Abnormalities of the executive control network in multiple sclerosis phenotypes: An fMRI effective connectivity study

Regional GABA levels modulate abnormal resting-state network functional connectivity and cognitive impairment in multiple sclerosis

More evidence shows that changes in functional connectivity with regard to brain networks and neurometabolite levels correlated to cognitive impairment in multiple sclerosis. However, the neurological basis underlying the relationship among neurometabolite levels, functional connectivity, and cognitive impairment remains unclear. For this purpose, we used a combination of magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging to study gamma-aminobutyric acid and glutamate concentrations in the posterior cingulate cortex, medial prefrontal cortex and left hippocampus, and inter-network functional connectivity in 29 relapsing-remitting multiple sclerosis patients and 34 matched healthy controls. Neuropsychological tests were used to evaluate the cognitive function. We found that relapsing-remitting multiple sclerosis patients demonstrated significantly reduced gamma-aminobutyric acid and glutamate concentrations and aberrant functional connectivity involving cognitive-related networks compared to healthy controls, and both alterations were associated with specific cognition decline. Moreover, mediation analyses indicated that decremented hippocampus gamma-aminobutyric acid levels in relapsing-remitting multiple sclerosis patients mediated the association between inter-network functional connectivity in various components of default mode network and verbal memory deficits. In summary, our findings shed new lights on the essential function of GABAergic system abnormalities in regulating network dysconnectivity and functional connectivity in relapsing-remitting multiple sclerosis patients, suggesting potential novel approach to treatment.

Structural and functional magnetic resonance imaging correlates of fatigue and dual-task performance in progressive multiple sclerosis

BACKGROUND

Frontal cortico-subcortical dysfunction may contribute to fatigue and dual-task impairment of walking and cognition in progressive multiple sclerosis (PMS).

PURPOSE

To explore the associations among fatigue, dual-task performance and structural and functional abnormalities of frontal cortico-subcortical network in PMS.

METHODS

Brain 3 T structural and functional MRI sequences, Modified Fatigue Impact Scale (MFIS), dual-task motor and cognitive performances were obtained from 57 PMS patients and 10 healthy controls (HC). The associations of thalamic, caudate nucleus and dorsolateral prefrontal cortex (DLPFC) atrophy, microstructural abnormalities of their connections and their resting state effective connectivity (RS-EC) with fatigue and dual-task performance were investigated using random forest.

RESULTS

Thirty-seven PMS patients were fatigued (F) (MFIS ≥ 38). Compared to HC, non-fatigued (nF) and F-PMS patients had significantly worse dual-task performance (p ≤ 0.002). Predictors of fatigue (out-of-bag [OOB]-accuracy = 0.754) and its severity (OOB-R² = 0.247) were higher Expanded Disability Status scale (EDSS) score, lower RS-EC from left-caudate nucleus to left-DLPFC, lower fractional anisotropy between left-caudate nucleus and left-thalamus, higher mean diffusivity between right-caudate nucleus and right-thalamus, and longer disease duration. Microstructural abnormalities in connections among thalami, caudate nuclei and DLPFC, mainly left-lateralized in nF-PMS and more bilateral in F-PMS, higher RS-EC from left-DLPFC to right-DLPFC in nF-PMS and lower RS-EC from left-caudate nucleus to left-DLPFC in F-PMS, higher EDSS score, higher WM lesion volume, and lower cortical volume predicted worse dual-task performances (OOB-R² from 0.426 to 0.530).

CONCLUSIONS

In PMS, structural and functional frontal cortico-subcortical abnormalities contribute to fatigue and worse dual-task performance, with different patterns according to the presence of fatigue.

Graph-Based Analysis of Brain Connectivity in Multiple Sclerosis Using Functional MRI: A Systematic Review

(1) Background: Multiple sclerosis (MS) is an immune system disease in which myelin in the nervous system is affected. This abnormal immune system mechanism causes physical disabilities and cognitive impairment. Functional magnetic resonance imaging (fMRI) is a common neuroimaging technique used in studying MS. Computational methods have recently been applied for disease detection, notably graph theory, which helps researchers understand the entire brain network and functional connectivity. (2) Methods: Relevant databases were searched to identify articles published since 2000 that applied graph theory to study functional brain connectivity in patients with MS based on fMRI. (3) Results: A total of 24 articles were included in the review. In recent years, the application of graph theory in the MS field received increased attention from computational scientists. The graph-theoretical approach was frequently combined with fMRI in studies of functional brain connectivity in MS. Lower EDSSs of MS stage were the criteria for most of the studies (4) Conclusions: This review provides insights into the role of graph theory as a computational method for studying functional brain connectivity in MS. Graph theory is useful in the detection and prediction of MS and can play a significant role in identifying cognitive impairment associated with MS.

Neurorehabilitation in Multiple Sclerosis-A Review of Present Approaches and Future Considerations

Multiple sclerosis is an increasingly prevalent disease, representing the leading cause of non-traumatic neurological disease in Europe and North America. The most common symptoms include gait deficits, balance and coordination impairments, fatigue, spasticity, dysphagia and an overactive bladder. Neurorehabilitation therapeutic approaches aim to alleviate symptoms and improve the quality of life through promoting positive immunological transformations and neuroplasticity. The purpose of this study is to evaluate the current treatments for the most debilitating symptoms in multiple sclerosis, identify areas for future improvement, and provide a reference guide for practitioners in the field. It analyzes the most cited procedures currently in use for the management of a number of symptoms affecting the majority of patients with multiple sclerosis, from different training routines to cognitive rehabilitation and therapies using physical agents, such as electrostimulation, hydrotherapy, cryotherapy and electromagnetic fields. Furthermore, it investigates the quality of evidence for the aforementioned therapies and the different tests applied in practice to assess their utility. Lastly, the study looks at potential future candidates for the treatment and evaluation of patients with multiple sclerosis and the supposed benefits they could bring in clinical settings.

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.

Cingulo-Opercular and Frontoparietal Network Control of Effort and Fatigue in Mild Traumatic Brain Injury

Neural substrates of fatigue in traumatic brain injury (TBI) are not well understood despite the considerable burden of fatigue on return to productivity. Fatigue is associated with diminishing performance under conditions of high cognitive demand, sense of effort, or need for motivation, all of which are associated with cognitive control brain network integrity. We hypothesize that the pathophysiology of TBI results in damage to diffuse cognitive control networks, disrupting coordination of moment-to-moment monitoring, prediction, and regulation of behavior. We investigate the cingulo-opercular (CO) and frontoparietal (FP) networks, which are engaged to sustain attention for task and maintain performance. A total of 61 individuals with mild TBI and 42 orthopedic control subjects participated in functional MRI during performance of a constant effort task requiring altering the amount of effort (25, 50, or 75% of maximum effort) utilized to manually squeeze a pneumostatic bulb across six 30-s trials. Network-based statistics assessed within-network organization and fluctuation with task manipulations by group. Results demonstrate small group differences in network organization, but considerable group differences in the evolution of task-related modulation of connectivity. The mild TBI group demonstrated elevated CO connectivity throughout the task with little variation in effort level or time on task (TOT), while CO connectivity diminished over time in controls. Several interregional CO connections were predictive of fatigue in the TBI group. In contrast, FP connectivity fluctuated with task manipulations and predicted fatigue in the controls, but connectivity fluctuations were delayed in the mild traumatic brain injury (mTBI) group and did not relate to fatigue. Thus, the mTBI group's hyper-connectivity of the CO irrespective of task demands, along with hypo-connectivity and delayed peak connectivity of the FP, may allow for attainment of task goals, but also contributes to fatigue. Findings are discussed in relation to performance monitoring of prediction error that relies on internal cues from sensorimotor feedback during task performance. Delay or inability to detect and respond to prediction errors in TBI, particularly evident in bilateral insula-temporal CO connectivity, corresponds to day-to-day fatigue and fatigue during task performance.

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.

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.

Social cognition in multiple sclerosis and its subtypes: A meta-analysis

BACKGROUND

Multiple sclerosis (MS) is an immune-mediated demyelinating disease that disrupts several social cognitive abilities, including the theory of mind (ToM) and facial emotion recognition (FER). It is unclear how specific ToM subcomponents, including cognitive and affective ToM, are affected in patients with MS and the social cognitive abilities in MS subtypes.

METHODS

A search of PubMed, Web of Science, and Embase databases was conducted until June 2020. Effect sizes were calculated using Hedges g with a random-effects model.

RESULTS

A total of 45 studies were included. Relative to health controls (HCs), patients with MS and its subtypes (including relapsing-remitting MS [RRMS] and progressive MS) exhibited impairments in ToM (g = -0.77, g = -0.70, g = -0.75, respectively), cognitive ToM (g = -0.72, g = -0.83, g = -0.73, respectively), affective ToM (g = -0.84, g = -0.63, g = -0. 50, respectively), and FER (g = -0.62, g = -0.53, g = -1.07, respectively). In addition, there was no difference between progressive primary MS and secondary progressive MS in overall ToM, cognitive ToM, affective ToM, and FER. Compared to patients with RRMS, patients with progressive MS showed no difference in overall ToM, cognitive ToM, and affective ToM but had more serious defects in FER (g = -0.57).

CONCLUSIONS

These quantitative results indicate that patients with MS and its subtypes have a differential impairment of the core aspects of social cognitive processing (including ToM and FER), which may help develop the structured social cognitive interventions in MS.

Dorsolateral prefrontal circuit effective connectivity mediates the relationship between white matter structure and PASAT-3 performance in multiple sclerosis

Three decades ago a series of parallel circuits were described involving the frontal cortex and deep grey matter structures, with putative roles in control of motor and oculomotor function, cognition, behaviour and emotion. The circuit comprising the dorsolateral prefrontal cortex, caudate, globus pallidus and thalamus has a putative role in regulating executive functions. The aim of this study is to investigate effective connectivity (EC) of the dorsolateral-prefrontal circuit and its association with PASAT-3 performance in people with multiple sclerosis(MS). We use Granger causality analysis of resting-state functional MRI from 52 people with MS and 36 healthy people to infer that reduced EC in the afferent limb of the dorsolateral prefrontal circuit occurs in the people with MS with cognitive dysfunction (left: p = .006; right: p = .029), with bilateral EC reductions in this circuit resulting in more severe cognitive dysfunction than unilateral reductions alone (p = .002). We show that reduced EC in the afferent limb of the dorsolateral prefrontal circuit mediates the relationship between cognitive performance and macrostrucutral and microstructural alterations of white matter tracts in components of the circuit. Specificity is shown by the absence of any relationship between cognition and EC in the analogous and anatomically proximal motor circuit. We demonstrate good stability of the EC measures in people with MS over an interval averaging 8-months. Key positive and negative results are replicated in an independent cohort of people with MS. Our findings identify the dorsolateral prefrontal circuit as a potential target for therapeutic strategies aimed at improving cognition in people with MS.

Cognitive Fatigue Is Associated with Altered Functional Connectivity in Interoceptive and Reward Pathways in Multiple Sclerosis

Cognitive fatigue is common and debilitating among persons with multiple sclerosis (pwMS). Neural mechanisms underlying fatigue are not well understood, which results in lack of adequate treatment. The current study examined cognitive fatigue-related functional connectivity among 26 pwMS and 14 demographically matched healthy controls (HCs). Participants underwent functional magnetic resonance imaging (fMRI) scanning while performing a working memory task (n-back), with two conditions: one with higher cognitive load (2-back) to induce fatigue and one with lower cognitive load (0-back) as a control condition. Task-independent residual functional connectivity was assessed, with seeds in brain regions previously implicated in cognitive fatigue (dorsolateral prefrontal cortex (DLPFC), ventromedial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), insula, and striatum). Cognitive fatigue was measured using the Visual Analogue Scale of Fatigue (VAS-F). Results indicated that as VAS-F scores increased, HCs showed increased residual functional connectivity between the striatum and the vmPFC (crucial in reward processing) during the 2-back condition compared to the 0-back condition. In contrast, pwMS displayed increased residual functional connectivity from interoceptive hubs—the insula and the dACC—to the striatum. In conclusion, pwMS showed a hyperconnectivity within the interoceptive network and disconnection within the reward circuitry when experiencing cognitive fatigue.

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.

Anterior Insular Resting-State Functional Connectivity is Related to Cognitive Reserve in Multiple Sclerosis

BACKGROUND AND PURPOSE

Cognitive dysfunction is common in multiple sclerosis (MS). The dorsal anterior insula (dAI) is a key hub of the salience network (SN) orchestrating access to critical cognitive brain regions. The aim of this study was to assess whole-brain dAI intrinsic functional connectivity (iFC) using resting-state functional MRI (rs-fMRI) in people with MS and healthy controls (HC) and test the relationship between cognitive reserve (CR) and dAI iFC in people with MS.

METHODS

We studied 28 people with relapsing-remitting MS and 28 HC. CR index was quantified by combining premorbid IQ, leisure activities, and education level. For whole-brain iFC analyses, the bilateral dAI were used as seeds. Individual subject correlation maps were entered into general linear models for group comparison and to analyze the effect of CR index on dAI iFC, controlling for multiple comparisons. The correlation between CR index and iFC was assessed using a linear regression model.

RESULTS

rs-fMRI analyses revealed a negative relationship between CR index and iFC within the left dAI and a left occipital cluster in people with MS including regions of the cuneus, superior occipital gyrus, and parieto-occipital sulcus. The regression analysis showed that people with MS and a higher CR index had a statistically significantly reduced iFC within the left dAI and the cluster.

CONCLUSIONS

CR is relevant to functional connectivity within one of the main nodes of the SN, the dAI, and occipital regions in MS. These results have implications for how CR may modulate the susceptibility to cognitive dysfunction in MS.

Social cognition in multiple sclerosis and its subtypes: A protocol for systematic review and meta-analysis

BACKGROUND

Multiple sclerosis (MS) is an inflammatory and degenerative neurological disorder of the central nervous system. Cognitive impairment is frequent in MS patients, which not only includes deficits in abilities assessed by traditional neuropsychological batteries, but also often features impairments in social cognition (including theory of mind and facial emotion recognition). Recently, numerous studies have assessed social cognition performance in MS. However, there have been inconsistent findings. Besides, it is not clear how social cognitive abilities are affected in MS subtypes. The aim of this study is to conduct a meta-analysis to characterize social cognition performance in MS and its subtypes (clinically isolated syndrome, relapsing-remitting MS, progressive primary MS, and secondary progressive MS).

METHODS

Literature sources will be divided into 2 sections: electronic sources and manual sources. A systematic literature search will be performed for eligible studies published up to June 10, 2020 in 3 international databases (Embase, PubMed, and Web of Science). In addition, manual sources will be searched, such as the references of all included studies. Two researchers will independently conduct the work such as article retrieval, screening, quality evaluation, data collection. Meta-analysis will be conducted using Stata 15.0 software.

RESULTS

The results of this study will be published in a peer-reviewed journal.

CONCLUSIONS

This meta-analysis will provide a high-quality synthesis from existing evidence for social cognition performance in MS and its subtypes.

PROSPERO REGISTRATION NUMBER

INPLASY202070028.

Treatment and management of cognitive dysfunction in patients with multiple sclerosis

Cognitive impairment is a common and devastating manifestation of multiple sclerosis (MS). Although disease-modifying therapies have been efficacious for reducing relapse rates in MS, such treatments are ineffective for treating cognitive dysfunction. Alternative treatment approaches for mitigating cognitive problems are greatly needed in this population. To date, cognitive rehabilitation and exercise training have been identified as possible candidates for treating MS-related cognitive impairment; however, cognitive dysfunction is still often considered to be poorly managed in patients with MS. This Review provides a comprehensive overview of recent developments in the treatment and management of cognitive impairment in people with MS. We describe the theoretical rationales, current states of the science, field-wide challenges and recent advances in cognitive rehabilitation and exercise training for treating MS-related cognitive impairment. We also discuss future directions for research into the treatment of cognitive impairment in MS that should set the stage for the inclusion of cognitive rehabilitation and exercise training into clinical practice within the next decade.

Longitudinal assessment of resting-state fMRI in temporal lobe epilepsy: A two-year follow-up study

In this study, we aimed to detect longitudinal alterations in local spontaneous brain activity and functional connectivity (FC) of the default mode network (DMN) in patients with temporal lobe epilepsy (TLE) over a two-year follow-up. We used amplitude of low-frequency fluctuation (ALFF) analysis and independent component analysis (ICA) to explore differences in local spontaneous brain activity and FC strength. In total, 33 participants (16 patients with TLE and 17 age- and gender-matched healthy controls (HCs)) were recruited in this study. All participants performed the Attention Network Test (ANT) for evaluation of the executive control function. Compared with healthy patients at baseline, patients with TLE at follow-up exhibited increased ALFF values in the left medial frontal gyrus, as well as reduced FC values in the left inferior parietal gyrus (IPG) within the DMN. Patients with TLE revealed executive dysfunction, but no progressive deterioration was observed during follow-up. This study revealed the abnormal distribution of ALFF values and Rs-FC changes over a two-year follow-up period in TLE, both of which demonstrated different reorganization trajectories and loss of efficiency.

Continuous reorganization of cortical information flow in multiple sclerosis: A longitudinal fMRI effective connectivity study

Effective connectivity (EC) is able to explore causal effects between brain areas and can depict mechanisms that underlie repair and adaptation in chronic brain diseases. Thus, the application of EC techniques in multiple sclerosis (MS) has the potential to determine directionality of neuronal interactions and may provide an imaging biomarker for disease progression. Here, serial longitudinal structural and resting-state fMRI was performed at 12-week intervals over one year in twelve MS patients. Twelve healthy subjects served as controls (HC). Two approaches for EC quantification were used: Causal Bayesian Network (CBN) and Time-resolved Partial Directed Coherence (TPDC). The EC strength was correlated with the Expanded Disability Status Scale (EDSS) and Fatigue Scale for Motor and Cognitive functions (FSMC). Our findings demonstrated a longitudinal increase in EC between specific brain regions, detected in both the CBN and TPDC analysis in MS patients. In particular, EC from the deep grey matter, frontal, prefrontal and temporal regions showed a continuous increase over the study period. No longitudinal changes in EC were attested in HC during the study. Furthermore, we observed an association between clinical performance and EC strength. In particular, the EC increase in fronto-cerebellar connections showed an inverse correlation with the EDSS and FSMC. Our data depict continuous functional reorganization between specific brain regions indicated by increasing EC over time in MS, which is not detectable in HC. In particular, fronto-cerebellar connections, which were closely related to clinical performance, may provide a marker of brain plasticity and functional reserve in MS.

Characterization of inhibitory failure in Multiple Sclerosis: Evidence of impaired conflict resolution

INTRODUCTION

Inhibitory control deficits are frequently reported in Multiple Sclerosis (MS), although it is unclear whether these deficits represent a global or process-specific failure. Notably, most models of inhibitory control recognize at least two dissociable processes, the most consistent being: (a) the inhibition of a dominant response: response suppression, and (b) the inhibition of a dominant response and initiation of a nondominant response: executive control. This study aimed to ascertain the processes underlying inhibitory failure in MS.

METHOD

Twenty-three MS patients and 25 healthy controls completed a battery of commonly used inhibitory tasks, with measures from each task entered into a principal components analysis with orthogonal (varimax) rotation.

RESULTS

As anticipated, two components emerged, with tasks evaluating response suppression (stop signal, go/no go) loading on a common component, and tasks evaluating executive control (Stroop, antisaccade, endogenously-cued saccade) loading on a separate common component. Composite scores were generated for each component and compared between groups. Unlike response suppression scores, executive control scores were significantly poorer for MS patients.

CONCLUSIONS

Inhibitory control deficits in MS may reflect poor resolution in the context of competing processes, rather than difficulty in preventing the execution of an inappropriate response.

Uncovering the association between fatigue and fatigability in multiple sclerosis using cognitive control

BACKGROUND

Fatigue and cognitive dysfunction are two common symptoms experienced by patients with multiple sclerosis (MS). The relationship between subjective and objective fatigue (fatigability) in MS is poorly understood. Cognitive control tasks might be more conducive to fatigability and more likely to show associations between subjective and objective cognitive fatigue in MS.

OBJECTIVE

To study the association between objective fatigability, as induced by a cognitive control task called the Blocked Cyclic Naming Task (BCNT), subjective fatigue and baseline cognitive functioning in patients with MS.

METHODS

Twenty-one patients with MS completed baseline questions about their disease, the Montreal Cognitive Assessment (MoCA) battery and self-reported questionnaires on trait fatigue, sleep and depression. Disability was captured using the expanded disability status scale (EDSS). Participants then performed the BCNT and were asked about their level of state momentary fatigue before and after the BCNT. The BCNT consists of several blocks of either related or unrelated pictures that participants name as quickly as possible. The pictures cycled 4 times in each block and the difference in the response times (RTs) between related and unrelated blocks was captured. Data were analyzed using repeated measures analysis of variance and Pearson correlations.

RESULTS

MS participants' performance declined for the related, but not unrelated blocks. The difference in RTs between related and unrelated conditions increased with repetition across cycles (p < 0.001). Participants also showed objective fatigability with less repetition priming (p = 0.02) in the 4th quarter and with greater differences between related and unrelated conditions in the later part of the task. Objective fatigability was strongly associated with participants' assessment of their level of momentary state fatigue (r = 0.612, p = 0.007).

CONCLUSION

Using the appropriate tools, this study showed an association between subjective and objective cognitive fatigue in people with MS. The BCNT and cognitive control are useful tools in assessing patients with MS and should be explored in future, larger studies in this population.

Integrative CNS Plasticity With Exercise in MS: The PRIMERS (PRocessing, Integration of Multisensory Exercise-Related Stimuli) Conceptual Framework

There is a proliferation of research examining the effects of exercise on mobility and cognition in the general population and those with neurological disorders as well as focal research examining possible neural mechanisms of such effects. However, there is seemingly a lack of focus on what it is about exercise, in particular, that drives adaptive central nervous system neuroplasticity. We propose a novel conceptual framework (ie, PRIMERS) that describes such adaptations as occurring via activity-dependent neuroplasticity based on the integrative processing of multisensory input and associated complex motor output that is required for the regulation of physiological systems during exercise behavior. This conceptual framework sets the stage for the systematic examination of the effects of exercise on brain connectivity, brain structure, and molecular/cellular mechanisms that explain improvements in mobility and cognition in the general population and persons with multiple sclerosis (MS). We argue that exercise can be viewed as an integrative, systems-wide stimulus for neurorehabilitation because impaired mobility and cognition are common and co-occurring in MS.

Altered neural mechanisms of cognitive control in patients with primary progressive multiple sclerosis: An effective connectivity study

Primary progressive multiple sclerosis (PPMS) leads to physical and cognitive disability. Specifically, cognitive deficits in PPMS have been explained by both grey matter atrophy and white matter lesions. However, existing research still lacks in the understanding of how the brain of a patient with PPMS functions under cognitive control demands. Thus, the aim of the current study was to examine information integration in patients with PPMS using a search-based effective connectivity method. Fourteen patients with PPMS and 22 age- and gender-matched healthy controls (HC) performed the Stroop task, a cognitively demanding interference task that taxes neural resources required for cognitive control and response inhibition. Results showed that compared to HC, PPMS patients exhibited poor behavioral performance and alterations in information flow, manifested in the form of the loss of top-down connections, reversal of connections, and hyperconnectivity. Significant correlations were observed between connection strengths and behavioral measures. The connection between the posterior parietal cortex (PCC) and left posterior parietal lobule, which was present in both groups, showed a negative correlation with performance accuracy on incongruent trials. The connection between the left dorsolateral prefrontal cortex and PCC showed a positive correlation with performance accuracy on incongruent trials. However, the adaptive nature of this connection was not significant on a behavioral level as the PPMS group performed significantly worse compared to the HC group during the Stroop task. Thus, the current study provides important evidence about effective connectivity patterns that can be characterized as maladaptive cerebral re-organization in the PPMS brain. Hum Brain Mapp 38:2580-2588, 2017. © 2017 Wiley Periodicals, Inc.