RESUMO
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.
RESUMO
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.
