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Background: Reports of cognitive impairment in inflammatory bowel disease (IBD) have been mixed. IBD and cardiovascular disease are often co-morbid, yet it remains unknown whether vascular comorbidity confers a risk for decreased cognitive functioning, as observed in other populations. Methods: Participants with IBD were recruited from a longitudinal study of immune-mediated disease. Participants were administered a standardized neuropsychological test protocol, evaluating information processing speed, verbal learning and memory, visual learning and memory, and verbal fluency/executive function. Cognitive test scores were standardized using local regression-based norms, adjusting for age, sex, and education. Vascular risk was calculated using a modified Framingham Risk Score (FRS). We tested the association between FRS and cognitive test scores using a quantile regression model, adjusting for IBD type. Results: Of 84 IBD participants, 54 had ulcerative colitis and 30 had Crohn’s disease; mean (SD) age was 53.36 (13.95) years, and a high proportion were females (n = 58). As the risk score (FRS) increased, participants demonstrated lower performance in information processing speed (β=-0.12; 95% CI: -0.24, -0.006) and verbal learning (β=-0.14; 95% CI: -0.28, -0.01) at the 50th percentile. After adjusting for IBD type, higher FRS remained associated with lower information processing speed (β=-0.13; 95% CI: -0.24, -0.03). Conclusion: Vascular comorbidity is associated with lower cognitive functioning in persons with IBD, particularly in the areas of information processing speed and verbal learning. These findings suggest that prevention, identification, and treatment of vascular comorbidity in IBD may play a critical role for improving functional outcomes in IBD.

The Comorbidity and Cognition in Multiple Sclerosis (CCOMS) study represents a coordinated effort by a team of clinicians, neuropsychologists, and neuroimaging experts to investigate the neural basis of cognitive changes and their association with comorbidities among persons with multiple sclerosis (MS). The objectives are to determine the relationships among psychiatric (e.g., depression or anxiety) and vascular (e.g., diabetes, hypertension, etc.) comorbidities, cognitive performance, and MRI measures of brain structure and function, including changes over time. Because neuroimaging forms the basis for several investigations of specific neural correlates that will be reported in future publications, the goal of the current manuscript is to briefly review the CCOMS study design and baseline characteristics for participants enrolled in the three study cohorts (MS, psychiatric control, and healthy control), and provide a detailed description of the MRI hardware, neuroimaging acquisition parameters, and image processing pipelines for the volumetric, microstructural, functional, and perfusion MRI data.

Objective Anti-leucine-rich glioma-inactivated 1 limbic encephalitis (LGI1-LE) is a rare autoimmune condition that affects the structural integrity and functioning of the brain’s limbic system. Little is known about its impact on long-term neuropsychological functioning and the structural integrity of the medial temporal lobe. Here we examined the long-term neuropsychological and neuroanatomical outcomes of a 68-year-old male who acquired LGI1-LE. Methods Our case patient underwent standardized neuropsychological testing at two time points. Volumetric analyses of T1-weighted images were undertaken at four separate time points and qualitatively compared with a group of age-matched healthy controls. Results At the time of initial assessment, our case study exhibited focal impairments in verbal and visual episodic memory and these impairments continued to persist after undergoing a course of immunotherapy. Furthermore, in reference to an age-matched healthy control group, over the course of 11 months, volumetric brain imaging analyses revealed that areas of the medial temporal lobe including specific hippocampal subfields (e.g., CA1 and dentate gyrus) underwent a subacute period of volumetric enlargement followed by a chronic period of volumetric reduction in the same regions. Conclusions In patients with persisting neurocognitive deficits, LGI1-LE may produce chronic volume loss in specific areas of the medial temporal lobe; however, this appears to follow a subacute period of volume enlargement possibly driven by neuro-inflammatory processes.

Background: Longitudinal studies assessing depression and anxiety effects on cognition in multiple sclerosis (MS) are limited. Objective: We tested whether within-person fluctuations in symptoms of depression or anxiety over time affect cognition in persons with MS, inflammatory bowel disease (IBD), rheumatoid arthritis (RA), and a lifetime history of depression/anxiety disorders (DEP/ANX) but without an immune-mediated inflammatory diseases (IMID). Methods: We followed participants (MS: 255, IBD: 247, RA: 154, and DEP/ANX: 306) for 3 years. Annually, they completed the hospital anxiety and depression scale (HADS) and cognitive tests including the symbol digit modalities test (SDMT). We evaluated associations of elevated symptoms (scores ⩾ 11) of anxiety (HADS-A) and depression (HADS-D) with SDMT z-scores using multivariable linear models—estimating between-person and within-person effects. Results: Participants with MS performed worse on the SDMT than participants in the DEP/ANX cohort (β = −0.68; 95% CI: −0.88, −0.48). Participants with elevated HADS-A scores performed worse on the SDMT than those without elevated scores (β = −0.43; 95% CI: −0.65, −0.21), particularly those with RA. Time-varying within-person elevations in depressive symptoms were associated with worse SDMT performance (β = −0.12; 95% CI: −0.21, −0.021). Conclusions: Across persons, elevated symptoms of anxiety adversely affected information processing. Elevated symptoms of depression within-persons over time were associated with declines in information processing speed.

Background Spatially normalizing brain MRI data to a template is commonly performed to facilitate comparisons between individuals or groups. However, the presence of multiple sclerosis (MS) lesions and other MS-related brain pathologies may compromise the performance of automated spatial normalization procedures. We therefore aimed to systematically compare five commonly used spatial normalization methods for brain MRI – including linear (affine), and nonlinear MRIStudio (LDDMM), FSL (FNIRT), ANTs (SyN), and SPM (CAT12) algorithms – to evaluate their performance in the presence of MS-related pathologies. Methods 3 Tesla MRI images (T1-weighted and T2-FLAIR) were obtained for 20 participants with MS from an ongoing cohort study (used to assess a real dataset) and 1 healthy control participant (used to create a simulated lesion dataset). Both raw and lesion-filled versions of each participant's T1-weighted brain images were warped to the Montreal Neurological Institute (MNI) template using all five normalization approaches for the real dataset, and the same procedure was then repeated using the simulated lesion dataset (i.e., total of 400 spatial normalizations). As an additional quality-assurance check, the resulting deformations were also applied to the corresponding lesion masks to evaluate how each processing pipeline handled focal white matter lesions. For each normalization approach, inter-subject variability (across normalized T1-weighted images) was quantified using both mutual information (MI) and coefficient of variation (COV), and the corresponding normalized lesion volumes were evaluated using paired-sample t-tests. Results All four nonlinear warping methods outperformed conventional linear normalization, with SPM (CAT12) yielding the highest MI values, lowest COV values, and proportionately-scaled lesion volumes. Although lesion-filling improved spatial normalization accuracy for each of the methods tested, these effects were small compared to differences between normalization algorithms. Conclusions SPM (CAT12) warping, ideally combined with lesion-filling, is recommended for use in future MS brain imaging studies requiring spatial normalization.

Various MRI techniques, including myelin water imaging, T1w/T2w ratio mapping and diffusion-based imaging can be used to characterize tissue microstructure. However, surprisingly few studies have examined the degree to which these MRI measures are related within and between various brain regions. Therefore, whole-brain MRI scans were acquired from 31 neurologically-healthy participants to empirically measure and compare myelin water fraction (MWF), T1w/T2w ratio, fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) in 25 bilateral (10 grey matter; 15 white matter) regions-of-interest (ROIs). Except for RD vs. T1w/T2w, MD vs. T1w/T2w, moderately significant to highly significant correlations (p

Objective To determine whether comorbid diabetes and hypertension are associated with cognition in multiple sclerosis (MS) after accounting for psychiatric comorbidities. Methods Participants completed a structured psychiatric interview, the Hospital Anxiety and Depression Scale (HADS), a comorbidity questionnaire, and cognitive testing including the Symbol Digit Modalities Test (SDMT), California Verbal Learning Test (CVLT-II), Brief Visuospatial Memory Test-Revised (BVMT-R), and verbal fluency. Test scores were converted to age-, sex- and education-adjusted z-scores. We evaluated associations between diabetes and hypertension and the four cognitive z-scores using a multivariate linear model, adjusting for comorbid depression and anxiety disorders, psychotropic medications, disease-modifying therapies, smoking status and body mass index. Results Of 111 participants, most were women (82.9%) with relapsing remitting MS (83.5%), of mean (SD) age 49.6 (12.7) years. Comorbidity was common; 22.7% participants had hypertension, 10.8% had diabetes, 9.9% had current major depression, and 9.9% had current anxiety disorders. Mean (SD) z-scores were: SDMT −0.66 (1.15), CVLT-II −0.43 (1.32), BVMT-R −0.49 (1.07) and fluency −0.59 (0.86). Diabetes (p = 0.02) and anxiety disorder (p = 0.02) were associated with cognitive function overall. Diabetes was associated with lower BVMT-R (β = −1.18, p = 0.0015) and fluency (β = −0.63, p = 0.037) z-scores. Anxiety was associated with lower SDMT (β = -1.07, p = 0.0074) z-scores. Elevated anxiety symptoms (HADS-A ≥ 11) were associated with lower z-scores on the SDMT and CVLT-II. Conclusion Comorbidities, including diabetes and anxiety, are associated with cognitive dysfunction in MS. Their presence may contribute to the heterogeneous pattern of impairments seen across individuals and they may represent targets for improved management of cognitive symptoms.

Normal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state functional magnetic resonance imaging studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here, we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent signals to analyze resting-state fMRI data from 620 subjects divided into two groups (middle-age group (n = 310); age range, 50–64 years versus older group (n = 310); age range, 65–91 years). Applying the intrinsic-ignition framework to assess the effect of spontaneous local activation events on local–global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain. A.E. was supported by the Catalan project Imagenoma de L'Envelliment (Aging Imageomics Study). G.D. was supported by the Spanish Ministry of Economy and Competitiveness, Spain (grant agreement number PSI2016- 75688-P, MINECO/AEI/FEDER-EU); European Union's Horizon 2020 FET Flagship Human Brain Project (grant agreement number 785907, HBP SGA2); the Catalan Research Support, Spain (grant agreement number 2017 SGR 1545) and La Marató TV3 2017 (grant agreement 201725.33).

Biomarkers of aging are urgently needed to identify individuals at high risk of developing age-associated disease or disability. Growing evidence from population-based studies points to whole-body magnetic resonance imaging's (MRI) enormous potential for quantifying subclinical disease burden and for assessing changes that occur with aging in all organ systems. The Aging Imageomics Study aims to identify biomarkers of human aging by analyzing imaging, biopsychosocial, cardiovascular, metabolomic, lipidomic, and microbiome variables. This study recruited 1030 participants aged >= 50 years (mean 67, range 50-96 years) that underwent structural and functional MRI to evaluate the brain, large blood vessels, heart, abdominal organs, fat, spine, musculoskeletal system and ultrasonography to assess carotid intima-media thickness and plaques. Patients were notified of incidental findings detected by a certified radiologist when necessary. Extensive data were also collected on anthropometrics, demographics, health history, neuropsychology, employment, income, family status, exposure to air pollution and cardiovascular status. In addition, several types of samples were gathered to allow for microbiome, metabolomic and lipidomic profiling. Using big data techniques to analyze all the data points from biological phenotyping together with health records and lifestyle measures, we aim to cultivate a deeper understanding about various biological factors (and combinations thereof) that underlie healthy and unhealthy aging.

There is growing interest in developing magnetic resonance imaging (MRI) biomarkers of brain connectivity from resting-state functional (rs-fMRI) and diffusion tensor imaging (DTI) to aid in the diagnosis and management of patients with mild traumatic brain injury (mTBI). To determine whether early MRI biomarkers of brain connectivity are useful in predicting outcome after mTBI, we conducted a systematic review using the following inclusion criteria: 1) patients aged16 years with mTBI, 2) MRI performed during the first month post-injury, 3) outcome measure available, 4) control group, and 5) original article published in a peer-reviewed journal. Of the 1351 citations identified, 14 studies met inclusion criteria (5 rs-fMRI and 10 DTI; 680 patients with mTBI vs. 436 controls) including those where MRI was performed from12 h to 1 month post-injury. The most common clinical outcome measure used in these studies was symptom burden using the Rivermead Post-Concussion Questionnaire. The most frequently studied brain connectivity MRI biomarkers were global functional connectivity, default-mode network, and fractional anisotropy (FA). Despite the scant evidence and considerable methodological heterogeneity observed among studies, we conclude that brain connectivity MRI biomarkers obtained within 1 month of injury may be potentially useful in predicting outcome in mTBI. Further longitudinal studies are needed to evaluate the effect of mTBI on MRI-based brain connectivity biomarkers and examine how incorporation of these tests can inform the clinical care of individual mTBI patients.

Background and Purpose— Physiological effects of stroke are best assessed over entire brain networks rather than just focally at the site of structural damage. Resting-state functional magnetic resonance imaging can map functional-anatomic networks by analyzing spontaneously correlated low-frequency activity fluctuations across the brain, but its potential usefulness in predicting functional outcome after acute stroke remains unknown. We assessed the ability of resting-state functional magnetic resonance imaging to predict functional outcome after acute stroke. Methods— We scanned 37 consecutive reperfused stroke patients (age, 69±14 years; 14 females; 3-day National Institutes of Health Stroke Scale score, 6±5) on day 3 after symptom onset. After imaging preprocessing, we used a whole-brain mask to calculate the correlation coefficient matrices for every paired region using the Harvard-Oxford probabilistic atlas. To evaluate functional outcome, we applied the modified Rankin Scale at 90 days. We used region of interest analyses to explore the functional connectivity between regions and graph-computation analysis to detect differences in functional connectivity between patients with good functional outcome (modified Rankin Scale score ≤2) and those with poor outcome (modified Rankin Scale score >2). Results— Patients with good outcome had greater functional connectivity than patients with poor outcome. Although 3-day National Institutes of Health Stroke Scale score was the most accurate independent predictor of 90-day modified Rankin Scale (84.2%), adding functional connectivity increased accuracy to 94.7%. Preserved bilateral interhemispheric connectivity between the anterior inferior temporal gyrus and superior frontal gyrus and decreased connectivity between the caudate and anterior inferior temporal gyrus in the left hemisphere had the greatest impact in favoring good prognosis. Conclusions— These data suggest that information about functional connectivity from resting-state functional magnetic resonance imaging may help predict 90-day stroke outcome.

Tissue contrast can be enhanced by dividing T1-weighted (T1w) images by T2-weighted (T2w) images to map the so-called T1w/T2w ratio, which has become an increasingly popular technique for quantifying brain tissue changes associated with neurodevelopment, aging, and a variety of neurodegenerative diseases. However, although it is self-evident that T1w/T2w ratios increase with the amount of T2-weighting in the T2w image – which is determined by the echo time (TE), all else being equal – longer TEs also reduce the signal-to-noise ratio (SNR) of the T2w images, and it is not clear how these SNR characteristics affect the reliability of T1w/T2w measurements. Therefore, the current study systematically investigated how different amounts of T2-weighting affected T1w/T2w measurements in order to determine whether there is an optimal amount of T2-weighting. T1w images were acquired from 10 neurologically healthy adults using a 3D turbo field echo (TFE) sequence, and a series of T2-weighted images were extracted from a multi-echo 3D combined gradient- and spin-echo (GRASE) sequence. Analyses of 12 anatomically defined brain regions revealed that both the mean and standard deviation of the T1w/T2w measurements increased exponentially with TE of the T2w images, and that T2w images with TE ≈ 120–160 ms yielded the most consistent/reproducible contrast between white matter ROIs and the whole-brain T1w/T2w signal. Furthermore, comparisons between T1w/T2w measurements and multi-component T2-relaxation myelin water fractions (MWFs) in the same brain regions revealed that T2w images with TE ≥ 160 ms drastically reduced the degree of correlation between T1w/T2w measurements and MWF. Overall, these findings suggest that: 1) there is a substantial trade-off between increased T1w/T2w contrast (based on longer TEs for the T2w images) and the reliability of quantitative T1w/T2w signals; and 2) the optimal TE for T2w GRASE scans is between 120 ms and 160 ms for calculating T1w/T2w ratios.

Although centerlines (aka ‘skeletons’ or ‘medial axes’) are among the most efficient ways to represent items in digital images, and obtaining these from 2D shapes is relatively straight forward, extracting centerlines from 3D objects has remained a challenge—particularly if they are not smooth or uniform. Therefore, we have developed a novel 3D centerline extraction method for discrete binary objects using a ‘divide and conquer’ approach, in which any 3D object is sliced into a series of 2D images (in the X, Y and Z directions), a geometric (Voronoi) algorithm is applied to each planar image to extract the 2D centerlines, and the information is recombined (using an intersection technique) to obtain the centerline of the original 3D object. Validation of this approach was performed using a ground truth benchmark, standard 3D database objects, and more complex anatomical structures (segmented from medical imaging data). The algorithm consistently performed well for objects of moderate complexity, but occasionally left discontinuities in the extracted 3D skeletons of the most complex objects. Therefore, in order to deal with such cases, an optional 3D interpolation step—based on Delaunay triangles and a spherical search to establish the nearest neighboring points in 3D space—was developed to allow continuous centerlines to be extracted from even the most complex anatomical structures tested. As a result, we anticipate that this approach could have wide-ranging applications, including data reduction for large microscopy and other 3D imaging datasets, automatic quantification of medical imaging data along anatomical structures, and others.

Background Few studies have evaluated the association between comorbidities associated with increased vascular risk and brain volume changes in multiple sclerosis (MS). To date, findings have not been consistent with respect to which comorbidities are associated with lower brain volumes or whether comorbidities associated with increased vascular risk are associated with greater brain volume loss over time. Objectives We aimed to evaluate the association between the Framingham Risk Score (FRS) which evaluates vascular risk and normalized whole brain volume in MS. Methods We included 98 participants with MS who underwent two brain MRIs two years apart, from which whole brain volumes were calculated. Each participant reported their comorbidities and medications taken. Blood pressure, height and weight were recorded and we calculated the FRS. We tested the association between the FRS at baseline and brain volume at the second time point using quantile regression adjusting for baseline normalized brain volume, age, gender and use of disease-modifying therapy. Results As the FRS increased, brain volume was lower, both at enrollment (β= -0.24; 95%CI: -0.42, -0.04) and at follow-up (-0.27; 95%CI: -0.45, -0.08). After further adjustment for age, gender, and use of disease modifying therapy, higher FRS remained associated with lower brain volume at follow-up at the 90th percentile of brain volume (β= -2.22; 95%CI: -3.40, -1.04) but not at the 10th or 50th percentiles. Conclusion Higher FRS were associated with lower brain volumes in persons with MS at baseline, and with brain volume loss over time. This effect was most pronounced for persons with higher brain volumes at baseline, which suggests that prevention, detection and effective management of comorbidities associated with vascular risk in people with MS is particularly important early in the disease course.

The authors prospectively studied patients with motor deficits secondary to primary intracerebral hemorrhage within the first 12 hours of symptom onset. Patients underwent multimodal MR imaging including DTI. Intracerebral hemorrhage, perihematomal edema location and volume, and corticospinal tract involvement were assessed. The corticospinal tract was considered affected when the tractogram passed through the intracerebral hemorrhage and/or the perihematomal edema. The authors calculated affected corticospinal tract-to-unaffected corticospinal tract ratios for fractional anisotropy, mean diffusivity, and axial and radial diffusivities. Significant independent predictors of motor outcome were NIHSS and modified NIHSS at admission, posterior limb of the internal capsule involvement by intracerebral hemorrhage at admission, intracerebral hemorrhage volume at admission, 72-hour NIHSS, and 72-hour modified NIHSS. The sensitivity, specificity, and positive and negative predictive values for poor motor outcome at 3 months by a combined modified NIHSS of >6 and posterior limb of the internal capsule involvement in the first 12 hours from symptom onset were 84%, 79%, 65%, and 92%, respectively. BACKGROUND AND PURPOSE: Predicting motor outcome following intracerebral hemorrhage is challenging. We tested whether the combination of clinical scores and DTI-based assessment of corticospinal tract damage within the first 12 hours of symptom onset after intracerebral hemorrhage predicts motor outcome at 3 months. MATERIALS AND METHODS: We prospectively studied patients with motor deficits secondary to primary intracerebral hemorrhage within the first 12 hours of symptom onset. Patients underwent multimodal MR imaging including DTI. We assessed intracerebral hemorrhage and perihematomal edema location and volume, and corticospinal tract involvement. The corticospinal tract was considered affected when the tractogram passed through the intracerebral hemorrhage or/and the perihematomal edema. We also calculated affected corticospinal tract-to-unaffected corticospinal tract ratios for fractional anisotropy, mean diffusivity, and axial and radial diffusivities. Motor impairment was graded by the motor subindex scores of the modified NIHSS. Motor outcome at 3 months was classified as good (modified NIHSS 0-3) or poor (modified NIHSS 4-8). RESULTS: Of 62 patients, 43 were included. At admission, the median NIHSS score was 13 (interquartile range = 8-17), and the median modified NIHSS score was 5 (interquartile range = 2-8). At 3 months, 13 (30.23%) had poor motor outcome. Significant independent predictors of motor outcome were NIHSS and modified NIHSS at admission, posterior limb of the internal capsule involvement by intracerebral hemorrhage at admission, intracerebral hemorrhage volume at admission, 72-hour NIHSS, and 72-hour modified NIHSS. The sensitivity, specificity, and positive and negative predictive values for poor motor outcome at 3 months by a combined modified NIHSS of >6 and posterior limb of the internal capsule involvement in the first 12 hours from symptom onset were 84%, 79%, 65%, and 92%, respectively (area under the curve = 0.89; 95% CI, 0.78-1). CONCLUSIONS: Combined assessment of motor function and posterior limb of the internal capsule damage during acute intracerebral hemorrhage accurately predicts motor outcome.

With larger data sets and more sophisticated analyses, it is becoming increasingly common for neuroimaging researchers to push (or exceed) the limitations of standalone computer workstations. Nonetheless, although high-performance computing platforms such as clusters, grids and clouds are already in routine use by a small handful of neuroimaging researchers to increase their storage and/or computational power, the adoption of such resources by the broader neuroimaging community remains relatively uncommon. Therefore, the goal of the current manuscript is to: 1) inform prospective users about the similarities and differences between computing clusters, grids and clouds; 2) highlight their main advantages; 3) discuss when it may (and may not) be advisable to use them; 4) review some of their potential problems and barriers to access; and finally 5) give a few practical suggestions for how interested new users can start analyzing their neuroimaging data using cloud resources. Although the aim of cloud computing is to hide most of the complexity of the infrastructure management from end-users, we recognize that this can still be an intimidating area for cognitive neuroscientists, psychologists, neurologists, radiologists, and other neuroimaging researchers lacking a strong computational background. Therefore, with this in mind, we have aimed to provide a basic introduction to cloud computing in general (including some of the basic terminology, computer architectures, infrastructure and service models, etc.), a practical overview of the benefits and drawbacks, and a specific focus on how cloud resources can be used for various neuroimaging applications.

Using functional magnetic resonance imaging, the authors aimed to determine the roles of the human spinal cord in mediating sexual responses in women. Functional magnetic resonance imaging of the entire lower thoracic, lumbar, and sacral spinal cord was performed using a sexual stimulation paradigm designed to elicit psychological and physical components of sexual arousal. Responses were measured in 9 healthy adult women during 3 consecutive conditions: (a) erotic audiovisual, (b) manual clitoral, and (c) audiovisual plus manual stimulation. Functional magnetic resonance imaging results in healthy subjects demonstrate that this method is sensitive for mapping sexual function in the spinal cord, and identify several key regions involved in human sexual response, including the intermediolateral cell column, the dorsal commissural nucleus, and the sacral parasympathetic nucleus. Using spinal functional magnetic resonance imaging, this study identified many of the spinal cord regions involved in female sexual responses. Results from audiovisual and manual clitoral stimulation correspond with previous data regarding lumbar and sacral neurologic changes during sexual arousal. This study provides the first characterization of neural activity in the human spinal cord underlying healthy female sexual responses and sets a foundation for future studies aimed at mapping changes that result from sexual dysfunction, spinal cord trauma or disease.

Tissue contrast can be enhanced by dividing T

Background: Recent studies utilizing perfusion as a surrogate of cortical integrity show promise for overall cognition, but the association between white matter (WM) damage and gray matter (GM) integrity in specific functional networks is not previously studied. Objective: To investigate the relationship between WM fiber integrity and GM node perfusion within six functional networks of relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS) patients. Methods: Magnetic resonance imaging (MRI) and neurocognitive testing were performed on 19 healthy controls (HC), 39 RRMS, and 45 SPMS patients. WM damage extent and severity were quantified with T2-hyper/T1-hypointense (T2h/T1h) lesion volume and degree of perfusion reduction in lesional and normal-appearing white matter (NAWM), respectively. A two-step linear regression corrected for confounders was employed. Results: Cognitive impairment was present in 20/39 (51%) RRMS and 25/45 (53%) SPMS patients. GM node perfusion was associated with WM fiber damage severity (WM hypoperfusion) within each network—including both NAWM ( R2 = 0.67–0.89, p < 0.0001) and T2h ( R2 = 0.39–0.62, p < 0.0001) WM regions—but was not significantly associated ( p > 0.01) with WM fiber damage extent (i.e. T2h/T1h lesion volumes). Conclusion: Overall, GM node perfusion was associated with severity rather than extent of WM network damage, supporting a primary etiology of GM hypoperfusion.

The objective of this study was to assess the feasibility of the use of functional magnetic resonance imaging (fMRI) to evaluate the spinal activation during sexual response of the thoracic, lumbar and sacral spinal cord. This is a laboratory-based pilot study in human females at a University-based medical center in the United States. In three healthy spinal cord injury (SCI) females, spinal cord activations during sexual audiovisual stimulation (alone), genital self-stimulation (alone) and simultaneous audiovisual and genital self-stimulation (combined) were assessed and then compared with each subjects’ remaining sensory and motor function. Spinal fMRI responses of the intermediolateral columns were found during audiovisual stimulation in both subjects with incomplete injuries, but they were not observed in the subject with a complete injury. Moreover, sacral responses to combined stimulation differed greatly between the subjects with complete and incomplete injuries. These results not only provide the first in vivo documentation of spinal fMRI responses associated with sexual arousal in women with SCIs, but also suggest that spinal cord fMRI is capable of distinguishing between injury subtypes. Therefore, although there are certain limitations associated with fMRI during sexual stimulation (for example, movement artifacts, an artificially controlled environment and so), these findings demonstrate the potential utility of incorporating spinal cord fMRI in future research to evaluate the impact of specific patterns of SCI on sexual responses and/or the effects of treatment.

It is well established that obesity decreases overall life expectancy and increases the risk of several adverse health conditions. Mounting evidence indicates that body fat is likely also associated with structural and functional brain changes, reduced cognitive function, and greater impulsivity. However, previously reported differences in brain structure and function have been variable across studies and difficult to reconcile due to sample population and methodological differences. To clarify these issues, we correlated two independent measures of body composition – i.e., body mass index (BMI) and body fat percent (BFP) – with structural and functional neuroimaging data obtained from a cohort of 32 neurologically healthy adults. Whole-brain voxel-wise analyses indicated that higher BMI and BFP were associated with widespread decreases in gray matter volume, white matter volume, and white matter microstructure (including several regions, such as the striatum and orbitofrontal cortex, which may influence value assessment, habit formation, and decision-making). Moreover, closer examination of resting state functional connectivity, white matter volume, and white matter microstructure throughout the default mode network (DMN), executive control network (ECN), and salience network (SN) revealed that higher BMI and BFP were associated with increased SN functional connectivity and decreased white matter volumes throughout all three networks (i.e., the DMN, ECN, and SN). Taken together, these findings: 1) offer a biologically plausible explanation for reduced cognitive performance, greater impulsivity, and altered reward processing among overweight individuals, and 2) suggest neurobiological mechanisms (i.e., altered functional and structural brain connectivity) that may affect overweight individuals’ ability to establish and maintain healthy lifestyle choices.

The purpose of this study was to determine whether spinal cord functional magnetic resonance imaging could be used to map neural activity throughout the lower thoracic, lumbar, and sacral spinal cord regions during sexual arousal in healthy men. The authors found that viewing erotic films and genital self-stimulation elicited predominantly increased signal, indicative of amplified neuronal input to the dorsal and ventral horns and in the autonomic preganglionic nuclei of the lower thoracic, lumbar, and sacral spinal cord. In addition, linear regression analyses revealed a number of robust correlations (|R| ≥ 0.7) between signal intensity changes in these spinal cord regions and self-reported ratings of mental and physical sexual arousal. Taken together, these results demonstrate that spinal cord functional magnetic resonance imaging is an effective and sensitive technique for mapping the neural correlates of sexual arousal in the spinal cords of able-bodied men. Most important, the results from this study indicate that spinal cord functional magnetic resonance imaging may have important applications as a clinical tool for assessing and mapping the changes that occur in the spinal cords of men suffering from sexual dysfunction as a result of spinal cord trauma.

Although event-related fMRI is able to reliably detect brief changes in brain activity and is now widely used throughout systems and cognitive neuroscience, there have been no previous reports of event-related spinal cord fMRI. This is likely attributable to the various technical challenges associated with spinal fMRI (e.g., imaging a suitable length of the cord, reducing image artifacts from the vertebrae and intervertebral discs, and dealing with physiological noise from spinal cord motion). However, with many of these issues now resolved, the largest remaining impediment for event-related spinal fMRI is a deprived understanding of the spinal cord fMRI signal time course. Therefore, in this study, we used a proton density-weighted HASTE sequence, with functional contrast based on signal enhancement by extravascular water protons (SEEP), and a motion-compensating GLM analysis to (i) characterize the SEEP response function in the human cervical spinal cord and (ii) demonstrate the feasibility of event-related spinal fMRI. This was achieved by applying very brief (1 s) epochs of 22°C thermal stimulation to the palm of the hand and measuring the impulse response function. Our results suggest that the spinal cord SEEP response (time to peak ≈8 s; FWHM ≈4 s; and probably lacking pre- and poststimulus undershoots) is slower than previous estimates of SEEP or BOLD responses in the brain, but faster than previously reported spinal cord BOLD responses. Finally, by detecting and mapping consistent signal-intensity changes within and across subjects, and validating these regions with a block-designed experiment, this study represents the first successful demonstration of event-related spinal fMRI.

Data acquired with functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) are often interpreted in terms of the underlying neuronal activity, despite mounting evidence that these signals do not always correlate with electrophysiological recordings. Therefore, considering the increasing popularity of functional neuroimaging, it is clear that a more comprehensive theory is needed to reconcile these apparent disparities and more accurately explain the mechanisms through which various PET and fMRI signals arise. In the present article, we have turned our attention to astrocytes, which vastly outnumber neurons and are known to serve a number of functions throughout the central nervous system (CNS). For example, astrocytes are known to be critically involved in neurotransmitter uptake and recycling, and empirical data suggests that brain activation increases both oxidative and glycolytic astrocyte metabolism. Furthermore, a number of recent studies imply that astrocytes are likely to play a key role in regulating cerebral blood delivery. Therefore, we propose that, by mediating neurometabolic and neurovascular processes throughout the CNS, astrocytes could provide a common physiological basis for fMRI and PET signals. Such a theory has significant implications for the interpretation of functional neuroimaging signals, because astrocytic changes reflect subthreshold neuronal activity, simultaneous excitatory/inhibitory synaptic inputs, and other transient metabolic demands that may not elicit electrophysiological changes. It also suggests that fMRI and PET signals may have inherently less sensitivity to decreases in synaptic input (i.e. 'negative activity') and/or inhibitory (GABAergic) neurotransmission.

Given the growing popularity of T1 -weighted/T2 -weighted (T1 w/T2 w) ratio measurements, the objective of the current study was to evaluate the concordance between T1 w/T2 w ratios obtained using conventional fast spin echo (FSE) versus combined gradient and spin echo (GRASE) sequences for T2 w image acquisition, and to compare the resulting T1 w/T2 w ratios with histologically validated myelin water fraction (MWF) measurements in several subcortical brain structures. In order to compare these measurements across a relatively wide range of myelin concentrations, whole-brain T1 w magnetization prepared rapid acquisition gradient echo (MPRAGE), T2 w FSE and three-dimensional multi-echo GRASE data were acquired from 10 participants with multiple sclerosis at 3 T. Then, after high-dimensional, non-linear warping, region of interest (ROI) analyses were performed to compare T1 w/T2 w ratios and MWF estimates (across participants and brain regions) in 11 bilateral white matter (WM) and four bilateral subcortical grey matter (SGM) structures extracted from the JHU_MNI_SS 'Eve' atlas. Although the GRASE sequence systematically underestimated T1 w/T2 w values compared to the FSE sequence (revealed by Bland-Altman and mountain plots), linear regressions across participants and ROIs revealed consistently high correlations between the two methods (r2 = 0.62 for all ROIs, r2 = 0.62 for WM structures and r2 = 0.73 for SGM structures). However, correlations between either FSE-based or GRASE-based T1 w/T2 w ratios and MWFs were extremely low in WM structures (FSE-based, r2 = 0.000020; GRASE-based, r2 = 0.0014), low across all ROIs (FSE-based, r2 = 0.053; GRASE-based, r2 = 0.029) and moderate in SGM structures (FSE-based, r2 = 0.20; GRASE-based, r2 = 0.17). Overall, our findings indicated a high degree of correlation (but not equivalence) between FSE-based and GRASE-based T1 w/T2 w ratios, and low correlations between T1 w/T2 w ratios and MWFs. This suggests that the two T1 w/T2 w ratio approaches measure similar facets of subcortical tissue microstructure, whereas T1 w/T2 w ratios and MWFs appear to be sensitized to different microstructural properties. On this basis, we conclude that multi-echo GRASE sequences can be used in future studies to efficiently elucidate both general (T1 w/T2 w ratio) and myelin-specific (MWF) tissue characteristics.

BACKGROUND AND PURPOSE: Recent literature indicates that cervical and upper-thoracic spinal cord motion adversely affect both structural and functional MR imaging (fMRI; particularly diffusion tensor imaging [DTI] and spinal fMRI), ultimately reducing the reliability of these methods for both research and clinical applications. In the present study, we investigated motion of the lower-thoracic, lumbar, and sacral cord segments to evaluate the incidence of similar motion-related confounds in these regions. MATERIALS AND METHODS: Recently developed methods, used previously for measuring cervical and upper-thoracic spinal cord motion, were employed in the present study to examine anteroposterior (A/P) and left-right (L/R) spinal cord motion in caudal regions. Segmented cinematic imaging was applied with a gradient-echo, turbo fast low-angle shot (turbo-FLASH) pulse sequence to acquire midline images of the cord at 24 cardiac phases throughout the lower-thoracic, lumbar, and sacral spinal cord regions. RESULTS: The magnitude of A/P motion was found to be largest in rostral cord regions, whereas in caudal regions (at the level of the T4/T5 vertebrae and below), peak cord motion was uniformly small (routinely ≤0.10 mm). L/R motion, however, was found to be minimal throughout the thoracic, lumbar, and sacral regions. CONCLUSION: Motion-related errors in spinal fMRI and DTI are expected to be significantly reduced throughout caudal regions of the spinal cord, thus yielding higher sensitivity and specificity compared with rostral regions. The paucity of such errors is expected to provide a means of observing the specific impact of motion (in rostral regions) and to enable the acquisition of uncorrupted DTI and fMRI data for studies of structure and function throughout lumbar and sacral regions.

Spinal cord (SC) motion is thought to be the dominant source of error in current diffusion and spinal functional MRI (fMRI) methods. However, until now, such motion has not been well characterized in three dimensions. While previous studies have predominantly examined motion in the superior/inferior (S/I) direction, the foci of the present study were the anterior/posterior (A/P) and right/left (R/L) components of human cervical and upper thoracic SC motion. Cardiac-gated, turbofast low-angle shot (turbo-FLASH) cinematic MRI was employed at 3T to acquire images of the cord at 24 phases throughout the cardiac cycle. Time-dependent signal fluctuations within voxels adjacent to the cord/cerebrospinal fluid (CSF) interface were then used to measure SC motion, which was found to occur predictably as a function of cardiac activity. Cord movement was largest in the A/P direction, for which principal components of motion were calculated, thereby indicating consistent patterns of SC oscillation that can potentially be used to improve SC imaging. Magn Reson Med 58:185–189, 2007. © 2007 Wiley-Liss, Inc.

Lactate is the metabolic byproduct of glycolysis, a process that, despite being less efficient than the complete oxidation of glucose to carbon dioxide and water, occurs throughout the brain. Glycolytic metabolism increases dramatically in response to ischemic events, but even during periods of

Data acquired with functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) are often interpreted in terms of the underlying neuronal activity, despite mounting evidence that these signals do not always correlate with electrophysiological recordings. Therefore, considering the increasing popularity of functional neuroimaging, it is clear that a more comprehensive theory is needed to reconcile these apparent disparities and more accurately explain the mechanisms through which various PET and fMRI signals arise. In the present article, we have turned our attention to astrocytes, which vastly outnumber neurons and are known to serve a number of functions throughout the central nervous system (CNS). For example, astrocytes are known to be critically involved in neurotransmitter uptake and recycling, and empirical data suggests that brain activation increases both oxidative and glycolytic astrocyte metabolism. Furthermore, a number of recent studies imply that astrocytes are likely to play a key role in regulating cerebral blood delivery. Therefore, we propose that, by mediating neurometabolic and neurovascular processes throughout the CNS, astrocytes could provide a common physiological basis for fMRI and PET signals. Such a theory has significant implications for the interpretation of functional neuroimaging signals, because astrocytic changes reflect subthreshold neuronal activity, simultaneous excitatory/inhibitory synaptic inputs, and other transient metabolic demands that may not elicit electrophysiological changes. It also suggests that fMRI and PET signals may have inherently less sensitivity to decreases in synaptic input (i.e. 'negative activity') and/or inhibitory (GABAergic) neurotransmission.

Functional magnetic resonance imaging of the spinal cord (spinal fMRI) has facilitated the noninvasive visualization of neural activity in the spinal cord (SC) and brainstem of both animals and humans. This technique has yet to gain the widespread usage of brain fMRI, due in part to the intrinsic technical challenges spinal fMRI presents and to the narrower scope of applications it fulfills. Nonetheless, methodological progress has been considerable and rapid. To date, spinal fMRI studies have investigated SC function during sensory or motor task paradigms in spinal cord injury (SCI), multiple sclerosis (MS) and neuropathic pain (NP) patient populations, all of which have yielded consistent and sensitive results. The most recent study in our laboratory has successfully used spinal fMRI to examine cervical SC activity in a SCI patient with a metallic fixation device spanning the C(4) to C(6) vertebrae, a critical step in realizing the clinical utility of the technique. The literature reviewed in this article suggests that spinal fMRI is poised for usage in a wide range of patient populations, as multiple groups have observed intriguing, yet consistent, results using standard, readily available MR systems and hardware. The next step is the implementation of this technique in the clinic to supplement standard qualitative behavioral assessments of SCI. Spinal fMRI may offer insight into the subtleties of function in the injured and diseased SC, and support the development of new methods for treatment and monitoring.

Functional magnetic resonance imaging (fMRI) of the cortex is a powerful tool for neuroscience research, and its use has been extended into the brainstem and spinal cord as well. However, there are significant technical challenges with extrapolating the developments that have been achieved in the cortex to their use in the brainstem and spinal cord. Here, we develop a normalized coordinate system for the cervical spinal cord and brainstem, demonstrating a semiautomated method for spatially normalizing and coregistering fMRI data from these regions. fMRI data from 24 experiments in eight volunteers are normalized and combined to create the first anatomical reference volume, and based on this volume, we define a standardized region-of-interest (ROI) mask, as well as a map of 52 anatomical regions, which can be applied automatically to fMRI results. The normalization is demonstrated to have an accuracy of less than 2 mm in 93% of anatomical test points. The reverse of the normalization procedure is also demonstrated for automatic alignment of the standardized ROI mask and region-label map with fMRI data in its original (unnormalized) format. A reliable method for spatially normalizing fMRI data is essential for analyses of group data and for assessing the effects of spinal cord injury or disease on an individual basis by comparing with results from healthy subjects.