CONCLUSION

The Italian version of FSIQ-RMS has excellent psychometric properties and can be used in research and clinical setting to evaluate physical, cognitive, and social fatigue in both RMS and SPMS.

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.

Divergent time-varying connectivity of thalamic sub-regions characterizes clinical phenotypes and cognitive status in multiple sclerosis

We aimed to investigate abnormal time-varying functional connectivity (FC) for thalamic sub-regions in multiple sclerosis (MS) and their clinical, cognitive and MRI correlates. Eighty-nine MS patients (49 relapsing-remitting [RR] MS; 40 progressive [P] MS) and 53 matched healthy controls underwent neurological, neuropsychological and resting state fMRI assessment. Time-varying connectivity (TVC) was quantified using sliding-window seed-voxel correlation analysis. Standard deviation of FC across windows was taken as measure of TVC, while mean connectivity across windows expressed static FC. MS patients showed reduced TVC vs controls between most of thalamic sub-regions and fronto-temporo-occipital regions. At the same time, they showed increased static FC between all thalamic sub-regions and structurally connected cortico-subcortical regions. TVC reduction was mainly driven by RRMS; while PMS exhibited a variable pattern of TVC abnormalities, characterized by reduced TVC between frontal/motor thalamic seeds and default-mode network areas and increased TVC vs controls/RRMS between posterior thalamic sub-regions and occipito-temporo-insular cortices, associated with severity of clinical disability. Compared with controls, both cognitively preserved and impaired patients showed reduced TVC between anterior thalamic sub-regions and frontal cortex. Cognitively impaired patients also showed increased TVC of the right postcentral thalamic sub-region with the cingulate cortex and postcentral gyrus vs both controls and cognitively preserved patients. Divergent patterns of TVC thalamic abnormalities were found between RRMS and PMS patients. TVC reduction in RRMS may represent the attempt of thalamic network to keep with stable connections. Conversely, increased TVC of posterior thalamic sub-regions characterized PMS and cognitively impaired MS, possibly reflecting maladaptive mechanisms.

Dynamic Functional Connectivity Better Predicts Disability Than Structural and Static Functional Connectivity in People With Multiple Sclerosis

Background: Advanced imaging techniques such as diffusion and functional MRI can be used to identify pathology-related changes to the brain's structural and functional connectivity (SC and FC) networks and mapping of these changes to disability and compensatory mechanisms in people with multiple sclerosis (pwMS). No study to date performed a comparison study to investigate which connectivity type (SC, static or dynamic FC) better distinguishes healthy controls (HC) from pwMS and/or classifies pwMS by disability status.

Aims: We aim to compare the performance of SC, static FC, and dynamic FC (dFC) in classifying (a) HC vs. pwMS and (b) pwMS who have no disability vs. with disability. The secondary objective of the study is to identify which brain regions' connectome measures contribute most to the classification tasks.

Materials and Methods: One hundred pwMS and 19 HC were included. Expanded Disability Status Scale (EDSS) was used to assess disability, where 67 pwMS who had EDSS<2 were considered as not having disability. Diffusion and resting-state functional MRI were used to compute the SC and FC matrices, respectively. Logistic regression with ridge regularization was performed, where the models included demographics/clinical information and either pairwise entries or regional summaries from one of the following matrices: SC, FC, and dFC. The performance of the models was assessed using the area under the receiver operating curve (AUC).

Results: In classifying HC vs. pwMS, the regional SC model significantly outperformed others with a median AUC of 0.89 (p <0.05). In classifying pwMS by disability status, the regional dFC and dFC metrics models significantly outperformed others with a median AUC of 0.65 and 0.61 (p < 0.05). Regional SC in the dorsal attention, subcortical and cerebellar networks were the most important variables in the HC vs. pwMS classification task. Increased regional dFC in dorsal attention and visual networks and decreased regional dFC in frontoparietal and cerebellar networks in certain dFC states was associated with being in the group of pwMS with evidence of disability.

Discussion: Damage to SCs is a hallmark of MS and, unsurprisingly, the most accurate connectomic measure in classifying patients and controls. On the other hand, dynamic FC metrics were most important for determining disability level in pwMS, and could represent functional compensation in response to white matter pathology in pwMS.

Analyzing the Effect of Resolution of Network Nodes on the Resting State Functional Connectivity Maps of Schizophrenic Human Brains

Functional connectivity (FC) mapping from resting-state functional magnetic resonance imaging (rsfMRI) data is a widely used technique to characterize the brain abnormalities in mental health disorders. Using atlases for brain parcellation is an important intermediate step in calculation of FC maps. Atlases with varying resolution (number of nodes in an atlas) have been deployed by researchers to study the abnormal brain functions in Schizophrenia. In this work, we compared the variations in FC maps of Schizophrenic brains obtained from three different atlases: AAL atlas (2002), Dosenbach atlas (2010), and the Brainnetome atlas (2016). To evaluate the atlas-dependent variations in FC maps, we relied on the capability of the features of FC maps in accurately classifying a given data into healthy or Schizophrenia group. Our results indicate that the high-resolution Dosenbach and Brainnetome atlases perform better than AAL atlas in terms of the accuracy, sensitivity and specificity of the SVM classifier.

Functional network dynamics and decreased conscientiousness in multiple sclerosis

BACKGROUND

Conscientiousness is a personality trait that declines in people with multiple sclerosis (PwMS) and its decline predicts worse clinical outcomes. This study aims to investigate the neural underpinnings of lower Conscientiousness in PwMS by examining MRI anomalies in functional network dynamics.

METHODS

70 PwMS and 50 healthy controls underwent personality assessment and resting-state MRI. Associations with dynamic functional network properties (i.e., eigenvector centrality) were evaluated, using a dynamic sliding-window approach.

RESULTS

In PwMS, lower Conscientiousness was associated with increased variability of centrality in the left insula (t_max = 4.21) and right inferior parietal lobule (t_max = 3.79); a relationship also observed in regressions accounting for handedness, disease duration, disability, and tract disruption in relevant structural networks (ΔR² = 0.071, p = 0.003; ΔR² = 0.094, p = 0.004). Centrality dynamics of the observed regions were not associated with Neuroticism (R² < 0.001, p = 0.956; R² < 0.001, p = 0.945). As well, higher Conscientiousness was associated with greater variability in connectivity for the left insula with the default-mode network (F = 3.92, p = 0.023) and limbic network (F = 5.66, p = 0.005).

CONCLUSION

Lower Conscientiousness in PwMS was associated with increased variability in network centrality, most prominently for the left insula and right inferior parietal cortex. This effect, specific to Conscientiousness and significant after accounting for disability and structural network damage, could indicate that overall stable network centrality is lost in patients with low Conscientiousness, especially for the insula and right parietal cortex. The positive relationship between Conscientiousness and variability of connectivity between left insula and default-mode network potentially affirms that dynamics between the salience and default-mode networks is related to the regulation of behavior.

A systematic review of resting state functional MRI connectivity changes and cognitive impairment in multiple sclerosis

INTRODUCTION

Cognitive impairment in multiple sclerosis (MS) is increasingly being investigated with resting state functional MRI (rs-fMRI) functional connectivity (FC) . However, results remain difficult to interpret, showing both high and low FC associated with cognitive impairment. We conducted a systematic review of rs-fMRI studies in MS to understand whether the direction of FC change relates to cognitive dysfunction, and how this may be influenced by the choice of methodology.

METHODS

Embase, Medline and PsycINFO were searched for studies assessing cognitive function and rs-fMRI FC in adults with MS.

RESULTS

Fifty-seven studies were included in a narrative synthesis. Of these, 50 found an association between cognitive impairment and FC abnormalities. Worse cognition was linked to high FC in 18 studies, and to low FC in 17 studies. Nine studies found patterns of both high and low FC related to poor cognitive performance, in different regions or for different MR metrics. There was no clear link to increased FC during early stages of MS and reduced FC in later stages, as predicted by common models of MS pathology. Throughout, we found substantial heterogeneity in study methodology, and carefully consider how this may impact on the observed findings.

DISCUSSION

These results indicate an urgent need for greater standardisation in the field - in terms of the choice of MRI analysis and the definition of cognitive impairment. This will allow us to use rs-fMRI FC as a biomarker in future clinical studies, and as a tool to understand mechanisms underpinning cognitive symptoms in MS.

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS.

Performance validity in outpatients with multiple sclerosis and cognitive complaints

BACKGROUND

Suboptimal performance during neuropsychological assessment renders cognitive test results invalid. However, suboptimal performance has rarely been investigated in multiple sclerosis (MS).

OBJECTIVES

To investigate potential underlying mechanisms of suboptimal performance in MS.

METHODS

Performance validity testing, neuropsychological assessments, neuroimaging, and questionnaires were analyzed in 99 MS outpatients with cognitive complaints. Based on performance validity testing patients were classified as valid or invalid performers, and based on neuropsychological test results as cognitively impaired or preserved. Group comparisons and correlational analyses were performed on demographics, patient-reported, and disease-related outcomes.

RESULTS

Twenty percent displayed invalid performance. Invalid and valid performers did not differ regarding demographic, patient-reported, and disease-related outcomes. Disease severity of invalid and valid performers with cognitive impairment was comparable, but worse than cognitively preserved valid performers. Lower performance validity scores related to lower cognitive functioning, lower education, being male, and higher disability levels (p < 0.05).

CONCLUSION

Suboptimal performance frequently occurs in patients with MS and cognitive complaints. In both clinical practice and in cognitive research, suboptimal performance should be considered in the interpretation of cognitive outcomes. Identification of factors that differentiate between suboptimal and optimal performers with cognitive impairment needs further exploration.

Microstructural MRI Correlates of Cognitive Impairment in Multiple Sclerosis: The Role of Deep Gray Matter

Although cognitive impairment (CI) is frequently observed in people with multiple sclerosis (pwMS), its pathogenesis is still controversial. Conflicting results emerged concerning the role of microstructural gray matter (GM) damage especially when involving the deep GM structures. In this study, we aimed at evaluating whether differences in cortical and deep GM structures between apparently cognitively normal (ACN) and CI pwMS (36 subjects in total) are present, using an extensive set of diffusion MRI (dMRI) indices and conventional morphometry measures. The results revealed increased anisotropy and restriction over several deep GM structures in CI compared with ACN pwMS, while no changes in volume were present in the same areas. Conversely, reduced anisotropy/restriction values were detected in cortical regions, mostly the pericalcarine cortex and precuneus, combined with reduced thickness of the superior frontal gyrus and insula. Most of the dMRI metrics but none of the morphometric indices correlated with the Symbol Digit Modality Test. These results suggest that deep GM microstructural damage can be a strong anatomical substrate of CI in pwMS and might allow identifying pwMS at higher risk of developing CI.

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.

Dynamic Functional Connectivity in the Main Clinical Phenotypes of Multiple Sclerosis

Introduction: Dynamic functional connectivity (dFC) allows capturing recurring patterns (states) of interaction among functional networks. In this study, we investigated resting state (RS) dFC abnormalities across the different clinical phenotypes of multiple sclerosis (MS) and assessed their correlation with motor and cognitive performances. Methods: RS functional magnetic resonance imaging (fMRI) and 3D T1-weighted MRI data were acquired from 128 MS patients (69 relapsing-remitting [RR] MS, 34 secondary progressive [SP] MS, and 25 primary progressive [PP] MS) and 40 healthy controls (HC). RS fMRI data underwent independent component analysis and sliding-window correlations, to identify recurring dFC states and between-group dFC differences in the main networks. Results: dFC identified three recurring connectivity states: State 1 (frequency of appearance during fMRI acquisition = 57%, low dFC strength), State 2 (frequency = 19%, middle-high dFC strength), and State 3 (frequency = 24%, high sensorimotor and visual dFC strength). Compared to HC, MS (as a whole), RRMS, and PPMS patients exhibited lower State1/State 3 dFC (p = 0.0001, corrected) between sensorimotor, cerebellar, and cognitive networks, and some dFC increments (p = 0.001-0.05, uncorrected) in sensorimotor, visual, default-mode, and frontal/attention networks in States 2 and 3. Similar results were observed in SPMS versus RRMS patients. In MS, dFC decrease in sensorimotor, default-mode, and frontal/attention networks was correlated with worse motor and cognitive performances. Conclusions: MS patients exhibited overall lower dFC, and marginally higher dFC in sensorimotor/cognitive networks in the less-frequent middle/high-connected States. dFC abnormalities became more severe in progressive MS and correlated with motor and cognitive impairment, suggesting the presence of maladaptive mechanisms concomitant with accumulation of damage.

Dalfampridine improves slowed processing speed in multiple sclerosis patients with mild motor disability: post hoc analysis of a randomized controlled trial

Objective

To evaluate baseline characteristics predictive of improving information processing speed in multiple sclerosis (MS) and the relationship between cognitive and motor response to dalfampridine (DA) treatment.

Methods

This is a post hoc analysis of a randomized, double-blind, placebo-controlled trial in patients with MS randomized to receive DA 10 mg or placebo twice daily for 12 consecutive weeks. Here, we include only data from 71 patients in the arm treated with DA. According to the median value of Symbol Digit Modalities Test (SDMT) response, patients were categorized as "full responders" (FR) or "partially responders" (PR).

Results

There was higher possibility of being FR in the presence of a baseline lower Expanded Disability Status Scale [odds ratio (OR) 0.69; 95% confidence interval (CI) 0.5-0.97, p = 0.034], a higher Multiple Sclerosis Functional Composite value (OR 1.37; 95%CI 1.05-1.8, p = 0.022), a lower Timed 25-Foot Walk Test (OR 0.76; 95% CI 0.6-0.98, p = 0.033), and a lower 9-Hole Peg Test with dominant hand (OR 0.92; 95% CI 0.86-0.99, p = 0.029). FR group did not show any significant improvement of motor performance compared with PR group.

Conclusion

The current analysis shows that in MS patients with cognitive deficit, the greatest improvement in SDMT provided by DA was observed in patients with milder motor impairment; cognitive and motor responses to treatments are not related.

Trial registration

EU Clinical Trials Register; ID 2013-002558-64 (https://www.clinicaltrialsregister.eu/ctr-search/search?query=2013-002558-64).

Delayed access to conscious processing in multiple sclerosis: Reduced cortical activation and impaired structural connectivity

Although multiple sclerosis (MS) is frequently accompanied by visuo‐cognitive impairment, especially functional brain mechanisms underlying this impairment are still not well understood. Consequently, we used a functional MRI (fMRI) backward masking task to study visual information processing stratifying unconscious and conscious in MS. Specifically, 30 persons with MS (pwMS) and 34 healthy controls (HC) were shown target stimuli followed by a mask presented 8–150 ms later and had to compare the target to a reference stimulus. Retinal integrity (via optical coherence tomography), optic tract integrity (visual evoked potential; VEP) and whole brain structural connectivity (probabilistic tractography) were assessed as complementary structural brain integrity markers. On a psychophysical level, pwMS reached conscious access later than HC (50 vs. 16 ms, p < .001). The delay increased with disease duration (p < .001, β = .37) and disability (p < .001, β = .24), but did not correlate with conscious information processing speed (Symbol digit modality test, β = .07, p = .817). No association was found for VEP and retinal integrity markers. Moreover, pwMS were characterized by decreased brain activation during unconscious processing compared with HC. No group differences were found during conscious processing. Finally, a complementary structural brain integrity analysis showed that a reduced fractional anisotropy in corpus callosum and an impaired connection between right insula and primary visual areas was related to delayed conscious access in pwMS. Our study revealed slowed conscious access to visual stimulus material in MS and a complex pattern of functional and structural alterations coupled to unconscious processing of/delayed conscious access to visual stimulus material in MS.

Mind the gap: from neurons to networks to outcomes in multiple sclerosis

MRI studies have provided valuable insights into the structure and function of neural networks, particularly in health and in classical neurodegenerative conditions such as Alzheimer disease. However, such work is also highly relevant in other diseases of the CNS, including multiple sclerosis (MS). In this Review, we consider the effects of MS pathology on brain networks, as assessed using MRI, and how these changes to brain networks translate into clinical impairments. We also discuss how this knowledge can inform the targeting of MS treatments and the potential future directions for research in this area. Studying MS is challenging as its pathology involves neurodegenerative and focal inflammatory elements, both of which could disrupt neural networks. The disruption of white matter tracts in MS is reflected in changes in network efficiency, an increasingly random grey matter network topology, relative cortical disconnection, and both increases and decreases in connectivity centred around hubs such as the thalamus and the default mode network. The results of initial longitudinal studies suggest that these changes evolve rather than simply increase over time and are linked with clinical features. Studies have also identified a potential role for treatments that functionally modify neural networks as opposed to altering their structure.

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

BACKGROUND

More than 80% of multiple sclerosis (MS) patients experience symptoms of fatigue. MS-related fatigue is only partly explained by structural (lesions and atrophy) and functional (brain activation and conventional static functional connectivity) brain properties.

OBJECTIVES

To investigate the relationship of dynamic functional connectivity (dFC) with fatigue in MS patients and to compare dFC with commonly used clinical and MRI parameters.

METHODS

In 35 relapsing-remitting MS patients (age: 42.83 years, female/male: 20/15, disease duration: 11 years) and 19 healthy controls (HCs) (age: 41.38 years, female/male: 11/8), fatigue was measured using the CIS-20r questionnaire at baseline and at 6-month follow-up. All subjects underwent structural and resting-state functional MRI at baseline. Global static functional connectivity (sFC) and dynamic functional connectivity (dFC) were calculated. dFC was assessed using a sliding-window approach by calculating the summed difference (diff) and coefficient of variation (cv) across windows. Moreover, regional connectivity between regions previously associated with fatigue in MS was estimated (i.e. basal ganglia and regions of the Default Mode Network (DMN): medial prefrontal, posterior cingulate and precuneal cortices). Hierarchical regression analyses were performed with forward selection to identify the most important correlates of fatigue at baseline. Results were not corrected for multiple testing due to the exploratory nature of the study.

RESULTS

Patients were more fatigued than HCs at baseline (p = 0.001) and follow-up (p = 0.002) and fatigue in patients was stable over time (p = 0.213). Patients had significantly higher baseline global dFC than HCs, but no difference in basal ganglia-DMN dFC. In the regression model for baseline fatigue in patients, basal ganglia-DMN dFC-cv (standardized β = -0.353) explained 12.5% additional variance on top of EDSS (p = 0.032). Post-hoc analysis revealed higher basal ganglia-DMN dFC-cv in non-fatigued patients compared to healthy controls (p = 0.013), whereas fatigued patients and healthy controls showed similar basal ganglia-DMN dFC.

CONCLUSIONS

Less dynamic connectivity between the basal ganglia and the cortex is associated with greater fatigue in MS patients, independent of disability status. Within patients, lower dynamics of these connections could relate to lower efficiency and increased fatigue. Increased dynamics in non-fatigued patients compared to healthy controls might represent a network organization that protects against fatigue or signal early network dysfunction.

Symbol Digit Modalities Test Variant in a Smartphone App for Persons With Multiple Sclerosis: Validation Study

Background

The decline of cognitive processing speed (CPS) is a common dysfunction in persons with multiple sclerosis (MS). The Symbol Digit Modalities Test (SDMT) is widely used to formally quantify CPS. We implemented a variant of the SDMT in MS sherpa, a smartphone app for persons with MS.

Objective

The aim of this study was to investigate the construct validity and test-retest reliability of the MS sherpa smartphone variant of the SDMT (sSDMT).

Methods

We performed a validation study with 25 persons with relapsing-remitting MS and 79 healthy control (HC) subjects. In the HC group, 21 subjects were matched to the persons with MS with regard to age, gender, and education and they followed the same assessment schedule as the persons with MS (the “HC matched” group) and 58 subjects had a less intense assessment schedule to determine reference values (the “HC normative” group). Intraclass correlation coefficients (ICCs) were determined between the paper-and-pencil SDMT and its smartphone variant (sSDMT) on 2 occasions, 4 weeks apart. Other ICCs were determined for test-retest reliability, which were derived from 10 smartphone tests per study participant, with 3 days in between each test. Seven study participants with MS were interviewed regarding their experiences with the sSDMT.

Results

The SDMT scores were on average 12.06% higher than the sSDMT scores, with a standard deviation of 10.68%. An ICC of 0.838 was found for the construct validity of the sSDMT in the combined analysis of persons with MS and HC subjects. Average ICCs for test-retest reliability of the sSDMT for persons with MS, the HC matched group, and the HC normative group were 0.874, 0.857, and 0.867, respectively. The practice effect was significant between the first and the second test of the persons with MS and the HC matched group and trivial for all other test-retests. The interviewed study participants expressed a positive attitude toward the sSDMT, but they also discussed the importance of adapting a smartphone cognition test in accordance with the needs of the individual persons with MS.

Conclusions

The high correlation between sSDMT and the conventional SDMT scores indicates a very good construct validity. Similarly, high correlations underpin a very good test-retest reliability of the sSDMT. We conclude that the sSDMT has the potential to be used as a tool to monitor CPS in persons with MS, both in clinical studies and in clinical practice.

Altered brain network function during attention-modulated visual processing in multiple sclerosis

BACKGROUND

Multiple sclerosis may damage cognitive performance in several domains, including attention. Although attention network deficits were described during rest, studies that investigate their function during task performance are scarce.

OBJECTIVE

To investigate connectivity within and between task-related networks in multiple sclerosis during a visual attention task as a function of cognitive performance.

METHODS

A total of 23 relapsing-remitting multiple sclerosis (RRMS) patients and 29 healthy controls underwent task-functional magnetic resonance imaging (fMRI) scans using a visual attention paradigm on a 3T scanner. Scans were analysed using tensor-independent component analysis (TICA). Functional connectivity was calculated within and between components. We assessed cognitive function with the Brief International Cognitive Assessment for MS (BICAMS) battery.

RESULTS

TICA extracted components related to visual processing, attention, executive function and the default-mode network. Subject scores of visual/attention-related and executive components were greater in healthy controls (p < 0.032, p < 0.023). Connectivity between visual/attention-related and default-mode components was higher in patients (p < 0.043), correlating with Brief Visuospatial Memory Test-Revised (BVMT-R) scores (R = -0.48, p < 0.036). Patients showed reduced connectivity between the right intraparietal sulcus (rIPS) and frontal eye field (rFEF), and bilateral frontal eye fields (p < 0.012, p < 0.003). Reduced rIPS-rFEF connectivity came with lower Symbol Digit Modalities Test (SDMT)/BVMT-R scores in patients (R = 0.53, p < 0.02, R = 0.46, p < 0.049).

CONCLUSION

Attention-related networks show altered connectivity during task performance in RRMS patients, scaling with cognitive disability.

Both Stationary and Dynamic Functional Interhemispheric Connectivity Are Strongly Associated With Performance on Cognitive Tests in Multiple Sclerosis

Although functional connectivity has been extensively studied in MS, robust estimates of both stationary (static connectivity at the time) and dynamic (connectivity variation across time) functional connectivity has not been commonly evaluated and neither has its association to cognition. In this study, we focused on interhemispheric connections as previous research has shown links between anatomical homologous connections and cognition. We examined functional interhemispheric connectivity (IC) in MS during resting-state functional MRI using both stationary and dynamic strategies and related connectivity measures to processing speed performance. Twenty-five patients with relapsing-remitting MS and 41 controls were recruited. Stationary functional IC was assessed between homologous Regions of Interest (ROIs) using correlation. For dynamic IC, a sliding window approach was used to quantify changes between homologous ROIs across time. We related IC measures to cognitive performance with correlation and regression. Compared to control subjects, MS demonstrated increased IC across homologous regions, which accurately predicted performance on the symbol digit modalities test (SDMT) (R ² = 0.96) and paced auditory serial addition test (PASAT) (R ² = 0.59). Dynamic measures were not different between the 2 groups, but dynamic IC was related to PASAT scores. The associations between stationary/dynamic connectivity and cognitive tests demonstrated that different aspects of functional IC were associated with cognitive processes. Processing speed measured in SDMT was associated with static interhemispheric connections and better PASAT performance, which requires working memory, sustain attention, and processing speed, was more related to rigid IC, underlining the neurophysiological mechanism of cognition in MS.

Disrupted Neural Synchrony Mediates the Relationship between White Matter Integrity and Cognitive Performance in Older Adults

Our main goal was to determine the influence of white matter integrity on the dynamic coupling between brain regions and the individual variability of cognitive performance in older adults. Electroencephalography was recorded while participants performed a task specifically designed to engage working memory and inhibitory processes, and the associations among functional activity, structural integrity, and cognitive performance were assessed. We found that the association between white matter microstructural integrity and cognitive functioning with aging is mediated by time-varying alpha and gamma phase-locking value. Specifically, better preservation of the inferior fronto-occipital fasciculus in older individuals drives faster task-related modulations of alpha and gamma long-range phase-locking value between the inferior frontal gyrus and occipital lobe and lower local phase-amplitude coupling in occipital lobes, which in turn drives better cognitive control performance. Our results help delineate the role of individual variability of white matter microstructure in dynamic synchrony and cognitive performance during normal aging.

The Cambridge Neuropsychological Test Automated Battery (CANTAB) Versus the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS) for the Assessment of Cognitive Function in Patients with Multiple Sclerosis

BACKGROUND

We determined how the Cambridge Neuropsychological Test Automated Battery (CANTAB) compared to the Minimal Assessment of Cognitive Function in multiple sclerosis (MACFIMS) in terms of sensitivity, specificity, and predictive values in detecting cognitive impairment in multiple sclerosis (MS) patients.

METHODS

Sixty MS patients were recruited, 2 of whom were lost to follow-up. On the first day of the neuropsychological examination, the standard MACFIMS battery and the day after, the CANTAB (paired-associate learning (PAL), reaction time (RTI), rapid visual information processing (RVP), and spatial working memory tasks (SWM)) were completed by the patients. The sensitivity, specificity, and predictive values of the CANTAB in the differentiation of cognitively impaired (CI) patients from not cognitively impaired (NCI) ones were compared with those of the MACFIMS battery using appropriate statistical tests.

RESULTS

Fifty-eight patients were categorized into two groups of CI (n=16 (27.58%)) and NCI (n=42 (72.41%)) based on the MACFIMS battery standard criteria. The best reporter indices and their cut-off scores for differentiation of CI from NCI patients in each task of the CANTAB were "total errors=13" for PAL, "between errors=26" for SWM, "five-choice reaction time=368.57" for RTI, and "mean latency=522.14" for RVP. The optimal cut-off point for distinguishing CI from NCI in the CANTAB was found to be an impaired function in 3 or more tasks [(AUC (95% CI): 0.97 (0.94-1.00); p<0.001)]. Accordingly, 36.20% of the patients were CI based on the CANTAB criteria. The inter-test agreement (CANTAB and MACFIMS batteries) was found to be the highest (Cohen's κ (95% CI): 0.80 (0.64-0.96)).

CONCLUSION

Results confirm that the CANTAB can discriminate CI from NCI MS patients with high accuracy, and its results are comparable to those of the MACFIMS battery; thus, they might be interchangeably used in the clinical practice.

Functional Connectivity and Structural Disruption in the Default-Mode Network Predicts Cognitive Rehabilitation Outcomes in Multiple Sclerosis

BACKGROUND AND PURPOSE

Efficacy of restorative cognitive rehabilitation can be predicted from baseline patient factors. In addition, patient profiles of functional connectivity are associated with cognitive reserve and moderate the structure-cognition relationship in people with multiple sclerosis (PwMS). Such interactions may help predict which PwMS will benefit most from cognitive rehabilitation. Our objective was to determine whether patient response to restorative cognitive rehabilitation is predictable from baseline structural network disruption and whether this relationship is moderated by functional connectivity.

METHODS

For this single-arm repeated measures study, we recruited 25 PwMS for a 12-week program. Following magnetic resonance imaging, participants were tested using the Symbol Digit Modalities Test (SDMT) pre- and postrehabilitation. Baseline patterns of structural and functional connectivity were characterized relative to healthy controls.

RESULTS

Lower white matter tract disruption in a network of region-pairs centered on the precuneus and posterior cingulate (default-mode network regions) predicted greater postrehabilitation SDMT improvement (P = .048). This relationship was moderated by profiles of functional connectivity within the network (R² = .385, P = .017, Interaction β = -.415).

CONCLUSION

Patient response to restorative cognitive rehabilitation is predictable from the interaction between structural network disruption and functional connectivity in the default-mode network. This effect may be related to cognitive reserve.

Working memory load-dependent changes in cortical network connectivity estimated by machine learning

Working memory engages multiple distributed brain networks to support goal-directed behavior and higher order cognition. Dysfunction in working memory has been associated with cognitive impairment in neuropsychiatric disorders. It is important to characterize the interactions among cortical networks that are sensitive to working memory load since such interactions can also hint at the impaired dynamics in patients with poor working memory performance. Functional connectivity is a powerful tool used to investigate coordinated activity among local and distant brain regions. Here, we identified connectivity footprints that differentiate task states representing distinct working memory load levels. We employed linear support vector machines to decode working memory load from task-based functional connectivity matrices in 177 healthy adults. Using neighborhood component analysis, we also identified the most important connectivity pairs in classifying high and low working memory loads. We found that between-network coupling among frontoparietal, ventral attention and default mode networks, and within-network connectivity in ventral attention network are the most important factors in classifying low vs. high working memory load. Task-based within-network connectivity profiles at high working memory load in ventral attention and default mode networks were the most predictive of load-related increases in response times. Our findings reveal the large-scale impact of working memory load on the cerebral cortex and highlight the complex dynamics of intrinsic brain networks during active task states.

Multi-scale resting state functional reorganization in response to multiple sclerosis damage

PURPOSE

In multiple sclerosis (MS), how brain functional changes relate to clinical conditions is still a matter of debate. The aim of this study was to investigate how functional connectivity (FC) reorganization at three different scales, ranging from local to whole brain, is related to tissue damage and disability.

METHODS

One-hundred-nineteen patients with MS were clinically evaluated with the Expanded Disability Status Scale and the Multiple Sclerosis Functional Composite. Patients and 42 healthy controls underwent a multimodal 3 T MRI, including resting-state functional MRI.

RESULTS

We identified 16 resting-state networks via independent component analysis and measured within-network, between-network, and whole-brain (global efficiency and degree centrality) FC. Within-network FC was higher in patients than in controls in default mode, frontoparietal, and executive-control networks, and corresponded to low clinical impairment (default mode network versus Expanded Disability Status Scale r = - 0.31, p < 0.01; right frontoparietal network versus Paced Auditory Serial Addition Test r = 0.33, p < 0.01). All measures of between-network and whole-brain FC, except default mode network global efficiency, were lower in patients than in controls, and corresponded to high disability (i.e., basal ganglia global efficiency versus Timed 25-Foot Walk r = - 0.25, p < 0.03; default mode global efficiency versus Expanded Disability Status Scale r = - 0.44, p < 0.001). Altered measures of within-network, between-network, and whole-brain FC were combined in functional indices that were linearly related to disease duration, Paced Auditory Serial Addition Test and lesion load and non-linearly related to Expanded Disability Status Scale.

CONCLUSION

We suggest that the combined evaluation of functional alterations occurring at different levels, from local to whole brain, could exhaustively describe neuroplastic changes in MS, while increased within-network FC likely represents adaptive compensatory processes, decreased between-network and whole-brain FC likely represent loss of functional network integration consequent to structural disruption.

Action observation training promotes motor improvement and modulates functional network dynamic connectivity in multiple sclerosis

We investigated modifications of resting state dynamic functional network connectivity (dFNC) following a 2-week action observation training (AOT) in 46 right-handed healthy controls (HC) and 41 patients with multiple sclerosis (pwMS) and dominant-hand motor impairment, who were randomized to AOT or control (C) training. PwMS had decreased baseline dFNC versus HC. After training, MS groups improved in right upper limb functions, mainly in AOT, and showed dFNC increase (larger in MS-AOT vs MS-C) in sensorimotor and cognitive networks (p range, ⩽0.001-0.01). Both HC groups showed decreased dFNC over time (p range, ⩽0.001-0.01). Clinical improvements following interventions correlated with sensorimotor and cognitive dFNC changes, suggesting their possible role in motor recovery.

Multiple brain networks support processing speed abilities of patients with multiple sclerosis

Objectives: Many people affected by multiple sclerosis (MS) experience cognitive impairment, especially decreases in information processing speed (PS). Neural disconnection is thought to represent the neural marker of this symptom, although the role played by alterations of specific functional brain networks still remains unclear. The aim is to investigate and compare patterns of association between PS-demanding cognitive performance and functional connectivity across two MS phenotypes. Methods: Forty patients with relapsing-remitting MS (RRMS) and 25 with secondary progressive MS (SPMS) had neuropsychological and MRI assessments. Multiple regression models were used to investigate the relationship between performance on tests of visuomotor and verbal PS, and on the verbal fluency tests, and functional connectivity of four cognitive networks, i.e. left and right frontoparietal, salience and default-mode, and two control networks, i.e. visual and sensorimotor. Results: Patients with SPMS were older and had longer disease history than patients with RRMS and presented with worse overall clinical conditions: higher disease severity, total lesion volume, and cognitive impairment rates. However, in both patient samples, cognitive performance across tests was negatively correlated with functional connectivity of the salience and default-mode networks, and positively with connectivity of the left frontoparietal network. Only the visuomotor PS scores of the RRMS group were also associated with connectivity of the sensorimotor network. Conclusions: PS-demanding cognitive performance in patients with MS appears mainly associated with strength of functional connectivity of frontal networks involved in the evaluation and manipulation of information, as well as the default mode network. These results are in line with the hypothesis that multiple neural networks are needed to support normal cognitive performance across MS phenotypes. However, different PS measures showed partially different patterns of association with functional connectivity. Therefore, further investigations are needed to clarify the contribution of inter-network communication to specific cognitive deficits due to MS.

Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis

Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called “sliding windows,” in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.

Reduced Network Dynamics on Functional MRI Signals Cognitive Impairment in Multiple Sclerosis

Background Previous studies have demonstrated extensive functional network disturbances in patients with multiple sclerosis (MS), showing a less efficient brain network. Recent studies indicate that the dynamic properties of the brain network show a strong correlation with cognitive function. Purpose To investigate network dynamics on functional MRI in cognitively impaired patients with MS. Materials and Methods In secondary analysis of prospectively acquired data, with imaging performed between 2008 and 2012, differences in regional functional network dynamics (ie, eigenvector centrality dynamics) between cognitively impaired and cognitively preserved participants with MS were investigated. Functional network dynamics were computed on images from functional MRI (3 T) by using a sliding-window approach. Cognitively impaired and preserved groups were compared by using a clusterwise permutation-based method. Results The study included 96 healthy control subjects and 332 participants with MS (including 226 women and 106 men; median age, 48.1 years ± 11.0). Among the 332 participants with MS, 87 were cognitively impaired and 180 had preserved cognitive function; mildly impaired patients (n = 65) were excluded. The cognitively impaired group included a higher proportion of men compared with the cognitively preserved group (35 of 87 [40%] vs 48 of 180 [27%], respectively; P = .02) and had a higher mean age (51.1 years vs 46.3 years, respectively; P < .01). The clusterwise permutation-based comparison at P less than .05 showed reduced centrality dynamics in default-mode, frontoparietal, and visual network regions on functional MRI in cognitively impaired participants versus cognitively preserved participants. A subsequent correlation and hierarchical clustering analysis revealed that the default-mode and visual networks normally demonstrate negatively correlated fluctuations in functional importance (r = -0.23 in healthy control subjects), with an almost complete loss of this negative correlation in cognitively impaired participants compared with cognitively preserved participants (r = -0.04 vs r = -0.14; corrected P = .02). Conclusion As shown on functional MRI, cognitively impaired patients with multiple sclerosis not only demonstrate reduced dynamics in default-mode, frontoparietal, and visual networks, but also show a loss of interplay between default-mode and visual networks. © RSNA, 2019 Online supplemental material is available for this article. See also the article by Eijlers et al and the editorial by Zivadinov and Dwyer in this issue.

Cognitive Impairment in Multiple Sclerosis With Regards to Disease Duration and Clinical Phenotypes

The relationships between cognitive impairment that exist during the clinical course of multiple sclerosis (MS) remain poorly described. The effect of disease duration has been studied in a few longitudinal cohorts and some cross-sectional studies that suggest that cognitive deficits tend to extend with disease duration. However, the effect of disease duration seems to be confounded by the effect of age. At the pre-clinical stage, cognitive deficits have been observed in patients with radiologically isolated syndromes, and their profile is similar than in clinically isolated syndromes (CIS) and relapsing-remitting MS (RRMS). The frequency of cognitive impairment tends to be higher in RRMS than in CIS. In these phenotypes, slowness of information processing speed (IPS) and episodic verbal and visuo-spatial memory deficits are frequently observed, but executive functions, and in particular verbal fluency, could also be impaired. More frequent and severe deficits are reported in SPMS than in RRMS with more severe deficits for memory tests, working memory and IPS. Similarly to what is observed in SPMS, patients with primary progressive MS (PPMS) present with a wide range of cognitive deficits in IPS, attention, working memory, executive functions, and verbal episodic memory with more tests and domains impaired than RRMS patients. Altogether these data suggested that not only the duration of the disease and age play an important role in the cognitive profile of patients, but also the phenotype itself, probably because of its specific pathological mechanism.