Functional Connectivity Lateralisation Shift of Resting State Networks is Linked to Visuospatial Memory and White Matter Microstructure in Relapsing-Remitting Multiple Sclerosis.

Laterality patterns of resting state networks (RSN) change in various neuropsychiatric conditions. Multiple sclerosis (MS) causes neuro-cognitive symptoms involving dysfunctional large-scale brain networks. Yet, whether healthy laterality patterns of RSNs are maintained in MS and whether altered laterality patterns explain disease symptoms has not been explicitly investigated. We analysed functional MRI and diffusion tensor imaging data from 24 relapsing-remitting MS patients and 25 healthy participants. We performed group-level independent component analysis and used dual regression to estimate individual versions of well-established RSNs. Voxelwise laterality indices were calculated for each RSN. Group differences were assessed via a general linear model-based approach. The relationship between functional laterality and white matter microstructural asymmetry was assessed using Tract-Based Spatial Statistics. Spearman's correlation was calculated between laterality indices and Brief International Cognitive Assessment for Multiple Sclerosis scores. Functional laterality of the dorsal attention network showed a significant leftward shift in the MS group in the posterior intraparietal sulcus (p < 0.033). Default-mode network laterality showed a significant leftward shift in the MS group in the angular gyrus (p < 0.005). Diminished dorsal attention network laterality was associated with increased fractional anisotropy asymmetry in the superior longitudinal fasciculus (p < 0.02). In the default-mode network, leftward laterality of the angular gyrus was associated with higher BVMT-R scores (R = - 0.52, p < 0.023). Our results confirm previous descriptions of RSN dysfunction in relapsing-remitting MS and show that altered functional connectivity lateralisation patterns of RSNs might contibute to cognitive performance and structural remodellation even in patients with mild clinical symptoms.

Altered brain network function during attention-modulated visual processing in multiple sclerosis.

BACKGROUND: Multiple sclerosis may damage cognitive performance in several domains, including attention. Although attention network deficits were described during rest, studies that investigate their function during task performance are scarce. OBJECTIVE: To investigate connectivity within and between task-related networks in multiple sclerosis during a visual attention task as a function of cognitive performance. METHODS: A total of 23 relapsing-remitting multiple sclerosis (RRMS) patients and 29 healthy controls underwent task-functional magnetic resonance imaging (fMRI) scans using a visual attention paradigm on a 3T scanner. Scans were analysed using tensor-independent component analysis (TICA). Functional connectivity was calculated within and between components. We assessed cognitive function with the Brief International Cognitive Assessment for MS (BICAMS) battery. RESULTS: TICA extracted components related to visual processing, attention, executive function and the default-mode network. Subject scores of visual/attention-related and executive components were greater in healthy controls (p < 0.032, p < 0.023). Connectivity between visual/attention-related and default-mode components was higher in patients (p < 0.043), correlating with Brief Visuospatial Memory Test-Revised (BVMT-R) scores (R = -0.48, p < 0.036). Patients showed reduced connectivity between the right intraparietal sulcus (rIPS) and frontal eye field (rFEF), and bilateral frontal eye fields (p < 0.012, p < 0.003). Reduced rIPS-rFEF connectivity came with lower Symbol Digit Modalities Test (SDMT)/BVMT-R scores in patients (R = 0.53, p < 0.02, R = 0.46, p < 0.049). CONCLUSION: Attention-related networks show altered connectivity during task performance in RRMS patients, scaling with cognitive disability.

Macro- and microstructural alterations of the subcortical structures in episodic cluster headache.

Background Previous functional and structural imaging studies have revealed that subcortical structures play a key a role in pain processing. The recurring painful episodes might trigger maladaptive plasticity or alternatively degenerative processes that might be detected by MRI as changes in size or microstructure. In the current investigation, we aimed to identify the macro- and microstructural alterations of the subcortical structures in episodic cluster headache. Methods High-resolution T1-weighted and diffusion-weighted MRI images with 60 gradient directions were acquired from 22 patients with cluster headache and 94 healthy controls. Surface-based segmentation analysis was used to measure the volume of the subcortical nuclei, and mean diffusion parameters (fractional anisotropy, mean, radial and axial diffusivity) were determined for these structures. In order to understand whether the size and diffusion parameters could be investigated in a headache lateralised manner, first the asymmetry of the size and diffusion parameters of the subcortical structures was analysed. Volumes and diffusion parameters were compared between groups and correlated with the cumulative number of headache days. To account for the different size of the patient and control group, a bootstrap approach was used to investigate the stability of the findings. Results A significant lateralisation of the size (caudate, putamen and thalamus) and the diffusion parameters of the subcortical structures were found in normal controls. In cluster headache patients, the mean fractional anisotropy of the right amygdalae, the mean axial and mean diffusivity of the right caudate nucleus and the radial diffusivity of the right pallidum were higher. The mean anisotropy of the right pallidum was lower in patients. Conclusion The analysis of the pathology in the subcortical structures in episodic cluster headache reveals important features of the disease, which might allow a deeper insight into the pathomechanism of the pain processing in this headache condition.

Ipsilateral Alteration of Resting State Activity Suggests That Cortical Dysfunction Contributes to the Pathogenesis of Cluster Headache.

The pathomechanism of cluster headache (CH) is not entirely understood, but central and peripheral components were suggested. A recent report showed that transcranial magnetic stimulation measured cortical excitability was increased in the hemisphere ipsilalteral to the pain. In the current study we set out to investigate the amplitude of resting brain fMRI activity to find signatures of the increased excitability. High resolution T1 weighted and resting state functional MRI images were acquired from seventeen patients with CH in pain free period and from twenty-six healthy volunteers. Patients' data were normalized (e.g. inverted along the midsagittal axis) according to the headache side. Independent component analysis and a modified dual regression approach were used to reveal the differences between the resting state networks. Furthermore, the timecourses were decomposed into five frequency bands by discrete wavelet decomposition and were also re-regressed to the original data to reveal frequency specific resting activity maps. Two of the identified resting state networks showed alterations in CH. When the data were inverted to have patients' headaches on the left, the ipsilateral attention network showed increased connectivity in 0.08-0.04 Hz frequency band in the in CH group. In the same dataset, cerebellar network showed higher functional connectivity in 0.02-0.01 Hz range in the ipsilateral cerebellum. When the data of patients having headache on the left were inverted to the right, similar increased signal was found in the ipsilateral attention network in 0.08-0.04 Hz band. The cerebellar network showed increased connectivity in the cerebellum in 0.02-0.01 Hz band in patients. The Fourier analysis of these area revealed increased power in CH at all cases. Our results showed alterations of brain functional networks in CH. The alterations of resting state activity were found in the hemisphere ipsilateral to the pain, signifying the altered cortical processing in the pathomechanism of CH.

Interictal brain activity differs in migraine with and without aura: resting state fMRI study.

BACKGROUND: Migraine 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. METHODS: Resting 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. RESULTS: In 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. DISCUSSION: The 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.

Late-stage α-synuclein accumulation in TNWT-61 mouse model of Parkinson's disease detected by diffusion kurtosis imaging.

Diffusion kurtosis imaging (DKI) by measuring non-Gaussian diffusion allows an accurate estimation of the distribution of water molecule displacement and may correctly characterize microstructural brain changes caused by neurodegeneration. The aim of this study was to evaluate the ability of DKI to detect changes induced by α-synuclein (α-syn) accumulation in α-syn over-expressing transgenic mice (TNWT-61) in both gray matter (GM) and white matter (WM) using region of interest (ROI) and tract-based spatial statistics analyses, respectively, and to explore the relationship between α-syn accumulation and DKI metrics in our regions of interest. Fourteen-month-old TNWT-61 mice and wild-type (WT) littermates underwent in vivo DKI scanning using the Bruker Avance 9.4 Tesla magnetic resonance imaging system. ROI analysis in the GM regions substantia nigra, striatum, hippocampus, sensorimotor cortex, and thalamus and tract-based spatial statistics analysis in WM were performed. Immunohistochemistry for α-syn was performed in TNWT-61 mice and correlated with DKI findings. We found increased kurtosis and decreased diffusivity values in GM regions such as the thalamus and sensorimotor cortex, and in WM regions such as the external and internal capsule, mamillothalamic tract, anterior commissure, cingulum, and corpus callosum in TNWT-61 mice as compared to WT mice. Furthermore, we report for the first time that α-syn accumulation is positively correlated with kurtosis and negatively correlated with diffusivity in the thalamus. The study provides evidence of an association between the amount of α-syn and the magnitude of DKI metric changes in the ROIs, with the potential of improving the clinical diagnosis of Parkinson's disease. We propose diffusion kurtosis imaging as a sensitive method for detecting human α-synuclein accumulation-induced changes in brain tissue, which may be reflective of Parkinson disease stage. Boxplots show the averaged mean kurtosis (orange) and mean diffusivity (blue) under the results of the analysis (*p < 0.05) in brains of wild-type (WT) and α-synuclein over-expressing (TNWT-61) mice. This approach might represent a novel biomarker for the early diagnosis of Parkinson's disease. Read the Editorial Highlight for this article on page 1117.

Gray matter atrophy in presymptomatic Huntington's patients.

BACKGROUND AND PURPOSE: Background - Huntington's disease is a progressive disease in which neurodegeneration is on-going from the early presymptomatic phase. Development of sensitive biomarkers in this presymptomatic stage that are able to monitor the disease progression and test the efficacy of putative neuroprotective treatments are essential. METHODS: Methods - Seven presymptomatic Huntington mutation carriers and ten age-matched healthy controls were recruited. Six of the patients participated in a 24 months longitudinal study having MRI scans 12 and 24 months after the baseline measurements. High resolution T1 weighted images were carried out and voxel based morphometry was used to analyse the data. Apart of group differences, correlation of CAG repeat number with focal cortical thickness and with global gray matter volume was calculated. RESULTS: Results - Focal cortical atrophy was found bilaterally in the superior temporal sulcus and in the left middle frontal gyrus in presymptomatic Huntington patients in whom no sign of cognitive or motor deterioration was detected. Global gray matter atrophy (p<0.048) and decreased total brain volume was found. The number of CAG triplets showed no correlation with the focal gray matter atrophy and total brain volume. Strong correlation between the CAG repeat number and global gray matter volume was found (p<0.016). CONCLUSION: Conclusion - Cortical atrophy is apparent in the early, presymptomatic stage of the disease. With further validation in large patient sample atrophy measure could be biomarker of disease progression and putatively of neurodegeneration.

Bit-table based biclustering and frequent closed itemset mining in high-dimensional binary data.

During the last decade various algorithms have been developed and proposed for discovering overlapping clusters in high-dimensional data. The two most prominent application fields in this research, proposed independently, are frequent itemset mining (developed for market basket data) and biclustering (applied to gene expression data analysis). The common limitation of both methodologies is the limited applicability for very large binary data sets. In this paper we propose a novel and efficient method to find both frequent closed itemsets and biclusters in high-dimensional binary data. The method is based on simple but very powerful matrix and vector multiplication approaches that ensure that all patterns can be discovered in a fast manner. The proposed algorithm has been implemented in the commonly used MATLAB environment and freely available for researchers.

Grey matter atrophy in patients suffering from multiple sclerosis.

White matter lesions are defining characteristics of multiple sclerosis (MS), whereas grey matter involvement is a less recognised attribute. Recent investigations using dedicated imaging approaches have made it possible to depict cortical lesions. Additionally, grey matter atrophy may be estimated using various methods. Several studies have suggested that grey matter atrophy closely correlates to clinical disability. In this review we have collected information on grey matter atrophy in MS and the effect of disease modifying therapies upon brain atrophy.

Limitation of hardness from thermal water by means of nanofiltration.

Geothermal conditions are extremely favourable in Hungary. Thermal water is accessible in 70% of the territory of the country, with a lowest temperature of 30°C. For energetic purposes, it can be utilized in two different ways: for supplying heat or generating electricity. In relation to utilization, one of the most serious problems derives from the chemical composition of thermal water. The present paper investigates the opportunities of preventing scaling by nanofiltration. Experiments were performed on a Thin Film NF DK membrane, thermostated at 50°C and at a pressure of 3.5 MPa with four different samples (from four Hungarian cities - Eger, Mezokövesd, Bogács, Miskolc-Tapolca) using batch plant. Reproducibility of experiments was also investigated using water samples from Komárom at 50 and 60°C. The results showed that NF DK could achieve high retention of divalent ions. The results of the second phase of the experiments proved that water flux and rejections were very stable. After filtration, the scaling properties of thermal water were simulated with the help of chemical equilibrium modelling software, called Visual MINTEQ 3.0. The results of the permeate samples prove that nanofiltration is a successful process in preventing scaling of thermal water for further use.

Evaluation of transorbital sonography measures of optic nerve diameter in the context of global and regional brain volume in multiple sclerosis.

Transorbital sonography (TOS) could be a swift and convenient method to detect the atrophy of the optic nerve, possibly providing a marker that might reflect other quantitative structural markers of multiple sclerosis (MS). Here we evaluate the utility of TOS as a complementary tool for assessing optic nerve atrophy, and investigate how TOS-derived measures correspond to volumetric brain markers in MS. We recruited 25 healthy controls (HC) and 45 patients with relapsing-remitting MS and performed B-mode ultrasonographic examination of the optic nerve. Patients additionally underwent MRI scans to obtain T1-weighted, FLAIR and STIR images. Optic nerve diameters (OND) were compared between HC, MS patients with and without history of optic neuritis (non-ON) using a mixed-effects ANOVA model. The relationship between within-subject-average OND and global and regional brain volumetric measures was investigated using FSL SIENAX, voxel-based morphometry and FSL FIRST. OND was significantly different between HC-MS (HC = 3.2 ± 0.4 mm, MS = 3 ± 0.4 mm; p < 0.019) and we found significant correlation between average OND and normalised whole brain (ß = 0.42, p < 0.005), grey matter (ß = 0.33, p < 0.035), white matter (ß = 0.38, p < 0.012) and ventricular cerebrospinal fluid volume (ß = - 0.36, p < 0.021) in the MS group. History of ON had no impact on the association between OND and volumetric data. In conclusion, OND is a promising surrogate marker in MS, that can be simply and reliably measured using TOS, and its derived measures correspond to brain volumetric measures. It should be further explored in larger and longitudinal studies.

Economic-oriented stochastic optimization in advanced process control of chemical processes.

Finding the optimal operating region of chemical processes is an inevitable step toward improving economic performance. Usually the optimal operating region is situated close to process constraints related to product quality or process safety requirements. Higher profit can be realized only by assuring a relatively low frequency of violation of these constraints. A multilevel stochastic optimization framework is proposed to determine the optimal setpoint values of control loops with respect to predetermined risk levels, uncertainties, and costs of violation of process constraints. The proposed framework is realized as direct search-type optimization of Monte-Carlo simulation of the controlled process. The concept is illustrated throughout by a well-known benchmark problem related to the control of a linear dynamical system and the model predictive control of a more complex nonlinear polymerization process.

The effect of lesion location on visuospatial attentional bias in patients with multiple sclerosis.

OBJECTIVE: Lateralization of visuospatial attention in healthy people, known as pseudoneglect, results in leftward bias during the Landmark or line bisection tasks. Cognitive dysfunctions in patients with multiple sclerosis (MS) might affect the visuospatial attentional abilities as well. In this study, we aimed to examine the association between atrophy and lesion location and the extent of lateralization of visuospatial attentional bias in patients with MS. METHOD: Visuospatial attentional bias was measured in 35 relapsing-remitting MS patients using the Landmark task. To evaluate the relation between spatial attentional bias and gray matter atrophy, voxel-based morphometry was performed on T1-weighted magnetic resonance (MR) images. In order to examine the effect of lesion location on visuospatial attentional bias, lesion-symptom mapping was conducted on the manually segmented lesions. RESULTS: The variability of visuospatial attentional bias was higher in MS patients compared to healthy controls (p < .04). Lesion probability mapping showed that lesions located along the left superior longitudinal fascicle are associated with the extent of visuospatial bias (p < .05). No correlation was found between gray matter atrophy and the attentional bias of the patients. CONCLUSIONS: Our results indicate that lesions affecting the integrity of white matter pathways in the fronto-parietal attentional network might be accountable for the higher variability of spatial attentional bias in patients with MS. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Connection between microstructural alterations detected by diffusion MRI and cognitive dysfunction in MS: A model-free analysis approach.

BACKGROUND: Cognitive decline is a prominent symptom of MS. Clear connection between cognitive status and white matter microstructural changes has not been unequivocally observed to date. OBJECTIVE: To characterise the relationship between white matter microstructure and cognitive performance a partial least squares (PLS) approach was used. METHODS: 53 RR MS patients' T1 and DTI images and BICAMS subtests were used in our analysis. Standard FSL pipeline was used to obtain diffusion parameters. A PLS approach was applied to reveal the diffusion parameter patterns responsible for the cognitive dysfunction. RESULTS: The first latent variable (LV) was mainly associated with demyelination, while the second and third explained axonal damage. While the first two LV represented mainly Brief Visuospatial Memory Test (BVMT) and Single Digit Modality Test (SDMT), the third LV depicted diffusion alterations mainly the verbal subtest. The first LVs spatial map showed demyelination in the corpus callosum. The second LVs spatial map showed the diffusion alterations in the thalamus. The third LV depicted diffusion alterations in the putative left superior longitudinal fascicle. CONCLUSION: Visual memory demanding tasks versus language functions depend on distinct patterns of diffusion parameters and the spatial organisation. Axial diffusivity alterations, a putative marker of irreversible axonal loss explained around 20% of variability in the cognitive functions.

Modulation of cortical resting state functional connectivity during a visuospatial attention task in Parkinson's disease.

Visual dysfunction is a recognized early symptom of Parkinson's disease (PD) that partly scales motor symptoms, yet its background is heterogeneous. With additional deficits in visuospatial attention, the two systems are hard to disentangle and it is not known whether impaired functional connectivity in the visual cortex is translative in nature or disrupted attentional modulation also contributes. In this study, we investigate functional connectivity modulation during a visuospatial attention task in patients with PD. In total, 15 PD and 16 age-matched healthy controls performed a visuospatial attention task while undergoing fMRI, in addition to a resting-state fMRI scan. Tensorial independent component analysis was used to investigate task-related network activity patterns. Independently, an atlas-based connectivity modulation analysis was performed using the task potency method. Spearman's rank correlation was calculated between task-related network expression, connectivity modulation, and clinical characteristics. Task-related networks including mostly visual, parietal, and prefrontal cortices were expressed to a significantly lesser degree in patients with PD (p < 0.027). Resting-state functional connectivity did not differ between the healthy and diseased cohorts. Connectivity between the precuneus and ventromedial prefrontal cortex was modulated to a higher degree in patients with PD (p < 0.004), while connections between the posterior parietal cortex and primary visual cortex, and also the superior frontal gyrus and opercular cortex were modulated to a lesser degree (p < 0.001 and p < 0.011). Task-related network expression and superior frontal gyrus-opercular cortex connectivity modulation were significantly associated with UPDRSIII motor scores and the Hoehn-Yahr stages (R = -0.72, p < 0.006 and R = -0.90, p < 0.001; R = -0.68, p < 0.01 and R = -0.71, p < 0.007). Task-related networks function differently in patients with PD in association with motor symptoms, whereas impaired modulation of visual and default-mode network connectivity was not correlated with motor function.

The Effects of Bilateral Theta-burst Stimulation on Executive Functions and Affective Symptoms in Major Depressive Disorder.

Major depressive disorder (MDD) is characterized by severe affective as well as cognitive symptoms. Moreover, cognitive impairment in MDD can persist after the remission of affective symptoms. Theta-burst stimulation (TBS) is a promising tool to manage the affective symptoms of major depressive disorder (MDD); however, its cognition-enhancing effects are sparsely investigated. Here, we aimed to examine whether the administration of bilateral TBS has pro-cognitive effects in MDD. Ten daily sessions of neuronavigated active or sham TBS were delivered bilaterally over the dorsolateral prefrontal cortex to patients with MDD. The n-back task and the attention network task were administered to assess working memory and attention, respectively. Affective symptoms were measured using the 21-item Hamilton Depression Rating Scale. We observed moderate evidence that the depressive symptoms of patients receiving active TBS improved compared to participants in the sham stimulation. No effects of TBS on attention and working memory were detected, supported by a moderate-to-strong level of evidence. The effects of TBS on psychomotor processing speed should be further investigated. Bilateral TBS has a substantial antidepressive effect with no immediate adverse effects on executive functions.

Two Classes of T1 Hypointense Lesions in Multiple Sclerosis With Different Clinical Relevance.

Background: Hypointense lesions on T1-weighted images have important clinical relevance in multiple sclerosis patients. Traditionally, spin-echo (SE) sequences are used to assess these lesions (termed black holes), but Fast Spoiled Gradient-Echo (FSPGR) sequences provide an excellent alternative. Objective: To determine whether the contrast difference between T1 hypointense lesions and the surrounding normal white matter is similar on the two sequences, whether different lesion types could be identified, and whether the clinical relevance of these lesions types are different. Methods: Seventy-nine multiple sclerosis patients' lesions were manually segmented, then registered to T1 sequences. Median intensity values of lesions were identified on all sequences, then K-means clustering was applied to assess whether distinct clusters of lesions can be defined based on intensity values on SE, FSPGR, and FLAIR sequences. The standardized intensity of the lesions in each cluster was compared to the intensity of the normal appearing white matter in order to see if lesions stand out from the white matter on a given sequence. Results: 100% of lesions on FSPGR images and 69% on SE sequence in cluster #1 exceeded a standardized lesion distance of Z = 2.3 (p < 0.05). In cluster #2, 78.7% of lesions on FSPGR and only 17.7% of lesions on SE sequence were above this cutoff value, meaning that these lesions were not easily seen on SE images. Lesion count in the second cluster (lesions less identifiable on SE) significantly correlated with the Expanded Disability Status Scale (EDSS) (R: 0.30, p ≤ 0.006) and with disease duration (R: 0.33, p ≤ 0.002). Conclusion: We showed that black holes can be separated into two distinct clusters based on their intensity values on various sequences, only one of which is related to clinical parameters. This emphasizes the joint role of FSPGR and SE sequences in the monitoring of MS patients and provides insight into the role of black holes in MS.

Resting-state functional heterogeneity of the right insula contributes to pain sensitivity.

Previous studies have described the structure and function of the insular cortex in terms of spatially continuous gradients. Here we assess how spatial features of insular resting state functional organization correspond to individual pain sensitivity. From a previous multicenter study, we included 107 healthy participants, who underwent resting state functional MRI scans, T1-weighted scans and quantitative sensory testing on the left forearm. Thermal and mechanical pain thresholds were determined. Connectopic mapping, a technique using non-linear representations of functional organization was employed to describe functional connectivity gradients in both insulae. Partial coefficients of determination were calculated between trend surface model parameters summarizing spatial features of gradients, modal and modality-independent pain sensitivity. The dominant connectopy captured the previously reported posteroanterior shift in connectivity profiles. Spatial features of dominant connectopies in the right insula explained significant amounts of variance in thermal (R2 = 0.076; p < 0.001 and R2 = 0.031; p < 0.029) and composite pain sensitivity (R2 = 0.072; p < 0.002). The left insular gradient was not significantly associated with pain thresholds. Our results highlight the functional relevance of gradient-like insular organization in pain processing. Considering individual variations in insular connectopy might contribute to understanding neural mechanisms behind pain and improve objective brain-based characterization of individual pain sensitivity.

Clustering Infertile Couples With Dyadic Approach: WHO-5-WBI as a Promising Tool for Assessing Psychological State.

Infertility may be associated with severe psychological burden and many couples need mental support. We used dyadic approach to identify couples with disturbed psychological condition and we tested the WHO-5 Well-Being Index (WHO-5-WBI) questionnaire as a possible, rapid screening method. Extensive psychological assessment of infertile couples was carried out with Beck's Depression Inventory, Spielberger State-Trait Anxiety Inventory, WHO-5-WBI, Symptom Check List-90 Revised Test, Fagerstrom Test for Nicotine Dependence, Alcohol Use Disorders Identification Test. Data of 128 patients (64 couples) were used in the statistical calculations. The Two-Step cluster analysis has revealed 2 groups, which could be separated supremely based on the level of experienced depression, anxiety and according to the general mental health. The WHO-5-WBI questionnaire showed consistent results while classifying couples into groups, which were formed. Our results indicate that infertility affects both spouses almost in the same extent in several psychological aspects. A cluster of couples with increased psychological burden could be clearly separated. The WHO-5-WBI questionnaire was a promising tool to screen reliably spouses based on their psychological state and identify couples that need psychological support during their fertility work-up and treatment.

Brain MRI Diffusion Encoding Direction Number Affects Tract-Based Spatial Statistics Results in Multiple Sclerosis.

BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) is a promising approach to detect the underlying brain pathology. These alterations can be seen in several diseases such as multiple sclerosis. Tract-based spatial statistics (TBSS) is an easy to use and robust way for analyzing diffusion data. The effect of acquisition parameters of DTI on TBSS has not been evaluated, especially the number of diffusion encoding directions (NDED), which is directly proportional with scan time. METHODS: We analyzed a large set of DTI data of healthy controls (N = 126) and multiple sclerosis patients (N = 78). The highest NDED (60 directions) was reduced and a tensor calculation was done separately for every subset. We calculated the mean and standard deviation of DTI parameters under the white matter mask. Moreover, the FMRIB Software Library TBSS pipeline was used on DTI images with 15, 30, 45, and 60 directions to compare differences between groups. Mean DTI parameters were compared between groups as a function of NDED. RESULTS: The mean value of FA and AD decreased with increasing number of directions. This was more pronounced in areas with smaller FA values. RD and MD were constant. The skeleton size reduced with elevating NDED along with the number of significant voxels. The TBSS analysis showed significant differences between groups throughout the majority of the skeleton and the group difference was associated with NDED. CONCLUSION: Our results suggested that results of TBSS depended on the NDED, which should be considered when comparing DTI data with varying protocols.