Imbalanced temporal states of cortical blood-oxygen-level-dependent signal variability during rest in episodic migraine.

BACKGROUND: Migraine has been associated with functional brain changes including altered connectivity and activity both during and between headache attacks. Recent studies established that the variability of the blood-oxygen-level-dependent (BOLD) signal is an important attribute of brain activity, which has so far been understudied in migraine. In this study, we investigate how time-varying measures of BOLD variability change interictally in episodic migraine patients. METHODS: Two independent resting state functional MRI datasets acquired on 3T (discovery cohort) and 1.5T MRI scanners (replication cohort) including 99 episodic migraine patients (n3T = 42, n1.5T=57) and 78 healthy controls (n3T = 46, n1.5T=32) were analyzed in this cross-sectional study. A framework using time-varying measures of BOLD variability was applied to derive BOLD variability states. Descriptors of BOLD variability states such as dwell time and fractional occupancy were calculated, then compared between migraine patients and healthy controls using Mann-Whitney U-tests. Spearman's rank correlation was calculated to test associations with clinical parameters. RESULTS: Resting-state activity was characterized by states of high and low BOLD signal variability. Migraine patients in the discovery cohort spent more time in the low variability state (mean dwell time: p = 0.014, median dwell time: p = 0.022, maximum dwell time: p = 0.013, fractional occupancy: p = 0.013) and less time in the high variability state (mean dwell time: p = 0.021, median dwell time: p = 0.021, maximum dwell time: p = 0.025, fractional occupancy: p = 0.013). Higher uptime of the low variability state was associated with greater disability as measured by MIDAS scores (maximum dwell time: R = 0.45, p = 0.007; fractional occupancy: R = 0.36, p = 0.035). Similar results were observed in the replication cohort. CONCLUSION: Episodic migraine patients spend more time in a state of low BOLD variability during rest in headache-free periods, which is associated with greater disability. BOLD variability states show potential as a replicable functional imaging marker in episodic migraine.

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.

Eye-tracking-aided characterization of saccades and antisaccades in SYNE1 ataxia patients: a pilot study.

BACKGROUND: SYNE1 ataxia is an autosomal recessive hereditary condition, the main characteristic features of which are gait and limb ataxia and cerebellar dysarthria. Reports have revealed that the clinical phenotype of SYNE1 ataxia is more complex than the first published cases with pure cerebellar signs indicated. The aim of this study was to characterize eye movement alterations in the first diagnosed Hungarian SYNE1 ataxia patients. RESULTS: Saccades and antisaccades were examined with an eye tracker device in 3 SYNE1 (one patient has two frameshift mutations [c.8515_8516insA, p.Met2839Asnfs*53 and c.11594_11595insG, p.Glu3866*] in a compound heterozygous state, whereas two subjects have a splicing variant [c.23146-2A > G] in a homozygous state), 6 Friedreich ataxia (FA) patients and 12 healthy controls. Besides that, detailed clinical phenotyping and comprehensive neuropsychological assessment were carried out in all patients with ataxia. In addition to the characteristic cerebellar alterations, pyramidal signs and polyneuropathy were observed at least in 2 SYNE1 ataxia patients, for which no other underlying reason was found. The eye tracking assessment revealed hypometric saccades in the longer amplitude (18.4°) saccadic paradigm in all SYNE1 patients, whereas 2 out of 3 SYNE1 subjects performed slow saccades as well. In the antisaccade task, higher incorrect ratios of antisaccades were demonstrated in SYNE1 patients compared to healthy controls, showing inverse correlation with working memory test results. The corresponding data of FA patients was dispersed over a wide range, partially overlapping with control data. CONCLUSIONS: The current study draws attention to the presence of eye movement disorders in patients with SYNE1 ataxia and demonstrates that alterations in the antisaccade paradigm may be related to working memory deficits.

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.

The effects of experimental pain on episodic memory and its top-down modulation: a preregistered pooled analysis.

Introduction: Pain can automatically interfere with ongoing cognitive processes such as attention and memory. The extent of pain's negative effects on cognitive functioning seems to depend on a balance between top-down and bottom-up factors. Objectives: In this large, preregistered, pooled reanalysis of 8 studies, we investigated the robustness of the detrimental effect of acute pain on recognition memory and whether top-down mechanisms such as pain-related expectations or cognitions (pain-related fear, pain catastrophizing) modulate this effect. Methods: Two hundred forty-seven healthy participants underwent similar experimental paradigms, including a visual categorization task with images randomly paired with (or without) concomitant painful stimulation and a subsequent unannounced recognition task. Recognition memory (ie, d', recollection, and familiarity) and categorization performance (ie, reaction time, accuracy) served as proxies for the effect of pain on cognitive performance. Results: Acute painful stimulation significantly impaired recognition performance (d', familiarity). However, recognition performance was not significantly modulated by participants' expectations regarding the effect of pain on task performance or pain-related cognitions in this sample of healthy participants. Conclusion: Our results corroborate the negative effects of pain on (visual) memory encoding reported in previous studies and reports of "memory problems" from patients with chronic pain. To characterize the role of bottom-up and top-down factors for the detrimental effects of pain, large-scale studies with more nuanced study designs are necessary. Future studies in patient cohorts must unravel the interaction of maladaptive pain-related cognitions and the often-reported impaired cognitive performance in chronic pain patients.

Setting the stage for pain relief: how treatment setting impacts interdisciplinary multimodal pain treatment for patients with chronic back pain.

ABSTRACT: While interdisciplinary multimodal pain treatment (IMPT) is an effective treatment option for chronic low back pain, it is usually accomplished as an inpatient treatment incurring substantial healthcare costs. Day hospital IMPT could be a resource-saving alternative approach, but whether treatment setting is associated with differences in treatment outcomes has not yet been studied. In a retrospective matched cohort study including data from N = 595 patients diagnosed with chronic back pain and undergoing IMPT at the back pain center in Essen, Germany, we investigated the association between treatment setting (ie, inpatient or day patient of an otherwise identical IMPT) and pain intensity, disability, and self-efficacy after treatment. Outcomes were assessed by questionnaires used in clinical routine, collected at pre-IMPT, post-IMPT, and at 3-, 6-, and 12-month follow-up. The results indicate that day patients showed greater improvements in pain-related disability at 3-month post-IMPT (d = 0.74) and in pain intensity at 6-month post-IMPT (d = 0.79), compared to a matched sample of inpatients. Moreover, day patients achieved higher scores in pain-related self-efficacy at discharge, 3- and 6-month post-IMPT (d = 0.62, 0.99, and 1.21, respectively) and reported fewer incapacity-for-work days than inpatients at 6-month post-IMPT (d = 0.45). These data suggest that day hospital IMPT can be as effective as inpatient treatment and might even be more effective for the less afflicted patients. Further research regarding treatment setting and indication could guide optimized and cost-efficient treatments that are more closely tailored to the individual patient's needs.

An externally validated resting-state brain connectivity signature of pain-related learning.

Pain can be conceptualized as a precision signal for reinforcement learning in the brain and alterations in these processes are a hallmark of chronic pain conditions. Investigating individual differences in pain-related learning therefore holds important clinical and translational relevance. Here, we developed and externally validated a novel resting-state brain connectivity-based predictive model of pain-related learning. The pre-registered external validation indicates that the proposed model explains 8-12% of the inter-individual variance in pain-related learning. Model predictions are driven by connections of the amygdala, posterior insula, sensorimotor, frontoparietal, and cerebellar regions, outlining a network commonly described in aversive learning and pain. We propose the resulting model as a robust and highly accessible biomarker candidate for clinical and translational pain research, with promising implications for personalized treatment approaches and with a high potential to advance our understanding of the neural mechanisms of pain-related learning.

Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach.

ABSTRACT: Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pearson r = 0.36, P < 0.0002, R2 = 0.13). The predictions were found to be specific to physical pain thresholds and not biased towards potential confounding effects (eg, anxiety, stress, depression, centre effects, and pain self-evaluation). Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.

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.

Periventricular magnetisation transfer abnormalities in early multiple sclerosis.

OBJECTIVE: Recent studies suggested that CSF-mediated factors contribute to periventricular (PV) T2-hyperintense lesion formation in multiple sclerosis (MS) and this in turn correlates with cortical damage. We thus investigated if such PV-changes are observable microstructurally in early-MS and if they correlate with cortical damage. METHODS: We assessed the magnetisation transfer ratio (MTR) in PV normal-appearing white matter (NAWM) and in MS lesions in 44 patients with a clinically isolated syndrome (CIS) suggestive of MS and 73 relapsing-remitting MS (RRMS) patients. Band-wise MTR values were related to cortical mean thickness (CMT) and compared with 49 healthy controls (HCs). For each band, MTR changes were assessed relative to the average MTR values of all HCs. RESULTS: Relative to HCs, PV-MTR was significantly reduced up to 2.63% in CIS and 5.37% in RRMS (p < 0.0001). The MTR decreased towards the lateral ventricles with 0.18%/mm in CIS and 0.31%/mm in RRMS patients, relative to HCs. In RRMS, MTR-values adjacent to the ventricle and in PV-lesions correlated positively with CMT and negatively with EDSS. CONCLUSION: PV-MTR gradients are present from the earliest stage of MS, consistent with more pronounced microstructural WM-damage closer to the ventricles. The positive association between reduced CMT and lower MTR in PV-NAWM suggests a common pathophysiologic mechanism. Together, these findings indicate the potential use of multimodal MRI as refined marker for MS-related tissue changes.

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).

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.

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.

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.

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.

Pain-free resting-state functional brain connectivity predicts individual pain sensitivity.

Individual differences in pain perception are of interest in basic and clinical research as altered pain sensitivity is both a characteristic and a risk factor for many pain conditions. It is, however, unclear how individual sensitivity to pain is reflected in the pain-free resting-state brain activity and functional connectivity. Here, we identify and validate a network pattern in the pain-free resting-state functional brain connectome that is predictive of interindividual differences in pain sensitivity. Our predictive network signature allows assessing the individual sensitivity to pain without applying any painful stimulation, as might be valuable in patients where reliable behavioural pain reports cannot be obtained. Additionally, as a direct, non-invasive readout of the supraspinal neural contribution to pain sensitivity, it may have implications for translational research and the development and assessment of analgesic treatment strategies.

Temporal instability of salience network activity in migraine with aura.

This study aims to investigate whether intranetwork dynamic functional connectivity and causal interactions of the salience network is altered in the interictal term of migraine. Thirty-two 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 through a dual regression approach. Salience network regions of interest (bilateral insulae and prefrontal cortices, dorsal anterior cingulate cortex) were obtained from the group average map through cluster-based thresholding. To describe intranetwork connectivity, average and dynamic conditional correlation was calculated. Causal interactions between the default-mode, dorsal attention, and salience network were characterised by spectral Granger's causality. Time-averaged correlation was lower between the right insula and prefrontal cortex in migraine without aura vs with aura and healthy controls (P < 0.038, P < 0.037). Variance of dynamic conditional correlation was higher in migraine with aura vs healthy controls and migraine with aura vs without aura between the right insula and dorsal anterior cingulate cortex (P < 0.011, P < 0.026), and in migraine with aura vs healthy controls between the dorsal anterior cingulate and left prefrontal cortex (P < 0.021). Causality was weaker in the <0.05 Hz frequency range between the salience and dorsal attention networks in migraine with aura (P < 0.032). Overall, migraineurs with aura exhibit more fluctuating connections in the salience network, which also affect network interactions, and could be connected to altered cortical excitability and increased sensory gain.

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.

Gray Matter Atrophy to Explain Subclinical Oculomotor Deficit in Multiple Sclerosis.

Eye movement deficits are frequently noted in multiple sclerosis during bedside clinical examination, but subtle dysfunction may remain undetected and might only be identified with advanced approaches. While classical neurology provides insight into the complex functional anatomy of oculomotor functions, little is known about the structural background of this dysfunction in MS. Thirty four clinically stable, treated relapsing-remitting MS patients with mild disability and 34 healthy controls were included in our study. Group difference and correlation with clinical parameters were analyzed in case of the latency, peak-velocity, gain, dysconjugacy index, and performance during a saccade and anti-saccade task. High-resolution T1 weighted, T2 FLAIR, and double inversion recovery images were acquired on 3T to evaluate the correlation between behavioral and MRI parameters, such as T2 lesion and T1 black-hole burden, global brain, gray, and white matter atrophy. VBM style analysis was used to identify the focal gray matter atrophy responsible for oculomotor dysfunction. Significantly increased latency in the prosaccade task and significantly worse performance in the anti-saccade task were found in MS patients. The detailed examination of conjugated eye movements revealed five subclinical internuclear ophthalmoparesis cases. The peak velocity and latency of the anti-saccade movement correlated with the number of black holes, but none of the eye movement parameters were associated with the T2 lesion burden or location. Global gray matter volume correlated with saccade and anti-saccade latency, whereas white matter and total brain volume did not. Local gray matter atrophy in the left inferio-parietal lobule and temporo-occipital junction correlated with anti-saccade peak velocity. Our results show that neurodegeneration-like features of the MRI (black-hole, gray matter atrophy) are the best predictors of eye movement deficit in MS. Concurring with the clinico-radiological paradox, T2 lesion burden cannot explain the behavioral results. Importantly, anti-saccade peak velocity correlates with gray matter atrophy in the left parietal regions, which are frequently implicated in attention tasks.