Background: Formerly white matter abnormalities in a mixed group of migraine patients with and without aura were shown. Here, we aimed to explore white matter alterations in a homogeneous group of migraineurs with aura and to delineate possible relationships between white matter changes and clinical variables.Methods: Eighteen patients with aura, 25 migraine patients without aura and 28 controls were scanned on a 1.5T MRI scanner. Diffusivity parameters of the white matter were estimated and compared between patients’ groups and controls using whole-brain tract-based spatial statistics.Results: Decreased radial diffusivity (p < 0.036) was found bilaterally in the parieto-occipital white matter, the corpus callosum, and the cingular white matter of migraine with aura (MwA) patients compared to controls. Migraine without aura (MwoA) patients showed no alteration compared to controls. MwA compared to MwoA showed increased fractional anisotropy (p < 0.048) in the left parieto-occipital white matter. In MwA a negative correlation was found between axial diffusivity and disease duration in the left superior longitudinal fascicle (left parieto-occipital region) and in the left corticospinal tract (p < 0.036) and with the number of the attacks in the right superior longitudinal fascicle (p < 0.048).Conclusion: We showed for the first time that there are white matter microstructural differences between these two subgroups of migraine and hence it is important to handle the two groups separately in further researches. We propose that degenerative and maladaptive plastic changes coexist in the disease and the diffusion profile is a result of these processes.

BackgroundMigraine is one of the most severe primary headache disorders. The nature of the headache and the associated symptoms during the attack suggest underlying functional alterations in the brain. In this study, we examined amplitude, the resting state fMRI fluctuation in migraineurs with and without aura (MWA, MWoA respectively) and healthy controls.MethodsResting state functional MRI images and T1 high-resolution images were acquired from all participants. For data analysis we compared the groups (MWA-Control, MWA-MWoA, MWoA-Control). The resting state networks were identified by MELODIC. The mean time courses of the networks were identified for each participant for all networks. The time-courses were decomposed into five frequency bands by discrete wavelet decomposition. The amplitude of the frequency-specific activity was compared between groups. Furthermore, the preprocessed resting state images were decomposed by wavelet analysis into five specific frequency bands voxel-wise. The voxel-wise amplitudes were compared between groups by non-parametric permutation test.ResultsIn the MWA-Control comparison the discrete wavelet decomposition found alterations in the lateral visual network. Higher activity was measured in the MWA group in the highest frequency band (0.16–0.08 Hz).In case of the MWA-MWoA comparison all networks showed higher activity in the 0.08–0.04 Hz frequency range in MWA, and the lateral visual network in in higher frequencies.In MWoA-Control comparison only the default mode network revealed decreased activity in MWoA group in the 0.08–0.04 Hz band.The voxel-wise frequency specific analysis of the amplitudes found higher amplitudes in MWA as compared to MWoA in the in fronto-parietal regions, anterior cingulate cortex and cerebellum.DiscussionThe amplitude of the resting state fMRI activity fluctuation is higher in MWA than in MWoA. These results are in concordance with former studies, which found cortical hyperexcitability in MWA.

Effects of gender on grey matter (GM) volume differences in subcortical structures of the human brain have consistently been reported. Recent research evidence suggests that both gender and brain size influences volume distribution in subcortical areas independently. The goal of this study was to determine the effects of the interplay between brain size, gender and age contributing to volume differences of subcortical GM in the human brain. High-resolution T1-weighted images were acquired from 53 healthy males and 50 age-matched healthy females. Total GM volume was determined using voxel-based morphometry. We used model-based subcortical segmentation analysis to measure the volume of subcortical nuclei. Main effects of gender, brain volume and aging on subcortical structures were examined using multivariate analysis of variance. No significant difference was found in total brain volume between the two genders after correcting for total intracranial volume. Our analysis revealed significantly larger hippocampus volume for females. Additionally, GM volumes of the caudate nucleus, putamen and thalamus displayed a significant age-related decrease in males as compared to females. In contrast to this only the thalamic volume loss proved significant for females. Strikingly, GM volume decreases faster in males than in females emphasizing the interplay between aging and gender on subcortical structures. These findings might have important implications for the interpretation of the effects of unalterable factors (i.e. gender and age) in cross-sectional structural MRI studies. Furthermore, the volume distribution and changes of subcortical structures have been consistently related to several neuropsychiatric disorders (e.g. Parkinson's disease, attention deficit hyperactivity disorder, etc.). Understanding these changes might yield further insight in the course and prognosis of these disorders.

Background: Migraine research is booming with the rapidly developing neuroimaging tools. Structural and functional alterations of the migrainous brain were detected with MRI. The outcome of a research study largely depends on the working hypothesis, on the chosen measurement approach and also on the subject selection. Against all evidence from the literature that migraine subtypes are different, most of the studies handle migraine with and without aura as one disease.Methods: Publications from PubMed database were searched for terms of “migraine with aura,” “migraine without aura,” “interictal,” “MRI,” “diffusion weighted MRI,” “functional MRI,” “compared to,” “atrophy” alone and in combination.Conclusion: Only a few imaging studies compared the two subforms of the disease, migraine with aura, and without aura, directly. Functional imaging investigations largely agree that there is an increased activity/activation of the brain in migraine with aura as compared to migraine without aura. We propose that this might be the signature of cortical hyperexcitability. However, structural investigations are not equivocal. We propose that variable contribution of parallel, competing mechanisms of maladaptive plasticity and neurodegeneration might be the reason behind the variable results.

This study aims to investigate whether intra-network dynamic functional connectivity and causal interactions of the salience network is altered in the interictal term of migraine. 32 healthy controls, 37 migraineurs without aura and 20 migraineurs with aura were recruited. Participants underwent a T1-weighted scan and resting-state fMRI protocol inside a 1.5T MR scanner. We obtained average spatial maps of resting-state networks using group independent component analysis, which yielded subject-specific time series via a dual regression approach. Salience network ROIs (bilateral insulae and prefrontal cortices, dorsal anterior cingulate cortex) were obtained from the group average map via cluster-based thresholding. To describe intra-network connectivity, average and dynamic conditional correlation was calculated. Causal interactions

Introduction: Brain structure and function were reported to be altered in migraine. Importantly our earlier results showed that white matter diffusion abnormalities and resting state functional activity were affected differently in the two subtypes of the disease, migraine with and without aura. Resting fluctuation of the BOLD signal in the white matter was reported recently. The question arising whether the white matter activity, that is strongly coupled with gray matter activity is also perturbed differentially in the two subtypes of the disease and if so, is it related to the microstructural alterations of the white matter.Methods: Resting state fMRI, 60 directional DTI images and high-resolution T1 images were obtained from 51 migraine patients and 32 healthy volunteers. The images were pre-processed and the white matter was extracted. Independent component analysis was performed to obtain white matter functional networks. The differential expression of the white matter functional networks in the two subtypes of the disease was investigated with dual-regression approach. The Fourier spectrum of the resting fMRI fluctuations were compared between groups. Voxel-wise correlation was calculated between the resting state functional activity fluctuations and white matter microstructural measures.Results: Three white matter networks were identified that were expressed differently in migraine with and without aura. Migraineurs with aura showed increased functional connectivity and amplitude of BOLD fluctuation. Fractional anisotropy and radial diffusivity showed strong correlation with the expression of the frontal white matter network in patients with aura.Discussion: Our study is the first to describe changes in white matter resting state functional activity in migraine with aura, showing correlation with the underlying microstructure. Functional and structural differences between disease subtypes suggest at least partially different pathomechanism, which may necessitate handling of these subtypes as separate entities in further studies.

Next to the disseminated clinical symptoms, cognitive dysfunctions are common features of multiple sclerosis (MS). Over the recent years several different MRI measures became available representing the various features of the pathology, but the contribution to various clinical and cognitive functions is not yet fully understood. In this multiparametric MRI study we set out to identify the set of parameters that best predict the clinical and cognitive disability in MS. High resolution T1 weighted structural and high angular resolution diffusion MRI images were measured in 53 patients with relapsing remitting MS and 53 healthy controls. Clinical disability was inflicted by EDSS and cognitive functions were evaluated with the BICAMS tests. The contribution of lesion load, partial brain, white matter, gray matter and subcortical volumes as well as the diffusion parameters in the area of the lesions and the normal appearing white matter were examined by model free, partial least square (PLS) approach. Significance of the predictors was tested with Variable Importance in the Projection (VIP) score and 1 was used for threshold of significance. The PLS analysis indicated that the axial diffusivity of the NAWM contributed the most to the clinical disability (VIP score: 1.979). For the visuo-spatial working memory the most critical contributor was the size of the bilateral hippocampi (VIP scores: 1.183 and 1.2 left and right respectively). For the verbal memory the best predictors were the size of the right hippocampus (VIP score: 1.972), lesion load (VIP score: 1.274) and the partial brain volume (VIP score: 1.119). In case of the information processing speed the most significant contribution was from the diffusion parameters (fractional anisotropy, mean and radial diffusivity, VIP scores: 1.615, 1.321 respectively) of the normal appearing white matter. Our results indicate that various MRI measurable factors of MS pathology contribute differently to clinical and cognitive disability. These results point out the importance of the volumetry of the subcortical structures and the diffusion measures of the white matter in understanding the disability progression.

Objective: Cortical pathology, periventricular demyelination, and lesion formation in multiple sclerosis (MS) are related (Hypothesis 1). Factors in the cerebrospinal fluid close to these compartments could possibly drive the parallel processes. Alternatively, the cortical atrophy could be caused by remote axonal transection (Hypothesis 2). Since MRI can differentiate between demyelination and axon loss, we used this imaging modality to investigate the correlation between the pattern of diffusion parameter changes in the periventricular- and deep white matter and the gray matter atrophy.Methods: High-resolution T1-weighted, FLAIR, and diffusion MRI images were acquired in 52 RRMS patients and 50 healthy, age-matched controls. We used EDSS to estimate the clinical disability. We used Tract Based Spatial Statistics to compare diffusion parameters (fractional anisotropy, mean, axial, and radial diffusivity) between groups. We evaluated global brain, white, and gray matter atrophy with SIENAX. Averaged, standard diffusion parameters were calculated in four compartment: periventricular lesioned and normal appearing white matter, non-periventricular lesioned and normal appearing white matter. PLS regression was used to identify which diffusion parameter and in which compartment best predicts the brain atrophy and clinical disability.Results: In our diffusion tensor imaging study compared to controls we found extensive alterations of fractional anisotropy, mean and radial diffusivity and smaller changes of axial diffusivity (maximal p > 0.0002) in patients that suggested demyelination in the lesioned and in the normal appearing white matter. We found significant reduction in total brain, total white, and gray matter (patients: 718.764 ± 14.968, 323.237 ± 7.246, 395.527 ± 8.050 cm3, controls: 791.772 ± 22.692, 355.350 ± 10.929, 436.422 ± 12.011 cm3; mean ± SE), (p < 0.015; p < 0.0001; p < 0.009; respectively) of patients compared to controls. The PLS analysis revealed a combination of demyelination-like diffusion parameters (higher mean and radial diffusivity in patients) in the lesions and in the non-lesioned periventricular white matter, which best predicted the gray matter atrophy (p < 0.001). Similarly, EDSS was best predicted by the radial diffusivity of the lesions and the non-lesioned periventricular white matter, but axial diffusivity of the periventricular lesions also contributed significantly (p < 0.0001).Interpretation: Our investigation showed that gray matter atrophy and white matter demyelination are related in MS but white matter axonal loss does not significantly contribute to the gray matter pathology.