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Summary: Objective: This systematic review aims to summarize the current body of evidence concerning the prevalence of obesity among clergy (i.e., the officially designated leaders of a religious group) in the United States. Method: From November 2022 to February 2023, five databases, one data repository, and gray matter were searched for articles and data sources. The search was restricted to articles published or raw data collected from 2001 to 2021. Study quality was assessed with a template, and heterogeneity was assessed using the I2 statistic. The protocol for this review was registered with PROSPERO (CRD42022376592). Results: Forty‐seven studies of clergy obesity involving 35,064 individuals were eligible. The pooled prevalence estimate of obesity across studies was 34.8% (95% confidence interval [CI]: 32.5–37.2). Obesity prevalence was found to be increasing over time and to vary considerably between clergy from different religious traditions. Compared to national estimates, from 2005 onwards, obesity prevalence was higher than in the US adult population. [ABSTRACT FROM AUTHOR]

Abacus‐based mental calculation (AMC) is a widely used educational tool for enhancing math learning, offering an accessible and cost‐effective method for classroom implementation. Despite its universal appeal, the neurocognitive mechanisms that drive the efficacy of AMC training remain poorly understood. Notably, although abacus training relies heavily on the rapid recall of number positions and sequences, the role of memory systems in driving long‐term AMC learning remains unknown. Here, we sought to address this gap by investigating the role of the medial temporal lobe (MTL) memory system in predicting long‐term AMC training gains in second‐grade children, who were longitudinally assessed up to fifth grade. Leveraging multimodal neuroimaging data, we tested the hypothesis that MTL systems, known for their involvement in associative memory, are instrumental in facilitating AMC‐induced improvements in math skills. We found that gray matter volume in bilateral MTL, along with functional connectivity between the MTL and frontal and ventral temporal‐occipital cortices, significantly predicted learning gains. Intriguingly, greater gray matter volume but weaker connectivity of the posterior parietal cortex predicted better learning outcomes, offering a more nuanced view of brain systems at play in AMC training. Our findings not only underscore the critical role of the MTL memory system in AMC training but also illuminate the neurobiological factors contributing to individual differences in cognitive skill acquisition. A video abstract of this article can be viewed at https://youtu.be/StVooNRc7T8. Research Highlights: We investigated the role of medial temporal lobe (MTL) memory system in driving children's math learning following abacus‐based mental calculation (AMC) training.AMC training improved math skills in elementary school children across their second and fifth grade.MTL structural integrity and functional connectivity with prefrontal and ventral temporal‐occipital cortices predicted long‐term AMC training‐related gains. [ABSTRACT FROM AUTHOR]

Background Objective Methods Results Conclusion White matter (WM) abnormalities have been implicated in clinically relevant functional decline in multiple system atrophy (MSA).To identify the WM and gray matter (GM) abnormalities in MSA and assess the utility of longitudinal structural and diffusion changes as surrogate markers for tracking disease progression in MSA.Twenty‐seven participants with early MSA [15 with clinically predominant cerebellar (MSA‐C) and 12 with clinically predominant parkinsonian features (MSA‐P)] and 14 controls were enrolled as a part of our prospective, longitudinal study of synucleinopathies. Using structural magnetic resonance imaging (MRI) and diffusion MRI (diffusion tensor and neurite orientation and dispersion density imaging), we analyzed whole and regional brain changes in these participants. We also evaluated temporal imaging trajectories based on up to three annual follow‐up scans and assessed the impact of baseline diagnosis on these imaging biomarkers using mixed‐effect models.MSA patients exhibited more widespread WM changes than GM, particularly in the cerebellum and brainstem, with greater severity in MSA‐C. Structural and diffusion measures in the cerebellum WM and brainstem deteriorated with disease progression. Rates of progression of these abnormalities were similar in both MSA subtypes, reflecting increasing overlap of clinical features over time.WM abnormalities are core features of MSA disease progression and advance at similar rates in clinical MSA subtypes. Multimodal MRI imaging reveals novel insights into the distribution and pattern of brain abnormalities and their progression in MSA. Selected structural and diffusion measures may be useful for tracking disease progression in MSA clinical trials. [ABSTRACT FROM AUTHOR]

A fundamental puzzle about brain development is why the volume of gray matter (GM) apparently declines as white matter (WM) grows when children enter adolescence. Since pruned synapses are too small to affect GM volume, a prevailing theory posits that an expanded distribution of myelin causes the inner edge of the GM to "whiten" while total brain volume remains steady, shifting the MRI‐measured WM:GM boundary closer to the brain's outer surface. This theory inherently predicts that GM volume loss is concurrent with WM volume growth across regions, within sexes and over time, although these predictions have yet to be explicitly tested. In this study, we test these predictions by mapping regional GM and WM volumetric changes in 2333 participants of the Adolescent Brain Cognitive Development study aged 9–14 years who each received three MRI scans 2 years apart. We show that average GM and WM volume changes follow distinct spatial, temporal, and sex‐specific patterns, indicating that GM volume loss is not balanced by WM volume growth, although cortical GM thinning is weakly correlated with WM growth in some regions. We conclude that myelin is not the main source of measured GM volume loss, and we propose alternative candidates. [ABSTRACT FROM AUTHOR]

The growing global obesity issue emphasizes the importance of understanding its health implications. Previous research has identified consistent alterations in gray matter (GM) volume in connection with obesity. Given the various implications of distinct fat compartments and the potential role of adipose tissue‐derived adipokines in brain health, a more detailed investigation of adiposity is required. This study investigates a sample of 65 males with varying body mass indices to explore the relationship between various fat compartments, adipokine levels, and volumetric GM variations, aiming to provide a deeper understanding of the interplay between adiposity, brain structure, and metabolic signals. Whole‐body magnetic resonance imaging (MRI) was used to assess total, visceral, and subcutaneous adipose tissue, while MR spectroscopy was performed to capture liver fat content. For the assessment of adipokine levels leptin and adiponectin concentrations were measured, and structural brain images underwent cortical and subcortical segmentation for GM volume and thickness. A predictive modeling approach with leave‐one‐out cross‐validation was used to predict body composition metrics and adipokine levels based on structural GM data. Our investigation revealed diminished GM volume and thickness correlated with elevated leptin levels in areas crucial for appetite regulation, decision‐making, and cognitive control, including the anterior insula, orbitofrontal cortex, and anterior cingulate cortex. These findings suggest a potential adverse impact of heightened leptin concentrations on brain health and eating habits. Contrary to expectations, our investigation found no significant relationship between GM volume and any of the measured fat compartments. This result prompts the need for further research to elucidate the relationship between obesity, adipokines, and brain structure. [ABSTRACT FROM AUTHOR]

Despite the clinical significance of narcissistic personality, its neural bases have not been clarified yet, primarily because of methodological limitations of the previous studies, such as the low sample size, the use of univariate techniques and the focus on only one brain modality. In this study, we employed for the first time a combination of unsupervised and supervised machine learning methods, to identify the joint contributions of grey matter (GM) and white matter (WM) to narcissistic personality traits (NPT). After preprocessing, the brain scans of 135 participants were decomposed into eight independent networks of covarying GM and WM via parallel ICA. Subsequently, stepwise regression and Random Forest were used to predict NPT. We hypothesized that a fronto‐temporo parietal network, mainly related to the default mode network, may be involved in NPT and associated WM regions. Results demonstrated a distributed network that included GM alterations in fronto‐temporal regions, the insula and the cingulate cortex, along with WM alterations in cerebellar and thalamic regions. To assess the specificity of our findings, we also examined whether the brain network predicting narcissism could also predict other personality traits (i.e., histrionic, paranoid and avoidant personalities). Notably, this network did not predict such personality traits. Additionally, a supervised machine learning model (Random Forest) was used to extract a predictive model for generalization to new cases. Results confirmed that the same network could predict new cases. These findings hold promise for advancing our understanding of personality traits and potentially uncovering brain biomarkers associated with narcissism. [ABSTRACT FROM AUTHOR]

Background and Objective: Spinal muscular atrophy (SMA) is one of the most common monogenic neuromuscular diseases, and the pathogenesis mechanisms, especially the brain network topological properties, remain unknown. This study aimed to use individual‐level morphological brain network analysis to explore the brain neural network mechanisms in SMA. Methods: Individual‐level gray matter (GM) networks were constructed by estimating the interregional similarity of GM volume distribution using both Kullback–Leibler divergence‐based similarity (KLDs) and Jesen‐Shannon divergence‐based similarity (JSDs) measurements based on Automated Anatomical Labeling 116 and Hammersmith 83 atlases for 38 individuals with SMA types 2 and 3 and 38 age‐ and sex‐matched healthy controls (HCs). The topological properties were analyzed by the graph theory approach and compared between groups by a nonparametric permutation test. Additionally, correlation analysis was used to assess the associations between altered topological metrics and clinical characteristics. Results: Compared with HCs, although global network topology remained preserved in individuals with SMA, brain regions with altered nodal properties mainly involved the right olfactory gyrus, right insula, bilateral parahippocampal gyrus, right amygdala, right thalamus, left superior temporal gyrus, left cerebellar lobule IV–V, bilateral cerebellar lobule VI, right cerebellar lobule VII, and vermis VII and IX. Further correlation analysis showed that the nodal degree of the right cerebellar lobule VII was positively correlated with the disease duration, and the right amygdala was negatively correlated with the Hammersmith Functional Motor Scale Expanded (HFMSE) scores. Conclusions: Our findings demonstrated that topological reorganization may prioritize global properties over nodal properties, and disrupted topological properties in the cortical–limbic‐cerebellum circuit in SMA may help to further understand the network pathogenesis underlying SMA. [ABSTRACT FROM AUTHOR]

Introduction: Traumatic brain injury (TBI) refers to damage to brain tissue by mechanical or blunt force via trauma. TBI is often associated with impaired cognitive abilities, like difficulties in memory, learning, attention, and other higher brain functions, that typically remain for years after the injury. Lithium is an elementary light metal that is only utilized in salt form due to its high intrinsic reactivity. This current review discusses the molecular mechanisms and therapeutic and neuroprotective effects of lithium in TBI. Method: The "Boolean logic" was used to search for articles on the subject matter in PubMed and PubMed Central, as well as Google Scholar. Results: Lithium's therapeutic action is extremely complex, involving multiple effects on gene secretion, neurotransmitter or receptor‐mediated signaling, signal transduction processes, circadian modulation, as well as ion transport. Lithium is able to normalize multiple short‐ as well as long‐term modifications in neuronal circuits that ultimately result in disparity in cortical excitation and inhibition activated by TBI. Also, lithium levels are more distinct in the hippocampus, thalamus, neo‐cortex, olfactory bulb, amygdala as well as the gray matter of the cerebellum following treatment of TBI. Conclusion: Lithium attenuates neuroinflammation and neuronal toxicity as well as protects the brain from edema, hippocampal neurodegeneration, loss of hemispheric tissues, and enhanced memory as well as spatial learning after TBI. [ABSTRACT FROM AUTHOR]

Background and purpose: In amyotrophic lateral sclerosis (ALS), there is an unmet need for more precise patient characterization through quantitative, ideally operator‐independent, assessments of disease extent and severity. Radially sampled averaged magnetization inversion recovery acquisitions (rAMIRA) magnetic resonance imaging enables gray matter (GM) and white matter (WM) area quantitation in the cervical and thoracic spinal cord (SC) with optimized contrast. We aimed to investigate rAMIRA‐derived SC GM and SC WM areas and their association with clinical phenotype and disability in ALS. Methods: A total of 36 patients with ALS (mean [SD] age 61.7 [12.6] years, 14 women) and 36 healthy, age‐ and sex‐matched controls (HCs; mean [SD] age 63.1 [12.1] years, 14 women) underwent two‐dimensional axial rAMIRA imaging at the inter‐vertebral disc levels C2/3–C5/C6 and the lumbar enlargement level Tmax. ALS Functional Rating Scale–revised (ALSFRS‐R) score, muscle strength, and sniff nasal inspiratory pressure (SNIP) were assessed. Results: Compared to HCs, GM and WM areas were reduced in patients at all cervical levels (p < 0.0001). GM area (p = 0.0001), but not WM area, was reduced at Tmax. Patients with King's Stage 3 showed significant GM atrophy at all levels, while patients with King's Stage 1 showed significant GM atrophy selectively at Tmax. SC GM area was significantly associated with muscle force at corresponding myotomes. GM area at C3/C4 was associated with ALSFRS‐R (p < 0.001) and SNIP (p = 0.0016). Conclusion: Patients with ALS assessed by rAMIRA imaging show significant cervical and thoracic SC GM and SC WM atrophy. SC GM area correlates with muscle strength and clinical disability. GM area reduction at Tmax may be an early disease sign. Longitudinal studies are warranted. [ABSTRACT FROM AUTHOR]

This study aims to investigate the structural reorganization in the sensorimotor area of the brain in patients with gliomas, distinguishing between those with impaired and unimpaired strength. Using voxel‐based morphometry (VBM) and region of interest (ROI) analysis, gray matter volumes (GMV) were compared in the contralesional primary motor gyrus, primary sensory gyrus, premotor area, bilateral supplementary motor area, and medial Brodmann area 8 (BA8). The results revealed that in patients with right hemisphere gliomas, the right medial BA8 volume was significantly larger in the impaired group than in the unimpaired group, with both groups exceeding the volume in 16 healthy controls (HCs). In patients with left hemisphere gliomas, the right supplementary motor area (SMA) was more pronounced in the impaired group compared to the unimpaired group, and both groups were greater than HCs. Additionally, the volumes of the right medial BA8 in both the impaired group were greater than HCs. Contralateral expansions in the gray matter of hand‐ and trunk‐related cortices of the premotor area, precentral gyrus, and postcentral gyrus were observed compared to HCs. Furthermore, a negative correlation was found between hand Medical Research Council (MRC) score and volumes of the contralateral SMA and bilateral medial BA8. Notably, our findings reveal consistent results across both analytical approaches in identifying significant structural reorganizations within the sensorimotor cortex. These consistent findings underscore the adaptive neuroplastic responses to glioma presence, highlighting potential areas of interest for further neurosurgical planning and rehabilitation strategies. [ABSTRACT FROM AUTHOR]

The aim of this study was to systematically investigate structural and functional alterations in amygdala subregions using multimodal magnetic resonance imaging (MRI) in patients with tinnitus with or without affective dysfunction. Sixty patients with persistent tinnitus and 40 healthy controls (HCs) were recruited. Based on a questionnaire assessment, 26 and 34 patients were categorized into the tinnitus patients with affective dysfunction (TPAD) and tinnitus patients without affective dysfunction (TPWAD) groups, respectively. MRI‐based measurements of gray matter volume, fractional anisotropy (FA), fractional amplitude of low‐frequency fluctuations (fALFF), regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC) were conducted within 14 amygdala subregions for intergroup comparisons. Associations between the MRI properties and clinical characteristics were estimated via partial correlation analyses. Compared with that of the HCs, the TPAD and TPWAD groups exhibited significant structural and functional changes, including white matter integrity (WMI), fALFF, ReHo, DC, and FC alterations, with more pronounced WMI changes in the TPAD group, predominantly within the left auxiliary basal or basomedial nucleus (AB/BM), right central nucleus, right lateral nuclei (dorsal portion), and left lateral nuclei (ventral portion containing basolateral portions). Moreover, the TPAD group exhibited decreased FC between the left AB/BM and left middle occipital gyrus and right superior frontal gyrus (SFG), left basal nucleus and right SFG, and right lateral nuclei (intermediate portion) and right SFG. In combination, these amygdalar alterations exhibited a sensitivity of 65.4% and specificity of 96.9% in predicting affective dysfunction in patients with tinnitus. Although similar structural and functional amygdala remodeling were observed in the TPAD and TPWAD groups, the changes were more pronounced in the TPAD group. These changes mainly involved alterations in functionality and white matter microstructure in various amygdala subregions; in combination, these changes could serve as an imaging‐based predictor of emotional disorders in patients with tinnitus. [ABSTRACT FROM AUTHOR]

Aim: While conservatism bias refers to the human need for more evidence for decision‐making than rational thinking expects, the jumping to conclusions (JTC) bias refers to the need for less evidence among individuals with schizophrenia/delusion compared to healthy people. Although the hippocampus‐midbrain‐striatal aberrant salience system and the salience, default mode (DMN), and frontoparietal networks ("triple networks") are implicated in delusion/schizophrenia pathophysiology, the associations between conservatism/JTC and these systems/networks are unclear. Methods: Thirty‐seven patients with schizophrenia and 33 healthy controls performed the beads task, with large and small numbers of bead draws to decision (DTD) indicating conservatism and JTC, respectively. We performed independent component analysis (ICA) of resting functional magnetic resonance imaging (fMRI) data. For systems/networks above, we investigated interactions between diagnosis and DTD, and main effects of DTD. We similarly applied ICA to structural and diffusion MRI to explore the associations between DTD and gray/white matter. Results: We identified a significant main effect of DTD with functional connectivity between the striatum and DMN, which was negatively correlated with delusion severity in patients, indicating that the greater the anti‐correlation between these networks, the stronger the JTC and delusion. We further observed the main effects of DTD on a gray matter network resembling the DMN, and a white matter network connecting the functional and gray matter networks (all P < 0.05, family‐wise error [FWE] correction). Function and gray/white matter showed no significant interactions. Conclusion: Our results support the novel association of conservatism and JTC biases with aberrant salience and default brain mode. [ABSTRACT FROM AUTHOR]

Objective: To investigate the relationship between neurocognitive deficits and structural changes on brain magnetic resonance imaging in people living with HIV (PLWH) with good virological control on combination antiretroviral therapy, compared with socioeconomically matched control participants recruited from the same communities. Methods: Brain magnetic resonance imaging scans, and clinical and neuropsychological data were obtained from virologically controlled PLWH (viral load of <50 c/mL and at least 1 year of combination antiretroviral therapy) and socioeconomically matched control participants. Magnetic resonance imaging was carried out on 3 T scanner with 8‐channel head coils and segmented using Classification using Derivative‐based Features. Multiple regression analysis was performed to examine the association between brain volume and various clinical and neuropsychiatric parameters adjusting for age, race, and sex. To evaluate longitudinal changes in brain volumes, a random coefficient model was used to evaluate the changes over time (age) adjusting for sex and race. Results: The cross‐sectional study included 164 PLWH and 51 controls, and the longitudinal study included 68 PLWH and 20 controls with 2 or more visits (mean 2.2 years, range 0.8–5.1 years). Gray matter (GM) atrophy rate was significantly higher in PLWH compared with control participants, and importantly, the GM and global atrophy was associated with the various neuropsychological domain scores. Higher volume of white matter hyperintensities were associated with increased atherosclerotic cardiovascular disease risk score, and decreased executive functioning and memory domain scores in PLWH. Interpretation: These findings suggest ongoing neurological damage even in virologically controlled participants, with significant implications for clinical management of PLWH. ANN NEUROL 2024;95:941–950 [ABSTRACT FROM AUTHOR]

Objective: Microglia/macrophages line the border of demyelinated lesions in both cerebral white matter and the cortex in the brains of multiple sclerosis patients. Microglia/macrophages associated with chronic white matter lesions are thought to be responsible for slow lesion expansion and disability progression in progressive multiple sclerosis, whereas those lining gray matter lesions are less studied. Profiling these microglia/macrophages could help to focus therapies on genes or pathways specific to lesion expansion and disease progression. Methods: We compared the morphology and transcript profiles of microglia/macrophages associated with borders of white matter (WM line) and subpial gray matter lesions (GM line) using laser capture microscopy. We performed RNA sequencing on isolated cells followed by immunocytochemistry to determine the distribution of translational products of transcripts increased in WM line microglia. Results: Cells in the WM line appear activated, with shorter processes and larger cell bodies, whereas those in the GM line appear more homeostatic, with smaller cell bodies and multiple thin processes. Transcript profiling revealed 176 genes in WM lines and 111 genes in GM lines as differentially expressed. Transcripts associated with immune activation and iron homeostasis were increased in WM line microglia, whereas genes belonging to the canonical Wnt signaling pathway were increased in GM line microglia. Interpretation: We propose that the mechanisms of demyelination and dynamics of lesion expansion are responsible for differential transcript expression in WM lines and GM lines, and posit that increased expression of the Fc epsilon receptor, spleen tyrosine kinase, and Bruton's tyrosine kinase, play a key role in regulating microglia/macrophage function at the border of chronic active white matter lesions. ANN NEUROL 2024;95:907–916 [ABSTRACT FROM AUTHOR]

Neuroferritinopathy is a disorder of neurodegeneration with brain iron accumulation that has no proven disease‐modifying treatments. Clinical trials require biomarkers of iron deposition. We examined brain iron accumulation in one presymptomatic FTL mutation carrier, two individuals with neuroferritinopathy and one healthy control using ultra‐high‐field 7T MRI. There was increased magnetic susceptibility, suggestive of iron deposition, in superficial and deep gray matter in both presymptomatic and symptomatic neuroferritinopathy. Cavitation of the putamen and globus pallidus increased with disease stage and at follow up. The widespread brain iron deposition in presymptomatic and early disease provides an opportunity for monitoring disease‐modifying intervention. [ABSTRACT FROM AUTHOR]

Objective: Abnormalities in the gray matter structure of cerebral small vessel disease (CSVD) have been observed throughout the brain. However, whether cortico‐cortical connections exist between regions of gray matter atrophy in patients with CSVD has not been fully elucidated. This question was tested by comparing the gray matter covariance networks in CSVD patients with and without cognitive impairment (CI). Methods: We performed multivariate modeling of the gray matter volume measurements of 61 patients with CI (CSVD‐CI), 85 patients without CI (CSVD‐NC), and 108 healthy controls using source‐based morphological analysis (SBM) to obtain gray matter structural covariance networks at the population level. Then, correlations between structural covariance networks and cognitive functions were analyzed in CSVD patients. Finally, a support vector machine (SVM) classifier was used with the gray matter covariance network as a classification feature to identify CI among the CSVD population. Results: The results of the analysis of all the subjects showed that compared with healthy controls, the expression of the thalamic covariance network, cerebellum covariance network, and calcarine cortex covariance network was reduced in patients with CSVD. Moreover, CSVD‐CI patients showed a significant reduction in the expression of the thalamic covariance network, encompassing the thalamus and the parahippocampal gyrus, relative to CSVD‐NC patients, which persisted after excluding CSVD patients with thalamic lacunes. In patients with CSVD, cognitive functions were positively correlated with measures of the thalamic covariance network. More than 80% of CSVD patients with CI were correctly identified by the SVM classifier. Interpretation: Our findings provide new evidence to explain the distribution state of gray matter reduction in CSVD patients, and the thalamic covariance network is the core region for early gray matter reduction during the development of CSVD disease, which is related to cognitive deficits. Reduced expression of thalamic covariance networks may provide a neuroimaging biomarker for the early identification of cognitive impairment in CSVD patients. [ABSTRACT FROM AUTHOR]

Background: Age-related declines in olfaction contribute to low quality of life and appear to occur with declines in cognitive function, including diminished episodic memory. We tested the hypothesis that low gray matter volume within cortical regions that support olfaction and episodic memory can explain age-related differences in olfactory and episodic memory functions. Methods: T1-weighted images, Sniffin' Sticks olfactory measures, and the NIH Toolbox-Cognition Battery were administered to 131 middle-aged to older adults (50-86 years; 66% female). Correlation was used to examine the associations between these measures. A network-based image processing approach was then used to examine the degree to which spatial patterns of gray matter variance were related to the olfactory and cognitive measures. Structural equation modeling was used to characterize the relative specificity of olfactory, cognitive, gray matter, and aging associations. Results: Olfactory threshold, discrimination, and identification exhibited small to medium effect size associations with episodic memory performance (rs=0.27-0.42, ps < 0.002). Gray matter volume within medial temporal and orbitofrontal cortex was also related to olfactory (discrimination and identification) and episodic memory function (rs = 0.21-0.36, ps < 0.019). Age and episodic memory explained the same variance in olfaction that was explained by the medial temporal and orbitofrontal pattern of gray matter volume. Conclusions: The results of this cross-sectional study suggest that identifying mechanisms contributing to differences in medial temporal and orbitofrontal cortex will advance our understanding of co-morbid olfactory and cognitive declines. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) levels have increased globally, which is considered the sixth reason for deaths. So, a requirement exists for economic and quantitative methods to follow up the gradual progression of AD. The current study presents a simulation for a non‐irradiated, safe, wearable, and noninvasive mobile approach for detecting the progression of Alzheimer's brain atrophy using the optical diffusion technique and for investigating the difference between the normal and the diseased brain. The virtual study was accomplished using COMSOL Multiphysics. The simulated head is implemented as the following: scalp, skull, cerebrospinal fluid, gray matter, and white matter. The optical properties of the heterogeneous tissue are observed using the fluence rate after irradiating the head with different wavelengths (630, 700, 810, 915, and 1000 nm) of lasers. Two assessment techniques were applied to evaluate the brain atrophy measurements; the first technique was an array of photodetectors, which were lined at the head posterior, while a matrix of photodetectors was applied over the head surface in the second technique. The results show that the surface photodetectors approach differentiates the normal from AD brains without measuring the brain atrophy percentages by applying 630 nm. The array of photodetectors distinguishes normal from AD brains without detecting the brain atrophy percentages when the wavelengths 630, 700, and 810 nm were applied. The line detector at 1000 nm evaluates the brain atrophy percentages with AD. The future explores applying those techniques in vivo and analyzing the information by the spectrometer for extensively safer early detection of neural disorders. [ABSTRACT FROM AUTHOR]

Background and Purpose: Despite reports of changes in gray matter and white matter in individuals with migraines, research on detecting whole‐brain gross volume changes in migraines is very rare. Therefore, we aimed to investigate gross volume changes associated with migraine and test its potential in developing a neuroimaging biomarker for objective diagnosis of migraine. Methodology: In this study, 45 patients with migraine and 46 healthy controls were scanned using a 3T MRI scanner, and 3D, T1‐weighted brain MR images were obtained. First, Tensor‐based morphometry and Voxel‐based morphometry were performed using Computational Anatomy Toolbox (CAT 12) to compute gross volumes, gray matter volumes, white matter volumes, and cerebrospinal fluid volumes. Univariate analyses were performed using two‐sample t‐test and the results were corrected for multiple comparisons. Second, multivariate pattern analyses (MVPA) were conducted to classify the patients with migraine and healthy controls. Results: Reduced gross volumes in patients were detected in middle frontal gyrus, superior frontal gyrus, inferior temporal gyrus and middle temporal gyrus of right cerebrum, middle temporal gyrus and angular gyrus of the left cerebrum, cuneus, and left cerebellum. Reduced gray matter volumes were detected in superior frontal, right middle frontal, right inferior temporal, and right middle temporal. The results of MVPA indicated that gross volume changes can improve the classification accuracy (73.63%) than other structural metrics such as gray matter (70%), white matter (66.3%), and cerebrospinal fluid volumes (58.69%). Conclusion: We conclude that the gross volumetric alterations can serve as a better neuroimaging marker for the objective diagnosis of migraine. [ABSTRACT FROM AUTHOR]

Summary: The combination of brain structural and functional connectivity offers complementary insights into its organisation. Multilayer network analysis explores various relationships across different layers within a single system. We aimed to investigate changes in the structural and functional multilayer network in 69 patients with primary restless legs syndrome (RLS) compared with 50 healthy controls. Participants underwent diffusion tensor imaging (DTI) and resting state‐functional magnetic resonance imaging (rs‐fMRI) using a three‐tesla MRI scanner. We constructed a structural connectivity matrix derived from DTI using a DSI program and made a functional connectivity matrix based on rs‐fMRI using an SPM program and CONN toolbox. A multilayer network analysis, using BRAPH program, was then conducted to assess the connectivity patterns in both groups. At the global level, significant differences there were between the patients with RLS and healthy controls. The average multiplex participation was lower in patients with RLS than in healthy controls (0.804 vs. 0.821, p = 0.042). Additionally, several regions showed significant differences in the nodal level in multiplex participation between patients with RLS and healthy controls, particularly the frontal and temporal lobes. The regions affected included the inferior frontal gyrus, medial orbital gyrus, precentral gyrus, rectus gyrus, insula, superior and inferior temporal gyrus, medial and lateral occipitotemporal gyrus, and temporal pole. These results represent evidence of diversity in interactions between structural and functional connectivity in patients with RLS, providing a more comprehensive understanding of the brain network in RLS. This may contribute to a precise diagnosis of RLS, and aid the development of a biomarker to track treatment effectiveness. [ABSTRACT FROM AUTHOR]

Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas‐based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age‐specific 1‐ and 2‐year‐old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high‐quality DTI and structural MRI data were obtained from 50 healthy children to build up three‐dimensional age‐specific 1‐ and 2‐year‐old brain templates and atlases. Age‐specific templates include a single‐subject template as well as two population‐averaged templates from linear and nonlinear transformation, respectively. Each age‐specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age‐specific atlases. These established 1‐ and 2‐year‐old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy. [ABSTRACT FROM AUTHOR]

Developmental topographical disorientation (DTD) refers to the lifelong inability to orient by means of cognitive maps in familiar surroundings despite otherwise well‐preserved general cognitive functions, and the absence of any acquired brain injury or neurological condition. While reduced functional connectivity between the hippocampus and other brain regions has been reported in DTD individuals, no structural differences in gray matter tissue for the whole brain neither for the hippocampus were detected. Considering that the human hippocampus is the main structure associated with cognitive map‐based navigation, here, we investigated differences in morphological and morphometric hippocampal features between individuals affected by DTD (N = 20) and healthy controls (N = 238). Specifically, we focused on a developmental anomaly of the hippocampus that is characterized by the incomplete infolding of hippocampal subfields during fetal development, giving the hippocampus a more round or pyramidal shape, called incomplete hippocampal inversion (IHI). We rated IHI according to standard criteria and extracted hippocampal subfield volumes after FreeSurfer's automatic segmentation. We observed similar IHI prevalence in the group of individuals with DTD with respect to the control population. Neither differences in whole hippocampal nor major hippocampal subfield volumes have been observed between groups. However, when assessing the IHI independent criteria, we observed that the hippocampus in the DTD group is more medially positioned comparing to the control group. In addition, we observed bigger hippocampal fissure volume for the DTD comparing to the control group. Both of these findings were stronger for the right hippocampus comparing to the left. Our results provide new insights regarding the hippocampal morphology of individuals affected by DTD, highlighting the role of structural anomalies during early prenatal development in line with the developmental nature of the spatial disorientation deficit. [ABSTRACT FROM AUTHOR]

Introduction: Hemodialysis patients have increased white matter and gray matter pathology in the brain relative to controls based on MRI. Diffusion tensor imaging is useful in detecting differences between hemodialysis and controls but has not identified the expected longitudinal decline in hemodialysis patients. In this study we implemented specialized post‐processing techniques to reduce noise to detect longitudinal changes in diffusion tensor imaging parameters and evaluated for any association with changes in cognition. Methods: We collected anatomical and diffusion MRIs as well as cognitive testing from in‐center hemodialysis patients at baseline and 1 year later. Gray matter thickness, white matter volume, and white matter diffusion tensor imaging parameters were measured to identify longitudinal changes. We analyzed the diffusion tensor imaging parameters by averaging the whole white matter and using a pothole analysis. Eighteen hemodialysis patients were included in the longitudinal analysis and 15 controls were used for the pothole analysis. We used the NIH Toolbox Cognition Battery to assess cognitive performance over the same time frame. Findings: Over the course of a year on hemodialysis, we found a decrease in white matter fractional anisotropy across the entire white matter (p < 0.01), and an increase in the number of white matter fractional anisotropy voxels below pothole threshold (p = 0.03). We did not find any relationship between changes in whole brain structural parameters and cognitive performance. Discussion: By employing noise reducing techniques, we were able to detect longitudinal changes in diffusion tensor imaging parameters in hemodialysis patients. The fractional anisotropy declines over the year indicate significant decreases in white matter health. However, we did not find that declines in fractional anisotropy was associated with declines in cognitive performance. [ABSTRACT FROM AUTHOR]

Objective: Few studies have focused on brain structure in atypical anorexia nervosa (atypical AN). This study investigates differences in gray matter volume (GMV) between females with anorexia nervosa (AN) and atypical AN, and healthy controls (HC). Method: Structural magnetic resonance imaging data were acquired for 37 AN, 23 atypical AN, and 41 HC female participants. Freesurfer was used to extract GMV, cortical thickness, and surface area for six brain lobes and associated cortical regions of interest (ROI). Primary analyses employed linear mixed‐effects models to compare group differences in lobar GMV, followed by secondary analyses on ROIs within significant lobes. We also explored relationships between cortical gray matter and both body mass index (BMI) and symptom severity. Results: Our primary analyses revealed significant lower GMV in frontal, temporal and parietal areas (FDR <.05) in AN and atypical AN when compared to HC. Lobar GMV comparisons were non‐significant between atypical AN and AN. The parietal lobe exhibited the greatest proportion of affected cortical ROIs in both AN versus HC and atypical AN versus HC. BMI, but not symptom severity, was found to be associated with cortical GMV in the parietal, frontal, temporal, and cingulate lobes. No significant differences were observed in cortical thickness or surface area. Discussion: We observed lower GMV in frontal, temporal, and parietal areas, when compared to HC, but no differences between AN and atypical AN. This indicates potentially overlapping structural phenotypes between these disorders and evidence of brain changes among those who are not below the clinical underweight threshold. Public significance: Despite individuals with atypical anorexia nervosa presenting above the clinical weight threshold, lower cortical gray matter volume was observed in partial, temporal, and frontal cortices, compared to healthy individuals. No significant differences were found in cortical gray matter volume between anorexia nervosa and atypical anorexia nervosa. This underscores the importance of continuing to assess and target weight gain in clinical care, even for those who are presenting above the low‐weight clinical criteria. [ABSTRACT FROM AUTHOR]

Regular participation in sports results in a series of physiological adaptations. However, little is known about the brain adaptations to physical activity. Here we aimed to investigate whether young endurance athletes and non‐athletes differ in the gray and white matter of the brain and whether cardiorespiratory fitness (CRF) is associated with these differences. We assessed the CRF, volumes of the gray and white matter of the brain using structural magnetic resonance imaging (sMRI), and brain white matter connections using diffusion magnetic resonance imaging (dMRI) in 20 young male endurance athletes and 21 healthy non‐athletes. While total brain volume was similar in both groups, the white matter volume was larger and the gray matter volume was smaller in the athletes compared to non‐athletes. The reduction of gray matter was located in the association areas of the brain that are specialized in processing of sensory stimuli. In the microstructure analysis, significant group differences were found only in the association tracts, for example, the inferior occipito‐frontal fascicle (IOFF) showing higher fractional anisotropy and lower radial diffusivity, indicating stronger myelination in this tract. Additionally, gray and white matter brain volumes, as well as association tracts correlated with CRF. No changes were observed in other brain areas or tracts. In summary, the brain signature of the endurance athlete is characterized by changes in the integration of sensory and motor information in the association areas. This study unveils the intriguing relationship between regular endurance sports participation, brain structure, and cardiorespiratory fitness. The findings shed light on the intricate interplay between physical activity and brain physiology, contributing valuable insights to our understanding of the brain's response to exercise. [ABSTRACT FROM AUTHOR]

Nodular heterotopia (NH)–related drug‐resistant epilepsy is challenging due to the deep location of the NH and the complexity of the underlying epileptogenic network. Using ictal stereo‐electroencephalography (SEEG) and functional connectivity (FC) analyses in 14 patients with NH‐related drug‐resistant epilepsy, we aimed to determine the leading structure during seizures. For this purpose, we compared node IN and OUT strength between bipolar channels inside the heterotopia and inside gray matter, at the group level and at the individual level. At seizure onset, the channels within NH belonging to the epileptogenic and/or propagation network showed higher node OUT‐strength than the channels within the gray matter (p =.03), with higher node OUT‐strength than node IN‐strength (p =.03). These results are in favor of a "leading" role of NH during seizure onset when involved in the epileptogenic‐ or propagation‐zone network (50% of patients). However, when looking at the individual level, no significant difference between NH and gray matter was found, except for one patient (in two of three seizures). This result confirms the heterogeneity and the complexity of the epileptogenic network organization in NH and the need for SEEG exploration to characterize more precisely patient‐specific epileptogenic network organization. [ABSTRACT FROM AUTHOR]

Gray matter (GM) atrophy and white matter (WM) lesions may contribute to cognitive decline in patients with delayed neurological sequelae (DNS) after carbon monoxide (CO) poisoning. However, there is currently a lack of evidence supporting this relationship. This study aimed to investigate the volume of GM, cortical thickness, and burden of WM lesions in 33 DNS patients with dementia, 24 DNS patients with mild cognitive impairment, and 51 healthy controls. Various methods, including voxel‐based, deformation‐based, surface‐based, and atlas‐based analyses, were used to examine GM structures. Furthermore, we explored the connection between GM volume changes, WM lesions burden, and cognitive decline. Compared to the healthy controls, both patient groups exhibited widespread GM atrophy in the cerebral cortices (for volume and cortical thickness), subcortical nuclei (for volume), and cerebellum (for volume) (p <.05 corrected for false discovery rate [FDR]). The total volume of GM atrophy in 31 subregions, which included the default mode network (DMN), visual network (VN), and cerebellar network (CN) (p <.05, FDR‐corrected), independently contributed to the severity of cognitive impairment (p <.05). Additionally, WM lesions impacted cognitive decline through both direct and indirect effects, with the latter mediated by volume reduction in 16 subregions of cognitive networks (p <.05). These preliminary findings suggested that both GM atrophy and WM lesions were involved in cognitive decline in DNS patients following CO poisoning. Moreover, the reduction in the volume of DMN, VN, and posterior CN nodes mediated the WM lesions‐induced cognitive decline. [ABSTRACT FROM AUTHOR]

Cognitive reserve (CR) explains differential susceptibility of cognitive performance to neuropathology. However, as brain pathologies progress, cognitive decline occurs even in individuals with initially high CR. The interplay between the structural brain health (= level of brain reserve) and CR‐related brain networks therefore requires further research. Our sample included 142 individuals aged 60–70 years. National Adult Reading Test intelligence quotient (NART‐IQ) was our CR proxy. On an in‐scanner Letter Sternberg task, we used ordinal trend (OrT) analysis to extract a task‐related brain activation pattern (OrT slope) for each participant that captures increased expression with task load (one, three, and six letters). We assessed whether OrT slope represents a neural mechanism underlying CR by associating it with task performance and NART‐IQ. Additionally, we investigated how the following brain reserve measures affect the association between NART‐IQ and OrT slope: mean cortical thickness, total gray matter volume, and brain volumes proximal to the areas contained in the OrT patterns. We found that higher OrT slope was associated with better task performance and higher NART‐IQ. Further, the brain reserve measures were not directly associated with OrT slope, but they affected the relationship between NART‐IQ and OrT slope: NART‐IQ was associated with OrT slope only in individuals with high brain reserve. The degree of brain reserve has an impact on how (and perhaps whether) CR can be implemented in brain networks in older individuals. [ABSTRACT FROM AUTHOR]

Background: Prior research has shown smaller cortical and subcortical gray matter volumes among individuals with attention‐deficit/hyperactivity disorder (ADHD). However, neuroimaging studies often do not differentiate between inattention and hyperactivity/impulsivity, which are distinct core features of ADHD. The present study uses an approach to disentangle overlapping variance to examine the neurostructural heterogeneity of inattention and hyperactivity/impulsivity dimensions. Methods: We analyzed data from 10,692 9‐ to 10‐year‐old children from the Adolescent Brain Cognitive Development (ABCD) Study. Confirmatory factor analysis was used to derive factors representing inattentive and hyperactive/impulsive traits. We employed structural equation modeling to examine these factors' associations with gray matter volume while controlling for the shared variance between factors. Results: Greater endorsement of inattentive traits was associated with smaller bilateral caudal anterior cingulate and left parahippocampal volumes. Greater endorsement of hyperactivity/impulsivity traits was associated with smaller bilateral caudate and left parahippocampal volumes. The results were similar when accounting for socioeconomic status, medication, and in‐scanner motion. The magnitude of these findings increased when accounting for overall volume and intracranial volume, supporting a focal effect in our results. Conclusions: Inattentive and hyperactivity/impulsivity traits show common volume deficits in regions associated with visuospatial processing and memory while at the same time showing dissociable differences, with inattention showing differences in areas associated with attention and emotion regulation and hyperactivity/impulsivity associated with volume differences in motor activity regions. Uncovering such biological underpinnings within the broader disorder of ADHD allows us to refine our understanding of ADHD presentations. [ABSTRACT FROM AUTHOR]

Recent studies have shown that white–gray contrast (WGC) of either cortical or subcortical gray matter provides for accurate predictions of age in typically developing (TD) children, and that, at least for the cortex, it changes differently with age in subjects with autism spectrum disorder (ASD) compared to their TD peers. Our previous study showed different patterns of contrast change between ASD and TD in sensorimotor and association cortices. While that study was confined to the cortex, we hypothesized that subcortical structures, particularly the thalamus, were involved in the observed cortical dichotomy between lower and higher processing. The current paper investigates that hypothesis using the WGC measures from the thalamus in addition to those from the cortex. We compared age‐related WGC changes in the thalamus to those in the cortex. To capture the simultaneity of this change across the two structures, we devised a metric capturing the co‐development of the thalamus and cortex (CoDevTC), proportional to the magnitude of cortical and thalamic age‐related WGC change. We calculated this metric for each of the subjects in a large homogeneous sample taken from the Autism Brain Imaging Data Exchange (ABIDE) (N = 434). We used structural MRI data from the largest high‐quality cross‐sectional sample (NYU) as well as two other large high‐quality sites, GU and OHSU, all three using Siemens 3T scanners. We observed that the co‐development features in ASD and TD exhibit contrasting patterns; specifically, some higher‐order thalamic nuclei, such as the lateral dorsal nucleus, exhibited reduction in codevelopment with most of the cortex in ASD compared to TD. Moreover, this difference in the CoDevTC pattern correlates with a number of behavioral measures across multiple cognitive and physiological domains. The results support previous notions of altered connectivity in autism, but add more specific evidence about the heterogeneity in thalamocortical development that elucidates the mechanisms underlying the clinical features of ASD. [ABSTRACT FROM AUTHOR]

Background: A growing number of experimental studies have shown an association between the gut microbiota (GM) and facial skin aging. However, the causal relationship between GM and facial skin aging remains unclear to date. Methods: We conducted a two‐sample Mendelian randomization (MR) analysis to investigate the potential causal relationship between GM and facial skin aging. MR analysis was mainly performed using the inverse‐variance weighting (IVW) method, complemented by the weighted median (MW) method, MR‐Egger regression, and weighted mode, and sensitivity analysis was used to test the reliability of MR analysis results. Results: Eleven GM taxa associated with facial skin aging were identified by IVW method analysis, Family Victivallaceae (p = 0.010), Genus Eubacterium coprostanoligenes group (p = 0.038), and Genus Parasutterella (p = 0.011) were negatively associated with facial skin aging, while Phylum Verrucomicrobia (p = 0.034), Family Lactobacillaceae (p = 0.017) and its subgroups Genus Lactobacillus (p = 0.038), Genus Parabacteroides (p = 0.040), Genus Eggerthella (p = 0.049), Genus Family XIII UCG001 (p = 0.036), Genus Phascolarctobacterium (p = 0.027), and Genus Ruminococcaceae UCG005 (p = 0.012) were positively associated with facial skin aging. At Class and Order levels, we did not find a causal relationship between GM and facial skin aging. Results of sensitivity analyses did not show evidence of pleiotropy and heterogeneity. Conclusion: Our findings confirm the causal relationship between GM and facial skin aging, providing a new perspective on delaying facial aging. [ABSTRACT FROM AUTHOR]

Multiple sclerosis is a chronic autoimmune disease of the central nervous system characterized by myelin loss, axonal damage, and glial scar formation. Still, the underlying processes remain unclear, as numerous pathways and factors have been found to be involved in the development and progression of the disease. Therefore, it is of great importance to find suitable animal models as well as reliable methods for their precise and reproducible analysis. Here, we describe the impact of demyelination on clinically relevant gray matter regions of the hippocampus and cerebral cortex, using the previously established cuprizone model for aged mice. We could show that bioinformatic image analysis methods are not only suitable for quantification of cell populations, but also for the assessment of de‐ and remyelination processes, as numerous objective parameters can be considered for reproducible measurements. After cuprizone‐induced demyelination, subsequent remyelination proceeded slowly and remained incomplete in all gray matter areas studied. There were regional differences in the number of mature oligodendrocytes during remyelination suggesting region‐specific differences in the factors accounting for remyelination failure, as, even in the presence of oligodendrocytes, remyelination in the cortex was found to be impaired. Upon cuprizone administration, synaptic density and dendritic volume in the gray matter of aged mice decreased. The intensity of synaptophysin staining gradually restored during the subsequent remyelination phase, however the expression of MAP2 did not fully recover. Microgliosis persisted in the gray matter of aged animals throughout the remyelination period, whereas extensive astrogliosis was of short duration as compared to white matter structures. In conclusion, we demonstrate that the application of the cuprizone model in aged mice mimics the impaired regeneration ability seen in human pathogenesis more accurately than commonly used protocols with young mice and therefore provides an urgently needed animal model for the investigation of remyelination failure and remyelination‐enhancing therapies. [ABSTRACT FROM AUTHOR]

In this article, we present a new approach to distinguish progressive mild cognitively impaired (pMCI) subjects, who eventually develop Alzheimer's disease (AD) from stable MCI (sMCI) subjects whose situation does not deteriorate into AD. The proposed approach combines the discriminating capabilities of classifiers and representation learning capacities of autoencoders into a unified architecture, and is hence termed as joint autoencoder and classifier deep neural network (JACDNN). JACDNN employs a single classifier and multiple autoencoders that are trained together to perform pattern classification. The classifier in JACDNN is trained using standard approaches to distinguish between subject from different classes using the binary cross entropy loss. The autoencoders in JACDNN, regularizes individual layers in the network used for classification to learn representations useful for reconstructing a given input. The performance of JACDNN has been evaluated on several machine learning problems pertaining to dementia, namely AD versus cognitively normal (CN) subjects, AD versus sMCI, CN versus pMCI, and pMCI versus sMCI. These problems are targeted using two datasets. The first dataset consist of gray matter (GM) features of subjects and the second dataset consist of combination of GM and white matter (WM) features. It is observed that better classification results are obtained when the classifier is built on GM and WM as compared with GM features alone. Performance comparison of JACDNN with other existing approaches has been conducted for these problems. The results clearly indicate that JACDNN performs better than other existing approaches for these problems. [ABSTRACT FROM AUTHOR]

Background: Despite extensive efforts to obtain accurate segmentation of magnetic resonance imaging (MRI) scans of a head, it remains challenging primarily due to variations in intensity distribution, which depend on the equipment and parameters used. Purpose: The goal of this study is to evaluate the effectiveness of an automatic segmentation method for head MRI scans using a multistep Dense U‐Net (MDU‐Net) architecture. Methods: The MDU‐Net‐based method comprises two steps. The first step is to segment the scalp, skull, and whole brain from head MRI scans using a convolutional neural network (CNN). In the first step, a hybrid network is used to combine 2.5D Dense U‐Net and 3D Dense U‐Net structure. This hybrid network acquires logits in three orthogonal planes (axial, coronal, and sagittal) using 2.5D Dense U‐Nets and fuses them by averaging. The resultant fused probability map with head MRI scans then serves as the input to a 3D Dense U‐Net. In this process, different ratios of active contour loss and focal loss are applied. The second step is to segment the cerebrospinal fluid (CSF), white matter, and gray matter from extracted brain MRI scans using CNNs. In the second step, the histogram of the extracted brain MRI scans is standardized and then a 2.5D Dense U‐Net is used to further segment the brain's specific tissues using the focal loss. A dataset of 100 head MRI scans from an OASIS‐3 dataset was used for training, internal validation, and testing, with ratios of 80%, 10%, and 10%, respectively. Using the proposed approach, we segmented the head MRI scans into five areas (scalp, skull, CSF, white matter, and gray matter) and evaluated the segmentation results using the Dice similarity coefficient (DSC) score, Hausdorff distance (HD), and the average symmetric surface distance (ASSD) as evaluation metrics. We compared these results with those obtained using the Res‐U‐Net, Dense U‐Net, U‐Net++, Swin‐Unet, and H‐Dense U‐Net models. Results: The MDU‐Net model showed DSC values of 0.933, 0.830, 0.833, 0.953, and 0.917 in the scalp, skull, CSF, white matter, and gray matter, respectively. The corresponding HD values were 2.37, 2.89, 2.13, 1.52, and 1.53 mm, respectively. The ASSD values were 0.50, 1.63, 1.28, 0.26, and 0.27 mm, respectively. Comparing these results with other models revealed that the MDU‐Net model demonstrated the best performance in terms of the DSC values for the scalp, CSF, white matter, and gray matter. When compared with the H‐Dense U‐Net model, which showed the highest performance among the other models, the MDU‐Net model showed substantial improvements in the HD view, particularly in the gray matter region, with a difference of approximately 9%. In addition, in terms of the ASSD, the MDU‐Net model outperformed the H‐Dense U‐Net model, showing an approximately 7% improvements in the white matter and approximately 9% improvements in the gray matter. Conclusion: Compared with existing models in terms of DSC, HD, and ASSD, the proposed MDU‐Net model demonstrated the best performance on average and showed its potential to enhance the accuracy of automatic segmentation for head MRI scans. [ABSTRACT FROM AUTHOR]

Background and Purpose: Magnetic resonance spectroscopy (MRS) measures neurochemicals in vivo. Glutathione (GSH) is a neuroprotective chemical shown to vary significantly in patients with Alzheimer's disease (AD). This work investigates the reproducibility of GSH measures in the mesial temporal lobe (MTL) to identify its potential clinical utility. Methods: MRS data were acquired from eight healthy volunteers (31.1 ± 5.2 years; 4 male/female) using Mescher‐Garwood‐Point Resolved Spectroscopy (MEGA‐PRESS) from the MTL in the left hemisphere across two scan sessions in the same visit. Total N‐acetylaspartate (tNAA), choline (tCho), creatine (tCr), and GSH were quantified. Reproducibility of quantifications of these neurochemicals were tested using coefficient of variance (CV) between scan sessions. Reproducibility of voxel placement on the left MTL was calculated by measuring the tissue overlap and percent of hippocampus within that voxel. CV measured across different scan sessions in each individual, with a CV<15% was accepted as "good" reproducibility. Paired t‐tests were carried out to establish the significant differences between the two scans across each individual with p<.05 as significant. Results: TNAA (%CV = 7.2; p =.5), tCr (%CV = 7.8; p =.6) and tCho (%CV = 9.3; p =.4), and GSH (%CV = 22; p =.1). The dice coefficient that reflects the level of overlap of hippocampal tissue in the voxel was shown to be 0.8 ± 0.1. Voxel tissue composition were: Scan 1 (cerebrospinal fluid [CSF]: 5 ± 1%, white matter [WM]: 52 ± 3%, gray matter [GM]: 43 ± 3%); Scan 2 (CSF: 5 ± 1%, WM: 52 ± 4%, GM: 44 ± 4%). Conclusion: The data suggest measures of abundant metabolites in the MTL using the MEGA‐PRESS sequence has a high reproducibility. Reproducibility of GSH in this area was poorer requiring care when interpreting measures of GSH in the MTL for clinical translational purposes. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to compare cerebrovascular reactivity between patients with migraine and controls using state‐of‐the‐art magnetic resonance imaging (MRI) techniques. Background: Migraine is associated with an increased risk of cerebrovascular disease, but the underlying mechanisms are still not fully understood. Impaired cerebrovascular reactivity has been proposed as a link. Previous studies have evaluated cerebrovascular reactivity with different methodologies and results are conflicting. Methods: In this single‐center, observational, case–control study, we included 31 interictal patients with migraine without aura (aged 19–66 years, 17 females) and 31 controls (aged 22–64 years, 18 females) with no history of vascular disease. Global and regional cerebrovascular reactivities were assessed with a dual‐echo arterial spin labeling (ASL) 3.0 T MRI scan of the brain which measured the change in cerebral blood flow (CBF) and BOLD (blood oxygen level dependent) signal to inhalation of 5% carbon dioxide. Results: When comparing patients with migraine to controls, cerebrovascular reactivity values were similar between the groups, including mean gray matter CBF‐based cerebrovascular reactivity (3.2 ± 0.9 vs 3.4 ± 1% ΔCBF/mmHg CO2; p = 0.527), mean gray matter BOLD‐based cerebrovascular reactivity (0.18 ± 0.04 vs 0.18 ± 0.04% ΔBOLD/mmHg CO2; p = 0.587), and mean white matter BOLD‐based cerebrovascular reactivity (0.08 ± 0.03 vs 0.08 ± 0.02% ΔBOLD/mmHg CO2; p = 0.621).There was no association of cerebrovascular reactivity with monthly migraine days or migraine disease duration (all analyses p > 0.05). Conclusion: Cerebrovascular reactivity to carbon dioxide seems to be preserved in patients with migraine without aura. Plain Language Summary: Patients with migraine have a higher risk of vascular diseases, possibly due to a decreased function of the blood vessels, but past studies have not consistently shown this. We compared the function of blood vessels in the brains of patients with migraine and those without migraine by looking how brain blood flow changed in response to breathing in carbon dioxide. We found no differences in the ways in which blood vessels responded to inhaled carbon dioxide between the groups, which suggests that this aspect of blood vessel function does not differ between patients with and without migraine. [Correction added on 20th March 2024, after first online publication: The "Plain Language Summary" section has been added]. [ABSTRACT FROM AUTHOR]

Neuroimaging data have been widely used to understand the neural bases of human behaviors. However, most studies were either based on a few predefined regions of interest or only able to reveal limited vital regions, hence not providing an overarching description of the relationship between neuroimaging and behaviors. Here, we proposed a voxel‐based pattern regression that not only could investigate the overall brain‐associated variance (BAV) for a given behavioral measure but could also evaluate the shared neural bases between different behaviors across multiple neuroimaging data. The proposed method demonstrated consistently high reliability and accuracy through comprehensive simulations. We further implemented this approach on real data of adolescents (IMAGEN project, n = 2089) and adults (HCP project, n = 808) to investigate brain‐based variances of multiple behavioral measures, for instance, cognitive behaviors, substance use, and psychiatric disorders. Notably, intelligence‐related scores showed similar high BAVs with the gray matter volume across both datasets. Further, our approach allows us to reveal the latent brain‐based correlation across multiple behavioral measures, which are challenging to obtain otherwise. For instance, we observed a shared brain architecture underlying depression and externalizing problems in adolescents, while the symptom comorbidity may only emerge later in adults. Overall, our approach will provide an important statistical tool for understanding human behaviors using neuroimaging data. [ABSTRACT FROM AUTHOR]

Spinocerebellar ataxia type 3 (SCA3) is an inherited movement disorder characterized by a progressive decline in motor coordination. Despite the extensive functional connectivity (FC) alterations reported in previous SCA3 studies in the cerebellum and cerebellar‐cerebral pathways, the influence of these FC disturbances on the hierarchical organization of cerebellar functional regions remains unclear. Here, we compared 35 SCA3 patients with 48 age‐ and sex‐matched healthy controls using a combination of voxel‐based morphometry and resting‐state functional magnetic resonance imaging to investigate whether cerebellar hierarchical organization is altered in SCA3. Utilizing connectome gradients, we identified the gradient axis of cerebellar hierarchical organization, spanning sensorimotor to transmodal (task‐unfocused) regions. Compared to healthy controls, SCA3 patients showed a compressed hierarchical organization in the cerebellum at both voxel‐level (p <.05, TFCE corrected) and network‐level (p <.05, FDR corrected). This pattern was observed in both intra‐cerebellar and cerebellar‐cerebral gradients. We observed that decreased intra‐cerebellar gradient scores in bilateral Crus I/II both negatively correlated with SARA scores (left/right Crus I/II: r = −.48/−.50, p =.04/.04, FDR corrected), while increased cerebellar‐cerebral gradients scores in the vermis showed a positive correlation with disease duration (r =.48, p =.04, FDR corrected). Control analyses of cerebellar gray matter atrophy revealed that gradient alterations were associated with cerebellar volume loss. Further FC analysis showed increased functional connectivity in both unimodal and transmodal areas, potentially supporting the disrupted cerebellar functional hierarchy uncovered by the gradients. Our findings provide novel evidence regarding alterations in the cerebellar functional hierarchy in SCA3. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study is to investigate differences in gray matter volume and cortical complexity between Parkinson's disease with depression (PDD) patients and Parkinson's disease without depression (PDND) patients. Methods: A total of 41 PDND patients, 36 PDD patients, and 38 healthy controls (HC) were recruited and analyzed by Voxel‐based morphometry (VBM) and surface‐based morphometry (SBM). Differences in gray matter volume and cortical complexity were compared using the one‐way analysis of variance (ANOVA) and correlated with the Hamilton Depression Scale‐17 (HAMD‐17) scores. Results: PDD patients exhibited significant cortical atrophy in various regions, including bilateral medial parietal–occipital–temporal lobes, right dorsolateral temporal lobes, bilateral parahippocampal gyrus, and bilateral hippocampus, compared to HC and PDND groups. A negative correlation between the GMV of left precuneus and HAMD‐17 scores in the PDD group tended to be significant (r = −0.318, p = 0.059). Decreased gyrification index was observed in the bilateral insular and dorsolateral temporal cortex. However, there were no significant differences found in fractal dimension and sulcal depth. Conclusion: Our research shows extensive cortical structural changes in the insular cortex, parietal–occipital–temporal lobes, and hippocampal regions in PDD. This provides a morphological perspective for understanding the pathophysiological mechanism underlying depression in Parkinson's disease. [ABSTRACT FROM AUTHOR]

Objectives: Gait disorder (GD) is a common problem in cerebral small vessel disease (CSVD). This study aimed to determine (1) the early characteristics of GD in CSVD, (2) cerebellar neuroimaging features related to GD in CSVD, and (3) the association of cognitive impairment with GD. Methods: In total, 183 subjects were enrolled in this study: patients with CSVD with normal cognitive function (CSVD‐NC) group (64 subjects), patients with CSVD with mild cognitive impairment (CSVD‐MCI) group (66 subjects), and a healthy control (HC) group (53 subjects). The GD patterns were evaluated using the ReadyGo three‐dimensional motion balance testing system. Meanwhile, we analyzed the cerebrum and cerebellum structurally and functionally. Correlation analyses were conducted among gait indicators, neuroimaging features, and neuropsychological tests. Results: Both the CSVD‐NC and CSVD‐MCI groups had a reduced stride length, cortical atrophy in the left cerebellum VIIIb, and decreased functional connectivity between the left cerebellum VIIIb and left SFGmed compared with the HC group. In the correlation analysis, the gray matter probability of the left cerebellum VIIIb was closely related to stride length in the HC group. In the CSVD‐MCI group, linguistic function, memory, and attention were significantly correlated with gait performance. Conclusion: Decreased stride length was the earliest characteristic of GD in CSVD. Structural and functional regulation of the left cerebellum VIIIb could play a particularly important role in early GD in CSVD. [ABSTRACT FROM AUTHOR]

Recent studies have suggested that emotional reactivity changes with age, but the neural basis is still unclear. The insula may be critical for the emotional reactivity. The current study examined how ageing affects emotional reactivity using the emotional reactivity task data from a human sample (Cambridge Center for Age and Neuroscience, N = 243, age 18–88 years). The resting‐state magnetic resonance measurements from the same sample were used to investigate the potential mechanisms of the insula. In the initial analysis, we conducted partial correlation assessments to examine the associations between emotional reactivity and age, as well as between the gray matter volume (GMV) of the insula and age. Our results revealed that emotional reactivity, especially positive emotional reactivity, decreased with age and that the GMV of the insula was negatively correlated with age. Subsequently, the bilateral insula was divided into six subregions to calculate the whole brain resting‐state functional connectivity (rsFC). The mediating effect of the rsFC on age and emotional reactivity was then calculated. The results showed that the rsFC of the left anterior insula (AI) with the right hippocampus, and the rsFCs of the right AI with the striatum and the thalamus were mediated the relationship between positive emotional reactivity and age. Our findings suggest that attenuating emotional reactivity with age may be a strategic adaptation fostering emotional stability and diminishing emotional vulnerability. Meanwhile, the findings implicate a key role for the AI in the changes in positive emotional reactivity with age. [ABSTRACT FROM AUTHOR]

Purpose: To compare the strength of associations between different indices of cardiorespiratory fitness (CRF) and brain health outcomes in children with overweight/obesity. Methods: Participants were 100 children aged 8–11 years. CRF was assessed using treadmill exercise test (peak oxygen uptake [V̇O2peak], treadmill time, and V̇O2 at ventilatory threshold) and 20‐metre shuttle run test (20mSRT, laps, running speed, estimated V̇O2peak using the equations by Léger et al., Mahar et al., and Matsuzaka et al.). Intelligence, executive functions, and academic performance were assessed using validated methods. Total gray matter and hippocampal volumes were assessed using structural MRI. Results: V̇O2peak/body mass (β = 0.18, 95% CI = 0.01–0.35) and treadmill time (β = 0.18–0.21, 95% CI = 0.01–0.39) were positively associated with gray matter volume. 20mSRT laps were positively associated with executive functions (β = 0.255, 95% CI = 0.089–0.421) and academic performance (β = 0.199–0.255, 95% CI = 0.006–0.421), and the running speed was positively associated with executive functions (β = 0.203, 95% CI = 0.039–0.367). Estimated V̇O2peak/Léger et al. was positively associated with intelligence, executive functions, academic performance, and gray matter volume (β = 0.205–0.282, 95% CI = 0.013–0.500). Estimated V̇O2peak/Mahar et al. and V̇O2peak/Matsuzaka et al. (speed) were positively associated with executive functions (β = 0.204–0.256, 95% CI = 0.031–0.436). Conclusion: Although V̇O2peak is considered the gold standard indicator of CRF in children, peak performance (laps or running speed) and estimated V̇O2peak/Léger et al. derived from 20mSRT had stronger and more consistent associations with brain health outcomes than other indices of CRF in children with overweight/obesity. [ABSTRACT FROM AUTHOR]

Despite the importance of the developing cerebellum on cognition, the associations between physical fitness and cerebellar volume in adolescents remain unclear. We explored the associations of physical fitness with gray matter (GM) volume of VI, VIIb and Crus I & II, which are cerebellar lobules related to cognition, in 40 (22 females; 17.9 ± 0.8 year‐old) adolescents, and whether the associations were sex‐specific. Peak oxygen uptake (V̇O2peak) and power were assessed by maximal ramp test on a cycle ergometer, muscular strength with standing long jump (SLJ), speed‐agility with the shuttle‐run test (SRT), coordination with the Box and Block Test (BBT) and neuromuscular performance index (NPI) as the sum of SLJ, BBT and SRT z‐scores. Body composition was measured using a dual‐energy X‐ray absorptiometry. Cerebellar volumes were assessed by magnetic resonance imaging. V̇O2peak relative to lean mass was inversely associated with the GM volume of the cerebellum (standardized regression coefficient (β) = −0.038, 95% confidence interval (CI) ‐0.075 to 0.001, p = 0.044). Cumulative NPI was positively associated with the GM volume of Crus I (β = 0.362, 95% CI 0.045 to 0.679, p = 0.027). In females, better performance in SRT was associated with a larger GM volume of Crus I (β = −0.373, 95% CI ‐0.760 to −0.028, p = 0.036). In males, cumulative NPI was inversely associated with the GM volume of Crus II (β = −0.793, 95% CI ‐1.579 to −0.008 p = 0.048). Other associations were nonsignificant. In conclusion, cardiorespiratory fitness, neuromuscular performance and speed‐agility were associated with cerebellar GM volume, and the strength and direction of associations were sex‐specific. [ABSTRACT FROM AUTHOR]

Objectives: We have previously demonstrated difficulties in written production in dementia with Lewy bodies (DLB) patients. We now aim to determine the neural correlates of writing production in DLB, combining clinical data and structural MRI measures. Method: Sixteen prodromal to mild DLB patients were selected to participate in the study. The GREMOTS test was used to assess writing production. Using three‐dimensional T1 brain MRI images, correlations between the GREMOTS test and grey matter (GM) volume were performed using voxel‐based morphometry (VBM; SPM12, XjView and Matlab R2021b softwares). Results: VBM analysis (p < 0.001, uncorrected) revealed a positive and significant correlation between both left anterior insula and left supramarginal gyrus GM volumes and DLB patients' ability to write logatoms using the phonological route. The handwriting deficit was negatively and significantly correlated to the supplementary motor area. The parkinsonism‐like characteristics of agraphia were negatively and significantly correlated with both right anterior and right posterior cerebellum GM volumes. Our study also revealed a negative and significant correlation between grammatical spelling impairments and an area of the orbitofrontal gyrus, and a negative and significant correlation between supramarginal gyrus and general slowness in dictation tasks. Conclusion: Writing disorders in early DLB patients appears to be GM decreases in several brain regions, such as the left anterior insula, the left supramaginal gyrus, as well as two areas of the right cerebellum. Key points: The difficulties of DLB patients in WP would be underpinned by GM volume changes in several cerebral regions, our main finding being a correlation between difficulties in dictation of logatoms and decreased GM volume in the left AI.The handwriting difficulties of DLB patients may to be related to early GM changes in the SMA for praxis difficulties and in the right cerebellum for difficulties in the rhythm and fluency of writing.Grammatical difficulties in dictation of long sentences are relatively attributable to a weakness in working memory and are correlated with atrophy of the frontal gyrus.The general slowness of the patients in dictation tests are correlated with the atrophy of the left supramarginal gyrus. [ABSTRACT FROM AUTHOR]

Background and Aims: Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)‐derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies. Design and Setting: Cross‐sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14–22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17–22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22–37 years). Cases: Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected. Measurements Graph theory metrics of segregation and integration were used to summarize SCN. Findings Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = −0.029, P = 0.002], lower modularity (AUC = −0.14, P = 0.004), lower average shortest path length (AUC = −0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = −0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar. Conclusion: Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN‐derived metrics to detect brain‐related psychopathology. [ABSTRACT FROM AUTHOR]

Background and purpose: Prior studies reported conflicting findings regarding the association of nonalcoholic fatty liver disease (NAFLD) and liver fibrosis with measures of brain health. We examined whether NAFLD and liver fibrosis are associated with structural brain imaging measures in middle‐ and old‐age adults. Methods: In this cross‐sectional study among dementia‐ and stroke‐free individuals, data were pooled from the Offspring and Third Generation cohorts of the Framingham Heart Study (FHS), the Rotterdam Study (RS), and the Study of Health in Pomerania. NAFLD was assessed through abdominal imaging. Transient hepatic elastography (FibroScan) was used to assess liver fibrosis in FHS and RS. Linear regression models were used to explore the relation of NAFLD and liver fibrosis with brain volumes, including total brain, gray matter, hippocampus, and white matter hyperintensities, adjusting for potential confounders. Results were combined using fixed effects meta‐analysis. Results: In total, 5660 and 3022 individuals were included for NAFLD and liver fibrosis analyses, respectively. NAFLD was associated with smaller volumes of total brain (β = −3.5, 95% confidence interval [CI] = −5.4 to −1.7), total gray matter (β = −1.9, 95% CI = −3.4 to −0.3), and total cortical gray matter (β = −1.9, 95% CI = −3.7 to −0.01). In addition, liver fibrosis (defined as liver stiffness measure ≥8.2 kPa) was related to smaller total brain volumes (β = −7.3, 95% CI = −11.1 to −3.5). Heterogeneity between studies was low. Conclusions: NAFLD and liver fibrosis may be directly related to brain aging. Larger and prospective studies are warranted to validate these findings and identify liver‐related preventive strategies for neurodegeneration. [ABSTRACT FROM AUTHOR]

Background: Adult horses with proprioceptive ataxia and behavior changes that have histologic lesions consistent with neurodegenerative disease have been increasingly recognized. Hypothesis/Objectives: Describe the history, clinical findings and histopathologic features of horses presented to a referral institution with neuroaxonal degeneration. Animals: One hundred horses with a necropsy diagnosis of neuroaxonal degeneration compatible with neuroaxonal dystrophy/degenerative myeloencephalopathy (eNAD/EDM). Methods: Retrospective study of horses presented to the University of Pennsylvania, New Bolton Center, between 2017 and 2021 with a necropsy diagnosis of eNAD/EDM. Results: Affected horses had a median age of 8 years (range, 1‐22), and the majority were Warmbloods (72). Sixty‐eight horses had behavioral changes, and all 100 had proprioceptive ataxia (median grade, 2/5). Fifty‐seven horses had abnormal findings on cervical vertebral radiographs, and 14 had myelographic findings consistent with compressive myelopathy. No antemortem diagnostic test results were consistently associated with necropsy diagnosis of neurodegenerative disease. All 100 horses had degenerative lesions characteristic of eNAD in the brainstem gray matter, and 24 had concurrent degenerative features of EDM in the spinal cord white matter. Conclusions and Clinical Importance: Clinical and histopathologic findings in this large group of horses with neurodegenerative disease were most consistent with eNAD/EDM, but with a different signalment and clinical presentation from earlier descriptions. The increasing occurrence of neurodegenerative disease in horses and the safety risk posed emphasize the importance of focused research in affected horses. [ABSTRACT FROM AUTHOR]

Background and Purpose: Thalamic hypometabolism is a consistent finding in brain PET with F‐18 fluorodeoxyglucose (FDG) in patients with neurofibromatosis type 1 (NF1). However, the pathophysiology of this metabolic alteration is unknown. We hypothesized that it might be secondary to disturbance of peripheral input to the thalamus by NF1‐characteristic peripheral nerve sheath tumors (PNSTs). To test this hypothesis, we investigated the relationship between thalamic FDG uptake and the number, volume, and localization of PNSTs. Methods: This retrospective study included 22 adult NF1 patients (41% women, 36.2 ± 13.0 years) referred to whole‐body FDG‐PET/contrast‐enhanced CT for suspected malignant transformation of PNSTs and 22 sex‐ and age‐matched controls. Brain FDG uptake was scaled voxelwise to the individual median uptake in cerebellar gray matter. Bilateral mean and left‐right asymmetry of thalamic FDG uptake were determined using a left‐right symmetric anatomical thalamus mask. PNSTs were manually segmented in contrast‐enhanced CT. Results: Thalamic FDG uptake was reduced in NF1 patients by 2.0 standard deviations (p <.0005) compared to controls. Left‐right asymmetry was increased by 1.3 standard deviations (p =.013). Thalamic hypometabolism was higher in NF1 patients with ≥3 PNSTs than in patients with ≤2 PNSTs (2.6 vs. 1.6 standard deviations, p =.032). The impact of the occurrence of paraspinal/paravertebral PNSTs and of the mean PNST volume on thalamic FDG uptake did not reach statistical significance (p =.098 and p =.189). Left‐right asymmetry of thalamic FDG uptake was not associated with left‐right asymmetry of PNST burden (p =.658). Conclusions: This study provides first evidence of left‐right asymmetry of thalamic hypometabolism in NF1 and that it might be mediated by NF1‐associated peripheral tumors. [ABSTRACT FROM AUTHOR]

Background and purpose: Magnetic resonance imaging (MRI) measures of tissue microstructure are important for monitoring brain white matter (WM) disorders like leukodystrophies and multiple sclerosis. They should be sensitive to underlying pathological changes. Three whole‐brain isotropic quantitative methods were applied and compared within a cohort of controls and leukodystrophy patients: two novel myelin water imaging (MWI) techniques (multi‐compartment relaxometry diffusion‐informed MWI: MCR‐DIMWI, and multi‐echo T2 relaxation imaging with compressed sensing: METRICS) and neurite orientation dispersion and density imaging (NODDI). Methods: For 9 patients with different leukodystrophies (age range 0.4‐62.4 years) and 15 control subjects (2.3‐61.3 years), T1‐weighted MRI, fluid‐attenuated inversion recovery, multi‐echo gradient echo with variable flip angles, METRICS, and multi‐shell diffusion‐weighted imaging were acquired on 3 Tesla. MCR‐DIMWI, METRICS, NODDI, and quality control measures were extracted to evaluate differences between patients and controls in WM and deep gray matter (GM) regions of interest (ROIs). Pearson correlations, effect size calculations, and multi‐level analyses were performed. Results: MCR‐DIMWI and METRICS‐derived myelin water fractions (MWFs) were lower and relaxation times were higher in patients than in controls. Effect sizes of MWF values and relaxation times were large for both techniques. Differences between patients and controls were more pronounced in WM ROIs than in deep GM. MCR‐DIMWI‐MWFs were more homogeneous within ROIs and more bilaterally symmetrical than METRICS‐MWFs. The neurite density index was more sensitive in detecting differences between patients and controls than fractional anisotropy. Most measures obtained from MCR‐DIMWI, METRICS, NODDI, and diffusion tensor imaging correlated strongly with each other. Conclusion: This proof‐of‐concept study shows that MCR‐DIMWI, METRICS, and NODDI are sensitive techniques to detect changes in tissue microstructure in WM disorders. [ABSTRACT FROM AUTHOR]

Background and Purpose: Voxel‐based morphometry (VBM) studies of people with focal epilepsies revealed gray matter (GM) alterations in brain regions involved in cardiorespiratory regulation, which have been linked to the risk of sudden unexpected death in epilepsy (SUDEP). It remains unclear whether the type and localization of epileptogenic lesions influence the occurrence of such alterations. Methods: To test the hypothesis that VBM alterations of autonomic network regions are independent of epileptogenic lesions and that they reveal structural underpinnings of SUDEP risk, VBM was performed in 100 people with focal epilepsies without an epileptogenic lesion identifiable on MRI (mean age ± standard deviation = 35 ± 11 years, 56 female). The group was further stratified in high (sample size n = 29) and low risk of SUDEP (n = 71). GM volumes were compared between these two subgroups and to 100 matched controls. Results: People with epilepsy displayed higher GM volume in both amygdalae and parahippocampal gyri and lower GM volume in the cerebellum and occipital (p<.05, familywise error corrected). There were no significant volumetric differences between high and low SUDEP risk subgroups. Conclusion: Our findings confirm that autonomic networks are structurally altered in people with focal epilepsy and they question VBM as a suitable method to show structural correlates of the SUDEP risk score. [ABSTRACT FROM AUTHOR]