fMRI evidence of brain reorganization during attention and memory tasks in multiple sclerosis

FMRI insights into the neural alterations and clinical correlates in multiple sclerosis: A comprehensive overview of systematic reviews and meta-analyses

INTRODUCTION

Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammatory demyelination in the central nervous system. Functional Magnetic Resonance Imaging (fMRI) has emerged as an effective method for studying MS pathology. This review provides a comprehensive overview of fMRI applications, clarifying alterations in brain activity and identifying relevant biomarkers.

METHODS

A systematic search of electronic databases and manual reference list checks at March 2024 yielded 470 articles. After duplicate removal, 456 articles underwent screening, 44 were assessed in full, and 12 systematic reviews and meta-analyses met inclusion criteria. Quality assessment was conducted.

RESULTS

Included studies reported high methodological quality. fMRI revealed decreased functional connectivity within the default mode network, correlating with impaired information processing speed, and increased connectivity in compensatory networks during working memory tasks. Graph theory metrics identified disrupted global efficiency and clustering in functional networks, linked to gray matter atrophy. Neuroplasticity studies demonstrated cortical reorganization after cognitive rehabilitation, particularly in the prefrontal cortex. MS-related fatigue was associated with altered anterior cingulate cortex and thalamic activity, while depression correlated with reduced amygdala-prefrontal connectivity.

DISCUSSION

fMRI has enhanced understanding of MS, revealing specific neural correlates of cognitive decline, neuroplasticity, fatigue, and depression. However, variability in MS subtypes and non-standardized protocols hinder consistency, while motion artifacts and cerebral blood flow changes complicate interpretation. Standardizing imaging protocols and integrating novel techniques could improve reliability and enable clinical applications to optimize patient monitoring and interventions.

Functional MRI and cognition in multiple sclerosis-Where are we now?

Multiple sclerosis-related cognitive impairment (MSrCI) affects most patients with multiple sclerosis (MS), significantly contributing to disability and socioeconomic challenges. MSrCI manifests across all disease stages, mainly impacting working memory, information processing, and attention. To date, the underlying mechanisms of MSrCI remain unclear, with its pathogenesis considered multifactorial. While conventional MRI findings correlate with MSrCI, there is no consensus on reliable imaging metrics to detect or diagnose cognitive impairment (CI). Functional MRI (fMRI) has provided unique insights into the brain's neuroplasticity mechanisms, revealing evidence of compensatory mechanisms in response to tissue damage, both beneficial and maladaptive. This review summarizes the current literature on the application of resting-state fMRI (rs-fMRI) and task-based fMRI (tb-fMRI) in understanding neuroplasticity and its relationship with cognitive changes in people with MS (pwMS). Searches of databases, including PubMed/Medline, Embase, Scopus, and the Web of Science, were conducted for the most recent fMRI cognitive studies in pwMS. Key findings ifrom rs-fMRI studies reveal disruptions in brain connectivity and hub integration, leading to CI due to decreased network efficiency. tb-fMRI studies highlight abnormal brain activation patterns in pwMS, with evidence of increased fMRI activity in earlier disease stages as a beneficial compensatory response, followed by reduced activation correlating with increased lesion burden and cognitive decline as the disease progresses. This suggests a gradual exhaustion of compensatory mechanisms over time. These findings support fMRI not only as a diagnostic tool for MSrCI but also as a potential imaging biomarker to improve our understanding of disease progression.

Effects of mindfulness-based interventions on cognition in people with multiple sclerosis: a systematic review and meta-analysis of randomized controlled trials

Introduction

Cognitive impairment affects up to 65% of people with multiple sclerosis (PwMS), undermining functional independence and quality of life. The objective of this study is to synthesize existing randomized controlled trial (RCT) evidence on the effects of Mindfulness-based interventions (MBIs) on cognitive function in PwMS.

Methods

A systematic literature search was conducted to identify RCTs assessing MBIs effects on cognitive functioning in PwMS. Using pre-defined criteria, two independent reviewers screened titles, abstracts, and extracted data from included studies. Meta-analysis was performed, where possible, using a random effects model. Narrative synthesis was undertaken. Preferred Reporting Items for Systematic Reviews and Meta-analysis guidance was followed. PROSPERO_ID:(CRD42021286429).

Results

Twelve eligible RCTs were identified, n=700 PwMS. MBIs included both standardized and tailored interventions, in-person and virtually. A variety of measures of cognitive functioning were reported. Five studies (n=254 PwMS) were included in meta-analysis; pooled results suggested MBIs effectively improved scores on the Paced Auditory Serial Addition Test (PASAT)-2 (SMD=0.38; 95% CI 0.06-0.71; I2 63%; p=0.02), whereas improvements were of borderline significance on the PASAT-3 (SMD=0.32; 95% CI -0.01-0.64; I2 65%; p=0.06), and, although trending to positive, were statistically insignificant on the Perceived Deficits Questionnaire (SMD=0.34; 95 CI -0.05-0.74; I2 0%; p=0.09) and Symbol Digits Modality Test (SMD=0.25; 95% CI -0.15-0.66; I2 0%; p=0.21).

Conclusion

Preliminary findings in meta-analysis are inconsistent but suggest potential benefits from MBI training on cognitive functioning in PwMS. High quality RCTs are necessary to test more definitively the impact of MBIs on cognitive functioning in PwMS.

Systematic review registration

PROSPERO, identifier CRD42021286429.

Identification of cognitive load-dependent activation patterns using working memory task-based fMRI at various levels of difficulty

Working memory, which is regarded as the foundation of cognitive processes, is a system that stores, processes, and manipulates information in short intervals of time that are actually needed for daily functioning. This study aimed to assess the brain activity of healthy controls (HC) while performing the N-back task, which is one of the most popularly used tests for evaluating working memory along with functional magnetic resonance imaging (fMRI). In this regard, we collected fMRI data from right-handed individuals in a 3.0 T scanner during the Persian version of the visual variant N-back task performance with three levels of complexity varied throughout the experiment (1, 2, and 3-back conditions) to increase the cognitive demands. The statistical parametric mapping (SPM12) software was used to analyze fMRI data for the identification of cognitive load-dependent activation patterns based on contrast images obtained from different levels of task difficulty. Our findings showed that as cognitive complexity increased, the number of significant activation clusters and cluster extent increased in several areas distributed in the cerebellum, frontoparietal lobes, insula, SMA, and lenticular nucleus, the majority of which are recognized for their role in working memory. Furthermore, deactivation patterns during 1-, 2-, and 3-back vs. 0-back contrasts revealed significant clusters in brain regions that are mostly described as being part of the default mode network (DMN). Based on previous research, our results supported the recognized involvement of the mentioned cortical and subcortical areas in various types or levels of N-back tasks. This study found that altering activation patterns by increasing task difficulty could aid in evaluating the various stages of cognitive dysfunction in many brain diseases such as multiple sclerosis (MS) and Alzheimer's disease by comparing controls in future studies to apply early appropriate treatment strategies.

Depressive symptoms, anxiety and cognitive impairment: emerging evidence in multiple sclerosis

Neuropsychiatric abnormalities may be broadly divided in two categories: disorders of mood, affect, and behavior and abnormalities affecting cognition. Among these conditions, clinical depression, anxiety and neurocognitive disorders are the most common in multiple sclerosis (MS), with a substantial impact on patients' quality of life and adherence to treatments. Such manifestations may occur from the earliest phases of the disease but become more frequent in MS patients with a progressive disease course and more severe clinical disability. Although the pathogenesis of these neuropsychiatric manifestations has not been fully defined yet, brain structural and functional abnormalities, consistently observed with magnetic resonance imaging (MRI), together with genetic and immunologic factors, have been suggested to be key players. Even though the detrimental clinical impact of such manifestations in MS patients is a matter of crucial importance, at present, they are often overlooked in the clinical setting. Moreover, the efficacy of pharmacologic and non-pharmacologic approaches for their amelioration has been poorly investigated, with the majority of studies showing marginal or no beneficial effect of different therapeutic approaches, possibly due to the presence of multiple and heterogeneous underlying pathological mechanisms and intrinsic methodological limitations. A better evaluation of these manifestations in the clinical setting and improvements in the understanding of their pathophysiology may offer the potential to develop tools for differentiating these mechanisms in individual patients and ultimately provide a principled basis for treatment selection. This review provides an updated overview regarding the pathophysiology of the most common neuropsychiatric symptoms in MS, the clinical and MRI characteristics that have been associated with mood disorders (i.e., depression and anxiety) and cognitive impairment, and the treatment approaches currently available or under investigation.

Disease phenotype prediction in multiple sclerosis

Progressive multiple sclerosis (PMS) is currently diagnosed retrospectively. Here, we work toward a set of biomarkers that could assist in early diagnosis of PMS. A selection of cerebrospinal fluid metabolites (n = 15) was shown to differentiate between PMS and its preceding phenotype in an independent cohort (AUC = 0.93). Complementing the classifier with conformal prediction showed that highly confident predictions could be made, and that three out of eight patients developing PMS within three years of sample collection were predicted as PMS at that time point. Finally, this methodology was applied to PMS patients as part of a clinical trial for intrathecal treatment with rituximab. The methodology showed that 68% of the patients decreased their similarity to the PMS phenotype one year after treatment. In conclusion, the inclusion of confidence predictors contributes with more information compared to traditional machine learning, and this information is relevant for disease monitoring.

Effect of deep gray matter atrophy on information processing speed in early relapsing-remitting multiple sclerosis

BACKGROUND

Cognitive dysfunction, including reduced Information processing speed (IPS), is relatively common in multiple sclerosis(MS). IPS deficits have profound effects on several aspects of patients' life. Previous studies showed that deep gray matter atrophy is highly correlated with overall cognitive impairment in MS. However, the effect of deep gray matter atrophy on IPS deficits is not well understood. In this study, we evaluated the effects of deep gray matter volume changes on IPS in people with early relapse-remitting MS (RRMS) compared to healthy control.

METHODS

In this case-control study, we enrolled 63 case with RRMS and 36 healthy controls. All patients were diagnosed within 6 years. IPS was evaluated using the Integrated Cognitive Assessment (ICA) test. We also performed a 1.5T MRI to evaluate deep gray matter structures.

RESULTS

People with RRMS had lower accuracy in the ICA test (p = .01). However, the reaction time did not significantly differ between RRMS and control groups (p = .6). Thalamus volume was significantly lower in the RRMS group with impaired IPS compared to the RRMS with normal IPS and control groups (p < 10-4). Other deep gray matter structures were not significantly different between the RRMS with impaired IPS group and the RRMS with normal IPS group.

CONCLUSION

Some people with MS are impaired in IPS even in the early stages of the disease. Thalamic atrophy affected IPS in these patients, however atrophy in other deep gray matter structures, including caudate, putamen, globus pallidus, hippocampus, amygdala, accumbens, and cerebellum, were not significantly correlated with IPS impairment in early RRMS.

Is There Reduced Hemodynamic Brain Activation in Multiple Sclerosis Even with Undisturbed Cognition?

Cognitive impairments related to changes in deep gray matter and other brain regions occur in up to 70% of people with multiple sclerosis. But do such brain changes also occur in patients without significant cognitive impairment? Eighteen participants with relapsing-remitting multiple sclerosis (RRMS) and fifteen healthy controls participated in this study. Cognitive status, depression, and fatigue were assessed using the Multiple Sclerosis Inventory of Cognition (MUSIC), Beck's Depression Inventory (BDI-II), and the Fatigue Severity Scale (FSS). fMRI was recorded while a participant performed the modified attention network test (ANT). The effects of ANT executive attention network on hemodynamic activation of a priori defined regions of interest, including the hippocampus, anterior cingulate cortex (ACC), thalamus, caudate nucleus, pallidum, and putamen were studied. The individual lesion load was estimated. For fMRI data analysis a general linear model with randomization statistics including threshold-free cluster enhancement as implemented in the FSL software was used. Participants with RRMS showed reduced activation of the executive attention network in the hippocampus, pallidum, and ACC. The thalamus was involved in both group activations but did not differ between groups. In summary, functional changes in the brain can also be demonstrated in RRMS patients without cognitive deficits. The affected brain regions can best be assigned to the attention network for executive control. This association could likely serve as a biological indicator of susceptibility to imminent cognitive impairment in MS.

TRACking health behaviors in people with Multiple Sclerosis (TRAC-MS): Study protocol and description of the study sample

Introduction

People with multiple sclerosis (PwMS) experience a range of physical, cognitive, and affective symptoms. Behavioral interventions targeting increased physical activity show promising support as low-cost methods to improve working memory, episodic memory, and processing speed in PwMS. In this randomized controlled trial, we will examine the efficacy of a pedometer-tracking intervention, designed to increase low-to-moderate levels of physical activity, for improving working memory in PwMS.

Methods and Analysis

Eighty-seven PwMS, between the ages of 30-59, have been recruited for the study. Seventy-five of the eligible and interested individuals were randomized to six-month health behavior monitoring groups: a Step-track group or a Water-track group (serving as the active control). Neuropsychological measures, assessing the primary outcome of the study, were administered at pre, midpoint, and post-intervention. Exploratory factor analysis of neuropsychological measures resulted in three factors: a working memory/processing speed factor, a visual episodic memory factor, and a verbal episodic memory factor. Changes in this latent measure of working memory/processing speed is the primary outcome of the current study. Functional MRI data will be analyzed to examine changes in the functional connectivity of the neural network supporting working memory.

Ethics and dissemination

The institutional review board granted approval for the study and all participants provided written informed consent. The results of this study will provide support showing that step-tracking increases overall levels of physical activity, improves working memory and processing speed, and strengthens the neural circuitry that supports better cognition. Evidence from this study will thus offer promising support for the routine use of step-tracking devices to improve cognitive functioning in PwMS. Study results will be disseminated through peer-reviewed publications and presentations at scientific conferences.

Employing Connectome-Based Models to Predict Working Memory in Multiple Sclerosis

Introduction: Individuals with multiple sclerosis (MS) are vulnerable to deficits in working memory (WM), but the search for neural correlates of WM within circumscribed areas has been inconclusive. Given the widespread neural alterations observed in MS, predictive modeling approaches that capitalize on whole-brain connectivity may better capture individual differences in WM. Materials and Methods: We applied connectome-based predictive modeling to functional magnetic resonance imaging data from WM tasks in two independent samples with relapsing-remitting MS. In the internal sample (n_internal = 36), cross-validation was used to train a model to predict accuracy on the Paced Visual Serial Addition Test from functional connectivity. We hypothesized that this MS-specific model would successfully predict performance on the N-back task in the validation cohort (n_validation = 36). In addition, we assessed the generalizability of existing WM networks derived in healthy young adults to these samples, and we explored anatomical differences between the healthy and MS networks. Results: We successfully derived an MS-specific predictive model of WM in the internal sample (full: r_s = 0.47, permuted p = 0.011), but the predictions were not significant in the validation cohort (r_s = -0.047; p = 0.78, mean squared error [MSE] = 0.006, R² = -2.21%). In contrast, the healthy networks successfully predicted WM in both MS samples (internal: r_s = 0.33 p = 0.049, MSE = 0.009, R² = 13.4%; validation cohort: r_s = 0.46, p = 0.005, MSE = 0.005, R² = 16.9%), demonstrating their translational potential. Discussion: Functional networks identified in a large sample of healthy individuals predicted significant variance in WM in MS. Networks derived in small samples of people with MS may have limited generalizability, potentially due to disease-related heterogeneity. The robustness of models derived in large clinical samples warrants further investigation. ClinicalTrials.gov ID: NCT03244696.

Cerebrovascular Reactivity and Neurovascular Coupling in Multiple Sclerosis-A Systematic Review

The inflammatory processes observed in the central nervous system in multiple sclerosis (MS) could damage the endothelium of the cerebral vessels and lead to a dysfunctional regulation of vessel tonus and recruitment, potentially impairing cerebrovascular reactivity (CVR) and neurovascular coupling (NVC). Impaired CVR or NVC correlates with declining brain health and potentially plays a causal role in the development of neurodegenerative disease. Therefore, we examined studies on CVR or NVC in MS patients to evaluate the evidence for impaired cerebrovascular function as a contributing disease mechanism in MS. Twenty-three studies were included (12 examined CVR and 11 examined NVC). Six studies found no difference in CVR response between MS patients and healthy controls. Five studies observed reduced CVR in patients. This discrepancy can be because CVR is mainly affected after a long disease duration and therefore is not observed in all patients. All studies used CO₂ as a vasodilating stimulus. The studies on NVC demonstrated diverse results; hence a conclusion that describes all the published observations is difficult to find. Future studies using quantitative techniques and larger study samples are needed to elucidate the discrepancies in the reported results.

Symptom Interconnectivity in Multiple Sclerosis: A Narrative Review of Potential Underlying Biological Disease Processes

Introduction

Fatigue, cognitive impairment, depression, and pain are highly prevalent symptoms in multiple sclerosis (MS). These often co-occur and may be explained by a common etiology. By reviewing existing literature, we aimed to identify potential underlying biological processes implicated in the interconnectivity between these symptoms.

Methods

A literature search was conducted to identify articles reporting research into the biological mechanisms responsible for the manifestation of fatigue, cognitive impairment, depression, and pain in MS. PubMed was used to search for articles published from July 2011 to July 2021. We reviewed and assessed findings from the literature to identify biological processes common to the symptoms of interest.

Results

Of 693 articles identified from the search, 252 were selected following screening of titles and abstracts and assessing reference lists of review articles. Four biological processes linked with two or more of the symptoms of interest were frequently identified from the literature: (1) direct neuroanatomical changes to brain regions linked with symptoms of interest (e.g., thalamic injury associated with cognitive impairment, fatigue, and depression), (2) pro-inflammatory cytokines associated with so-called ‘sickness behavior,’ including manifestation of fatigue, transient cognitive impairment, depression, and pain, (3) dysregulation of monoaminergic pathways leading to depressive symptoms and fatigue, and (4) hyperactivity of the hypothalamic–pituitary-adrenal (HPA) axis as a result of pro-inflammatory cytokines promoting the release of brain noradrenaline, serotonin, and tryptophan, which is associated with symptoms of depression and cognitive impairment.

Conclusion

The co-occurrence of fatigue, cognitive impairment, depression, and pain in MS appears to be associated with a common set of etiological factors, namely neuroanatomical changes, pro-inflammatory cytokines, dysregulation of monoaminergic pathways, and a hyperactive HPA axis. This association of symptoms and biological processes has important implications for disease management strategies and, eventually, could help find a common therapeutic pathway that will impact both inflammation and neuroprotection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-022-00368-2.

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

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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.

Current evidence on the potential therapeutic applications of transcranial magnetic stimulation in multiple sclerosis: a systematic review of the literature

INTRODUCTION

A growing number of studies have evaluated the effects of transcranial magnetic stimulation (TMS) for the symptomatic treatment of multiple sclerosis (MS).

METHODS

We performed a PubMed search for articles, recent books, and recommendations from the most relevant clinical practice guidelines and scientific societies regarding the use of TMS as symptomatic treatment in MS.

CONCLUSIONS

Excitatory electromagnetic pulses applied to the affected cerebral hemisphere allow us to optimise functional brain activity, including the transmission of nerve impulses through the demyelinated corticospinal pathway. Various studies into TMS have safely shown statistically significant improvements in spasticity, fatigue, lower urinary tract dysfunction, manual dexterity, gait, and cognitive deficits related to working memory in patients with MS; however, the exact level of evidence has not been defined as the results have not been replicated in a sufficient number of controlled studies. Further well-designed, randomised, controlled clinical trials involving a greater number of patients are warranted to attain a higher level of evidence in order to recommend the appropriate use of TMS in MS patients across the board. TMS acts as an adjuvant with other symptomatic and immunomodulatory treatments. Additional studies should specifically investigate the effect of conventional repetitive TMS on fatigue in these patients, something that has yet to see the light of day.

Current evidence on the potential therapeutic applications of transcranial magnetic stimulation in multiple sclerosis: A systematic review of the literature

INTRODUCTION

A growing number of studies have evaluated the effects of transcranial magnetic stimulation (TMS) for the symptomatic treatment of multiple sclerosis (MS).

METHODS

We performed a PubMed search for articles, recent books, and recommendations from the most relevant clinical practice guidelines and scientific societies regarding the use of TMS as symptomatic treatment in MS.

CONCLUSIONS

Excitatory electromagnetic pulses applied to the affected cerebral hemisphere allow us to optimise functional brain activity, including the transmission of nerve impulses through the demyelinated corticospinal pathway. Various studies into TMS have safely shown statistically significant improvements in spasticity, fatigue, lower urinary tract dysfunction, manual dexterity, gait, and cognitive deficits related to working memory in patients with MS; however, the exact level of evidence has not been defined as the results have not been replicated in a sufficient number of controlled studies. Further well-designed, randomised, controlled clinical trials involving a greater number of patients are warranted to attain a higher level of evidence in order to recommend the appropriate use of TMS in MS patients across the board. TMS acts as an adjuvant with other symptomatic and immunomodulatory treatments. Additional studies should specifically investigate the effect of conventional repetitive TMS on fatigue in these patients, something that has yet to see the light of day.

Correlations between hippocampal functional connectivity, structural changes, and clinical data in patients with relapsing-remitting multiple sclerosis: a case-control study using multimodal magnetic resonance imaging

Multiple sclerosis is associated with structural and functional brain alterations leading to cognitive impairments across multiple domains including attention, memory, and the speed of information processing. The hippocampus, which is a brain important structure involved in memory, undergoes microstructural changes in the early stage of multiple sclerosis. In this study, we analyzed hippocampal function and structure in patients with relapsing-remitting multiple sclerosis and explored correlations between the functional connectivity of the hippocampus to the whole brain, changes in local brain function and microstructure, and cognitive function at rest. We retrospectively analyzed data from 20 relapsing-remitting multiple sclerosis patients admitted to the Department of Neurology at the China-Japan Union Hospital of Jilin University, China, from April 2015 to November 2019. Sixteen healthy volunteers were recruited as the healthy control group. All participants were evaluated using a scale of extended disability status and the Montreal cognitive assessment within 1 week before and after head diffusion tensor imaging and functional magnetic resonance imaging. Compared with the healthy control group, the patients with relapsing-remitting multiple sclerosis had lower Montreal cognitive assessment scores and regions of simultaneously enhanced and attenuated whole-brain functional connectivity and local functional connectivity in the bilateral hippocampus. Hippocampal diffusion tensor imaging data showed that, compared with the healthy control group, patients with relapsing-remitting multiple sclerosis had lower hippocampal fractional anisotropy values and higher mean diffusivity values, suggesting abnormal hippocampal structure. The left hippocampus whole-brain functional connectivity was negatively correlated with the Montreal cognitive assessment score (r = −0.698, P = 0.025), and whole-brain functional connectivity of the right hippocampus was negatively correlated with extended disability status scale score (r = −0.649, P = 0.042). The mean diffusivity value of the left hippocampus was negatively correlated with the Montreal cognitive assessment score (r = −0.729, P = 0.017) and positively correlated with the extended disability status scale score (r = 0.653, P = 0.041). The right hippocampal mean diffusivity value was positively correlated with the extended disability status scale score (r = 0.684, P = 0.029). These data suggest that the functional connectivity and presence of structural abnormalities in the hippocampus in patients with relapse-remission multiple sclerosis are correlated with the degree of cognitive function and extent of disability. This study was approved by the Ethics Committee of China-Japan Union Hospital of Jilin University, China (approval No. 201702202) on February 22, 2017.

Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor problems for people with a detrimental effect on the functioning of the nervous system. In order to diagnose MS, multiple screening methods have been proposed so far; among them, magnetic resonance imaging (MRI) has received considerable attention among physicians. MRI modalities provide physicians with fundamental information about the structure and function of the brain, which is crucial for the rapid diagnosis of MS lesions. Diagnosing MS using MRI is time-consuming, tedious, and prone to manual errors. Research on the implementation of computer aided diagnosis system (CADS) based on artificial intelligence (AI) to diagnose MS involves conventional machine learning and deep learning (DL) methods. In conventional machine learning, feature extraction, feature selection, and classification steps are carried out by using trial and error; on the contrary, these steps in DL are based on deep layers whose values are automatically learn. In this paper, a complete review of automated MS diagnosis methods performed using DL techniques with MRI neuroimaging modalities is provided. Initially, the steps involved in various CADS proposed using MRI modalities and DL techniques for MS diagnosis are investigated. The important preprocessing techniques employed in various works are analyzed. Most of the published papers on MS diagnosis using MRI modalities and DL are presented. The most significant challenges facing and future direction of automated diagnosis of MS using MRI modalities and DL techniques are also provided.

Relationship Between Cerebrovascular Reactivity and Cognition Among People With Risk of Cognitive Decline

Vascular risk factors (e.g., obesity and hypertension) are associated with cerebral small vessel disease, Alzheimer's disease (AD) pathology, and dementia. Reduced perfusion may reflect the impaired ability of blood vessels to regulate blood flow in reaction to varying circumstances such as hypercapnia (increased end-tidal partial pressures of CO2). It has been shown that cerebrovascular reactivity (CVR) measured with blood-oxygen-level-dependent (BOLD) MRI is correlated with cognitive performance and alterations of CVR may be an indicator of vascular disfunction leading to cognitive decline. However, the underlying mechanism of CVR alterations in BOLD signal may not be straight-forward because BOLD signal is affected by multiple physiological parameters, such as cerebral blood flow (CBF), cerebral blood volume, and oxygen metabolism. Arterial spin labeling (ASL) MRI quantitatively measures blood flow in the brain providing images of local CBF. Therefore, in this study, we measured CBF and its changes using a dynamic ASL technique during a hypercapnia challenge and tested if CBF or CVR was related to cognitive performance using the Mini-mental state examination (MMSE) score. Seventy-eight participants underwent cognitive testing and MRI including ASL during a hypercapnia challenge with a RespirAct computer-controlled gas blender, targeting 10 mmHg higher end-tidal CO2 level than the baseline while end-tidal O2 level was maintained. Pseudo-continuous ASL (PCASL) was collected during a 2-min baseline and a 2-min hypercapnic period. CVR was obtained by calculating a percent change of CBF per the end-tidal CO2 elevation in mmHg between the baseline and the hypercapnic challenge. Multivariate regression analyses demonstrated that baseline resting CBF has no significant relationship with MMSE, while lower CVR in the whole brain gray matter (β = 0.689, p = 0.005) and white matter (β = 0.578, p = 0.016) are related to lower MMSE score. In addition, region of interest (ROI) based analysis showed positive relationships between MMSE score and CVR in 26 out of 122 gray matter ROIs.

Blood Oxygenation Level-Dependent Response to Multiple Grip Forces in Multiple Sclerosis: Going Beyond the Main Effect of Movement in Brodmann Area 4a and 4p

This study highlights the importance of looking beyond the main effect of movement to study alterations in functional response in the presence of central nervous system pathologies such as multiple sclerosis (MS). Data show that MS selectively affects regional BOLD (blood oxygenation level dependent) responses to variable grip forces (GF). It is known that the anterior and posterior BA 4 areas (BA 4a and BA 4p) are anatomically and functionally distinct. It has also been shown in healthy volunteers that there are linear (first order, typical of BA 4a) and nonlinear (second to fourth order, typical of BA 4p) BOLD responses to different levels of GF applied during a dynamic motor paradigm. After modeling the BOLD response with a polynomial expansion of the applied GFs, the particular case of BA 4a and BA 4p were investigated in healthy volunteers (HV) and MS subjects. The main effect of movement (zeroth order) analysis showed that the BOLD signal is greater in MS compared with healthy volunteers within both BA 4 subregions. At higher order, BOLD-GF responses were similar in BA 4a but showed a marked alteration in BA 4p of MS subjects, with those with greatest disability showing the greatest deviations from the healthy response profile. Therefore, the different behaviors in HV and MS could only be uncovered through a polynomial analysis looking beyond the main effect of movement into the two BA 4 subregions. Future studies will investigate the source of this pathophysiology, combining the present fMRI paradigm with blood perfusion and nonlinear neuronal response analysis.

A Scoping Review of Cognitive Training in Neurodegenerative Diseases via Computerized and Virtual Reality Tools: What We Know So Far

Most prevalent neurodegenerative diseases such as Alzheimer's disease, frontotemporal dementia, Parkinson's disease and multiple sclerosis are heterogeneous in their clinical profiles and underlying pathophysiology, although they typically share the presence of cognitive impairment that worsens significantly during the course of the disease. Viable pharmacological options for cognitive symptoms in these clinical conditions are currently lacking. In recent years, several studies have started to apply Computerized Cognitive Training (CCT) and Virtual Reality (VR) tools to try and contrast patients' cognitive decay over time. However, no in-depth literature review of the contribution of these promising therapeutic options across main neurodegenerative diseases has been conducted yet. The present paper reports the state-of-the-art of CCT and VR studies targeting cognitive impairment in most common neurodegenerative conditions. Our twofold aim is to point out the scientific evidence available so far and to support health professionals to consider these promising therapeutic tools when planning rehabilitative interventions, especially when the access to regular and frequent hospital consultations is not easy to be provided.

Depression and Fatigue in Patients With Multiple Sclerosis Have No Influence on the Parameters of Cognitive Evoked Potentials

PURPOSE

The purpose of this study was to examine if depression and fatigue affect event-related brain potentials (ERPs) in patients with relapsing-remitting multiple sclerosis, and to assess the significance of ERP as an indicator of cognitive impairment.

METHODS

A total of 81 relapsing-remitting multiple sclerosis patients and 32 healthy control subjects participated in the study. Cognitive functions were evaluated using a standard PASAT, the symbol digit modality test, and ERP. The degrees of depressive symptomatology and fatigue were assessed with Beck Depression Inventory, the Fatigue Severity Scale, and the Fatigue Impact Scale.

RESULTS

Fatigue and depression had a negative effect on the cognitive functions examined by neuropsychological tests. Depression and fatigue did not influence ERP amplitude and latency findings. Depression level was negatively correlated with symbol digit modality test score (r = -0.135, P < 0.05). Fatigue level was negatively correlated with the results for PASAT A (r = -0.225, P < 0.05) and PASAT B (r = -0.342, P < 0.01). Reaction time was positively associated with depression (r = 0.246, P = 0.01) and fatigue (r = 0.281, P = 0.01).

CONCLUSIONS

Depression and fatigue have no effect on ERP amplitude and latency, so they cannot participate in risk assessment for the development of cognitive impairment in patients with relapsing-remitting multiple sclerosis.

Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis

Cognitive impairment is a frequent and meaningful symptom in multiple sclerosis (MS), caused by the accrual of brain structural damage only partially counteracted by effective functional reorganization. As both these aspects can be successfully investigated through the application of advanced neuroimaging, here, we offer an up-to-date overview of the latest findings on structural, functional and metabolic correlates of cognitive impairment in adults with MS, focusing on the mechanisms sustaining damage accrual and on the identification of useful imaging markers of cognitive decline.

Gray Matter Atrophy in the Cortico-Striatal-Thalamic Network and Sensorimotor Network in Relapsing-Remitting and Primary Progressive Multiple Sclerosis

Gray matter atrophy in multiple sclerosis (MS) is thought to be associated with disability and cognitive impairment, but previous studies have sometimes had discordant results, and the atrophy patterns of relapsing-remitting multiple sclerosis (RRMS) and primary progressive multiple sclerosis (PPMS) remain to be clarified. We conducted a meta-analysis using anisotropic effect-size-based algorithms (AES-SDM) to identify consistent findings from whole-brain voxel-based morphometry (VBM) studies of gray matter volume (GMV) in 924 RRMS patients and 204 PPMS patients. This study is registered with PROSPERO (number CRD42019121319). Compared with healthy controls, RRMS and PPMS patients showed gray matter atrophy in the cortico-striatal-thalamic network, sensorimotor network, and bilateral insula. RRMS patients had a larger GMV in the left insula, cerebellum, right precentral gyrus, and bilateral putamen as well as a smaller GMV in the bilateral cingulate, caudate nucleus, right thalamus, superior temporal gyrus and left postcentral gyrus than PPMS patients. The disease duration, Expanded Disability Status Scale score, Paced Auditory Serial Addition Test z-score, and T2-weighted lesion load were associated with specific gray matter regions in RRMS or PPMS. Alterations in the cortico-striatal-thalamic networks, sensorimotor network, and insula may be involved in the common pathogenesis of RRMS and PPMS. The deficits in the cingulate gyrus and caudate nucleus are more apparent in RRMS than in PPMS. The more severe cerebellum atrophy in PPMS may be a brain feature associated with its neurological manifestations. These imaging biomarkers provide morphological evidence for the pathophysiology of MS and should be verified in future research.

Linking Cognitive Impairment to Neuroinflammation in Multiple Sclerosis using neuroimaging tools

Multiple sclerosis (MS) is a complex chronic immune disease in the central nervous system, causing neurological disability among young and middle-aged adults. Impaired cognition is now emerging as a major clinical symptom being present in more than 50% of MS patients. Recent data support that neuroinflammation mediated by glial cells plays a key part in MS course and, particularly, microglia is responsible for the pruning of synapses possibly impacting on vital neural networks maintenance. However, the knowledge of microglia-mediated mechanisms underlying cognitive impairment in MS is poor and unfortunately, there are no medicines to overcome this "invisible" symptom. Interestingly, the use of powerful diagnostic imaging tools as structural and functional MRI as well as PET brought new insights into some biological mechanisms, but no link between the possibility to use early visible alterations to predict cognitive deficits was clarified yet. In this review, we focus on the interplay between MS-related cognitive structures and neuroinflammation, specifically the presence of microglia and their reactivity. Moreover, we also discuss new imaging tools to assess cognitive impairment and to track microglia activation. Understanding the role of microglia in cognitive impairment and how it can be prevented may be a promising contribution to innovative therapeutic strategies that culminate in the improvement of MS patients' life quality.

Brain activity pattern changes after adaptive working memory training in multiple sclerosis

Cognitive impairment and related abnormal brain activity are common in people with multiple sclerosis (PwMS). Adaptive training based on working memory (WM) has been shown to ameliorate cognitive symptoms, although the effects at a neural level are unclear. The aim of this study was to expand the existing research on the effects of an adaptive WM rehabilitative intervention on brain functional activity in PwMS. A sample of eighteen PwMS performed an 8-week home-based cognitive rehabilitation treatment based on adaptive WM training. PwMS were assessed before and after treatment using a validated neuropsychological battery and undergoing an fMRI session while carrying out a cognitive task (i.e., Paced Visual Serial Addition Test - PVSAT). fMRI activations were compared to the activation pattern elicited by eighteen matched healthy subjects performing the same task. At baseline, we found abnormal brain activity during PVSAT in PwMS when compared to healthy subjects, with a pattern including several bilateral activation clusters. Following rehabilitation, PwMS improved cognitive performance, as evaluated by the neuropsychological battery, and showed a different activation map with clusters mainly located in the right cerebellum and in the left hemisphere. The only significant cluster in the right hemisphere was located in the inferior parietal lobule, and the BOLD signal extracted in this area significantly correlated with cognitive performance both before and after the treatment. We suggest that WM training can improve the cognitive performance and reduce the abnormal activation of PwMS by partially maintaining or even restoring brain cognitive function.

Distributed causality in resting-state network connectivity in the acute and remitting phases of RRMS

BACKGROUND

Although previous studies have shown that intra-network abnormalities in brain functional networks are correlated with clinical/cognitive impairment in multiple sclerosis (MS), there is little information regarding the pattern of causal interactions among cognition-related resting-state networks (RSNs) in different disease stages of relapsing-remitting MS (RRMS) patients. We hypothesized that abnormalities of causal interactions among RSNs occurred in RRMS patients in the acute and remitting phases.

METHODS

Seventeen patients in the acute phases of RRMS, 24 patients in the remitting phases of RRMS, and 23 appropriately matched healthy controls participated in this study. First, we used group independent component analysis to extract the time courses of the spatially independent components from all the subjects. Then, the Granger causality analysis was used to investigate the causal relationships among RSNs in the spectral domain and to identify correlations with clinical indices.

RESULTS

Compared with the patients in the acute phase of RRMS, patients in the remitting phase of RRMS showed a significantly lower expanded disability status scale, modified fatigue impact scale scores, and significantly higher paced auditory serial addition test (PASAT) scores. Compared with healthy subjects, during the acute phase, RRMS patients had significantly increased driving connectivity from the right executive control network (rECN) to the anterior salience network (aSN), and the causal coefficient was negatively correlated with the PASAT score. During the remitting phase, RRMS patients had significantly increased driving connectivity from the rECN to the aSN and from the rECN to the visuospatial network.

CONCLUSIONS

Together with the disease duration (mean disease duration < 5 years) and relatively better clinical scores than those in the acute phase, abnormal connections, such as the information flow from the rECN to the aSN and the rECN to the visuospatial network, might provide adaptive compensation in the remitting phase of RRMS.

The neurovascular basis of processing speed differences in humans: A model-systems approach using multiple sclerosis

Behavioral studies investigating fundamental cognitive abilities provide evidence that processing speed accounts for large proportions of performance variability between individuals. Processing speed decline is a hallmark feature of the cognitive disruption observed in healthy aging and in demyelinating diseases such as multiple sclerosis (MS), neuromyelitis optica, and Wilson's disease. Despite the wealth of evidence suggesting a central role for processing speed in cognitive decline, the neural mechanisms of this fundamental ability remain unknown. Intact neurovascular coupling, acute localized blood flow increases following neural activity, is essential for optimal neural function. We hypothesized that efficient coupling forms the neural basis of processing speed. Because MS features neural-glial-vascular system disruption, we used it as a model to test this hypothesis. To assess the integrity of the coupling system, we measured blood-oxygen-level-dependent (BOLD) signal in healthy controls (HCs) and MS patients using a 3T MRI scanner while they viewed radial checkerboards that flickered periodically at 8 ​Hz. To assess processing speed and cognitive function, we administered a battery of neuropsychological tests. While MS patients exhibited reduced ΔBOLD with reductions in processing speed, no such relationships were observed in HCs. To further investigate the mechanisms that underlie ΔBOLD-processing speed relationships, we assessed the physiologic components that constitute ΔBOLD signal (i.e., cerebral blood flow, ΔCBF; cerebral metabolic rate of oxygen, ΔCMRO₂; neurovascular coupling ratio) in speed-preserved and -impaired MS patients. While ΔCBF and ΔCMRO₂ showed no group-differences, the neurovascular coupling ratio was significantly reduced in speed-impaired MS patients compared to speed-preserved MS patients. Together, these results suggest that neurovascular uncoupling might underlie cognitive slowing in MS and might be the central pathogenic mechanism governing processing speed decline.

Mechanism of visual network dysfunction in relapsing-remitting multiple sclerosis and its relation to cognition

OBJECTIVE

To investigate if changes in brain network function and connectivity contribute to the abnormalities in visual event related potentials (ERP) in relapsing-remitting multiple sclerosis (RRMS), and explore their relation to a decrease in cognitive performance.

METHODS

We evaluated 72 patients with RRMS and 89 healthy control subjects in a cross-sectional study. Visual ERP were generated using illusory and non-illusory stimuli and recorded using 21 EEG scalp electrodes. The measured activity was modelled using Dynamic Causal Modelling. The model network consisted of 4 symmetric nodes including the primary visual cortex (V1/V2) and the Lateral Occipital Complex. Patients and controls were tested with a neuropsychological test battery consisting of 18 cognitive tests covering six cognitive domains.

RESULTS

We found reduced cortical connectivity in bottom-up and interhemispheric connections to the right lateral occipital complex in patients (p < 0.001). Furthermore, interhemispherical connections were related to cognitive dysfunction in several domains (attention, executive function, visual perception and organization, processing speed and global cognition) for patients (p < 0.05). No relation was seen between cortical network connectivity and cognitive function in the healthy control subjects.

CONCLUSION

Changes in the functional connectivity to higher cortical regions provide a neurobiological explanation for the changes of the visual ERP in RRMS.

SIGNIFICANCE

This study suggests that changes in connectivity to higher cortical regions partly explain visual network dysfunction in RRMS where a lower interhemispheric connectivity may contribute to impaired cognitive function.

Brain activation patterns associated with paragraph learning in persons with multiple sclerosis: The MEMREHAB trial

The modified Story Memory Technique (mSMT) is a memory rehabilitation program that combines training in visualization and context formation to improve learning and memory. Previous studies have shown improvement in learning and memory in individuals with multiple sclerosis (MS) after undergoing the mSMT, including changes in brain activity related to working memory and word encoding. The current study examined changes in brain activity in 16 individuals diagnosed with MS (n _treatment = 6; n _{placebo control} = 10) when they were presented with to-be-remembered information within a meaningful context (i.e. a paragraph) from before to after mSMT treatment. We expected treatment-related changes in brain activation in the language network (LAN), default mode network (DMN), and executive control network (ECN). Consistent with this prediction, fMRI results revealed reduced brain activation in the LAN, DMN and ECN after completing the mSMT treatment in the context of paragraph learning. While no significant behavioral changes were observed, a marginally significant improvement with a large effect size was noted between baseline and follow-up performance on the Rivermead Behavioral Memory Test in persons who completed treatment. Results are discussed in terms of the impact of imagery training on patterns of cerebral activation when learning words presented within a context.

Considerations of power and sample size in rehabilitation research

With the current emphasis on power and reproducibility, pressures are rising to increase sample sizes in rehabilitation research in order to reflect more accurate effect estimation and generalizable results. The conventional way of increasing power by enrolling more participants is less feasible in some fields of research. In particular, rehabilitation research faces considerable challenges in achieving this goal. We describe the specific challenges to increasing power by recruiting large sample sizes and obtaining large effects in rehabilitation research. Specifically, we discuss how variability within clinical populations, lack of common standards for selecting appropriate control groups; potentially reduced reliability of measurements of brain function in individuals recovering from a brain injury; biases involved in a priori effect size estimation, and higher budgetary and staffing requirements can influence considerations of sample and effect size in rehabilitation. We also describe solutions to these challenges, such as increased sampling per participant, improving experimental control, appropriate analyses, transparent result reporting and using innovative ways of harnessing the inherent variability of clinical populations. These solutions can improve statistical power and produce reliable and valid results even in the face of limited availability of large samples.

Granger causality analysis in combination with directed network measures for classification of MS patients and healthy controls using task-related fMRI

Several studies have already assessed brain network variations in multiple sclerosis (MS) patients and healthy controls (HCs). The underlying neural system's functioning is apparently too complicated, however. Therefore, the neural time series' analysis through new methods is the aim of any recent research. Functional magnetic resonance imaging (fMRI) is a prominent modality for investigating the human brain's neural substrate, especially when cognitive impairment occurs. The present study was an attempt to investigate the brain network's differences between MS patients and HCs using graph-theoretic measures constructed by an effective connectivity measure through statistical tests. The results of the significant measures were then evaluated through machine learning methods. To this end, we gathered blood-oxygen level dependent (BOLD) fMRI data of the participants during the execution of paced auditory serial addition test (PASAT). Granger causality analysis (GCA) was then employed between brain regions' time series on each subject in order to construct a brain network. Afterward, the Wilcoxon rank-sum test was implemented to find the alteration of brain networks between the mentioned groups. According to the results, Global flow coefficient was significantly different between HCs and patients. Moreover, MS disease impacted several areas of the brain including Hippocampus, Para Hippocampal, Thalamus, Cuneus, Superior temporal gyrus, Heschl, Caudate, Medial Frontal Superior Gyrus, Fusiform, Pallidum, and several parts of Cerebellum in centrality measures and local flow coefficient. Most of the obtained regions were related to the cognitive impacts of the disease. We also found the best subset of graph features by means of Fisher score, and classified them to evaluate the features strength for the discrimination of MS patients from HCs via several machine learning methods. Having used the combination of Wilcoxon rank-sum test and Fisher score, we were able to classify MS patients from HCs using linear support vector machine (SVM) with an accuracy of 95%. With regard to the few existing studies on brain network of MS patients, especially during a cognitive task execution, our findings showed that the selected graph measures by Wilcoxon rank-sum test and Fisher score from the GCA-based brain networks resulted in a promising classification accuracy.

Analysis of brain functional connectivity network in MS patients constructed by modular structure of sparse weights from cognitive task-related fMRI

Cognitive dysfunction in multiple sclerosis (MS) seems to be the result of neural disconnections, leading to a wide range of brain functional network alterations. It is assumed that the analysis of the topological structure of brain connectivity network can be used to assess cognitive impairments in MS disease. We aimed to identify these brain connectivity pattern alterations and detect the significant features for the distinction of MS patients from healthy controls (HC). In this regard, the importance of functional brain networks construction for better exhibition of changes, inducing the improved reflection of functional organization structure should be precisely considered. In this paper, we strove to introduce a framework for modeling the functional connectivity network by considering the two most important intrinsic sparse and modular structures of brain. For the proposed approach, we first derived group-wise sparse representation via learning a common over-complete dictionary matrix from the aggregated cognitive task-based functional magnetic resonance imaging (fMRI) data of all subjects of the two groups to be able to investigate between-group differences. We then applied the modularity concept on achieved sparse coefficients to compute the connectivity strength between the two brain regions. We examined the changes in network topological properties between relapsing-remitting MS (RRMS) and matched HC groups by considering the pairwise connections of regions of the resulted weighted networks and extracting graph-based measures. We found that the informative brain regions were related to their important connectivity weights, which could distinguish MS patients from the healthy controls. The experimental findings also proved the discrimination ability of the modularity measure among all the global features. In addition, we identified such local feature subsets as eigenvector centrality, eccentricity, node strength, and within-module degree, which significantly differed between the two groups. Moreover, these nodal graph measures have been served as the detectors of brain regions, affected by different cognitive deficits. In general, our findings illustrated that integration of sparse representation, modular structure, and pairwise connectivity strength in combination with the graph properties could help us with the early diagnosis of cognitive alterations in the case of MS.

A focus on secondary progressive multiple sclerosis (SPMS): challenges in diagnosis and definition

Secondary progressive multiple sclerosis (SPMS) is the second most common form of multiple sclerosis (MS). One in two relapse remitting multiple sclerosis (RRMS) patients will develop SPMS within 15 years and up to two-thirds after 30 years, leading to a progressive decrease of neurological function and limitation of daily activities. Nevertheless, the SPMS diagnosis is often established retrospectively and delayed up to 3 years due to several patient- and clinician-related factors. Definitive clinical diagnostic criteria are lacking and research is currently ongoing to identify imaging and biochemical biomarkers. As new therapies are introduced, early SPMS diagnosis may represent a window of opportunity for intervention. New approaches, endpoints or technologies could help physicians establishing a diagnosis. Here, we review SPMS in relation to its diagnostic and definition challenges and current screening techniques and tools.

A focus on secondary progressive multiple sclerosis (SPMS): challenges in diagnosis and definition

Secondary progressive multiple sclerosis (SPMS) is the second most common form of multiple sclerosis (MS). One in two relapse remitting multiple sclerosis (RRMS) patients will develop SPMS within 15 years and up to two-thirds after 30 years, leading to a progressive decrease of neurological function and limitation of daily activities. Nevertheless, the SPMS diagnosis is often established retrospectively and delayed up to 3 years due to several patient- and clinician-related factors. Definitive clinical diagnostic criteria are lacking and research is currently ongoing to identify imaging and biochemical biomarkers. As new therapies are introduced, early SPMS diagnosis may represent a window of opportunity for intervention. New approaches, endpoints or technologies could help physicians establishing a diagnosis. Here, we review SPMS in relation to its diagnostic and definition challenges and current screening techniques and tools.

Functional correlates of cognitive dysfunction in clinically isolated syndromes

Cognitive dysfunction can be identified in patients with clinically isolated syndromes suggestive of multiple sclerosis using ocular motor testing. This study aimed to identify the functional neural correlates of cognitive dysfunction in patients with clinically isolated syndrome using MRI. Eighteen patients with clinically isolated syndrome and 17 healthy controls were recruited. Subjects underwent standard neurological and neuropsychological testing. Subjects also underwent functional MRI (fMRI) during a cognitive ocular motor task, involving pro-saccade (direct gaze towards target) and anti-saccade (direct gaze away from target) trials. Ocular motor performance variables (averaged response time and error rate) were calculated for each subject. Patients showed a trend towards a greater rate of anti-saccade errors (p = 0.09) compared to controls. Compared to controls, patients exhibited increased activation in the right postcentral, right supramarginal gyrus, and the right parietal operculum during the anti-saccade>pro-saccade contrast. This study demonstrated that changes in functional organisation of cognitive brain networks is associated with subtle cognitive changes in patients with clinically isolated syndrome.

Working memory profiles of patients with multiple sclerosis: Where does the impairment lie?

Introduction: Previous studies have mostly provided general estimations regarding Working Memory impairment in patients with Multiple Sclerosis. The aim of the present study was to investigate the relative degree of impairment in the four Working Memory components in Multiple Sclerosis. Method: Thirty-eight patients diagnosed with MS and 27 matched controls were assessed using 12 different cognitive tasks of the four components, i.e. phonological loop, visuospatial sketchpad, central executive and episodic buffer. More precisely, Greek translated and adapted versions of the following tasks were administered: Digit recall, Word recall, Non-word recall, Block recall, Mazes recall, Visual Patterns recall, Backward Digit recall, Backward Block recall, Listening recall, Logical Memory I-Immediate Story recall and Greek Verbal Learning Test, which is based on the California Verbal Learning Test. Results: The phonological loop, the central executive and the spatial subcomponent of the visuospatial sketchpad were found to be equally disrupted in MS patients. The episodic buffer was found to be more heavily affected. On the other hand, the visual subcomponent of the visuospatial sketchpad proved to be preserved. Conclusions: WM subcomponents are differentially affected in patients with MS. This novel finding is discussed within the framework of existing knowledge regarding WM impairment in MS.

The attentional cost of movement in multiple sclerosis

Individuals living with multiple sclerosis frequently have impairments in mobility. These impairments are more pronounced when they engage in a cognitively demanding mobility tasks (i.e., walking and talking, obstacle clearance, etc). Based in part on the attentional capacity model of movement, these impairments are suggested to result from greater attentional demands. Yet, this model has not been directly tested in neurological populations. The objective of the study was to determine whether individuals with multiple sclerosis have greater attentional cost of movement across a range of tasks. This study tested probe reaction times of 20 individuals with multiple sclerosis and 26 healthy controls in five different movement tasks. The tasks were specifically chosen to challenge the perceptual-motor system based on variations in static and dynamic balance requirements. Participants were asked to verbally respond as quickly as possible to randomly presented audio probes during motor performance. Task order was randomized, and average probe reaction time was calculated for each task. The results showed tasks requiring dynamic stability had greater probe reaction times in both healthy controls and individuals with multiple sclerosis. Furthermore, individuals with multiple sclerosis had longer probe reaction times across all tasks compared to healthy controls. Yet, there was no relationship between probe reaction times and performance during a complex walking scenario. The results indicate the attentional capacity model may be inadequate to explain cognitive-motor interaction in people with multiple sclerosis. Future studies should address the theoretical framework of cognitive-motor interaction, which may influence the design of interventions aimed at improving performance in individuals with MS.

Enhanced Recruitment During Executive Control Processing in Cognitively Preserved Patients With Pediatric-Onset MS

OBJECTIVES

Youth and young adults with pediatric-onset multiple sclerosis (MS) are vulnerable to executive dysfunction; however, some patients do not demonstrate functional deficits despite showing abnormalities on structural magnetic resonance imaging (MRI). Cognitively intact adults with MS have shown enhanced activation patterns relative to healthy controls on working memory tasks. We aim to evaluate whether cognitively preserved pediatric-onset MS patients engage compensatory recruitment strategies to facilitate age-normative performance on a task of working memory.

METHODS

Twenty cognitively preserved patients (mean age=18.7±2.7 years; 15 female) and 20 age- and sex-matched controls (mean age=18.5±2.9 years; 15 female) underwent neuropsychological testing and 3.0 Tesla MRI, including structural and functional acquisitions. Patterns of activation during the Alphaspan task, a working memory paradigm with two levels of executive control demand, were examined via whole-brain and region of interest (ROI) analyses.

RESULTS

Across all participants, lower accuracy and greater activation of regions implicated in working memory were observed during the high demand condition. MS patients demonstrated 0.21 s longer response time than controls. ROI analyses revealed enhanced activation for pediatric-onset MS patients relative to controls in the right middle frontal, left paracingulate, right supramarginal, and left superior parietal gyri during the low executive demand condition, over and above differences in response time. MS patients also demonstrated heightened activation in the right supramarginal gyrus in the high executive demand condition.

CONCLUSIONS

Our findings suggest that pediatric-onset MS patients may engage compensatory recruitment strategies during working memory processing. (JINS, 2019, 25, 432-442).

Identifying risk factors for cognitive issues in multiple sclerosis

INTRODUCTION

Cognitive impairment (CI) in Multiple Sclerosis (MS) has progressively regained clinical and research interest and is currently recognized as a debilitating and burdensome problem for these patients. Studying risk and protecting factors that may influence the development and course of CI is currently an area of increasing interest, due to the potential for preventive strategies. Areas covered: In this narrative review the authors briefly addressed the physiopathologic basis, assessment and management of CI in MS and then focused on identifying modifiable and not modifiable risk factors for CI in MS, providing an overview of the current knowledge in the field and indicating avenues for future research. Expert opinion: Improving our understanding of potentially modifiable environmental and lifestyle risk factors or protective factors for CI is important in order to prompt preventive strategies and orient patient counselling and clinical management. To this aim, we need to enhance the current level of evidence linking lifestyle factors to cognition and evaluate some factors that were only preliminary addressed in research. Moreover, we need to explore the role of each factor into the subject cognitive outcome, next to the possible interactions between different environmental factors as well as between environmental and genetic factors.

Neurophysiological Assessment of Cognitive Dysfunction in Patients with Multiple Sclerosis

Cognitive impairment occurs in a high percentage in all forms of multiple sclerosis, regardless of physical disability. Slowing the speed of information processing is one of the most difficult and the most frequently mentioned, but impairment of memory, attention, executive functions are included also. Long latency event related potentials (ERP) are much more objective means of cognitive functioning evaluation. Different types of immunomodulatory therapies which are used for relapsing- remitting forms of multiple sclerosis may affect the results of ERP. ERP can evaluate subclinical changes and provide important information on the evolution of cognitive changes in patients with MS.

Functional Magnetic Resonance Imaging Correlations Between Fatigue and Cognitive Performance in Patients With Relapsing Remitting Multiple Sclerosis

The correlation between fatigue and cognitive performance in multiple sclerosis (MS) is well reported, but the intimate mechanisms of the fatigue impact on cognition are not fully defined yet. The aim of this study is to investigate blood oxygen level-dependent (BOLD) activations in relapsing remitting MS (RRMS) patients with and without cognitive dysfunction and the impact of fatigue on cortical activations. Forty-two patients with RRMS were enrolled in the study. Cognitive functioning was assessed by the Symbol Digit Modalities Test (SDMT) and Paced Serial Addition Test (PASAT). A cutoff point of a total score of 55 on the SDMT was used to divide the patients into two groups: cognitively impaired (CI), SDMT score equal to or below 55 points, and cognitively preserved (CP), SMDT score above 55 points. Fatigue was assessed by the Modified Fatigue Impact Scale (MFIS). Participants were assessed with the Beck Depression Inventory (BDI) prior to inclusion in order to exclude major depressive episode. Functional Magnetic Resonance Imaging (fMRI) scanning was performed on a 3T MRI. The PVSAT (Paced Visual Serial Addition Test) paradigm was applied as a cognitive task. All functional data were analyzed with SPM12 and statistical analysis with SPSS 19.0. No statistically significant differences between CI and CP patients were found (p=0.953, p=0.322) in the MFIS and BDI score. Performance on the PASAT in CI patients was 34.07±13.721, for CP patients 46.42±11.453, and the SDMT performance in the CI patient group was 42.40±9.179, in the CP group 57.83±2.552. Between-group analysis revealed increased activations in left Brodmann area (BA) 40 in CP patients with several clusters located in the left supramarginal gyrus. Regression analysis showed increased BOLD signal in left BA 40, right BA 40, and left BA 6, associated with a higher score on MFIS. Stronger BOLD signal in left BA 31 was associated with a lower score on MFIS. Significance level was set to p<0.05, FWE (family-wise error) corrected. The differences in BOLD activations suggest the presence of cortical reorganization in our CP patients. The impact of fatigue on cortical activation during a cognitive task is demonstrated by inconformity of activated areas depending on the MFIS score. Our results suggest that activation in BA 40 may represent a mechanism for diminishing fatigue impact on cognitive functioning in CP patients.

The Role of fMRI in the Assessment of Neuroplasticity in MS: A Systematic Review

Neuroplasticity, which is the ability of the brain to adapt to internal and external environmental changes, physiologically occurs during growth and in response to damage. The brain's response to damage is of particular interest in multiple sclerosis, a chronic disease characterized by inflammatory and neurodegenerative damage to the central nervous system. Functional MRI (fMRI) is a tool that allows functional changes related to the disease and to its evolution to be studied in vivo. Several studies have shown that abnormal brain recruitment during the execution of a task starts in the early phases of multiple sclerosis. The increased functional activation during a specific task observed has been interpreted mainly as a mechanism of adaptive plasticity designed to contrast the increase in tissue damage. More recent fMRI studies, which have focused on the activity of brain regions at rest, have yielded nonunivocal results, suggesting that changes in functional brain connections represent mechanisms of either adaptive or maladaptive plasticity. The few longitudinal studies available to date on disease evolution have also yielded discrepant results that are likely to depend on the clinical features considered and the length of the follow-up. Lastly, fMRI has been used in interventional studies to investigate plastic changes induced by pharmacological therapy or rehabilitation, though whether such changes represent a surrogate of neuroplasticity remains unclear. The aim of this paper is to systematically review the existing literature in order to provide an overall description of both the neuroplastic process itself and the evolution in the use of fMRI techniques as a means of assessing neuroplasticity. The quantitative and qualitative approach adopted here ensures an objective analysis of published, peer-reviewed research and yields an overview of up-to-date knowledge.

The Role of Premotor Areas in Dual Tasking in Healthy Controls and Persons With Multiple Sclerosis: An fNIRS Imaging Study

Persons with multiple sclerosis (pwMS) experience declines in physical and cognitive abilities and are challenged by dual-tasks. Dual-tasking causes a drop in performance, or what is known as dual-task cost (DTC). This study examined DTC of walking speed (WS) and cognitive performance (CP) in pwMS and healthy controls (HCs) and the effect of dual-tasking on cortical activation of bilateral premotor cortices (PMC) and bilateral supplementary motor area (SMA). Fourteen pwMS and 14 HCs performed three experimental tasks: (1) single cognitive task while standing (SingCog); (2) single walking task (SingWalk); and (3) dual-task (DualT) that included concurrent performance of the SingCog and SingWalk. Six trials were collected for each condition and included measures of cortical activation, WS and CP. WS of pwMS was significantly lower than HC, but neuropsychological (NP) measures were not significantly different. pwMS and HC groups had similar DTC of WS, while DTC of CP was only significant in the MS group; processing speed and visual memory predicted 55% of this DTC. DualT vs. SingWalk recruited more right-PMC activation only in HCs and was associated with better processing speed. DualT vs. SingCog recruited more right-PMC activation and bilateral-SMA activation in both HC and pwMS. Lower baseline WS and worse processing speed measures in pwMS predicted higher recruitment of right-SMA (rSMA) activation suggesting maladaptive recruitment. Lack of significant difference in NP measures between groups does not rule out the influence of cognitive factors on dual-tasking performance and cortical activations in pwMS, which might have a negative impact on quality of life.

Longitudinal study of functional brain network reorganization in clinically isolated syndrome

BACKGROUND

There is a lack of longitudinal studies exploring the topological organization of functional brain networks at the early stages of multiple sclerosis (MS).

OBJECTIVE

This study aims to assess potential brain functional reorganization at rest in patients with CIS (PwCIS) after 1 year of evolution and to characterize the dynamics of functional brain networks at the early stage of the disease.

METHODS

We prospectively included 41 PwCIS and 19 matched healthy controls (HCs). They were scanned at baseline and after 1 year. Using graph theory, topological metrics were calculated for each region. Hub disruption index was computed for each metric.

RESULTS

Hub disruption indexes of degree and betweenness centrality were negative at baseline in patients (p < 0.05), suggesting brain reorganization. After 1 year, hub disruption indexes for degree and betweenness centrality were still negative (p < 0.00001), but such reorganization appeared more pronounced than at baseline. Different brain regions were driving these alterations. No global efficiency differences were observed between PwCIS and HCs either at baseline or at 1 year.

CONCLUSION

Dynamic changes in functional brain networks appear at the early stages of MS and are associated with the maintenance of normal global efficiency in the brain, suggesting a compensatory effect.

Glutamate-sensitive imaging and evaluation of cognitive impairment in multiple sclerosis

BACKGROUND

Cognitive impairment (CI) profoundly impacts quality of life for patients with multiple sclerosis (MS). Dysfunctional regulation of glutamate in gray matter (GM) has been implicated in the pathogenesis of MS by post-mortem pathological studies and in CI by in vivo magnetic resonance spectroscopy, yet GM pathology is subtle and difficult to detect using conventional T₁- and T₂-weighted magnetic resonance imaging (MRI). There is a need for high-resolution, clinically accessible imaging techniques that probe molecular changes in GM.

OBJECTIVE

To study cortical GM pathology related to CI in MS using glutamate-sensitive chemical exchange saturation transfer (GluCEST) MRI at 7.0 Tesla (7T).

METHODS

A total of 20 patients with relapsing-remitting MS and 20 healthy controls underwent cognitive testing, anatomical imaging, and GluCEST imaging. Glutamate-sensitive image contrast was quantified for cortical GM, compared between cohorts, and correlated with clinical measures of CI.

RESULTS AND CONCLUSION

Glutamate-sensitive contrast was significantly increased in the prefrontal cortex of MS patients with accumulated disability (p < 0.05). In addition, glutamate-sensitive contrast in the prefrontal cortex was significantly correlated with symbol digit modality test (r_S = -0.814) and choice reaction time (r_S = 0.772) scores in patients (p < 0.05), suggesting that GluCEST MRI may have utility as a marker for GM pathology and CI.

Meta-analytic evidence for a core problem solving network across multiple representational domains

Problem solving is a complex skill engaging multi-stepped reasoning processes to find unknown solutions. The breadth of real-world contexts requiring problem solving is mirrored by a similarly broad, yet unfocused neuroimaging literature, and the domain-general or context-specific brain networks associated with problem solving are not well understood. To more fully characterize those brain networks, we performed activation likelihood estimation meta-analysis on 280 neuroimaging problem solving experiments reporting 3166 foci from 1919 individuals across 131 papers. The general map of problem solving revealed broad fronto-cingulo-parietal convergence, regions similarly identified when considering separate mathematical, verbal, and visuospatial problem solving domain-specific analyses. Conjunction analysis revealed a common network supporting problem solving across diverse contexts, and difference maps distinguished functionally-selective sub-networks specific to task type. Our results suggest cooperation between representationally specialized sub-network and whole-brain systems provide a neural basis for problem solving, with the core network contributing general purpose resources to perform cognitive operations and manage problem demand. Further characterization of cross-network dynamics could inform neuroeducational studies on problem solving skill development.