Brain Regions Of Interest Research Articles

Association between adverse childhood experiences and brain volumes among Japanese community-dwelling older people: Findings from the NEIGE study

BackgroundAdverse childhood experiences (ACEs) can affect later-life health outcomes via brain structural differences. However, there is no sufficient empirical evidence about whether brain morphological differences remain until old ages. ObjectiveWe examined the association between ACEs and brain volumes among older individuals. Participants and settingResidents aged 65–84 years in Tokamachi City, Japan, were randomly recruited, and 491 participants were included in the analysis. MethodsACEs were assessed with a self-reported questionnaire. The volumes of seven brain regions of interests were evaluated via structural magnetic resonance imaging. ResultsIn total, 143 (27.1%) participants experienced one ACE and 33 (6.7%) two or more ACEs. Participants with two or more ACEs had a larger anterior cingulate cortex volume (B = 0.346, 95% confidence interval [CI] = 0.04 to 0.66) and smaller hippocampal (B = −0.287, 95% CI = −0.58 to 0.001) and amygdala (B = −0.313, 95% CI = −0.59 to −0.03) volumes. Interestingly, we observed a distinct association between deprivation and threat. That is, deprivation was associated with a smaller amygdala volume (B = −0.164, 95% CI = −0.32 to −0.01) and threat with a larger anterior cingulate cortex volume (B = 0.401, 95% CI = 0.11 to 0.70). ConclusionsACEs were associated with the volumes of brain regions such as anterior cingulate cortex, hippocampus, and amygdala, which are responsible for emotion and self-regulation in older population. The effect of ACEs on the amygdala was commonly driven by deprivation experiences and that on the anterior cingulate cortex by threat.

Note on Neurofeedback of Patients of Insomnia

FMRI (functional magnetic resonance imaging) is meant for measuring the blood oxygenation level based signal in the brain. It is a quantity that comes from various physiological and biophysical sources and denotes to neural activity a vascular coupling. FMRI has particular preference over other neuroimaging non-invasive methods like electroencephalographic recordings (EEG). rtfMRI, (real time fmri) is a process that adopts functional counsel from a MRI scanner where the fMRI keep runs to data acquisition. Currently, rtfMRI is applied to intraoperative surgical guidance, brain–computer interfaces , and neurofeedback. Insomnia is a disorder in sleep that constantly affects several crores of people worldwide. People with insomnia finds it hard to go to asleep or remain asleep. Using rest-state functional connectivity depending on variations in certain regions of interest in brain one can examine connectivity alterations on patients of insomnia.. In this paper, we have reported on the findings of Huan Zhang et al’s approach concerning rt-fMRI (real-time functional magnetic resonance neurofeedback) therapy for training for patients of insomnia.

T2 quantification in brain using 3D fast spin‐echo imaging with long echo trains

PurposeThree‐dimensional fast spin‐echo (FSE) sequences commonly use very long echo trains (>64 echoes) and severely reduced refocusing angles. They are increasingly used in brain exams due to high, isotropic resolution and reasonable scan time when using long trains and short interecho spacing. In this study, T 2 quantification in 3D FSE is investigated to achieve increased resolution when comparing with established 2D (proton‐density dual‐echo and multi‐echo spin‐echo) methods.MethodsThe FSE sequence design was explored to use long echo trains while minimizing T 2 fitting error and maintaining typical proton density and T 2‐weighted contrasts. Constant and variable flip angle trains were investigated using extended phase graph and Bloch equation simulations. Optimized parameters were analyzed in phantom experiments and validated in vivo in comparison to 2D methods for eight regions of interest in brain, including deep gray‐matter structures and white‐matter tracts.ResultsPhantom and healthy in vivo brain T 2 measurements showed that optimized variable echo‐train 3D FSE performs similarly to previous 2D methods, while achieving three‐fold‐higher slice resolution, evident visually in the 3D T 2 maps. Optimization resulted in better T 2 fitting and compared well with standard multi‐echo spin echo (within the 8‐ms confidence limits defined based on Bland‐Altman analysis).Conclusion T 2 mapping using 3D FSE with long echo trains and variable refocusing angles provides T 2 accuracy in agreement with 2D methods with additional high‐resolution benefits, allowing isotropic views while avoiding incidental magnetization transfer effects. Consequently, optimized 3D sequences should be considered when choosing T 2 mapping methods for high anatomic detail.

Evaluating the impacts of color, graphics, and architectural features on wayfinding in healthcare settings using EEG data and virtual response testing

Wayfinding difficulties in healthcare facilities have been shown to increase anxiety among patients and visitors, to reduce staff operational efficiency, and to increase operational costs. There is evidence that wayfinding-oriented interior design features can mitigate these problems, but the robust evaluation of wayfinding design strategies is hindered by the unique nature of each building and the expense of testing different navigational aids. The current study implemented a novel testing approach using virtual reality and EEG data to evaluate the effects of three different interior designs, using altered color patterns, graphics, and architectural features intended to enhance wayfinding in a specific hospital facility. Multiple sources of data including self-reported responses, behavioral metrics, and measurements of neural activity in wayfinding-relevant brain regions were collected. The results indicated that the most extensive wayfinding design was associated with improvements in some orientation behaviors and with greater neurological activation in the brain regions of interest. However, these findings did not translate into improved wayfinding times or reductions in self-reported stress, fatigue, or confusion. The authors discuss the implications of these findings and make extensive recommendations for the future directions of evidence-based pre-construction design testing. The streamlined testing platform and data-analysis approach that was developed in this work can make this evidence-based approach more feasible for other researchers and professional designers, eventually leading to a broad comparative data-set incorporating a wide range of buildings and participants.

DevfOLD: a toolbox for designing age-specific fNIRS channel placement.

.Significance: Near-infrared spectroscopy (NIRS) is a noninvasive technique that uses scalp-placed sensors to measure cerebral hemoglobin concentration. Commercial NIRS instruments do not allow for whole-head coverage and do not intrinsically indicate which brain areas generate the NIRS signal. Hence, the challenge is to design source–detector channel arrangement that maximizes sensitivity to a given brain region of interest (ROI). Existing methods for optimizing channel placement design have been developed using adult head models. Thus, they have limited utility for developmental research.Aim: We aim to build an application from an existing toolbox (fOLD) that guides NIRS channel configuration based on age group, stereotaxic atlas, and ROI (devfOLD).Approach: The devfOLD provides NIRS channel-to-ROI specificity computed using photon propagation simulation with realistic head models from infant, child, and adult age groups.Results: Cortical locations and user-specified specificity cut-off values influence the between-age consistency and differences in the ROI-to-channel correspondence among the example infant and adult age groups.Conclusions: The study highlights the importance of incorporating age-specific head models for optimizing NIRS channel configurations. The devfOLD toolbox is publicly shared and compatible with multiple operating systems.

Associations Between Traumatic Stress, Brain Volumes and Post-traumatic Stress Disorder Symptoms in Children: Data from the ABCD Study

Reduced volumes in brain regions of interest (ROIs), primarily from adult samples, are associated with posttraumatic stress disorder (PTSD). We extended this work to children using data from the Adolescent Brain Cognitive Development (ABCD) Study® (N = 11,848; Mage = 9.92). Structural equation modeling and an elastic-net (EN) machine-learning approach were used to identify potential effects of traumatic events (TEs) on PTSD symptoms (PTSDsx) directly, and indirectly via the volumes 300 subcortical and cortical ROIs. We then estimated the genetic and environmental variation in the phenotypes. TEs were directly associated with PTSDsx (r = 0.92) in children, but their indirect effects (r < 0.0004)—via the volumes of EN-identified subcortical and cortical ROIs—were negligible at this age. Additive genetic factors explained a modest proportion of the variance in TEs (23.4%) and PTSDsx (21.3%), and accounted for most of the variance of EN-identified volumes of four of the five subcortical (52.4–61.8%) three of the nine cortical ROIs (46.4–53.3%) and cerebral white matter in the left hemisphere (57.4%). Environmental factors explained most of the variance in TEs (C = 61.6%, E = 15.1%), PTSDsx (residual-C = 18.4%, residual-E = 21.8%), right lateral ventricle (C = 15.2%, E = 43.1%) and six of the nine EN-identified cortical ROIs (C = 4.0–13.6%, E = 56.7–74.8%). There is negligible evidence that the volumes of brain ROIs are associated with the indirect effects of TEs on PTSDsx at this age. Overall, environmental factors accounted for more of the variation in TEs and PTSDsx. Whereas additive genetic factors accounted for most of the variability in the volumes of a minority of cortical and in most of subcortical ROIs.

Extracting BOLD signals based on time-constrained multiset canonical correlation analysis for brain functional network estimation and classification

Brain functional network (BFN), usually estimated from blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI), has been proven to be a powerful tool to study the organization of the brain and discover biomarkers for diagnosis of brain disorders. Prior to BFN estimation and classification, extracting representative BOLD signals from brain regions of interest (ROIs) is a critical step. Traditional extraction methods include averaging, peaking operation and dimensionality reduction, often leading to signal cancellation and information loss. In this paper, we propose a novel method, namely time-constrained multiset canonical correlation analysis (TMCCA), to extract representative BOLD signals for subsequent BFN estimation and classification. Different from traditional methods that equally treat all BOLD signals in a ROI, the proposed method assigns weights to different BOLD signals, and learns the optimal weights to make the extracted representative signals jointly maximize the multiple correlations between ROIs. Importantly, time-constraint is incorporated into our proposed method, which can effectively encode nonlinear relationship among BOLD signals. To evaluate the effectiveness of the proposed method, the extracted BOLD signals is used to estimate BFN and, in turn, identify brain disorders, including mild cognitive impairment (MCI) and autistic spectrum disorder (ASD). Experimental results demonstrate that our proposed TMCCA can lead to better performance than traditional methods.

Self‐reported poor sleep accelerates hippocampal volume loss in cognitively normal healthy elderly

AbstractBackgroundPoor sleep quality is a known risk factor for the development of Alzheimer’s disease (AD). However, minimal data is available on the rate of brain tissue volume loss related to self‐reported poor sleep. Our previous cross‐sectional study in cognitively normal elderly adults age 60 and over, demonstrated that poor sleepers exhibited significantly smaller volumes, approximately 7%, in the bilateral hippocampi, superior parietal lobules and left amygdala and smaller cortical thicknesses, over 3%, in the right superior frontal, medial orbitofrontal cortices and frontal pole, compared to normal sleepers (Alperin et al, 2019). Current study is a follow‐up longitudinal investigation comparing rates of tissue loss in these brain regions of interest (ROIs) between elderly good and poor sleepers with normal cognition.MethodForty‐eight cognitively normal elderly individuals age 60 to 92 years were classified into two groups: 23 normal sleepers with self‐reported Pittsburgh Sleep Quality Index (PSQI) &lt; 5 and 25 poor sleepers with PSQI ≥ 5. The two groups were equivalent in terms of age, gender, years of education and white matter hyperintensity (WMH) load. The volumes and thickness of the ROIs were measured at baseline and at follow‐up scans to assess rates of tissue loss using FreeSurfer software. Rates of tissue loss over 2 years were compared between two groups.ResultNo significant association was found between sleep quality, WMH load and rates of thickness loss. Compared to normal sleepers, poor sleepers exhibited 2.8 times higher rates of volume loss in the hippocampus, and 3.3 times higher rate in the posterior cingulate. Global PSQI at baseline was significantly and negatively associated with rates of volume loss in the right hippocampus (rs=‐0.33) and right posterior cingulate cortex (rs=‐0.47). Scores in verbal memory was negatively associated with rates of volume loss in the right hippocampus (r≥0.388).ConclusionPoor sleep quality is associated with significantly accelerated volume loss in the hippocampus and the posterior cingulate cortex in cognitively normal elderly individuals. Intervention for improving sleep quality should be highly considered in cognitively normal elderly adults to delay onset of cognitive impairment and onset of AD.

Recommendations of Choice of Head Coil and Prescan Normalize Filter Depend on Region of Interest and Task.

The performance of MRI head coils together with the influence of the prescan normalize filter in different brain regions was evaluated. Functional and structural data were recorded from 26 participants performing motor, auditory, and visual tasks in different conditions: with the 20- and 64-channel Siemens head/neck coil and the prescan normalize filter turned ON or OFF. Data were analyzed with the MRIQC tool to evaluate data quality differences. The functional data were statistically evaluated by comparison of the β estimates and the time-course signal-to-noise ratio (tSNR) in four regions of interest, i.e., the auditory, visual, and motor cortices and the thalamus. The MRIQC tool indicated a better data quality for both functional and structural data with the prescan normalize filter, with an advantage for the 20-channel head coil in functional data and an advantage for the 64-channel head coil in structural measurements. Nevertheless, recommendations for the functional data regarding choice of head coils and prescan normalize filter depend on the brain regions of interest. Higher β estimates and tSNR values occurred in the auditory cortex and thalamus with the prescan normalize filter, whereas the contrary was true for the visual and motor cortices. Due to higher β estimates in the visual cortex in the 64-channel head coil, this head coil is recommended for studies investigating the visual cortex. For most of the research questions, the 20-channel head coil is better suited for functional experiments, with the prescan normalize filter, especially when investigating deep brain areas. For anatomical studies, the 64-channel head coil seemed to be the better choice.

Brain Glucose Metabolism is Reduced After Radiation Therapy for Head and Neck Cancer

The effects of cancer treatment exposures on the brain are poorly understood, particularly for cancers outside of the central nervous system. Patients with head and neck cancer (HNC) treated with radiation (RT) often have portions of their brain exposed to moderate doses of radiation, particularly within the posterior fossa. The purpose of this study was to characterize changes in brain metabolism using 18-fluorodeoxyglucose (FDG) PET after HNC treatment, with emphasis on accounting for the distribution of the radiation exposure.This study included patients who received RT for newly diagnosed HNC at an academic center since 2012 for whom an FDG PET scan was utilized for RT treatment planning, a subsequent PET was obtained within 6 months of completing RT, and both PET scans included the entire brain. Brain regions of interest (ROIs) were defined using the original RT treatment plans and included the intersection of the brain with the 10 Gy, 20 Gy, 30 Gy isodose lines, typically contained within the posterior fossa. The portion of the brain outside of the 3 Gy isodose line was also defined as an ROI relatively spared from radiation (< 3 Gy ROI). PET scans were individually coregistered to the skull on treatment planning CT. The mean standardized uptake values (SUVMean) for each ROI were extracted. The paired samples t-test was used to assess differences in pre- and post-RT SUVMean for each ROI as well as to compare the percent change in SUV between ROIs.A total of 50 patients met the inclusion criteria. Pre-RT average SUVMean was statistically higher for the < 3 Gy ROI than the 10 Gy, 20 Gy, and 30 Gy ROIs (P < 0.01 for each pairwise comparison), consistent with expected baseline differences between cortical and subcortical brain structures. The average SUVMean of the post-RT PET was statistically lower than the pre-RT PET for all ROIs (Table). The percent decline in SUVMean for the < 3 Gy ROI (-11.7% SD: 15.9%) was statistically greater than for the 10 Gy ROI (-7.9% SD: 16.1%, P < 0.001), 20 Gy ROI (-7.3%, SD: 17.3%, P = 0.007), but not the 30 Gy ROI (-6.7% SD: 22.2%, P = 0.076). The percent decline in SUVMean was not statistically different when comparing the 10 Gy vs. 20 Gy ROIs (P = 0.458) or 10 Gy vs. 30 Gy ROIs (P = 0.569).In this population of patients receiving RT for HNC we observed a decrease in SUVMean when comparing pre- and post-RT FDG PET. The decline in SUVMean was greatest in the portion of the brain that was relatively spared from radiation. Further research is needed to clarify whether the observed changes are a direct result of radiation exposure or differences in regional brain metabolism, assess for a dose effect, and to relate changes on PET with patient-centered outcomes.

Modulation of Functional Connectivity in Response to Mirror Visual Feedback in Stroke Survivors: An MEG Study.

Background. Several brain regions are activated in response to mirror visual feedback (MVF). However, less is known about how these brain areas and their connectivity are modulated in stroke patients. This study aimed to explore the effects of MVF on brain functional connectivity in stroke patients. Materials and Methods. We enrolled 15 stroke patients who executed Bilateral-No mirror, Bilateral-Mirror, and Unilateral-Mirror conditions. The coherence values among five brain regions of interest in four different frequency bands were calculated from magnetoencephalographic signals. We examined the differences in functional connectivity of each two brain areas between the Bilateral-No mirror and Bilateral-Mirror conditions and between the Bilateral-Mirror and Unilateral-Mirror conditions. Results. The functional connectivity analyses revealed significantly stronger connectivity between the posterior cingulate cortex and primary motor cortex in the beta band (adjusted p = 0.04) and possibly stronger connectivity between the precuneus and primary visual cortex in the theta band (adjusted p = 0.08) in the Bilateral-Mirror condition than those in the Bilateral-No mirror condition. However, the comparisons between the Bilateral-Mirror and Unilateral-Mirror conditions revealed no significant differences in cortical coherence in all frequency bands. Conclusions. Providing MVF to stroke patients may modulate the lesioned primary motor cortex through visuospatial and attentional cortical networks.

The Analysis of Alzheimer's Disease Diagnosis Based on sMRI Slice Image

Morphological networks constructed with structural magnetic resonance imaging (sMRI) images have been widely investigated by exploring interregional alterations of different brain regions of interest (ROI) in the spatial domain for Alzheimer’s disease (AD) classification. However, few attentions are attracted to construct a subband-based individual network with the sMRI image in the frequency domain. In order to verify the feasibility of constructing individual networks with subbands and extract features from the subband-based individual network for AD classification, in this study, we propose a novel method to capture correlations of the abnormal energy distribution patterns related to AD by constructing nonsubsampled contourlet subband-based individual networks (NCSINs) in the frequency domain. Specifically, a 2-dimensional representation of the preprocessed sMRI image is firstly reshaped by downsampling and reconstruction steps. Then, the nonsubsampled contourlet transform is performed on the 2-dimensional representation to obtain directional subbands, and each directional subband at one scale is described by a column energy feature vector (CV) regarded as a node of the NCSIN. Subsequently, edge between any two nodes is weighted with connection strength (CS). Finally, the concatenation of node and edge features of the NCSINs at different scales is used as a network feature of the sMRI image for AD classification. Meanwhile, the support vector machine (SVM) classifier with a radial basis function (RBF) kernel is applied for categorizing 680 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Experimental results demonstrate that it is feasible to construct the subband-based individual network in the frequency domain and also show that our NCSIN method outperforms five other state-of-the-art approaches.

Functional Roles of Neuronal Nitric Oxide Synthase in Neurodegenerative Diseases and Mood Disorders

Nitric oxide synthase (NOS) is well known for its involvement in the regulation of the nervous, cardiovascular, and immune systems. Neuronal NOS (nNOS) is the most characterized NOS among all the isoforms. It accounts for most of the production of nitric oxide (NO) in the nervous system required for synaptic transmission and neuroplasticity. Previous studies have described the localization of nNOS in specific brain regions of interest. There is substantial evidence in the literature suggesting that nNOS signaling has significant involvement in several disease pathologies. However, the association between brain nNOS expression profiles and disease remains largely unknown. In this review, we attempt to delineate the contribution of nNOS signaling in memory and mood disorders in order to achieve a better understanding of nNOS in disease modulation.

Emotion depends on context, culture and their interaction: evidence from effective connectivity.

Situated models of emotion hypothesize that emotions are optimized for the context at hand, but most neuroimaging approaches ignore context. For the first time, we applied Granger causality (GC) analysis to determine how an emotion is affected by a person’s cultural background and situation. Electroencephalographic recordings were obtained from mainland Chinese (CHN) and US participants as they viewed and rated fearful and neutral images displaying either social or non-social contexts. Independent component analysis and GC analysis were applied to determine the epoch of peak effect for each condition and to identify sources and sinks among brain regions of interest. We found that source–sink couplings differed across culture, situation and culture × situation. Mainland CHN participants alone showed preference for an early-onset source–sink pairing with the supramarginal gyrus as a causal source, suggesting that, relative to US participants, CHN participants more strongly prioritized a scene’s social aspects in their response to fearful scenes. Our findings suggest that the neural representation of fear indeed varies according to both culture and situation and their interaction in ways that are consistent with norms instilled by cultural background.

A Review on Mental Stress Assessment Methods Using EEG Signals

Mental stress is one of the serious factors that lead to many health problems. Scientists and physicians have developed various tools to assess the level of mental stress in its early stages. Several neuroimaging tools have been proposed in the literature to assess mental stress in the workplace. Electroencephalogram (EEG) signal is one important candidate because it contains rich information about mental states and condition. In this paper, we review the existing EEG signal analysis methods on the assessment of mental stress. The review highlights the critical differences between the research findings and argues that variations of the data analysis methods contribute to several contradictory results. The variations in results could be due to various factors including lack of standardized protocol, the brain region of interest, stressor type, experiment duration, proper EEG processing, feature extraction mechanism, and type of classifier. Therefore, the significant part related to mental stress recognition is choosing the most appropriate features. In particular, a complex and diverse range of EEG features, including time-varying, functional, and dynamic brain connections, requires integration of various methods to understand their associations with mental stress. Accordingly, the review suggests fusing the cortical activations with the connectivity network measures and deep learning approaches to improve the accuracy of mental stress level assessment.

Microglia activation in postmortem brains with schizophrenia demonstrates distinct morphological changes between brain regions.

Schizophrenia (SCZ) is a psychiatric disorder that can include symptoms of disorganized speech and thoughts with uncertain underlying mechanisms possibly linked to over‐activated microglia. In this study, we used brain samples from sixteen donors with SCZ and thirteen control donors to assess the differential activation of microglia by quantifying density and 3D reconstruction of microglia stained with ionized calcium‐binding adaptor molecule‐1 (Iba1). Our samples consisted of sections from the frontal, temporal, and cingulate cortical gray matter, subcortical white matter regions (SCWM), and included the anterior corpus callosum. In the first series of studies, we performed a density analysis followed by a spatial analysis to ascertain the microglial density, distribution, and soma size in SCZ brains. Second, we performed a series of morphological quantification techniques to investigate the arborization patterns of the microglia in SCZ. The results demonstrated an increase in microglia density in the cortical gray matter regions in SCZ cases, while in the SCWM, there was a significant increase in microglia density in the frontal and temporal, but not in the other brain regions of interest (ROIs). Spatial analysis using the “nearest neighbor” demonstrated that there was no effect in “clustering”, but there were shorter distances between microglia seen in the SCZ cases. The morphological measures showed that there was a region‐dependent increase in the microglia soma size in the SCZ cases while the Sholl analysis revealed a significant decrease in the microglia arborization in the SCZ cases across all the ROI’s studied. An in‐depth 3D reconstruction of microglia in Brodmann area 9 cortical region found that there was a significant association between age and reduced microglial arborization in the SCZ cases. This region‐dependent age association can help determine whether longitudinal changes in microglial activation across age are brain region‐dependent, which may point to potential therapeutic targets.

Seeking a Widely Adoptable Practical Standard to Estimate Signal-to-Noise Ratio in Magnetic Resonance Imaging for Multiple-Coil Reconstructions.

Signal-to-noise ratio (SNR) is used to evaluate the performance of magnetic resonance (MR) imaging systems. Accurate and consistent estimations are needed to routinely use SNR to assess coils and image reconstruction techniques. To identify a reliable and practical method for SNR estimation in multiple-coil reconstructions. Technical evaluation and comparison. A uniform phantom and four healthy volunteers: 35, 38, 39 y/o males, 25 y/o female. Two-dimensional multislice gradient-echo pulse sequence at 3 T and 7 T. Reference-standard SNR was calculated from 100 multiple replicas. Six SNR methods were compared against it: difference image (DI), analytic array combination (AC), pseudo-multiple-replica (PMR), generalized pseudo-replica (GPR), smoothed image subtraction (SIS), and DI with temporal instability correction (TIC). The assessment was repeated for different multiple-coil reconstructions. SNR methods were evaluated in terms of relative deviation (RD) and normalized mutual information (NMI) with respect to the reference-standard, using a linear regression (0.05 significance level) to assess how different factors affect accuracy. Average RD (phantom) for DI, AC, PMR, GPR, SIS, and TIC was 7.9%, 6%, 6.7%, 10.1%, 40%, and 14.6%, respectively. RD increased with acceleration. SNR maps with AC were the most similar to the reference standard (NMI=0.358). Considering all brain regions of interest, average RD for all SNR methods varied 96% among volunteers but remained approximately 10% for AC, PMR, and GPR, whereas it was more than 30% for DI, SIS, and TIC. RD was mainly affected by image reconstruction (beta=12) for AC and SNR entropy for SIS (beta=19). AC provided accurate and robust SNR estimation. PMR and GPR are more generally applicable than AC. DI and TIC should be used only at low acceleration factors, when an additional noise-only scan cannot be acquired. SIS is a single-acquisition alternative to DI for generalized autocalibrating partial parallel acquisition (GRAPPA) reconstructions. 1 TECHNICAL EFFICACY: Stage 1.

Investigating morphological changes in the brain in relation to etiology and duration of olfactory dysfunction with voxel-based morphometry

Olfactory loss (OL) affects up to 20% of the general population and is related to changes in olfaction-related brain regions. This study investigated the effect of etiology and duration of OL on gray matter volume (GMV) of these regions in 257 patients. Voxel-based morphometry was applied to measure GMV in brain regions of interest to test the effects of etiology and duration on regional GMV and the relation between olfactory function and regional GMV. Etiology of OL had a significant effect on GMV in clusters representing the gyrus rectus and orbitofrontal cortex (OFC), bilaterally. Patients with congenital anosmia had reduced GMV in the gyrus rectus and an increased OFC volume compared to patients with acquired OL. There was a significant association between volume of the left OFC and olfactory function. This implies that changes in GMV in patients with acquired OL are mainly reflected in the OFC and depend on olfactory function. Morphology of olfactory areas in the brain therefore seems to relate to olfactory function and the subsequent degree of exposure to olfactory input in patients with acquired OL. Differences in GMV in congenital anosmia are most likely due to the fact that patients were never able to smell.

Patterns of Sulcal depth and cortical thickness in Parkinson's disease.

Previous voxel-based morphometry (VBM) and cortical thickness (CT) studies on Parkinson's disease (PD) have mainly reported the gray matter size reduction, whereas the shape of cortical surface can also change in PD patients. For the first time, we analyzed sulcal depth (SD) patterns in PD patients by using whole brain region of interest (ROI)-based approach. In a cross-sectional study, high-resolution brain structural MRI images were collected from 60 PD patients without dementia and 56 age-and sex-matched healthy controls (HC). SD and CT were estimated using the Computational Anatomy Toolbox (CAT12) and statistically compared between groups on whole brain ROI-based level using statistical parametric mapping 12 (SPM12). Additionally, correlations between regional brain changes and clinical variables were also examined. Compared to HC, PD patients showed lower SD in widespread regions, including temporal (the bilateral transverse temporal, the left inferior temporal, the right middle temporal and the right superior temporal), insular (the left insula), frontal (the left pars triangularis, the left pars opercularis and the left precentral), parietal (the bilateral superior parietal) and occipital (the right cuneus) regions. For CT, only the left pars opercularis showed lower CT in PD patients compared to HC. No regions showed higher SD or CT in PD patients compared to HC. In PD patients, a significant positive correlation was found between SD of the left pars opercularis and MMSE scores, such that lower MMSE scores were related to lower SD of the left pars opercularis. Our results of widespread lower SD, but relatively localized lower CT, indicate that SD seems to be more sensitive to brain changes than CT and may be mainly affected by white matter damage. Hence, SD may be a more promising indicator to investigate the surface shape changes in PD patients. The significant positive correlation between SD of the left pars opercularis and MMSE scores suggests that SD may be prognostic of future cognitive decline.

Adjunction of the Lipase Inhibitor Orlistat Improves Grape Seed Extract Neuroprotection against Brain Ischemia/Reperfusion Injury in Rats

Abstract: Aim: Stroke is a public health concern for which there is currently no prophylaxis. In this study, we assessed the protective effect of Grape Seed Extract (GSE) and Orlistat (ORL) against brain ischemia/reperfusion (I/R) injury. Methods: Adult male Wistar rats were treated either with GSE (2.5 g/kg), ORL (4 mg/kg) or both drugs for one week and ischemia performed during 30 min by a bilateral common carotid artery occlusion (BCCAO), followed by 60 min reperfusion. Rats were then sacrificed, their whole brain used for infarct size determination using TTC staining or dissected into cortex, hippocampus and cerebellum for biochemical analysis of I/R-induced oxidative stress and energy failure. Results: In the three brain regions of interest, I/R disturbed protein carbonylation, xanthine oxidase (XO), catalase (CAT), glutathione peroxidase (GPx) and superoxide dismutase (SOD) activities, as well as intracellular mediators as hydrogen peroxide (H2O2), calcium and iron. Furthermore I/R altered energy fueling through the decrease of α-ketoglutarate dehydrogenase (α-KGDH) and fumarase (FH) together with mitochondrial complexes I and II along with glutamatergic excitotoxicity through glutamate dehydrogenase (GDH) and glutamine synthetase (GS) activities into cortex and hippocampal areas but not into cerebellum. In addition I/R affected mitochondrial viability as assessed by MTT staining and the moonlighting apoptosis inducer glyceraldehyde-3- phosphate dehydrogenase (GAPDH). Conclusion: Interestingly, GSE prevented efficiently the deleterious effects of I/R and the best protection was obtained when combining the two drugs, especially within cortex and hippocampus compartments. Thus, adjunction of ORL to GSE treatment is a promising strategy to improve neuroprotection from stroke. Key words: Brain I/R, GSE, Orlistat, Neuroprotection, Energy failure.