Summary metrics of memory subnetwork functional connectivity alterations in multiple sclerosis.

BACKGROUND: Memory dysfunction is common in multiple sclerosis (MS); mechanistic understanding of its causes is lacking. Large-scale network resting-state functional connectivity (RSFC) is sensitive to memory dysfunction. OBJECTIVE: We derived and tested summary metrics of memory network RSFC. METHODS: Cognitive data and 3T magnetic resonance imaging (MRI) scans were collected from 235 MS patients and 35 healthy controls (HCs). Index scores were calculated as RSFC within (anteriority index, AntI) and between (integration index, IntI) dorsomedial anterior temporal and medial temporal memory subnetworks. Group differences in index expression were evaluated. Associations between index scores and memory/non-memory cognition were evaluated; relationships between T2 lesion volume (T2LV) and index scores were assessed. RESULTS: Index scores were related to memory and T2LV in MS patients, who showed marginally elevated AntI relative to HC (p = 0.06); no group differences were found for IntI. Better memory was associated with higher AntI (ß = 0.15, p = 0.018) and IntI (ß = 0.16, p = 0.014). No associations were found for non-memory cognition. Higher T2LV was associated with higher AntI and IntI; exploratory mediation analysis revealed significant inconsistent mediation, that is, higher index scores partially suppressed the negative association between T2LV and memory. CONCLUSION: Summary, within-subject metrics permit replication and circumvent challenges of traditional (incommensurate) RSFC variables to advance development of mechanistic models of memory dysfunction in MS.

Associations of social network structure with cognition and amygdala volume in multiple sclerosis: An exploratory investigation.

BACKGROUND: Humans are inherently social, biologically programmed to connect with others. Social connections are known to impact mental and physical health. OBJECTIVE: The aim of this study was to test whether social network structure is linked to cognition, mood, fatigue, and regional brain volumes in persons with multiple sclerosis (MS). METHODS: A questionnaire quantifying individual-level social network structure (size, density, effective size, and constraint), a comprehensive battery of neuropsychological tests, and magnetic resonance imaging (MRI) was administered to 51 persons with relapsing-remitting MS. Linear regressions assessed associations of network variables to cognition, depression, fatigue, and structural brain volumes. RESULTS: Higher network density and constraint, indicating stronger connections among network members, were associated with worse language functions. Conversely, larger network effective size, a measure of non-redundant network members, was associated with better language functions. No relationships of network structure to depression or fatigue were found. Larger network size was related to larger amygdala volume. CONCLUSION: Findings suggest that social network structure is linked to language function and amygdala volume in persons with MS. Patients with close-knit networks showed worse language function than those with open networks. Longitudinal studies with larger samples are warranted to evaluate potential causal links between social network structure and MS-related cognitive impairment.

Hippocampal volume is more related to patient-reported memory than objective memory performance in early multiple sclerosis.

BACKGROUND: When persons with multiple sclerosis (MS) report memory decline but objective memory performance is normal, there is a bias toward believing objective test results. OBJECTIVE: Investigate whether subjective memory decline or objective memory performance is more related to hippocampal and hippocampal subfield volumes in early MS. METHODS: Persons with early MS (n = 185; ⩽5.0 years diagnosed) completed a subjective memory questionnaire; an objective memory composite was derived from four memory tests. Total hippocampal and subfield volumes were derived from high-resolution 3.0 T magnetic resonance images (MRIs). Partial correlations assessed links between hippocampal volumes and both subjective and objective memory, controlling for age, sex, mood, and pre-morbid intelligence quotient (IQ). RESULTS: Lower total hippocampal and CA1 volumes were related to worse subjective memory but not objective memory (controlling for multiple comparisons). Correlations between subjective memory and both CA1 and subiculum were significantly stronger than were correlations between objective memory and these subfields. Patients in the worst tertile of subjective memory complaints (but not objective memory) had lower hippocampal volumes than 35 demographically similar healthy controls. CONCLUSION: Patient-report is inherently a longitudinal assessment of within-person memory change in everyday life, which may be more sensitive to subtle disease-related changes than cross-sectional objective tests. Findings align with the aging literature.

Classifying multiple sclerosis patients on the basis of SDMT performance using machine learning.

OBJECTIVE: To build a model to predict cognitive status reflecting structural, functional, and white matter integrity changes in early multiple sclerosis (MS). METHODS: Based on Symbol Digit Modalities Test (SDMT) performance, 183 early MS patients were assigned "lower" or "higher" performance groups. Three-dimensional (3D)-T2, T1, diffusion weighted, and resting-state magnetic resonance imaging (MRI) data were acquired in 3T. Using Random Forest, five models were trained to classify patients into two groups based on 1-demographic/clinical, 2-lesion volume/location, 3-local/global tissue volume, 4-local/global diffusion tensor imaging, and 5-whole-brain resting-state-functional-connectivity measures. In a final model, all important features from previous models were concatenated. Area under the receiver operating characteristic curve (AUC) values were calculated to evaluate classifier performance. RESULTS: The highest AUC value (0.90) was achieved by concatenating all important features from neuroimaging models. The top 10 contributing variables included volumes of bilateral nucleus accumbens and right thalamus, mean diffusivity of left cingulum-angular bundle, and functional connectivity among hubs of seven large-scale networks. CONCLUSION: These results provide an indication of a non-random brain pattern mostly compromising areas involved in attentional processes specific to patients who perform worse in SDMT. High accuracy of the final model supports this pattern as a potential neuroimaging biomarker of subtle cognitive changes in early MS.

Dissociable cognitive patterns related to depression and anxiety in multiple sclerosis.

BACKGROUND: Individuals with multiple sclerosis (MS) frequently present with depression and anxiety, as well as cognitive impairment, challenging clinicians to disentangle interrelationships among these symptoms. OBJECTIVE: To identify cognitive functions associated with anxiety and depression in MS. METHODS: Mood and cognition were measured in 185 recently diagnosed patients (Reserve Against Disability in Early Multiple Sclerosis (RADIEMS) cohort), and an independent validation sample (MEM CONNECT cohort, n = 70). Partial correlations evaluated relationships of cognition to anxiety and depression controlling for age, sex, education, and premorbid verbal intelligence. RESULTS: In RADIEMS cohort, lower anxiety was associated with better nonverbal memory (rp = -0.220, p = 0.003) and lower depression to better attention/processing speed (rp = -0.241, p = 0.001). Consistently, in MEM CONNECT cohort, lower anxiety was associated with better nonverbal memory (rp = -0.271, p = 0.028) and lower depression to better attention/processing speed (rp = -0.367, p = 0.002). Relationships were unchanged after controlling for T2 lesion volume and fatigue. CONCLUSION: Consistent mood-cognition relationships were identified in two independent cohorts of MS patients, suggesting that cognitive correlates of anxiety and depression are separable. This dissociation may support more precise models to inform treatment development. Treatment of mood symptoms may mitigate effects on cognition and/or treatment of cognition may mitigate effects on mood.

Mesial temporal lobe and subcortical grey matter volumes differentially predict memory across stages of multiple sclerosis.

BACKGROUND/OBJECTIVE: Memory deficits due to multiple sclerosis (MS) have been variably linked to lower subcortical grey matter (SCGM) and mesial temporal lobe (MTL) volumes. We investigated which is the better predictor and whether this changes across disease stages. METHODS/RESULTS: Memory was assessed in 315 patients. Magnetic resonance imaging (MRI) measured volumes of total brain, grey matter, white matter, MTL (hippocampus, amygdala) and SCGM (thalamus, caudate). MTL predicted memory in the total sample and in patients with earlier (<10 years) or later (⩾10 years) relapsing disease. SCGM (specifically thalamus) predicted memory in progressive patients. CONCLUSIONS: Neuroanatomical correlates of memory deficits differ across disease stages.

Cerebellar lobule atrophy and disability in progressive MS.

OBJECTIVE: To investigate global and lobular cerebellar volumetries in patients with progressive multiple sclerosis (MS), testing the contribution of cerebellar lobular atrophy to both motor and cognitive performances. METHODS: Eighty-two patients with progressive MS and 46 healthy controls (HC) were enrolled in this cross-sectional study. Clinical evaluation included motor and cognitive testing: Expanded Disability Status Scale, cerebellar Functional System score, Timed 25-Foot Walk Test, 9-Hole Peg Test (9-HPT), Symbol Digit Modalities Test (SDMT), Brief Visuospatial Memory Test-Revised (BVMT) and California Verbal Learning Test II (CVLT). Cerebellar volumes were automatically obtained using the Spatially Unbiased Infratentorial Toolbox. A hierarchical multiple linear regression analysis was performed to assess the relationship between MRI variables of supratentorial and cerebellar damage (grey matter fraction, T2 lesion volume, metrics of cerebellar atrophy and cerebellar lesion volume) and motor/cognitive scores. RESULTS: Patients with MS exhibited lower cerebellar volumes compared with HC. Regression analysis showed that cerebellar metrics accounted for extra variance in both motor and cognitive performances, with cerebellar lesion volume, cerebellar Lobules VI, Crus I and VIIIa atrophy being independent predictors of 9-HPT, SDMT, BVMT and CVLT performances. CONCLUSIONS: Atrophy of specific cerebellar lobules explains different aspects of motor and cognitive disability in patients with progressive MS. Investigation of cerebellar involvement provides further insight into the pathophysiological basis of clinical disability in progressive MS.

Protective personality traits: High openness and low neuroticism linked to better memory in multiple sclerosis.

BACKGROUND: Memory impairment in multiple sclerosis (MS) is common, although few risk/protective factors are known. OBJECTIVE: To examine relationships of personality to memory/non-memory cognition in MS. METHOD: 80 patients completed a cognitive battery and a personality scale measuring the "Big 5" traits: openness, neuroticism, agreeableness, extraversion, and conscientiousness. RESULTS: Memory was most related to openness, with higher openness linked to better memory and lower risk for memory impairment, controlling for age, atrophy, education, and intelligence quotient (IQ). Lower neuroticism was also related to better memory, and lower conscientiousness to memory impairment. Non-memory cognition was unrelated to personality. CONCLUSION: Personality may inform predictive models of memory impairment in MS.

MR spectroscopy and diffusion imaging in people with human immunodeficiency virus: Relationships to clinical and immunologic findings.

BACKGROUND AND PURPOSE: People with human immunodeficiency virus (HIV; PWH) present a complex array of immunologic and medical disorders that impact brain structure and metabolism, complicating the interpretation of neuroimaging. This pilot study of well-characterized multi-morbid PWH examined how medical and immunologic factors predicted brain characteristics on proton MR spectroscopy (1H-MRS) and diffusion-weighted imaging (DWI). METHODS: Eighteen individuals on combination antiretroviral therapy (cART), with mean age of 56 years, underwent medical history review, neuroimaging, and on the day of imaging, blood draw for assay of 20 plasma cytokines and flow cytometric characterization of peripheral blood mononuclear cell subsets. Predictors of n-acetyl aspartate, choline, myoinositol, glutamate/glutamine, fractional anisotropy and mean diffusivity were identified through bivariate correlation; those significant at p < .1000 were advanced to multivariate analysis, with models created for each neuroimaging outcome. RESULTS: Monocyte subsets and diverse cytokines accounted for 16 of 25 (64%) variables predicting 1H-MRS spectra in frontal gray and white matter and basal ganglia; monocyte subsets did not predict any DWI characteristic. In contrast, age, presence of hypertension, and duration of HIV infection accounted for 13 of 25 (52%) variables predicting diffusion characteristics in the corpus callosum, thalamic radiations, and basal ganglia but only 3 of 25 (12%) predictors of 1H-MRS features. CONCLUSIONS: 1H-MRS neurometabolites were most often predicted by immunologic factors sensitive to temporal variation, whereas DWI metrics were more often related to longer-term disease state. In multi-morbid cART-era populations, selection and interpretation of neuroimaging modalities should account for complex temporal and pathogenetic influences of immunologic abnormality, disease state, and aging.

Brain volumetric correlates of remotely versus in-person administered symbol digit modalities test in multiple sclerosis.

BACKGROUND: Prior studies in multiple sclerosis (MS) support reliability of telehealth-delivered cognitive batteries, although, to date, none have reported relationships of cognitive test performance to neural correlates across administration modalities. In this study we aimed to compare brain-behavior relationships, using the Symbol Digit Modalities Test (SDMT), the most reliable and sensitive cognitive measure in MS, measured from patients seen via telehealth versus in-person. METHODS: SDMT was administered to individuals with MS either in-person (N=60, mean age=39.7) or remotely via video conference (N=51, mean age=47.4). Magnetic resonance imaging (MRI) data was collected in 3-Tesla scanners. Using 3-dimensional T1 images cerebral, cortical, deep gray, cerebral white matter and thalamic nuclei volumes were calculated. Using a meta-analysis approach with an interaction term for participant group, individual regression models were run for each MRI measure having SDMT scores as the outcome variable in each model. In addition, the correlation and average difference between In-person and Remote group associations across the MRI measures were calculated. Finally, for each MRI variable I2 score was quantified to test the heterogeneity between the groups. RESULTS: Administration modality did not affect the association of SDMT performance with MRI measures. Brain tissue volumes showing high associations with the SDMT scores in one group also showed high associations in the other (r = 0.83; 95% CI = [0.07, 0.86]). The average difference between the In-person and the Remote group associations was not significant (ßRemote - ßIn-person = 0.14, 95% CI = [-0.04, 0.34]). Across MRI measures, the average I2 value was 14%, reflecting very little heterogeneity in the relationship of SDMT performance to brain volume. CONCLUSION: We found consistent relationships to neural correlates across in-person and remote SDMT administration modalities. Hence, our study extended the findings of the previous studies demonstrating the feasibility of remote administration of the SDMT.

Machine learning to investigate superficial white matter integrity in early multiple sclerosis.

BACKGROUND AND PURPOSE: This study aims todetermine the sensitivity of superficial white matter (SWM) integrity as a metric to distinguish early multiple sclerosis (MS) patients from healthy controls (HC). METHODS: Fractional anisotropy and mean diffusivity (MD) values from SWM bundles across the cortex and major deep white matter (DWM) tracts were extracted from 29 early MS patients and 31 age- and sex-matched HC. Thickness of 68 cortical regions and resting-state functional-connectivity (RSFC) among them were calculated. The distribution of structural and functional metrics between groups were compared using Wilcoxon rank-sum test. Utilizing a machine learning method (adaptive boosting), 6 models were built based on: 1-SWM, 2-DWM, 3-SWM and DWM, 4-cortical thickness, or 5-RSFC measures. In model 6, all features from previous models were incorporated. The models were trained with nested 5-folds cross-validation. Area under the receiver operating characteristic curve (AUCroc ) values were calculated to evaluate classification performance of each model. Permutation tests were used to compare the AUCroc values. RESULTS: Patients had higher MD in SWM bundles including insula, inferior frontal, orbitofrontal, superior and medial temporal, and pre- and post-central cortices (p < .05). No group differences were found for any other MRI metric. The model incorporating SWM and DWM features provided the best classification (AUCroc = 0.75). The SWM model provided higher AUCroc (0.74), compared to DWM (0.63), cortical thickness (0.67), RSFC (0.63), and all-features (0.68) models (p < .001 for all). CONCLUSION: Our results reveal a non-random pattern of SWM abnormalities at early stages of MS even before pronounced structural and functional alterations emerge.

Social support is linked to mental health, quality of life, and motor function in multiple sclerosis.

OBJECTIVE: To investigate associations of social support to psychological well-being, cognition, and motor functioning in patients with multiple sclerosis (MS). Secondarily, we were interested in exploring sex differences in these relationships, based on a bioevolutionary theoretical justification. METHODS: Social support was assessed in 185 recently diagnosed patients (RADIEMS cohort), and in an independent validation sample (MEMCONNECT cohort, n = 62). Patients also completed a comprehensive neurobehavioral evaluation including measures of mental health, fatigue, quality of life, cognition, and motor function. Correlations tested links between social support and these variables, along with potential gender differences. RESULTS: In both samples, higher social support was associated with better mental health, quality of life, subjective cognitive function, and less fatigue. In the RADIEMS cohort, higher social support was associated with better motor functions, particularly grip strength and gait endurance in women. CONCLUSIONS: These findings highlight associations of social support to overall psychological health and motor functioning in persons with MS, underlining the potential opportunity of evaluating and promoting social engagement in novel treatment strategies.

Dietary factors and MRI metrics in early Multiple Sclerosis.

BACKGROUND: Despite significant interest in diet by the MS community, research on this topic is limited; there are no published studies evaluating associations between diet and neuroimaging in MS. METHODS: We utilized baseline data from the RADIEMS cohort of early MS (diagnosed <5.0 years, n=180). Participants underwent brain MRIs to derive normalized total gray and thalamic volumes, T2 lesion volume, and white matter microstructural integrity of normal appearing white matter (NAWM). Participants completed food frequency questionnaires (FFQ) from which we calculated adherence scores to pre-specified dietary patterns including the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet. We evaluated intake of the following pre-specified dietary components: fruits, vegetables, legumes, nuts, whole grains, dairy, fried foods, processed meats, and fat intake. We used multivariable-adjusted linear regression to evaluate MRI metrics versus dietary measures. RESULTS: MIND diet score was associated with thalamic volume; individuals in the highest quartile of MIND diet scores had greater thalamic volumes versus those in the lowest quartile (Q4 vs. Q1: 1.03mL; 95%CI: 0.26mL, 1.79mL; p<0.01). For individual food/nutrients, higher intakes of full-fat dairy were associated with lower T2 lesion volumes (Q4 vs. Q1: -0.93mL; 95%CI: -1.51mL, -0.35ml; p<0.01). Higher intakes of marine omega-3 fatty acids were associated with greater NAWM microstructural integrity (Q4 vs. Q1: 0.40; 95%CI: 0.03, 0.76; p=0.04). Other foods/nutrients were not associated with MRI outcomes. CONCLUSIONS: In this first study focused on neuroimaging and diet in MS, we note significant associations in a cross-sectional early MS cohort. Longitudinal follow-up of imaging/clinical outcomes will provide additional insights.

Reduced Hippocampal GABA+ Is Associated With Poorer Episodic Memory in Healthy Older Women: A Pilot Study.

Background: The current pilot study was designed to examine the association between hippocampal γ-aminobutyric acid (GABA) concentration and episodic memory in older individuals, as well as the impact of two major risk factors for Alzheimer's disease (AD)-female sex and Apolipoprotein ε4 (ApoE ε4) genotype-on this relationship. Methods: Twenty healthy, community-dwelling individuals aged 50-71 (11 women) took part in the study. Episodic memory was evaluated using a Directed Forgetting task, and GABA+ was measured in the right hippocampus using a Mescher-Garwood point-resolved magnetic resonance spectroscopy (MRS) sequence. Multiple linear regression models were used to quantify the relationship between episodic memory, GABA+, ApoE ɛ4, and sex, controlling for age and education. Results: While GABA+ did not interact with ApoE ɛ4 carrier status to influence episodic memory (p = 0.757), the relationship between GABA+ and episodic memory was moderated by sex: lower GABA+ predicted worse memory in women such that, for each standard deviation decrease in GABA+ concentration, memory scores were reduced by 11% (p = 0.001). Conclusions: This pilot study suggests that sex, but not ApoE ɛ4 genotype, moderates the relationship between hippocampal GABA+ and episodic memory, such that women with lower GABA+ concentration show worse memory performance. These findings, which must be interpreted with caution given the small sample size, may serve as a starting point for larger studies using multimodal neuroimaging to understand the contributions of GABA metabolism to age-related memory decline.

Detection of subtle gait disturbance and future fall risk in early multiple sclerosis.

OBJECTIVE: To test the hypothesis that higher-challenge gait and balance tasks are more sensitive than traditional metrics to subtle patient-reported gait dysfunction and future fall risk in early multiple sclerosis (MS). METHODS: Persons with early MS (n = 185; ≤5 years diagnosed) reported gait function (MS Walking Scale) and underwent traditional disability metrics (Expanded Disability Status Scale [EDSS], Timed 25 Foot Walk). Patients and healthy controls (n = 50) completed clinically feasible challenge tasks of gait endurance (2-Minute Walk Test), standing balance (NIH Toolbox), and dynamic balance (balance boards; tandem walk on 2 ten-foot boards of different widths, 4.5 and 1.5 in). MRI assessed global and regional brain volumes, total T2 lesion volume (T2LV), infratentorial T2LVs and counts, and cervical cord lesion counts. Falls, near falls, and fall-related injuries were assessed after 1 year. We examined links between all tasks and patient-reported gait, MRI markers, and fall data. RESULTS: Patients performed worse on higher challenge balance, but not gait, tasks compared with healthy controls. Worse patient-reported gait disturbance was associated with worse performance on all tasks, but only dynamic balance was sensitive to mild patient-reported gait difficulty. Balance tasks were more correlated with MRI metrics than were walking tasks or EDSS score. Thirty percent of patients reported either a fall or near fall after 1 year, with poor dynamic balance as the only task independently predicting falls. CONCLUSIONS: Balance plays a leading role in gait dysfunction early in MS. Clinically feasible higher-challenge balance tasks were most sensitive to patient-reported gait, MRI disease markers, and risk of future falls, highlighting potential to advance functional outcomes in clinical practice and trials.

The Impact of MRI T1 Hypointense Brain Lesions on Cerebral Deep Gray Matter Volume Measures in Multiple Sclerosis.

BACKGROUND AND PURPOSE: Deep gray matter (DGM) atrophy has been shown at early stages of multiple sclerosis (MS) and reported as an informative marker of cognitive dysfunction and clinical progression. Therefore, accurate measurement of DGM structure volume is a key priority in MS research. Findings from prior studies have shown that hypointense T1 lesions may impact the accuracy of global brain volume measures; however, literature on the effects of hypointense T1 lesions on DGM structure volumes is sparse. METHODS: We explored the effects of hypointense T1 lesions on data from 54 relapsing remitting MS patients. Lesions were segmented both manually and with a freely available automatic lesion segmentation/in-painting algorithm (Lesion Segmentation Tool-LST). Volumes of 14 DGM structures were calculated from non-in-painted and in-painted images and compared via paired t-tests, intraclass correlation coefficient, and Dice similarity coefficient. RESULTS: There were no significant differences in DGM structural volumes between non-in-painted and in-painted images. Automatic lesion-segmentation/in-painting tool provided similar results to manual segmentation/in-painting. CONCLUSIONS: Our results suggest that lesion in-painting has a negligible impact on DGM structure volume measurement although some regions are more vulnerable to the impact of lesions than others. Furthermore, manual lesion segmentation/in-painting can be replaced by an automatic segmentation/in-painting process.

CCR2 on Peripheral Blood CD14+CD16+ Monocytes Correlates with Neuronal Damage, HIV-Associated Neurocognitive Disorders, and Peripheral HIV DNA: reseeding of CNS reservoirs?

HIV-associated neurocognitive disorders (HAND) occur in ~50% of HIV infected individuals despite combined antiretroviral therapy. Transmigration into the CNS of CD14+CD16+ monocytes, particularly those that are HIV infected and express increased surface chemokine receptor CCR2, contributes to neuroinflammation and HAND. To examine whether in HIV infected individuals CCR2 on CD14+CD16+ monocytes serves as a potential peripheral blood biomarker of HAND, we examined a cohort of 45 HIV infected people. We correlated CCR2 on CD14+CD16+ monocytes with cognitive status, proton magnetic resonance spectroscopy (1H-MRS) measured neurometabolite levels, and peripheral blood mononuclear cell (PBMC) HIV DNA copies. We determined that CCR2 was increased specifically on CD14+CD16+ monocytes from people with HAND (median [interquartile range (IQR)]) (63.3 [51.6, 79.0]), compared to those who were not cognitively impaired (38.8 [26.7, 56.4]) or those with neuropsychological impairment due to causes other than HIV (39.8 [30.2, 46.5]). CCR2 was associated with neuronal damage, based on the inverse correlation of CCR2 on CD14+CD16+ monocytes with total N-Acetyl Aspartate (tNAA)/total Creatine (tCr) (r2 = 0.348, p = 0.01) and Glutamine-Glutamate (Glx)/tCr (r2 = 0.356, p = 0.01) in the right and left caudate nucleus, respectively. CCR2 on CD14+CD16+ monocytes also correlated with PBMC HIV DNA copies (ρ = 0.618, p = 0.02) that has previously been associated with HAND. These findings suggest that CCR2 on CD14+CD16+ monocytes may be a peripheral blood biomarker of HAND, indicative of increased HIV infected CD14+CD16+ monocyte entry into the CNS that possibly increases the macrophage viral reservoir and contributes to HAND.

Diffusion Kurtosis Imaging Shows Similar Cerebral Axonal Damage in Patients with HIV Infection and Multiple Sclerosis.

BACKGROUND AND PURPOSE: In this pilot study, we sought to investigate the pathological changes in the white matter (WM) of medically complex, combination antiretroviral therapy (cART)-treated patients with human immunodeficiency virus (HIV), comparing them to patients with long-standing, secondary progressive multiple sclerosis (SPMS). METHODS: Using diffusion kurtosis imaging (DKI)-derived WM tract integrity (WMTI) metrics, 15 HIV and 15 age- and sex-matched SPMS patients with similar disease duration underwent magnetic resonance imaging analysis. Maps of WMTI metrics were created. Tract-based spatial statistics analysis of the whole brain and regions of interest analysis of the corpus callosum (CC) and the anterior thalamic radiations (ATRs) were performed and the derived WMTI metrics were compared between the groups of patients. RESULTS: Axonal water fraction, an index of chronic axonal loss, showed similarities between HIV and the chronic MS patients in all regions; in contrast, tortuosity, a measure more sensitive to myelin loss, was regionally variable. In addition, in HIV patients, WMTI metrics of the CC and left ATR were associated with cognitive test scores, suggesting clinical relevance for these measures of WM damage. CONCLUSIONS: We conclude that DKI-derived WMTI metrics may be a valuable tool in assessing the WM changes of medically complex HIV-infected individuals. While not powered to examine potential etiologies of WM changes in this pilot sample, regional variations in WMTI metrics were seen. When contrasted with changes consequent to chronic MS of similar duration, HIV and its comorbidities appear to result in similar degrees of axonal damage, but regionally variable amounts of myelin loss and extraxonal abnormality.

Simple index of functional connectivity at rest in Multiple Sclerosis fatigue.

OBJECTIVE: To investigate the EEG-derived functional connectivity at rest (FCR) patterns of fatigued Multiple Sclerosis (MS) patients in order to find good parameters for a future EEG-Neurofeedback intervention to reduce their fatigue symptoms. METHODS: We evaluated FCR between hemispheric homologous areas, via spectral coherence between pairs of corresponding left and right bipolar derivations, in the Theta, Alpha and Beta bands. We estimated FCR in 18MS patients with different levels of fatigue and minimal clinical severity and in 11 age and gender matched healthy controls. We used correlation analysis to assess the relationship between the fatigue scores and the FCR values differing between fatigued MS patients and controls. RESULTS: Among FCR values differing between fatigued MS patients and controls, fatigue symptoms increased with higher Beta temporo-parietal FCR (p=0.00004). Also, positive correlations were found between the fatigue levels and the fronto-frontal FCR in Beta and Theta bands (p=0.0002 and p=0.001 respectively). CONCLUSION: We propose that a future EEG-Neurofeedback system against MS fatigue would train patients to decrease voluntarily the beta coherence between the homologous temporo-parietal areas. SIGNIFICANCE: We extracted a feature for building an EEG-Neurofeedback system against fatigue in MS.

A subject-independent pattern-based Brain-Computer Interface.

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to "match" their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders.