Age‐associated patterns in gray matter volume,cerebral perfusion and BOLD oscillations in children and adolescents

Healthy brain development involves changes in brain structure and function that are believed to support cognitive maturation. However, understanding how structural changes such as grey matter thinning relate to functional changes is challenging. To gain insight into structure‐function relationships in development, the present study took a data driven approach to define age‐related patterns of variation in gray matter volume (GMV), cerebral blood flow (CBF) and blood‐oxygen level dependent (BOLD) signal variation (fractional amplitude of low‐frequency fluctuations; fALFF) in 59 healthy children aged 7–18 years, and examined relationships between modalities. Principal components analysis (PCA) was applied to each modality in parallel, and participant scores for the top components were assessed for age associations. We found that decompositions of CBF, GMV and fALFF all included components for which scores were significantly associated with age. The dominant patterns in GMV and CBF showed significant (GMV) or trend level (CBF) associations with age and a strong spatial overlap, driven by increased signal intensity in default mode network (DMN) regions. GMV, CBF and fALFF additionally showed components accounting for 3–5% of variability with significant age associations. However, these patterns were relatively spatially independent, with small‐to‐moderate overlap between modalities. Independence of age effects was further demonstrated by correlating individual subject maps between modalities: CBF was significantly less correlated with GMV and fALFF in older children relative to younger. These spatially independent effects of age suggest that the parallel decline observed in global GMV and CBF may not reflect spatially synchronized processes. Hum Brain Mapp 38:2398–2407, 2017. © 2017 Wiley Periodicals, Inc.     

Changes in structure and perfusion of grey matter tissues during recovery from Ischaemic subcortical stroke: a longitudinal MRI study

Stroke recovery with changes in volume and perfusion of grey matter (GM) tissues remains largely unknown. We hypothesized that GM atrophy co‐existed with GM plasticity presenting with increased volume and perfusion in specific regions in the period of post‐stroke recovery. Twelve well‐recovered stroke patients with pure subcortical lesions in the middle cerebral artery‐perfused zone were included. All of them underwent structural and perfusion magnetic resonance imaging (MRI) examinations at admission and a mean of 6 months after stroke onset. Differences in GM volume (GMV) on structural images and cerebral blood flow (CBF) derived from perfusion images between two examinations were compared using voxel‐based morphometry. The associations between changes in GMV and CBF with clinical scores were analysed. Decreased GMV was found in post‐central gyrus, pre‐central gyrus, precuneus, angular gyrus, insula, thalamus and cerebellum, and increased GMV was found in hippocampus, orbital gyrus and lingual gyrus (all corrected P < 0.05) at the follow‐up examination. Increased CBF was found in subcallosal cingulate gyrus, hippocampus and lingual gyrus (all corrected P < 0.05) at the follow‐up examination. Only decreased GMV in the anterior lobe of cerebellum was negatively associated with improvement of Barthel index (β = ?0.683, P = 0.014). Our study provides the imaging evidence of GM atrophy co‐existing with GM plasticity involving in increased volume and perfusion in specific regions (including cognition, vision and emotion) in well‐recovered stroke patients, which advances our understanding of neurobiology of stroke recovery.     

In vivo cholinergic basal forebrain degeneration and cognition in Parkinson's disease: Imaging results from the COPPADIS study

IntroductionWe aimed to assess associations between multimodal neuroimaging measures of cholinergic basal forebrain (CBF) integrity and cognition in Parkinson's disease (PD) without dementia.MethodsThe study included a total of 180 non-demented PD patients and 45 healthy controls, who underwent structural MRI acquisitions and standardized neurocognitive assessment through the PD-Cognitive Rating Scale (PD-CRS) within the multicentric COPPADIS-2015 study. A subset of 73 patients also had Diffusion Tensor Imaging (DTI) acquisitions. Volumetric and microstructural (mean diffusivity, MD) indices of CBF degeneration were automatically extracted using a stereotactic CBF atlas. For comparison, we also assessed multimodal indices of hippocampal degeneration. Associations between imaging measures and cognitive performance were assessed using linear models.ResultsCompared to controls, CBF volume was not significantly reduced in PD patients as a group. However, across PD patients lower CBF volume was significantly associated with lower global cognition (PD-CRS_total: r = 0.37, p < 0.001), and this association remained significant after controlling for several potential confounding variables (p = 0.004). Analysis of individual item scores showed that this association spanned executive and memory domains. No analogue cognition associations were observed for CBF MD. In covariate-controlled models, hippocampal volume was not associated with cognition in PD, but there was a significant association for hippocampal MD (p = 0.02).ConclusionsEarly cognitive deficits in PD without dementia are more closely related to structural MRI measures of CBF degeneration than hippocampal degeneration. In our multicentric imaging acquisitions, DTI-based diffusion measures in the CBF were inferior to standard volumetric assessments for capturing cognition-relevant changes in non-demented PD.     

Distinct functional and structural connections predict crystallised and fluid cognition in healthy adults

White matter pathways between neurons facilitate neuronal coactivation patterns in the brain. Insight into how these structural and functional connections underlie complex cognitive functions provides an important foundation with which to delineate disease‐related changes in cognitive functioning. Here, we integrate neuroimaging, connectomics, and machine learning approaches to explore how functional and structural brain connectivity relate to cognition. Specifically, we evaluate the extent to which functional and structural connectivity predict individual crystallised and fluid cognitive abilities in 415 unrelated healthy young adults (202 females) from the Human Connectome Project. We report three main findings. First, we demonstrate functional connectivity is more predictive of cognitive scores than structural connectivity, and, furthermore, integrating the two modalities does not increase explained variance. Second, we show the quality of cognitive prediction from connectome measures is influenced by the choice of grey matter parcellation, and, possibly, how that parcellation is derived. Third, we find that distinct functional and structural connections predict crystallised and fluid abilities. Taken together, our results suggest that functional and structural connectivity have unique relationships with crystallised and fluid cognition and, furthermore, studying both modalities provides a more comprehensive insight into the neural correlates of cognition.     

Morphological brain measures of cortico‐limbic inhibition related to resilience

Resilience is the ability to adequately adapt and respond to homeostatic perturbations. Although resilience has been associated with positive health outcomes, the neuro‐biological basis of resilience is poorly understood. The aim of the study was to identify associations between regional brain morphology and trait resilience with a focus on resilience‐related morphological differences in brain regions involved in cortico‐limbic inhibition. The relationship between resilience and measures of affect were also investigated. Forty‐eight healthy subjects completed structural MRI scans. Self‐reported resilience was measured using the Connor and Davidson Resilience Scale. Segmentation and regional parcellation of images was performed to yield a total of 165 regions. Gray matter volume (GMV), cortical thickness, surface area, and mean curvature were calculated for each region. Regression models were used to identify associations between morphology of regions belonging to executive control and emotional arousal brain networks and trait resilience (total and subscales) while controlling for age, sex, and total GMV. Correlations were also conducted between resilience scores and affect scores. Significant associations were found between GM changes in hypothesized brain regions (subparietal sulcus, intraparietal sulcus, amygdala, anterior mid cingulate cortex, and subgenual cingulate cortex) and resilience scores. There were significant positive correlations between resilience and positive affect and negative correlations with negative affect. Resilience was associated with brain morphology of regions involved in cognitive and affective processes related to cortico‐limbic inhibition. Brain signatures associated with resilience may be a biomarker of vulnerability to disease. © 2016 Wiley Periodicals, Inc.     

White matter microstructural development and cognitive ability in the first 2 years of life

White matter (WM) integrity has been related to cognitive ability in adults and children, but it remains largely unknown how WM maturation in early life supports emergent cognition. The associations between tract‐based measures of fractional anisotropy (FA) and axial and radial diffusivity (AD, RD) shortly after birth, at age 1, and at age 2 and cognitive measures at 1 and 2 years were investigated in 447 healthy infants. We found that generally higher FA and lower AD and RD across many WM tracts in the first year of life were associated with better performance on measures of general cognitive ability, motor, language, and visual reception skills at ages 1 and 2, suggesting an important role for the overall organization, myelination, and microstructural properties of fiber pathways in emergent cognition. RD in particular was consistently related to ability, and protracted development of RD from ages 1 to 2 years in several tracts was associated with higher cognitive scores and better language performance, suggesting prolonged plasticity may confer cognitive benefits during the second year of life. However, we also found that cognition at age 2 was weakly associated with WM properties across infancy in comparison to child and demographic factors including gestational age and maternal education. Our findings suggest that early postnatal WM integrity across the brain is important for infant cognition, though its role in cognitive development should be considered alongside child and demographic factors.     

A longitudinal characterization of perfusion in the aging brain and associations with cognition and neural structure

Cerebral perfusion declines across the lifespan and is altered in the early stages of several age‐related neuropathologies. Little is known, however, about the longitudinal evolution of perfusion in healthy older adults, particularly when perfusion is quantified using magnetic resonance imaging with arterial spin labeling (ASL). The objective was to characterize longitudinal perfusion in typically aging adults and elucidate associations with cognition and brain structure. Adults who were functionally intact at baseline (n = 161, ages 47–89) underwent ASL imaging to quantify whole‐brain gray matter perfusion; a subset (n = 136) had repeated imaging (average follow‐up: 2.3 years). Neuropsychological testing at each visit was summarized into executive function, memory, and processing speed composites. Global gray matter volume, white matter microstructure (mean diffusivity), and white matter hyperintensities were also quantified. We assessed baseline associations among perfusion, cognition, and brain structure using linear regression, and longitudinal relationships using linear mixed effects models. Greater baseline perfusion, particularly in the left dorsolateral prefrontal cortex and right thalamus, was associated with better executive functions. Greater whole‐brain perfusion loss was associated with worsening brain structure and declining processing speed. This study helps validate noninvasive MRI‐based perfusion imaging and underscores the importance of cerebral blood flow in cognitive aging.     

The association between resting‐state functional magnetic resonance imaging and aortic pulse‐wave velocity in healthy adults

Resting‐state functional magnetic resonance imaging (rs‐fMRI) is frequently used to study brain function; but, it is unclear whether BOLD‐signal fluctuation amplitude and functional connectivity are associated with vascular factors, and how vascular‐health factors are reflected in rs‐fMRI metrics in the healthy population. As arterial stiffening is a known age‐related cardiovascular risk factor, we investigated the associations between aortic stiffening (as measured using pulse‐wave velocity [PWV]) and rs‐fMRI metrics. We used cardiac MRI to measure aortic PWV (an established indicator of whole‐body vascular stiffness), as well as dual‐echo pseudo‐continuous arterial‐spin labeling to measure BOLD and CBF dynamics simultaneously in a group of generally healthy adults. We found that: (1) higher aortic PWV is associated with lower variance in the resting‐state BOLD signal; (2) higher PWV is also associated with lower BOLD‐based resting‐state functional connectivity; (3) regions showing lower connectivity do not fully overlap with those showing lower BOLD variance with higher PWV; (4) CBF signal variance is a significant mediator of the above findings, only when averaged across regions‐of‐interest. Furthermore, we found no significant association between BOLD signal variance and systolic blood pressure, which is also a known predictor of vascular stiffness. Age‐related vascular stiffness, as measured by PWV, provides a unique scenario to demonstrate the extent of vascular bias in rs‐fMRI signal fluctuations and functional connectivity. These findings suggest that a substantial portion of age‐related rs‐fMRI differences may be driven by vascular effects rather than directly by brain function.     

Dynamic brain structural changes after left hemisphere subcortical stroke

This study aimed to quantify dynamic structural changes in the brain after subcortical stroke and identify brain areas that contribute to motor recovery of affected limbs. High‐resolution structural MRI and neurological examinations were conducted at five consecutive time points during the year following stroke in 10 patients with left hemisphere subcortical infarctions involving motor pathways. Gray matter volume (GMV) was calculated using an optimized voxel‐based morphometry technique, and dynamic changes in GMV were evaluated using a mixed‐effects model. After stroke, GMV was decreased bilaterally in brain areas that directly or indirectly connected with lesions, which suggests the presence of regional damage in these “healthy” brain tissues in stroke patients. Moreover, the GMVs of these brain areas were not correlated with the Motricity Index (MI) scores when controlling for time intervals after stroke, which indicates that these structural changes may reflect an independent process (such as axonal degeneration) but cannot affect the improvement of motor function. In contrast, the GMV was increased in several brain areas associated with motor and cognitive functions after stroke. When controlling for time intervals after stroke, only the GMVs in the cognitive‐related brain areas (hippocampus and precuneus) were positively correlated with MI scores, which suggests that the structural reorganization in cognitive‐related brain areas may facilitate the recovery of motor function. However, considering the small sample size of this study, further studies are needed to clarify the exact relationships between structural changes and recovery of motor function in stroke patients. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.     

Parcellation of the human orbitofrontal cortex based on gray matter volume covariance

The human orbitofrontal cortex (OFC) is an enigmatic brain region that cannot be parcellated reliably using diffusional and functional magnetic resonance imaging (fMRI) because there is signal dropout that results from an inherent defect in imaging techniques. We hypothesise that the OFC can be reliably parcellated into subregions based on gray matter volume (GMV) covariance patterns that are derived from artefact‐free structural images. A total of 321 healthy young subjects were examined by high‐resolution structural MRI. The OFC was parcellated into subregions‐based GMV covariance patterns; and then sex and laterality differences in GMV covariance pattern of each OFC subregion were compared. The human OFC was parcellated into the anterior (OFCa), medial (OFCm), posterior (OFCp), intermediate (OFCi), and lateral (OFCl) subregions. This parcellation scheme was validated by the same analyses of the left OFC and the bilateral OFCs in male and female subjects. Both visual observation and quantitative comparisons indicated a unique GMV covariance pattern for each OFC subregion. These OFC subregions mainly covaried with the prefrontal and temporal cortices, cingulate cortex and amygdala. In addition, GMV correlations of most OFC subregions were similar across sex and laterality except for significant laterality difference in the OFCl. The right OFCl had stronger GMV correlation with the right inferior frontal cortex. Using high‐resolution structural images, we established a reliable parcellation scheme for the human OFC, which may provide an in vivo guide for subregion‐level studies of this region and improve our understanding of the human OFC at subregional levels. Hum Brain Mapp 36:538–548, 2015. © 2014 Wiley Periodicals, Inc.     

Cognitive and physiologic correlates of subclinical structural brain disease in elderly healthy control subjects

CONTEXT: Healthy elderly persons commonly show 4 types of change in brain structure-cortical atrophy, central atrophy, deep white-matter hyperintensities, and periventricular hyperintensities-as forms of subclinical structural brain disease (SSBD). OBJECTIVES: To characterize the volumes of SSBD present with aging and to determine the associations of SSBD, physiology, and cognitive function. DESIGN: Cross-sectional study. SETTING: University of California, Los Angeles, Neuropsychiatric Institute. SUBJECTS: Forty-three community-dwelling healthy control subjects, aged 60 through 93 years. MAIN OUTCOME MEASURES: Volumetric magnetic resonance imaging, neuropsychological testing, and quantitative electroencephalographic coherence (functional connectivity) between brain regions. RESULTS: Regression models demonstrated significant relationships between SSBD volumes, age, cognitive performance, and connectivity. Cortical and central atrophy and periventricular hyperintensities had significant associations with age while deep white-matter hyperintensities did not. Posterior atrophy showed stronger associations with age than did anterior atrophy. Only a subset of subjects at older ages showed large SSBD volumes; older subjects primarily showed increasing variance of SSBD. Although all subjects scored within the normal range on cognitive testing, SSBD volume was inversely related to performance, most notably on the Trail-Making Test part B and the Shipley-Hartford Abstract Reasoning test. Coherence had significant associations with SSBD. Path analysis supported mediation of the effects of deep white-matter hyperintensities and periventricular hyperintensities on cognition by altered connectivity. For several measures, cognitive performance was best explained by coherence, and only secondarily by SSBD. CONCLUSIONS: Modest volumes of SSBD were associated with decrements in cognitive performance within the normal range in healthy subjects. Lower coherence was associated with greater volumes of SSBD and increasing age. Path analysis models suggest that brain functional connectivity mediates some effects of SSBD on cognition.     

Reproducibility of brain‐cognition relationships using three cortical surface‐based protocols: An exhaustive analysis based on cortical thickness

People differ in their cognitive functioning. This variability has been exhaustively examined at the behavioral, neural and genetic level to uncover the mechanisms by which some individuals are more cognitively efficient than others. Studies investigating the neural underpinnings of interindividual differences in cognition aim to establish a reliable nexus between functional/structural properties of a given brain network and higher order cognitive performance. However, these studies have produced inconsistent results, which might be partly attributed to methodological variations. In the current study, 82 healthy young participants underwent MRI scanning and completed a comprehensive cognitive battery including measurements of fluid, crystallized, and spatial intelligence, along with working memory capacity/executive updating, controlled attention, and processing speed. The cognitive scores were obtained by confirmatory factor analyses. T₁‐weighted images were processed using three different surface‐based morphometry (SBM) pipelines, varying in their degree of user intervention, for obtaining measures of cortical thickness (CT) across the brain surface. Distribution and variability of CT and CT‐cognition relationships were systematically compared across pipelines and between two cognitively/demographically matched samples to overcome potential sources of variability affecting the reproducibility of findings. We demonstrated that estimation of CT was not consistent across methods. In addition, among SBM methods, there was considerable variation in the spatial pattern of CT‐cognition relationships. Finally, within each SBM method, results did not replicate in matched subsamples. Hum Brain Mapp 36:3227–3245, 2015. © 2015 Wiley Periodicals, Inc.     

Brain biomarkers and cognition across adulthood

Understanding the associations between brain biomarkers (BMs) and cognition across age is of paramount importance. Five hundred and sixty‐two participants (19–80 years old, 16 mean years of education) were studied. Data from structural T1, diffusion tensor imaging, fluid‐attenuated inversion recovery, and resting‐state functional magnetic resonance imaging scans combined with a neuropsychological evaluation were used. More specifically, the measures of cortical, entorhinal, and parahippocampal thickness, hippocampal and striatal volume, default‐mode network and fronto‐parietal control network, fractional anisotropy (FA), and white matter hyperintensity (WMH) were assessed. z‐Scores for three cognitive domains measuring episodic memory, executive function, and speed of processing were computed. Multiple linear regressions and interaction effects between each of the BMs and age on cognition were examined. Adjustments were made for age, sex, education, intracranial volume, and then, further, for general cognition and motion. BMs were significantly associated with cognition. Across the adult lifespan, slow speed was associated with low striatal volume, low FA, and high WMH burden. Poor executive function was associated with low FA, while poor memory was associated with high WMH burden. After adjustments, results were significant for the associations: speed‐FA and WMH, memory‐entorhinal thickness. There was also a significant interaction between hippocampal volume and age in memory. In age‐stratified analyses, the most significant associations for the young group occurred between FA and executive function, WMH, and memory, while for the old group, between entorhinal thickness and speed, and WMH and speed, executive function. Unique sets of BMs can explain variation in specific cognitive domains across adulthood. Such results provide essential information about the neurobiology of aging.     

Characterization of disease‐related covariance topographies with SSMPCA toolbox: Effects of spatial normalization and PET scanners

To generate imaging biomarkers from disease‐specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [¹⁸F]fluorodeoxyglucose PET scans from patients with PD and normal controls. Motor‐related (PDRP) and cognition‐related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5, and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in patients with PD imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease‐specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras. Hum Brain Mapp 35:1801–1814, 2014. © 2013 Wiley Periodicals, Inc.     

A neural signature of metabolic syndrome

That metabolic syndrome (MetS) is associated with age‐related cognitive decline is well established. The neurobiological changes underlying these cognitive deficits, however, are not well understood. The goal of this study was to determine whether MetS is associated with regional differences in gray‐matter volume (GMV) using a cross‐sectional, between‐group contrast design in a large, ethnically homogenous sample. T1‐weighted MRIs were sampled from the genetics of brain structure (GOBS) data archive for 208 Mexican‐American participants: 104 participants met or exceeded standard criteria for MetS and 104 participants were age‐ and sex‐matched metabolically healthy controls. Participants ranged in age from 18 to 74 years (37.3 ± 13.2 years, 56.7% female). Images were analyzed in a whole‐brain, voxel‐wise manner using voxel‐based morphometry (VBM). Three contrast analyses were performed, a whole sample analysis of all 208 participants, and two post hoc half‐sample analyses split by age along the median (35.5 years). Significant associations between MetS and decreased GMV were observed in multiple, spatially discrete brain regions including the posterior cerebellum, brainstem, orbitofrontal cortex, bilateral caudate nuclei, right parahippocampus, right amygdala, right insula, lingual gyrus, and right superior temporal gyrus. Age, as shown in the post hoc analyses, was demonstrated to be a significant covariate. A further functional interpretation of the structures exhibiting lower GMV in MetS reflected a significant involvement in reward perception, emotional valence, and reasoning. Additional studies are needed to characterize the influence of MetS's individual clinical components on brain structure and to explore the bidirectional association between GMV and MetS.     

Longitudinal associations between white matter maturation and cognitive development across early childhood

From birth to 5 years of age, brain structure matures and evolves alongside emerging cognitive and behavioral abilities. In relating concurrent cognitive functioning and measures of brain structure, a major challenge that has impeded prior investigation of their time‐dynamic relationships is the sparse and irregular nature of most longitudinal neuroimaging data. We demonstrate how this problem can be addressed by applying functional concurrent regression models (FCRMs) to longitudinal cognitive and neuroimaging data. The application of FCRM in neuroimaging is illustrated with longitudinal neuroimaging and cognitive data acquired from a large cohort (n = 210) of healthy children, 2–48 months of age. Quantifying white matter myelination by using myelin water fraction (MWF) as imaging metric derived from MRI scans, application of this methodology reveals an early period (200–500 days) during which whole brain and regional white matter structure, as quantified by MWF, is positively associated with cognitive ability, while we found no such association for whole brain white matter volume. Adjusting for baseline covariates including socioeconomic status as measured by maternal education (SES‐ME), infant feeding practice, gender, and birth weight further reveals an increasing association between SES‐ME and cognitive development with child age. These results shed new light on the emerging patterns of brain and cognitive development, indicating that FCRM provides a useful tool for investigating these evolving relationships.     

Activation‐based association profiles differentiate network roles across cognitive loads

Working memory (WM) is a complex and pivotal cognitive system underlying the performance of many cognitive behaviors. Although individual differences in WM performance have previously been linked to the blood oxygenation level‐dependent (BOLD) response across several large‐scale brain networks, the unique and shared contributions of each large‐scale brain network to efficient WM processes across different cognitive loads remain elusive. Using a WM paradigm and functional magnetic resonance imaging (fMRI) from the Human Connectome Project, we proposed a framework to assess the association and shared‐association strength between imaging biomarkers and behavioral scales. Association strength is the capability of individual brain regions to modulate WM performance and shared‐association strength measures how different regions share the capability of modulating performance. Under higher cognitive load (2‐back), the frontoparietal executive control network (FPN), dorsal attention network (DAN), and salience network showed significant positive activation and positive associations, whereas the default mode network (DMN) showed the opposite pattern, namely, significant deactivation and negative associations. Comparing the different cognitive loads, the DMN and FPN showed predominant associations and globally shared‐associations. When investigating the differences in association from lower to higher cognitive loads, the DAN demonstrated enhanced association strength and globally shared‐associations, which were significantly greater than those of the other networks. This study characterized how brain regions individually and collaboratively support different cognitive loads.     

Structural deficits in the emotion circuit and cerebellum are associated with depression, anxiety and cognitive dysfunction in methadone maintenance patients: a voxel-based morphometric study

Heroin users on methadone maintenance treatment (MMT) have elevated rates of co-morbid depression and are associated with have higher relapse rates for substance abuse. Structural abnormalities in MMT patients have been reported, but their impact on clinical performance is unknown. We investigated differences in gray matter volume (GMV) between 27 MMT patients and 23 healthy controls with voxel-based morphometry, and we correlated findings in the patients with Beck Depression Inventory scores, Beck Anxiety Inventory scores, and diminished cognitive functioning. MMT patients exhibited higher emotional deficits than healthy subjects. There was significantly smaller GMV in multiple cortices, especially in the left inferior frontal gyrus and left cerebellar vermis in the MMT group. The smaller GMV in the pre-frontal cortices, left sub-callosal cingulate gyrus, left post-central gyrus, left insula, and right cerebellar declive correlated with higher depression scores. The smaller GMV in the pre-frontal cortices, left sub-callosal cingulate gyrus, and left postcentral gyrus also correlated with higher anxiety scores, while smaller GMV in the cerebellum and bilateral insula was associated with impaired performance on tests of executive function. These results reveal that MMT patients have low GMV in brain regions that are hypothesized to influence cognition and emotion, and the GMV findings might be involved comorbid disorders in the MMT group.     

Parcellation of the human hippocampus based on gray matter volume covariance: Replicable results on healthy young adults

The hippocampus is a key brain region that participates in a range of cognitive and affective functions, and is involved in the etiopathogenesis of numerous neuropsychiatric disorders. The structural complexity and functional diversity of the hippocampus suggest the existence of structural and functional subdivisions within this structure. For the first time, we parcellated the human hippocampus with two independent data sets, each of which consisted of 198 T1‐weighted structural magnetic resonance imaging (sMRI) images of healthy young subjects. The method was based on gray matter volume (GMV) covariance, which was quantified by a bivariate voxel‐to‐voxel linear correlation approach, as well as a multivariate masked independent component analysis approach. We subsequently interrogated the relationship between the GMV covariance patterns and the functional connectivity patterns of the hippocampal subregions using sMRI and resting‐state functional MRI (fMRI) data from the same participants. Seven distinct GMV covariance‐based subregions were identified for bilateral hippocampi, with robust reproducibility across the two data sets. We further demonstrated that the structural covariance patterns of the hippocampal subregions had a correspondence with the intrinsic functional connectivity patterns of these subregions. Together, our results provide a topographical configuration of the hippocampus with converging structural and functional support. The resulting subregions may improve our understanding of the hippocampal connectivity and functions at a subregional level, which provides useful parcellations and masks for future neuroscience and clinical research on the structural and/or functional connectivity of the hippocampus.