Long-term neuroprotective effects of natalizumab and fingolimod in multiple sclerosis: Evidence from real-world clinical data.

BACKGROUND: The long-term effect of high efficacy disease modifying therapy (DMT) on neurodegeneration in people with multiple sclerosis (pwMS) is largely unknown. The aim of this study was to evaluate the long-term effect of natalizumab (NTZ) or fingolimod (FTY) therapy on the evolution of brain atrophy compared to moderate efficacy DMT in a real-world clinical setting. METHODS: A total of 438 pwMS with 2,439 MRI exams during treatment were analyzed: 252 pwMS treated with moderate efficacy DMT, 130 with NTZ and 56 with FTY. Evolution of brain atrophy was analyzed over an average follow-up of 6.6 years after treatment initiation. Brain segmentation was performed on clinical 3D-FLAIRs using SynthSeg and regional brain volume changes over time were compared between the treatment groups. RESULTS: Total brain, white matter and deep gray matter atrophy rates did not differ between moderate efficacy DMTs, NTZ and FTY. Annualized ventricle growth rates were lower in pwMS treated with NTZ (1.1 %/year) compared with moderate efficacy DMT (2.4 %/year, p < 0.001) and similar to FTY (2.0 %/year, p = 0.051). Cortical atrophy rates were lower in NTZ (-0.08 %/year) compared with moderate efficacy DMT (-0.16 %/year, p = 0.048). CONCLUSION: In a real-world clinical setting, pwMS treated with NTZ had slower ventricular expansion and cortical atrophy compared to those treated with moderate efficacy DMT.

Dynamic reconfigurations of brain networks in depressive and anxiety disorders: The influence of antidepressants.

Major Depressive Disorder (MDD) and anxiety disorders are highly comorbid recurrent psychiatric disorders. Reduced dynamic reconfiguration of brain regions across subnetworks may play a critical role underlying these deficits, with indications of normalization after treatment with antidepressants. This study investigated dynamic reconfigurations in controls and individuals with a current MDD and/or anxiety disorder including antidepressant users and non-users in a large sample (N = 207) of adults. We quantified the number of subnetworks a region switched to (promiscuity) as well as the total number of switches (flexibility). Average whole-brain (i.e., global) values and subnetwork-specific values were compared between diagnosis and antidepressant groups. No differences in reconfiguration dynamics were found between individuals with a current MDD (N = 49), anxiety disorder (N = 46), comorbid MDD and anxiety disorder (N = 55), or controls (N = 57). Global and sensorimotor network (SMN) promiscuity and flexibility were higher in antidepressant users (N = 49, regardless of diagnosis) compared to non-users (N = 101) and controls. Dynamic reconfigurations were considerably higher in antidepressant users relative to non-users and controls, but not significantly altered in individuals with a MDD and/or anxiety disorder. The increase in antidepressant users was apparent across the whole brain and in the SMN when investigating subnetworks. These findings help disentangle how antidepressants improve symptoms.

Comparing individual and group-level simulated neurophysiological brain connectivity using the Jansen and Rit neural mass model.

Computational models are often used to assess how functional connectivity (FC) patterns emerge from neuronal population dynamics and anatomical brain connections. It remains unclear whether the commonly used group-averaged data can predict individual FC patterns. The Jansen and Rit neural mass model was employed, where masses were coupled using individual structural connectivity (SC). Simulated FC was correlated to individual magnetoencephalography-derived empirical FC. FC was estimated using phase-based (phase lag index (PLI), phase locking value (PLV)), and amplitude-based (amplitude envelope correlation (AEC)) metrics to analyze their goodness of fit for individual predictions. Individual FC predictions were compared against group-averaged FC predictions, and we tested whether SC of a different participant could equally well predict participants' FC patterns. The AEC provided a better match between individually simulated and empirical FC than phase-based metrics. Correlations between simulated and empirical FC were higher using individual SC compared to group-averaged SC. Using SC from other participants resulted in similar correlations between simulated and empirical FC compared to using participants' own SC. This work underlines the added value of FC simulations using individual instead of group-averaged SC for this particular computational model and could aid in a better understanding of mechanisms underlying individual functional network trajectories.

Feasibility of detecting atrophy relevant for disability and cognition in multiple sclerosis using 3D-FLAIR.

BACKGROUND AND OBJECTIVES: Disability and cognitive impairment are known to be related to brain atrophy in multiple sclerosis (MS), but 3D-T1 imaging required for brain volumetrics is often unavailable in clinical protocols, unlike 3D-FLAIR. Here our aim was to investigate whether brain volumes derived from 3D-FLAIR images result in similar associations with disability and cognition in MS as do those derived from 3D-T1 images. METHODS: 3T-MRI scans of 329 MS patients and 76 healthy controls were included in this cross-sectional study. Brain volumes were derived using FreeSurfer on 3D-T1 and compared with brain volumes derived with SynthSeg and SAMSEG on 3D-FLAIR. Relative agreement was evaluated by calculating the intraclass correlation coefficient (ICC) of the 3D-T1 and 3D-FLAIR volumes. Consistency of relations with disability and average cognition was assessed using linear regression, while correcting for age and sex. The findings were corroborated in an independent validation cohort of 125 MS patients. RESULTS: The ICC between volume measured with FreeSurfer and those measured on 3D-FLAIR for brain, ventricle, cortex, total deep gray matter and thalamus was above 0.74 for SAMSEG and above 0.91 for SynthSeg. Worse disability and lower average cognition were similarly associated with brain (adj. R2 = 0.24-0.27, p < 0.01; adj. R2 = 0.26-0.29, p < 0.001) ventricle (adj. R2 = 0.27-0.28, p < 0.001; adj. R2 = 0.19-0.20, p < 0.001) and deep gray matter volumes (adj. R2 = 0.24-0.28, p < 0.001; adj. R2 = 0.27-0.28, p < 0.001) determined with all methods, except for cortical volumes derived from 3D-FLAIR. DISCUSSION: In this cross-sectional study, brain volumes derived from 3D-FLAIR and 3D-T1 show similar relationships to disability and cognitive dysfunction in MS, highlighting the potential of these techniques in clinical datasets.

Impaired saccadic eye movements in multiple sclerosis are related to altered functional connectivity of the oculomotor brain network.

BACKGROUND: Impaired eye movements in multiple sclerosis (MS) are common and could represent a non-invasive and accurate measure of (dys)functioning of interconnected areas within the complex brain network. The aim of this study was to test whether altered saccadic eye movements are related to changes in functional connectivity (FC) in patients with MS. METHODS: Cross-sectional eye movement (pro-saccades and anti-saccades) and magnetoencephalography (MEG) data from the Amsterdam MS cohort were included from 176 MS patients and 33 healthy controls. FC was calculated between all regions of the Brainnetome atlas in six conventional frequency bands. Cognitive function and disability were evaluated by previously validated measures. The relationships between saccadic parameters and both FC and clinical scores in MS patients were analysed using multivariate linear regression models. RESULTS: In MS pro- and anti-saccades were abnormal compared to healthy controls A relationship of saccadic eye movements was found with FC of the oculomotor network, which was stronger for regional than global FC. In general, abnormal eye movements were related to higher delta and theta FC but lower beta FC. Strongest associations were found for pro-saccadic latency and FC of the precuneus (beta band ß = -0.23, p = .006), peak velocity and FC of the parietal eye field (theta band ß = -0.25, p = .005) and gain and FC of the inferior frontal eye field (theta band ß = -0.25, p = .003). Pro-saccadic latency was also strongly associated with disability scores and cognitive dysfunction. CONCLUSIONS: Impaired saccadic eye movements were related to functional connectivity of the oculomotor network and clinical performance in MS. This study also showed that, in addition to global network connectivity, studying regional changes in MEG studies could yield stronger correlations.

Structural network topology and microstructural alterations of the anterior insula associate with cognitive and affective impairment in Parkinson's disease.

The aim of the current study was to assess the structural centrality and microstructural integrity of the cortical hubs of the salience network, the anterior insular cortex (AIC) subregions and anterior cingulate cortex (ACC), and their relationship to cognitive and affective impairment in PD. MRI of 53 PD patients and 15 age-matched controls included 3D-T1 for anatomical registration, and diffusion tensor imaging for probabilistic tractography. Network topological measures of eigenvector and betweenness centrality were calculated for ventral (vAI) and dorsal (dAI) AIC. Microstructural tract integrity between vAI, dAI and the ACC was quantified with fractional anisotrophy (FA) and mean diffusivity (MD). Structural integrity and connectivity were related to cognitive and affective scores. The dAI had significantly higher eigenvector centrality in PD than controls (p < 0.01), associated with higher depression scores (left dAI only, rs = 0.28, p < 0.05). Tracts between dAI and ACC showed lower FA and higher MD in PD (p < 0.05), and associated with lower semantic fluency, working memory and executive functioning, and higher anxiety scores (range 0.002 < p < 0.05). This study provides evidence for clinically relevant structural damage to the cortical hubs of the salience network in PD, possibly due to extensive local neuropathology and loss of interconnecting AIC-ACC tracts.

Dorsal attention network centrality increases during recovery from acute stress exposure.

Stress is a major risk factor for the development of almost all psychiatric disorders. In addition to the acute stress response, an efficient recovery in the aftermath of stress is important for optimal resilience. Increased stress vulnerability across psychiatric disorders may therefore be related to altered trajectories during the recovery phase following stress. Such recovery trajectories can be quantified by changes in functional brain networks. This study therefore evaluated longitudinal functional network changes related to stress in healthy individuals (N = 80), individuals at risk for psychiatric disorders (healthy siblings of schizophrenia patients) (N = 39), and euthymic bipolar I disorder (BD) patients (N = 36). Network changes were evaluated before and at 20 and 90 min after onset of an experimental acute stress task (Trier Social Stress Test) or a control condition. Whole-brain functional networks were analyzed using eigenvector centrality as a proxy for network importance, centrality change over time was related to the acute stress response and recovery for each group. In healthy individuals, centrality of the dorsal attention network (DAN; p = 0.007) changed over time in relation to stress. More specifically, DAN centrality increased during the recovery phase after acute stress exposure (p = 0.020), while no DAN centrality change was observed during the initial stress response (p = 0.626). Such increasing DAN centrality during stress recovery was also found in healthy siblings (p = 0.016), but not in BD patients (p = 0.554). This study highlights that temporally complex and precise changes in network configuration are vital to understand the response to and recovery from stress.

Introducing Multiple Screener: An unsupervised digital screening tool for cognitive deficits in MS.

BACKGROUND: Cognitive deficits affect up to 70% of all patients with Multiple Sclerosis (MS) and have a significant impact on quality of life. Cognitive assessments need to be performed by a neuropsychologist and are often time-consuming, hampering timely identification and adequate monitoring of cognitive decline in MS. OBJECTIVE: To develop a time-efficient, unsupervised, digital tool to screen for cognitive deficits in MS. METHODS: A digital (adjusted) version of the Brief International Cognitive Assessment for MS, including the Symbol Digit Modalities Test (SDMT, information processing speed), the California Verbal Learning Test (CVLT-II, verbal memory) and the Spatial Recall Test (SPART, visuospatial memory) was developed: Multiple Screener (intellectual property of Sanofi Genzyme). Firstly, the clarity and feasibility of the tool was confirmed by 16 patients with MS (mean age 50.9 years (SD 9.4, range 37-68). Next, in 60 healthy controls (HCs, mean age 44.5 years (SD 14.0, range 18-67), intraclass correlation coefficients (ICC) were calculated to describe how strongly the digital version resembled the paper and pencil-based assessment. Finally, 236 HCs (mean age 42.8 years (SD 12.8, range 18-69) were included to obtain norm scores for each test. RESULTS: ICCs between digital and paper and pencil-based assessment were excellent to good (SDMT (ICC 0.79, confidence interval (CI) 0.67-0.87); CVLT-II (ICC 0.77, CI 0.64-0.85); SPART (ICC 0.61, CI 0.42-0.75)). For each test, a regression-based correction for the effect of age was applied on the raw scores before converting them to norm Z-scores. Additionally, the SDMT scores needed correction for education and the CVLT-II for education and sex (subgroups were created). CONCLUSIONS: Performance on an adjusted, digital version of the BICAMS correlates highly with the standard paper-and-pencil based test scores in HCs. Multiple Screener is an unsupervised, digital tool, with available norm scores, ultimately allowing for easy monitoring of cognitive decline in patients with MS.

Predicting clinical progression in multiple sclerosis after 6 and 12 years.

BACKGROUND AND PURPOSE: To predict disability and cognition in multiple sclerosis (MS) after 6 and 12 years, using early clinical and imaging measures. METHODS: A total of 115 patients with MS were selected and followed up after 2 and 6 years, with 79 patients also being followed up after 12 years. Disability was measured using the Expanded Disability Status Scale (EDSS); cognition was measured only at follow-up using neuropsychological testing. Predictors of interest included EDSS score, baseline brain and lesion volumes and their changes over 2 years, baseline age, clinical phenotype, sex and educational level. RESULTS: Higher 6-year EDSS score was predicted by early EDSS score and whole-brain volume changes and baseline diagnosis of primary progressive MS (adjusted R2  = 0.56). Predictors for 12-year EDSS score included larger EDSS score changes and higher T1-hypointense lesion volumes (adjusted R2  = 0.38). Year 6 cognition was predicted by primary progressive MS phenotype, lower educational level, male sex and early whole-brain atrophy (adjusted R2  = 0.26); year 12 predictors included male sex, lower educational level and higher baseline T1-hypointense lesion volumes (adjusted R2  = 0.14). CONCLUSIONS: Patients with early signs of neurodegeneration and a progressive disease onset were more prone to develop both disability progression and cognitive dysfunction. Male sex and lower educational level only affected cognitive dysfunction, which remains difficult to predict and probably needs more advanced imaging measures.

Acid sphingomyelinase: No potential as a biomarker for multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) lacks reliable biomarkers that reflect disease activity. Recent evidence suggests that an altered sphingolipid metabolism is associated with MS pathogenesis. OBJECTIVE: To explore acid sphingomyelinase (ASM) activity and altered sphingolipid metabolism as potential biomarkers in serum of MS patients, to predict active and progressive disease, and response to disease modifying therapy (DMT). METHODS: Levels of serum ASM activity were longitudinally analyzed in 40 clinically isolated syndrome, 64 relapsing remitting (RR) and 10 primary progressive MS patients, and 22 healthy controls (HC). ASM activity and sphingolipid levels were measured in a different sample of 61 RRMS patients using DMT. RESULTS: A significant difference in ASM activity levels was observed between MS patients and HC (p < 0.001). There was no correlation between ASM activity levels and disease activity, progression or response to DMT. Ceramide (Cer)-C16:0 , Cer-C24:0 and sphingomyelin (SM)-C20:0, SM-C22:0, SM-C24:0 and SM-C24:1 showed a significant increase during fingolimod use. CONCLUSION: Although higher levels in MS patients were found, ASM activity levels do not show potential as a biomarker for predicting disease activity, progression or response to DMT. Two ceramides and four types of sphingomyelin require further investigation as potential markers for treatment response.

Is impaired information processing speed a matter of structural or functional damage in MS?

OBJECTIVE: Cognitive deficits, especially those of information processing speed (IPS), are common in multiple sclerosis (MS), however, the underlying neurobiological mechanisms remain poorly understood. In this study, we examined structural and functional brain changes separately, but also in an integrative manner, in relation to IPS performance. METHODS: IPS was measured using the symbol digit modalities test (SDMT) in 330 MS patients and 96 controls. Patients with IPS impairment (IPS-I, z-score < -1.5) were compared to patients with preserved IPS performance (IPS-P) on volumetric measures, white matter integrity loss (using diffusion tensor imaging) and the severity of functional connectivity changes (using resting-state fMRI). Significant predictors of IPS performance were used to create groups of mild or severe structural and/or functional damage to determine the relative effect of structural and/or functional changes on IPS. RESULTS: IPS-I patients, compared to IPS-P patients, showed lower deep gray matter volume and less WM integrity, but stronger increases in functional connectivity. Patients with predominantly structural damage had worse IPS (z-score = -1.49) than patients with predominantly functional changes (z-score = -0.84), although both structural and functional measures remained significant in a regression model. Patients with severe structural and functional changes had worst IPS (z-score = -1.95). CONCLUSION: The level of structural damage explains IPS performance better than functional changes. After integrating functional and structural changes, however, we were able to detect more subtle and stepwise decline in IPS. In subgroups with a similar degree of structural damage, more severe functional changes resulted in worse IPS scores than those with only mild functional changes.

White Matter Diffusion Changes during the First Year of Natalizumab Treatment in Relapsing-Remitting Multiple Sclerosis.

BACKGROUND AND PURPOSE: Natalizumab treatment strongly affects relapsing-remitting multiple sclerosis, possibly by restraining white matter damage. This study investigated changes in white matter diffusivity in patients with relapsing-remitting multiple sclerosis during their first year of natalizumab treatment by using diffusion tensor imaging. MATERIALS AND METHODS: The study included patients with relapsing-remitting multiple sclerosis initiating natalizumab at baseline (n = 22), patients with relapsing-remitting multiple sclerosis continuing interferon-ß or glatiramer acetate (n = 17), and healthy controls (n = 12). Diffusion tensor imaging parameters were analyzed at baseline and month 12. We measured the extent and severity of white matter damage with diffusion tensor imaging parameters such as fractional anisotropy, comparing the patient groups with healthy controls at both time points. RESULTS: The extent and severity of white matter damage were reduced significantly in the natalizumab group with time (fractional anisotropy-based extent, 56.8% to 47.2%; severity, z = -0.67 to -0.59; P = .02); this reduction was not observed in the interferon-ß/glatiramer acetate group (extent, 41.4% to 39.1%, and severity, z = -0.64 to -0.67; P = .94). Cognitive performance did not change with time in the patient groups but did correlate with the severity of damage (r = 0.53, P = < .001). CONCLUSIONS: In patients with relapsing-remitting multiple sclerosis starting natalizumab treatment, the extent and severity of white matter damage were reduced significantly in the first year of treatment. These findings may aid in explaining the large observed clinical effect of natalizumab in relapsing-remitting multiple sclerosis.

Enhanced axonal metabolism during early natalizumab treatment in relapsing-remitting multiple sclerosis.

BACKGROUND AND PURPOSE: The considerable clinical effect of natalizumab in patients with relapsing-remitting multiple sclerosis might be explained by its possible beneficial effect on axonal functioning. In this longitudinal study, the effect of natalizumab on absolute concentrations of total N-acetylaspartate, a marker for neuronal integrity, and other brain metabolites is investigated in patients with relapsing-remitting multiple sclerosis by using MR spectroscopic imaging. MATERIALS AND METHODS: In this explorative observational study, 25 patients with relapsing-remitting multiple sclerosis initiating natalizumab treatment were included and scanned every 6 months for 18 months. Additionally 18 matched patients with relapsing-remitting multiple sclerosis continuing treatment with interferon-ß or glatiramer acetate were included along with 12 healthy controls. Imaging included short TE 2D-MR spectroscopic imaging with absolute metabolite quantification of total N-acetylaspartate, creatine and phosphocreatine, choline-containing compounds, myo-inositol, and glutamate. Concentrations were determined for lesional white matter, normal-appearing white matter, and gray matter. RESULTS: At baseline in both patient groups, lower concentrations of total N-acetylaspartate and creatine and phosphocreatine were found in lesional white matter compared with normal-appearing white matter and additionally lower glutamate in lesional white matter of patients receiving natalizumab. In those patients, a significant yearly metabolite increase was found for lesional white matter total N-acetylaspartate (7%, P < .001), creatine and phosphocreatine (6%, P = .042), and glutamate (10%, P = .028), while lesion volumes did not change. In patients receiving interferon-ß/glatiramer acetate, no significant change was measured in lesional white matter for any metabolite, while whole-brain normalized lesion volumes increased. CONCLUSIONS: Patients treated with natalizumab showed an increase in total N-acetylaspartate, creatine and phosphocreatine, and glutamate in lesional white matter. These increasing metabolite concentrations might be a sign of enhanced axonal metabolism.

Structural degree predicts functional network connectivity: a multimodal resting-state fMRI and MEG study.

Communication between neuronal populations in the human brain is characterized by complex functional interactions across time and space. Recent studies have demonstrated that these functional interactions depend on the underlying structural connections at an aggregate level. Multiple imaging modalities can be used to investigate the relation between the structural connections between brain regions and their functional interactions at multiple timescales. We investigated if consistent modality-independent functional interactions take place between brain regions, and whether these can be accounted for by underlying structural properties. We used functional MRI (fMRI) and magnetoencephalography (MEG) recordings from a population of healthy adults together with a previously described structural network. A high overlap in resting-state functional networks was found in fMRI and especially alpha band MEG recordings. This overlap was characterized by a strongly interconnected functional core network in temporo-posterior brain regions. Anatomically realistically coupled neural mass models revealed that this strongly interconnected functional network emerges near the threshold for global synchronization. Most importantly, this functional core network could be explained by a trade-off between the product of the degrees of structurally-connected regions and the Euclidean distance between them. For both fMRI and MEG, the product of the degrees of connected regions was the most important predictor for functional network connectivity. Therefore, irrespective of the modality, these results indicate that a functional core network in the human brain is especially shaped by communication between high degree nodes of the structural network.

Functional brain network analysis using minimum spanning trees in Multiple Sclerosis: an MEG source-space study.

Cognitive dysfunction in Multiple Sclerosis (MS) is closely related to altered functional brain network topology. Conventional network analyses to compare groups are hampered by differences in network size, density and suffer from normalization problems. We therefore computed the Minimum Spanning Tree (MST), a sub-graph of the original network, to counter these problems. We hypothesize that functional network changes analysed with MSTs are important for understanding cognitive changes in MS and that changes in MST topology also represent changes in the critical backbone of the original brain networks. Here, resting-state magnetoencephalography (MEG) recordings from 21 early MS patients and 17 age-, gender-, and education-matched controls were projected onto atlas-based regions-of-interest (ROIs) using beamforming. The phase lag index was applied to compute functional connectivity between regions, from which a graph and subsequently the MST was constructed. Results showed lower global integration in the alpha2 (10-13Hz) and beta (13-30Hz) bands in MS patients, whereas higher global integration was found in the theta band. Changes were most pronounced in the alpha2 band where a loss of hierarchical structure was observed, which was associated with poorer cognitive performance. Finally, the MST in MS patients as well as in healthy controls may represent the critical backbone of the original network. Together, these findings indicate that MST network analyses are able to detect network changes in MS patients, which may correspond to changes in the core of functional brain networks. Moreover, these changes, such as a loss of hierarchical structure, are related to cognitive performance in MS.

Changes in functional network centrality underlie cognitive dysfunction and physical disability in multiple sclerosis.

BACKGROUND: Cognitive dysfunction in multiple sclerosis (MS) has a large impact on the quality of life and is poorly understood. OBJECTIVE: The aim of this study was to investigate functional network integrity in MS, and relate this to cognitive dysfunction and physical disability. METHODS: Resting state fMRI scans were included of 128 MS patients and 50 controls. Eigenvector centrality mapping (ECM) was applied, a graph analysis technique that ranks the importance of brain regions based on their connectivity patterns. Significant ECM changes were related to physical disability and cognitive dysfunction. RESULTS: In MS patients, ECM values were increased in bilateral thalamus and posterior cingulate (PCC) areas, and decreased in sensorimotor and ventral stream areas. Sensorimotor ECM decreases were related to higher EDSS (rho = -0.24, p = 0.007), while ventral stream decreases were related to poorer average cognition (rho = 0.23, p = 0.009). The thalamus displayed increased connectivity to sensorimotor and ventral stream areas. CONCLUSION: In MS, areas in the ventral stream and sensorimotor cortex appear to become less central in the entire functional network of the brain, which is associated with clinico-cognitive dysfunction. The thalamus, however, displays increased connectivity with these areas. These findings may aid in further elucidating the function of functional reorganization processes in MS.

Cognition in MS correlates with resting-state oscillatory brain activity: An explorative MEG source-space study.

Clinical and cognitive dysfunction in Multiple Sclerosis (MS) is insufficiently explained by structural damage as identified by traditional magnetic resonance imaging (MRI) of the brain, indicating the need for reliable functional measures in MS. We investigated whether altered resting-state oscillatory power could be related to clinical and cognitive dysfunction in MS. MEG recordings were acquired using a 151-channel whole-head MEG system from 21 relapsing remitting MS patients and 17 healthy age-, gender-, and education-matched controls, using an eyes-closed no-task condition. Relative spectral power was estimated for 78 regions of interest, using an atlas-based beamforming approach, for classical frequency bands; delta, theta, alpha1, alpha2, beta and gamma. These cortical power estimates were compared between groups by means of permutation analysis and correlated with clinical disability (Expanded Disability Status Scale: EDSS), cognitive performance and MRI measures of atrophy and lesion load. Patients showed increased power in the alpha1 band and decreased power in the alpha2 band, compared to controls, mainly in occipital, parietal and temporal areas, confirmed by a lower alpha peak-frequency. Increased power in the alpha1 band was associated with worse overall cognition and especially with information processing speed. Our quantitative relative power analysis of MEG recordings showed abnormalities in oscillatory brain dynamics in MS patients in the alpha band. By applying source-space analyses, this study provides a detailed topographical view of abnormal brain activity in MS patients, especially localized to occipital areas. Interestingly, poor cognitive performance was related to high resting-state alpha1 power indicating that changes in oscillatory activity might be of value as an objective measure of disease burden in MS patients.

Cognition is related to resting-state small-world network topology: an magnetoencephalographic study.

Brain networks and cognition have recently begun to attract attention: studies suggest that more efficiently wired resting-state brain networks are indeed correlated with better cognitive performance. "Small-world" brain networks combine local segregation with global integration, hereby subserving information processing. Furthermore, recent studies implicate that gender effects may be present in both network dynamics and its correlations with cognition. This study reports on the relation between resting-state functional brain topology with overall and domain-specific cognitive performance in healthy participants and possible gender differences herein. Healthy participants underwent neuropsychological tests, of which individual scores were converted to z-scores. Network analysis was performed on resting-state, eyes-closed magnetoencephalography (MEG) data, after determining functional connectivity between each pair of sensors. The clustering coefficient (local specialization), average path length (overall integration and efficiency) and "small-world index" (i.e. ratio between clustering and path length) were calculated in six frequency bands. 14 male and 14 female participants were included. Better total cognitive performance was related to increased local connectivity in the theta band, higher clustering coefficient (in delta and theta bands) and higher small-worldness (in theta and lower gamma bands). Women showed less clustering and shorter path length in the delta band. There were no significant correlations between network topology and cognitive functioning in females. In contrast, higher cognitive scores in men were associated with increased theta band clustering and small-worldness. These results provide further evidence for the value of functional brain network topology for cognitive functioning and suggest that gender is an important factor in this respect.