Gray Matter Voxels Research Articles

Displacement behaviors in chimpanzees (Pan troglodytes): A neurogenomics investigation of the RDoC Negative Valence Systems domain.

The current study aimed to systematically investigate genetic and neuroanatomical correlates of individual variation in scratching behaviors, a well-validated animal-behavioral indicator of negative emotional states with clear links to the NIMH Research Domain Criteria (RDoC) response to potential harm ("anxiety") construct within the Negative Valence Systems domain. Utilizing data from a sample of 76 captive chimpanzees (Pan troglodytes), we (a) examined the association between scratching and presence or absence of the RS3-containing DupB element in the AVPR1A 5' flanking region, (b) utilized voxel-based morphometry (VBM) to identify gray matter (GM) voxel clusters that differentiated AVPR1A genotype, and (c) conducted a VBM-guided voxel-of-interest analysis to examine the association between GM intensity and scratching. AVPR1A evidenced sexually dimorphic associations with scratching. VBM analyses revealed significant differences in GM by genotype across twelve clusters largely in the frontal cortex. Regions differentiating AVPR1A genotype showed sex-specific associations with scratching. Results suggest that sexually dimorphic associations between AVPR1A and scratching may be explained by genotype-specific neuroanatomical variation. The current study provides an example of the way in which chimpanzee research is uniquely poised for multilevel, systematic investigations of psychopathology-relevant constructs within the context of the RDoC framework.

Brain region ranking for 18FDG-PET computer-aided diagnosis of Alzheimer's disease

Abstract Positron emission tomography (PET) is a functional molecular imaging, which helps to diagnose neurodegenerative diseases, such as Alzheimer's disease (AD), by evaluating cerebral metabolic rate of glucose after administration of (18)F-fluoro-deoxy-glucose ((18)FDG). A quantitative evaluation, using computer aided methods, is of importance to improve medical care. In this paper a novel ranking method of the effectiveness of brain region of interest to classify healthy and AD brain is developed. Brain images are first segmented into 116 regions according to an anatomical atlas. A spatial normalization and four gray level normalization methods are used for comparison. Each extracted region is then characterized by a feature set based on gray level histogram moments, as well as age and gender of a subject. Using a receiver operating characteristic curve for each region, it was possible to define a Separating Power Factor (SPF) to rank region's ability to separate healthy from AD brain images. Using a set of selected regions, according to their rank, and when inputting them to a support vector machine classifier, it was possible to show that classification results were similar or slightly better than those obtained when using the whole gray matter voxels of the brain or the 116 regions as input features to the classifier. Computational time was reduced compared to the other methods to which our approach was compared.

Altered Structural Correlates of Impulsivity in Adolescents with Internet Gaming Disorder.

Recent studies suggested that internet gaming disorder (IGD) was associated with impulsivity and structural abnormalities in brain gray matter (GM). However, no morphometric study has examined the association between GM and impulsivity in IGD individuals. In this study, 25 adolescents with IGD and 27 healthy controls (HCs) were recruited, and the relationship between Barratt impulsiveness scale-11 (BIS) score and gray matter volume (GMV) was investigated with the voxel-based morphometric (VBM) correlation analysis. Then, the intergroup differences in correlation between BIS score and GMV were tested across all GM voxels. Our results showed that the correlations between BIS score and GMV of the right dorsomedial prefrontal cortex (dmPFC), the bilateral insula and the orbitofrontal cortex (OFC), the right amygdala and the left fusiform gyrus decreased in the IGD group compared to the HCs. Region-of-interest (ROI) analysis revealed that GMV in all these clusters showed significant positive correlations with BIS score in the HCs, while no significant correlation was found in the IGD group. Our findings demonstrated that dysfunction of these brain areas involved in the behavior inhibition, attention and emotion regulation might contribute to impulse control problems in IGD adolescents.

Resting-state functional connectivity abnormalities correlate with psychometric hepatic encephalopathy score in cirrhosis

Background & aimsNeurocognitive impairment is a common complication of cirrhosis and regarded as the important characteristic for early stage of hepatic encephalopathy (HE). This study aimed to investigate the changes in brain network centrality of functional connectivity among cirrhotic patients and uncover the mechanisms about early HE. MethodsTwenty-four cirrhotic patients without overt HE and 21 healthy controls were enrolled and underwent resting-state fMRI and Psychometric Hepatic Encephalopathy Score (PHES) tests. Whole-brain functional network was constructed by measuring the temporal correlations of every pairs of brain gray matter voxels; and then voxel-wise degree centrality (DC), an index reflecting importance of a node in functional integration, was calculated and compared between two groups. A seed-based resting-state functional connectivity (RSFC) analysis was further performed to investigate abnormal functional connectivity pattern of those regions with changed DC. ResultsCompared with controls, the cirrhotic patients had worse performances in all neurocognitive tests and lower PHES score. Meanwhile, patients showed decreased DC in bilateral medial prefrontal gyrus and anterior cingulate cortex, left middle frontal gyrus, and bilateral thalamus; while increased DC in right middle occipital gyrus and parahippocampal gyrus/inferior temporal gyrus. The seed-based RSFC analyses revealed that the relevant functional networks, such as default-mode and attention networks, visual network, and thalamo-cortical circuits, were disturbed in cirrhotic patients. The DC changes were correlated with PHES score in patient group. ConclusionsOur findings further confirm brain network disorganization in cirrhotic patients with neurocognitive impairments and may provide a new perspective for understanding HE-related mechanisms.

Relationship between simultaneously acquired resting-state regional cerebral glucose metabolism and functional MRI: A PET/MR hybrid scanner study

Recently introduced hybrid PET/MR scanners provide the opportunity to measure simultaneously, and in direct spatial correspondence, both metabolic demand and functional activity of the brain, hence capturing complementary information on the brain's physiological state. Here we exploited PET/MR simultaneous imaging to explore the relationship between the metabolic information provided by resting-state fluorodeoxyglucose-PET (FDG-PET) and fMRI (rs-fMRI) in neurologically healthy subjects.Regional homogeneity (ReHo), fractional amplitude of low frequency fluctuations (fALFF), and degree of centrality (DC) maps were generated from the rs-fMRI data in 23 subjects, and voxel-wise comparison to glucose uptake distribution provided by simultaneously acquired FDG-PET was performed. The mutual relationships among each couple of these four metrics were explored in terms of similarity, both of spatial distribution across the brain and the whole group, and voxel-wise across subjects, taking into account partial volume effects by adjusting for grey matter (GM) volume. Although a significant correlation between the spatial distribution of glucose uptake and rs-fMRI derived metrics was present, only a limited percentage of GM voxels correlated with PET across subjects. Moreover, the correlation between the spatial distributions of PET and rs-fMRI-derived metrics is spatially heterogeneous across both anatomic regions and functional networks, with lowest correlation strength in the limbic network (Spearman rho around −0.11 for DC), and strongest correlation for the default-mode network (up to 0.89 for ReHo and 0.86 for fALFF). Overall, ReHo and fALFF provided significantly higher correlation coefficients with PET (p=10−8 and 10−7, respectively) as compared to DC, while no significant differences were present between ReHo and fALFF. Local GM volume variations introduced a limited overestimation of the rs-fMRI to FDG correlation between the modalities under investigation through partial volume effects.These novel results provide the basis for future studies of alterations of the coupling between brain metabolism and functional connectivity in pathologic conditions.

Reproducibility of phase rotation stimulated echo acquisition mode at 3T in schizophrenia: Emphasis on glutamine.

To determine the reproducibility and reliability of glutamine (Gln), measured with a very short echo time phase rotation stimulated echo acquisition mode (VTE-PR STEAM) sequence at 3T, in subjects with schizophrenia. Seven subjects with schizophrenia were scanned twice with VTE-PR STEAM in a Siemens 3T TIM Trio scanner with a 32-channel head coil. Spectroscopic data were collected from two voxels in gray matter, one in the dorsal anterior cingulate and the other in the medial occipital cortex. Reproducibility was assessed using coefficients of variation (CVs) and reliability with standard error of measurement and intraclass correlations (ICCs). Phantoms containing increasing concentrations of Gln in a physiologic solution of other neurometabolites with overlapping resonances were scanned to assess the validity of spectral Gln measurement. Very good reliability and reproducibility for Gln in both regions of interest were supported by CVs of ≤10.0% and ICCs of ≥0.6, respectively. Phantom studies documented a robust correspondence between known Gln concentrations and VTE-PR STEAM measurements of this metabolite (R(2) = 0.988). The VTE-PR STEAM approach at 3T permits the longitudinal assessment of Gln and other (1) H MR spectroscopy neurometabolites in a clinically plausible setting.

Reduced Age-related Gray Matter Atrophy in Long-term Meditators within the Medial Occipital Lobe

Event Abstract Back to Event Reduced Age-related Gray Matter Atrophy in Long-term Meditators within the Medial Occipital Lobe Eileen Luders1* and Florian Kurth1 1 University of California, Los Angeles (UCLA), Neurology, United States Life expectancy around the world has risen dramatically, with more than ten years of life gained since 1970. After the age of forty, however, the human brain decreases by approximately five percent every decade. Thus, techniques that can diminish the negative impact of aging on the brain are desirable, especially if they are easily accessible, as well as cost and time efficient. The practice of meditation meets these criteria but studies exploring the brain-preserving effects of meditation are still sparse. To further expand this field of research, we examined the link between age and cerebral gray matter in a large sample of 50 long-term meditators and 50 control subjects. Both groups were matched for sex (28 M / 22 F) and for age (mean±SD: 51±12 years), which ranged from 24 to 77 years. Meditation experience ranged between 4 and 46 years (mean±SD: 19.8±11.4 years). T1-weighted images were processed using SPM8 and the VBM8 toolbox. This resulted in normalized, modulated, and smoothed gray matter segments. First, we tested for significant group-by-age interactions at thousands of gray matter voxels, while statistically correcting for multiple comparisons. Then, we extracted the gray matter from the significance cluster and calculated the age-related correlations separately within meditators and controls. We observed a significant group-by-age interaction in the right medial occipital lobe, spanning the anterior lingual gyrus. Correlating the resulting cluster-specific gray matter with age, we detected negative correlations in both groups, suggesting less gray matter in older subjects. However, the slopes of the regression lines were steeper in controls than in meditators. In addition, the negative link between age and gray matter was stronger in controls (r=-0.56; p<0.001) than in meditators (r=-0.14; p=0.32). These findings suggest less age-related gray matter atrophy within the aforementioned cluster of the medial occipital lobe in meditation practitioners. Keywords: Aging, Meditation, mindfulness, structural MRI, gray matter Conference: XII International Conference on Cognitive Neuroscience (ICON-XII), Brisbane, Queensland, Australia, 27 Jul - 31 Jul, 2014. Presentation Type: Poster Topic: Attention Citation: Luders E and Kurth F (2015). Reduced Age-related Gray Matter Atrophy in Long-term Meditators within the Medial Occipital Lobe. Conference Abstract: XII International Conference on Cognitive Neuroscience (ICON-XII). doi: 10.3389/conf.fnhum.2015.217.00304 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Feb 2015; Published Online: 24 Apr 2015. * Correspondence: Prof. Eileen Luders, University of California, Los Angeles (UCLA), Neurology, Los Angeles, United States, eileen.luders@ucla.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Eileen Luders Florian Kurth Google Eileen Luders Florian Kurth Google Scholar Eileen Luders Florian Kurth PubMed Eileen Luders Florian Kurth Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Contrast enhancement by combining T1- and T2-weighted structural brain MR Images.

In order to more precisely differentiate cerebral structures in neuroimaging studies, a novel technique for enhancing the tissue contrast based on a combination of T1-weighted (T1w) and T2-weighted (T2w) MRI images was developed. The combined image (CI) was calculated as CI = (T1w - sT2w)/(T1w + sT2w), where sT2w is the scaled T2-weighted image. The scaling factor was calculated to adjust the gray- matter (GM) voxel intensities in the T2w image so that their median value equaled that of the GM voxel intensities in the T1w image. The image intensity homogeneity within a tissue and the discriminability between tissues in the CI versus the separate T1w and T2w images were evaluated using the segmentation by the FMRIB Software Library (FSL) and FreeSurfer (Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital, Boston, MA) software. The combined image significantly improved homogeneity in the white matter (WM) and GM compared to the T1w images alone. The discriminability between WM and GM also improved significantly by applying the CI approach. Significant enhancements to the homogeneity and discriminability also were achieved in most subcortical nuclei tested, with the exception of the amygdala and the thalamus. The tissue discriminability enhancement offered by the CI potentially enables more accurate neuromorphometric analyses of brain structures.

P.1.c.007 Fronto–striatal glutamate in compulsive and impulsive syndromes: a review of MR spectroscopy studies

Chronic, heavy alcohol consumption may affect the concentration of neurometabolites assessed with proton magnetic resonance spectroscopy (1H-MRS). We investigated the largest sample reported to date (N=213) with the primary goal of determining how specific clinical features impact neurometabolite concentrations in an anterior cingulate gray matter voxel. This community-dwelling sample included both treatment-seeking and non-treatment-seeking individuals. A healthy control group (N=66) was matched for age and education. In multivariate analyses predicting neurometabolite concentrations, the heavy drinking group had greater concentrations overall. An age by group interaction was noted, as group difference across neurometabolites increased with age. More years drinking, but not more drinks per drinking day (DPDD), predicted greater concentrations of choline-containing compounds (Cho), creatine-phosphocreatine (Cre), glutamate–glutamine (Glx), and N-acetyl-aspartate (NAA). The effects of other clinical variables (depression, cigarette smoking, marijuana use) were negligible. After controlling for DPDD and years drinking, treatment-seeking status had no impact on neurometabolites. In the very oldest portion of the sample (mean age=50), however, a negative relationship was seen between NAA and years drinking. These results suggest that the nature of neurometabolite abnormalities in chronic heavy drinkers may vary as a function of duration of abuse.

Morphometric differences in planum temporale in schizophrenia and bipolar disorder revealed by statistical analysis of labeled cortical depth maps.

Differences in cortical thickness in the lateral temporal lobe, including the planum temporale (PT), have been reported in MRI studies of schizophrenia (SCZ) and bipolar disorder (BPD) patients. Most of these studies have used a single-valued global or local measure for thickness. However, additional and complementary information can be obtained by generating labeled cortical distance maps (LCDMs), which are distances of labeled gray matter (GM) voxels from the nearest point on the GM/white matter (WM) (inner) cortical surface. Statistical analyses of pooled and censored LCDM distances reveal subtle differences in PT between SCZ and BPD groups from data generated by Ratnanather et al. (Schizophrenia Research, http://dx.doi.org/10.1016/j.schres.2013.08.014). These results confirm that the left planum temporale (LPT) is more sensitive than the right PT in distinguishing between SCZ, BPD, and healthy controls. Also confirmed is a strong gender effect, with a thicker PT seen in males than in females. The differences between groups at smaller distances in the LPT revealed by pooled and censored LCDM analysis suggest that SCZ and BPD have different effects on the cortical mantle close to the GM/WM surface. This is consistent with reported subtle changes in the cortical mantle observed in post-mortem studies.

Early metabolic development of posteromedial cortex and thalamus in humans analyzed via in vivo quantitative magnetic resonance spectroscopy.

The posteromedial cortex (PMC) including the posterior cingulate, retrosplenial cortex, and medial parietal cortex/precuneus is an epicenter of cortical interactions in a wide spectrum of neural activity. Anatomic connections between PMC and thalamic components have been established in animal studies, but similar studies do not exist for the fetal and neonatal period. Magnetic resonance spectroscopy (MRS) allows for noninvasive measurement of metabolites in early development. Using single-voxel 3-T MRS, healthy term neonates (n = 31, mean postconception age 41.5 weeks ± 3.8 weeks) were compared with control children (n = 23, mean age 9.4 years ± 5.1 years) and young adults (n = 10, mean age 24.1 years ± 2.6 years). LCModel-based calculations compared metabolites within medial parietal gray matter (colocalizing to the PMC), posterior thalamus, and parietal white matter voxels. Common metabolic changes existed for neuronal-axonal maturation and structural markers in the PMC, thalamus, and parietal white matter with increasing NAA and glutamate and decreasing myoinositol and choline with age. Key differences in creatine and glucose metabolism were noted in the PMC, in contrast to the thalamic and parietal white matter locations, suggesting a unique role of energy metabolism. Significant parallel metabolite developmental changes of multiple other metabolites including aspartate, glutamine, and glutathione with age were present between PMC and parietal white matter but not between PMC and thalamus. These findings offer insight into the metabolic architecture of the interface between structural and functional topology of brain networks. Further investigation unifying metabolic changes with functional and anatomic pathways may further enhance the understanding of the PMC in posterior default mode network development.

Voxel-based comparison of state-of-the-art reconstruction algorithms for 18F-FDG PET brain imaging using simulated and clinical data

The resolution of a PET scanner (2.5–4.5mm for brain imaging) is similar to the thickness of the cortex in the (human) brain (2.5mm on average), hampering accurate activity distribution reconstruction. Many techniques to compensate for the limited resolution during or post-reconstruction have been proposed in the past and have been shown to improve the quantitative accuracy. In this study, state-of-the-art reconstruction techniques are compared on a voxel-basis for quantification accuracy and group analysis using both simulated and measured data of healthy volunteers and patients with epilepsy. MethodsMaximum a posteriori (MAP) reconstructions using either a segmentation-based or a segmentation-less anatomical prior were compared to maximum likelihood expectation maximization (MLEM) reconstruction with resolution recovery. As anatomical information, a spatially aligned 3D T1-weighted magnetic resonance image was used. Firstly, the algorithms were compared using normal brain images to detect systematic bias with respect to the true activity distribution, as well as systematic differences between two methods. Secondly, it was verified whether the algorithms yielded similar results in a group comparison study. ResultsSignificant differences were observed between the reconstructed and the true activity, with the largest errors when using (post-smoothed) MLEM. Only 5–10% underestimation in cortical gray matter voxel activity was found for both MAP reconstructions. Higher errors were observed at GM edges. MAP with the segmentation-based prior also resulted in a significant bias in the subcortical regions due to segmentation inaccuracies, while MAP with the anatomical prior which does not need segmentation did not. Significant differences in reconstructed activity were also found between the algorithms at similar locations (mainly in gray matter edge voxels and in cerebrospinal fluid voxels) in the simulated as well as in the clinical data sets. Nevertheless, when comparing two groups, very similar regions of significant hypometabolism were detected by all algorithms. ConclusionIncluding anatomical a priori information during reconstruction in combination with resolution modeling yielded accurate gray matter activity estimates, and a significant improvement in quantification accuracy was found when compared to post-smoothed MLEM reconstruction with resolution modeling. AsymBowsher provided the most accurate subcortical GM activity estimates. It is also reassuring that the differences found between the algorithms did not hamper the detection of hypometabolic regions in the gray matter when performing a voxel-based group comparison. Nevertheless, the size of the detected clusters differed. More elaborated and application-specific studies are required to decide which algorithm is best for a group analysis.

Meta-analytic connectivity modeling revisited: Controlling for activation base rates

Co-activation of distinct brain regions is a measure of functional interaction, or connectivity, between those regions. The co-activation pattern of a given region can be investigated using seed-based activation likelihood estimation meta-analysis of functional neuroimaging data stored in databases such as BrainMap. This method reveals inter-regional functional connectivity by determining brain regions that are consistently co-activated with a given region of interest (the “seed”) across a broad range of experiments. In current implementations of this meta-analytic connectivity modeling (MACM), significant spatial convergence (i.e. consistent co-activation) is distinguished from noise by comparing it against an unbiased null-distribution of random spatial associations between experiments according to which all gray-matter voxels have the same chance of convergence. As the a priori probability of finding activation in different voxels markedly differs across the brain, computing such a quasi-rectangular null-distribution renders the detection of significant convergence more likely in those voxels that are frequently activated. Here, we propose and test a modified MACM approach that takes this activation frequency bias into account. In this new specific co-activation likelihood estimation (SCALE) algorithm, a null-distribution is generated that reflects the base rate of reporting activation in any given voxel and thus equalizes the a priori chance of finding across-study convergence in each voxel of the brain. Using four exemplary seed regions (right visual area V4, left anterior insula, right intraparietal sulcus, and subgenual cingulum), our tests corroborated the enhanced specificity of the modified algorithm, indicating that SCALE may be especially useful for delineating distinct core networks of co-activation.

Do we measure gray matter activation with functional diffusion tensor imaging?

In this comment by Autio and Roberts (2014) on our second fDTI article “Functional Diffusion Tensor Imaging at 3 Tesla” (Mandl et al., 2013) the authors suggest that BOLD signal originating from gray matter could in part explain the reported task-related FA changes in white matter. The rationale is that the relative contribution from activated gray matter to the measured signal increases in voxels containing both gray and white matter. Because the ADC value for gray matter is between the parallel and perpendicular ADC for white matter, this increased contribution effectively could lead to an increase in the measured parallel ADC and a decrease in the measured perpendicular ADC and hence an increase in FA. Indeed, contamination by signal “leaking” from gray matter into white matter has been one of our major concerns in both our fDTI articles, together with the effects of motion. However, we think that the proposed mechanism by Autio and Roberts to the reported task-related FA changes does not contribute to our finding. One, the use of the non-parametric sign test in our first fDTI paper (Mandl et al., 2008) prevents that only a few voxels (e.g., the end points of the tract touching active gray matter) can result in activation of a complete tract. Two, the global shift of the histograms presented in Figure 5 Mandl et al. (2008) shows that a large part of the white matter voxels in the active tracts contribute to the measured task-related FA change. Of course this in itself does not rule out the proposed mechanism because it could be that the active tracts are (for a large part) surrounded by active gray matter voxels. This may for instance be the case for the optic radiations. These tracts are relatively short and are for a large part adjacent to (possible active) gray matter voxels. However, this certainly is not the case for the active thalamo-cortical tracts as can be seen in the supplementary movie (Mandl et al., 2008, Movie S1). This movie shows the combined fDTI and BOLD fMRI results for the tactile experiment in a single subject (subject nr 5). It can be readily seen that the hypothesized partial voluming with possible active gray matter could only occur at the endpoints of the fiber bundle. Furthermore, three, in the second fDTI paper (Mandl et al., 2013) we introduce a time lag between the stimulus and the start of the acquisition of a fDTI volume to make the measurement less sensitive to relatively fast varying signal changes (e.g., BOLD related signal changes). Still, similar effects were reported for the tactile experiment. Taken together we conclude that although the hypothesized mechanism by Autio and Roberts is intriguing and more experiments are needed to obtain better insight in the underlying mechanisms it cannot explain our measured task-related changes in FA in functional Diffusion Tensor Imaging.

From Circuit Activity to Network Connectivity and Back: The Case of Obsessive-Compulsive Disorder

From Circuit Activity to Network Connectivity and Back: The Case of Obsessive-Compulsive Disorder

Twelve-year monitoring of a patient with megalencephalic leukoencephalopathy with subcortical cysts

Megalencephalic leukoencephalopathy (MLC) with subcortical cysts is an infantile-onset inherited disease of the brain white matter with a defect in brain ion and water homoeostasis, which leads to an abnormal brain volume regulation. Clinical features of the disease can be variable, but patients typically show early-onset macrocephaly, motor abnormalities, seizures, and almost constant late-onset mild mental deterioration. Brain magnetic resonance imaging (MRI) reveals diffusely abnormal and mildly swollen white matter as well as subcortical cysts in the anterior temporal and frontoparietal regions. We describe here clinical findings and volumetric MRI and (1)H-MR spectroscopic imaging ((1)H-MRSI) data of a 12-year follow-up on a patient with MLC. The patient had only slight clinical worsening during the long follow-up. Volumetric findings showed substantially unchanged cystic volumes and mild brain atrophy rate. In addition, there was no over time increase in the volume of white matter hypointense lesions seen on FLAIR images at baseline, but the degree of hypointensity of these white matter voxels increased over 12 years. Longitudinal (1)H-MRSI examination showed long-term undetectable metabolite signals in the white matter, whereas the metabolic pattern of gray matter voxels remained unchanged over time. Results show that, in MLC, the chronic brain white matter changes resulting from the brain ion, and water homeostasis can be monitored by quantitative MRI modalities. This might be important for assessing treatment effects.

Is White Matter More Prone to Diffusion Lesion Reversal After Thrombolysis?

In acute ischemic stroke, white matter (WM) is considered more resistant to infarction than gray matter (GM). To test this hypothesis, we compared the fate of WM and GM voxels belonging to the acute diffusion-weighted imaging (DWI) lesion, expecting WM voxels to be more prone to reversal after thrombolysis. Reversible acute DWI (RAD) lesion was defined voxel-wise as an acute lesion on initial DWI (DWI1) with no visible lesion on 24-hour DWI (DWI2). Only patients with RAD lesions >10 mL and >10% of DWI1 from our previously reported cohort were eligible. The core was defined as voxels hyperintense on DWI1 and DWI2. Semiautomated segmentation of DWI1, core, and RAD lesions, normalization into standard space, and WM/GM segmentation allowed calculations of WM/GM proportions in each region of interest using a voxel-counting algorithm. Thirty patients were eligible (RAD lesion median volume [interquartile range], 23.3 mL [19.1-35.0 mL]; onset-to-treatment time, 134 minutes [105-185 minutes]). WM voxels fraction was greater in RAD lesions than in the core (59.4% [52.8%-68.9%] versus 49.6% [43.0%-57.5%]; P=0.011). The proportion of reversibility was greater for WM than for GM voxels (60.8% [25.5%-88.7%] versus 53.5% [21.1%-77.3%]; P=0.02). The percentage of RAD lesions increased with the proportion of WM present in the acute DWI lesion (P<0.0001; R=0.67). Acute DWI lesions predominantly involving WM may be more prone to reversal and, hence, to respond to therapy than their GM counterparts.

Relationship of clinical and cognitive variables with brain morphometric abnormalities in Alzheimer's disease: a voxel based morphometric study using 3-tesla MRI.

Alzheimer's disease (AD) is associated with widespread structural and functional brain alterations. The current study examined the gray matter (GM) voxel based morphometric (VBM) correlates of cognitive and clinical severity scores in patients with AD. The study included 34 patients with AD according to NINCDS/ADRDA AD criteria and 28 matched elderly controls. All subjects were clinically evaluated using Hindi Mental Status Examination (HMSE), Everyday Abilities Scale for India (EASI) and the Clinical Dementia Rating (CDR) scale. The structural Magnetic Resonance Imaging (MRI) data were acquired using a 3 Tesla MRI scanner and VBM analysis was performed using VBM5.1 toolbox. The patients with AD had significantly lower GM volume, white matter volume and total brain volume as compared to controls. The HMSE scores were positively correlated (p=0.009) and EASI (p=0.04) & CDR (p=0.0004) were negatively correlated with the total GM volumes in patients with AD. The VBM analysis revealed diffuse GM atrophy in patients with AD. Frontal& temporal GM volumes were positively correlated with the HMSE scores. Thus the results of the study replicate the previous observations of generalized GM atrophy, in an Indian sample with AD. The cognitive decline, clinical dementia severity and impairment in activities of daily living were correlated whole brain GM and WM volumes as well as with specific brain regional atrophy in AD. However further studies with larger samples & with more detailed cognitive evaluation are required for confirmation & validation of the relationship between regional morphometric abnormalities and cognitive deficits in AD.

Early anti-correlated BOLD signal changes of physiologic origin

Negative BOLD signals that are synchronous with resting state fluctuations have been observed in large vessels in the cortical sulci and surrounding the ventricles. In this study, we investigated the origin of these negative BOLD signals by applying a Cued Deep Breathing (CDB) task to create transient hypocapnia and a resultant global fMRI signal decrease. We hypothesized that a global stimulus would amplify the effect in large vessels and that using a global negative (vasoconstrictive) stimulus would test whether these voxels exhibit either inherently negative or simply anti-correlated BOLD responses. Significantly anti-correlated, but positive, BOLD signal changes during respiratory challenges were identified in voxels primarily located near edges of brain spaces containing CSF. These positive BOLD responses occurred earlier than the negative CDB response across most of gray matter voxels. These findings confirm earlier suggestions that in some brain regions, local, fractional changes in CSF volume may overwhelm BOLD-related signal changes, leading to signal anti-correlation. We show that regions with CDB anti-correlated signals coincide with most, but not all, of the regions with negative BOLD signal changes observed during a visual and motor stimulus task. Thus, the addition of a physiological challenge to fMRI experiments can help identify which negative BOLD signals are passive physiological anti-correlations and which may have a putative neuronal origin.

Do preprocessing algorithms and statistical models influence voxel-based morphometry (VBM) results in amyotrophic lateral sclerosis patients? A systematic comparison of popular VBM analytical methods

To study whether inconsistent findings in voxel-based morphometry (VBM) in amyotrophic lateral sclerosis (ALS) brain are due to use of different data preprocessing and statistical methods in two software packages. T1-weighted magnetic resonance imaging (MRI) was obtained during routine clinical imaging at 1.5T in ALS patients with frontotemporal dementia (ALS-FTD) (n=18) and in unaffected neurologic controls (n=15). Gray matter (GM) VBM analysis was carried out using FMRIB software library (FSL) 4.1.5 and statistical parametric mapping 8 (SPM8). Comparison of processing steps segmentation, registration, and statistical methods (nonparametric vs. parametric) between the two softwares was performed by subjecting the same dataset through standard VBM processing pipelines. GM volume was significantly (P<0.05) reduced in motor and extramotor regions of ALS-FTD when compared to controls. Percentage of atrophied GM voxels in the entire brain that reached statistical significance using FSL was 22.52% compared to 0.81% in SPM. Similarly, 0.81% (3308 voxels) reached statistical significance using nonparametric statistics when compared to parametric statistics (0.50%, 2056 voxels). The differences in GM volume atrophy measures found by FSL and SPM analytic methods indicate that variable results in previous VBM studies may arise from differences in their image processing algorithms and statistical models.