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Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

The relative contributions of genetic variation and experience in shaping the morphology of the adolescent brain are not fully understood. Using longitudinal data from 11,665 subjects in the ABCD Study, we fit vertex-wise variance components including family effects, genetic effects, and subject-level effects using a computationally efficient framework. Variance in cortical thickness and surface area is largely attributable to genetic influence, whereas sulcal depth is primarily explained by subject-level effects. Our results identify areas with heterogeneous distributions of heritability estimates that have not been seen in previous work using data from cortical regions. We discuss the biological importance of subject-specific variance and its implications for environmental influences on cortical development and maturation., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Neuroimaging is a popular method to map brain structural and functional patterns to complex human traits. Recently published observations cast doubt upon these prospects, particularly for prediction of cognitive traits from structural and resting state functional magnetic resonance imaging (MRI). We leverage baseline data from thousands of children in the Adolescent Brain Cognitive DevelopmentSM Study to inform the replication sample size required with univariate and multivariate methods across different imaging modalities to detect reproducible brain-behavior associations. We demonstrate that by applying multivariate methods to high-dimensional brain imaging data, we can capture lower dimensional patterns of structural and functional brain architecture that correlate robustly with cognitive phenotypes and are reproducible with only 41 individuals in the replication sample for working memory-related functional MRI, and ~ 100 subjects for structural and resting state MRI. Even with 100 random re-samplings of 100 subjects in discovery, prediction can be adequately powered with 66 subjects in replication for multivariate prediction of cognition with working memory task functional MRI. These results point to an important role for neuroimaging in translational neurodevelopmental research and showcase how findings in large samples can inform reproducible brain-behavior associations in small sample sizes that are at the heart of many research programs and grants., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME; however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive Development SM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of behavior. Previous studies suggested that FC patterns derived from task fMRI paradigms, which we refer to as task-based FC, are better correlated with individual differences in behavior than resting-state FC, but the consistency and generalizability of this advantage across task conditions was not fully explored. Using data from resting-state fMRI and three fMRI tasks from the Adolescent Brain Cognitive Development Study ® (ABCD), we tested whether the observed improvement in behavioral prediction power of task-based FC can be attributed to changes in brain activity induced by the task design. We decomposed the task fMRI time course of each task into the task model fit (the fitted time course of the task condition regressors from the single-subject general linear model) and the task model residuals, calculated their respective FC, and compared the behavioral prediction performance of these FC estimates to resting-state FC and the original task-based FC. The FC of the task model fit was better than the FC of the task model residual and resting-state FC at predicting a measure of general cognitive ability or two measures of performance on the fMRI tasks. The superior behavioral prediction performance of the FC of the task model fit was content-specific insofar as it was only observed for fMRI tasks that probed similar cognitive constructs to the predicted behavior of interest. To our surprise, the task model parameters, the beta estimates of the task condition regressors, were equally if not more predictive of behavioral differences than all FC measures. These results showed that the observed improvement of behavioral prediction afforded by task-based FC was largely driven by the FC patterns associated with the task design. Together with previous studies, our findings highlighted the importance of task design in eliciting behaviorally meaningful brain activation and FC patterns., Competing Interests: Declaration of Competing Interest Dr. Dale reports that he was a Founder of and holds equity in Cor-Techs Labs, Inc., and serves on its Scientific Advisory Board. He is a member of the Scientific Advisory Board of Human Longevity, Inc. He receives funding through research grants from GE Healthcare to UCSD. The terms of these arrangements have been reviewed by and approved by UCSD in accordance with its conflict-of-interest policies. Dr. Dale also reports that he has memberships with the following research consortia: Alzheimers Disease Genetics Consortium (ADGC); Enhancing NeuroImaging Genetics Through Meta-analysis (ENIGMA); Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL); Psychiatric Genomics Consortium (PGC). All other authors have no conflicts of interest., (Copyright © 2023. Published by Elsevier Inc.)

Importance: Incidental findings (IFs) are unexpected abnormalities discovered during imaging and can range from normal anatomic variants to findings requiring urgent medical intervention. In the case of brain magnetic resonance imaging (MRI), reliable data about the prevalence and significance of IFs in the general population are limited, making it difficult to anticipate, communicate, and manage these findings., Objectives: To determine the overall prevalence of IFs in brain MRI in the nonclinical pediatric population as well as the rates of specific findings and findings for which clinical referral is recommended., Design, Setting, and Participants: This cohort study was based on the April 2019 release of baseline data from 11 810 children aged 9 to 10 years who were enrolled and completed baseline neuroimaging in the Adolescent Brain Cognitive Development (ABCD) study, the largest US population-based longitudinal observational study of brain development and child health, between September 1, 2016, and November 15, 2018. Participants were enrolled at 21 sites across the US designed to mirror the demographic characteristics of the US population. Baseline structural MRIs were centrally reviewed for IFs by board-certified neuroradiologists and findings were described and categorized (category 1, no abnormal findings; 2, no referral recommended; 3; consider referral; and 4, consider immediate referral). Children were enrolled through a broad school-based recruitment process in which all children of eligible age at selected schools were invited to participate. Exclusion criteria were severe sensory, intellectual, medical, or neurologic disorders that would preclude or interfere with study participation. During the enrollment process, demographic data were monitored to ensure that the study met targets for sex, socioeconomic, ethnic, and racial diversity. Data were analyzed from March 15, 2018, to November 20, 2020., Main Outcomes and Measures: Percentage of children with IFs in each category and prevalence of specific IFs., Results: A total of 11 679 children (52.1% boys, mean [SD] age, 9.9 [0.62] years) had interpretable baseline structural MRI results. Of these, 2464 participants (21.1%) had IFs, including 2013 children (17.2%) assigned to category 2, 431 (3.7%) assigned to category 3, and 20 (0.2%) assigned to category 4. Overall rates of IFs did not differ significantly between singleton and twin gestations or between monozygotic and dizygotic twins, but heritability analysis showed heritability for the presence or absence of IFs (h2 = 0.260; 95% CI, 0.135-0.387)., Conclusions and Relevance: Incidental findings in brain MRI and findings with potential clinical significance are both common in the general pediatric population. By assessing IFs and concurrent developmental and health measures and following these findings over the longitudinal study course, the ABCD study has the potential to determine the significance of many common IFs.

Objective: The hippocampus is a key structure in feeding behaviors and weight regulation. Obesity may lead to disruptions in hippocampal structure. In animals, obesity-related factors (e.g., high-fat/sugar foods) are associated with hippocampal insult (e.g., alterations in the blood brain barrier). In humans, individuals with obesity, relative to healthy weight, have smaller hippocampal volumes. Few studies have examined the association between body weight and the hippocampus during adolescence, a critical brain development period. This study examined hippocampal volume and tissue signal intensity in adolescents across the weight spectrum., Methods: Structural magnetic resonance imaging and anthropomorphic data were available for 102 12- to 18-year-old adolescents (53% female; 15.07 [SD 1.84] years; standardized BMI [BMIz] scores using the Centers for Disease Control and Prevention growth charts: 0.54 [SD 1.17]) from the Pediatric Imaging, Neurocognition, and Genetics database. Linear regression models controlling for age, sex, genetic ancestry, scanner, and household income examined the relationship between BMIz, hippocampal volume, and T2-weighted hippocampal signal intensity., Results: BMIz was negatively associated with T2-weighted hippocampal signal intensity in the left (t = -3.05; P = 0.003; r = -0.21) and right (t = -2.50; P = 0.01; r = -0.36) hippocampi. BMIz was not significantly associated with hippocampal volume., Conclusions: BMIz is associated with hippocampal tissue characteristics during adolescence, which could impact later brain development., (© 2020 The Obesity Society.)

Purpose To evaluate whether patients with neurofibromatosis type 1 (NF1)-a multisystem neurodevelopmental disorder with myriad imaging manifestations, including focal transient myelin vacuolization within the deep gray nuclei, brainstem, and cerebellum-exhibit differences in cortical and subcortical structures, particularly in subcortical regions where these abnormalities manifest. Materials and Methods In this retrospective study, by using clinically obtained three-dimensional T1-weighted MR images and established image analysis methods, 10 intracranial volume-corrected subcortical and 34 cortical regions of interest (ROIs) were quantitatively assessed in 32 patients with NF1 and 245 age- and sex-matched healthy control subjects. By using linear models, ROI cortical thicknesses and volumes were compared between patients with NF1 and control subjects, as a function of age. With hierarchic cluster analysis and partial correlations, differences in the pattern of association between cortical and subcortical ROI volumes in patients with NF1 and control subjects were also evaluated. Results Patients with NF1 exhibited larger subcortical volumes and thicker cortices of select regions, particularly the hippocampi, amygdalae, cerebellar white matter, ventral diencephalon, thalami, and occipital cortices. For the thalami and pallida and 22 cortical ROIs in patients with NF1, a significant inverse association between volume and age was found, suggesting that volumes decrease with increasing age. Moreover, compared with those in control subjects, ROIs in patients with NF1 exhibited a distinct pattern of clustering and partial correlations. Discussion Neurofibromatosis type 1 is characterized by larger subcortical volumes and thicker cortices of select structures. Most apparent within the hippocampi, amygdalae, cerebellar white matter, ventral diencephalon, thalami and occipital cortices, these neurofibromatosis type 1-associated volumetric changes may, in part, be age dependent. © RSNA, 2018 Online supplemental material is available for this article.

Background: Neuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis., Methods: In this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0·0156., Findings: Our sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohen's d=-0·15), amygdala (d=-0·19), caudate (d=-0·11), hippocampus (d=-0·11), putamen (d=-0·14), and intracranial volume (d=-0·10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0·95) and thalamus (p=0·39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (<15 years) versus adults (>21 years): in the accumbens (Cohen's d=-0·19 vs -0·10), amygdala (d=-0·18 vs -0·14), caudate (d=-0·13 vs -0·07), hippocampus (d=-0·12 vs -0·06), putamen (d=-0·18 vs -0·08), and intracranial volume (d=-0·14 vs 0·01). There was no difference between children and adults for the pallidum (p=0·79) or thalamus (p=0·89). Case-control differences in adults were non-significant (all p>0·03). Psychostimulant medication use (all p>0·15) or symptom scores (all p>0·02) did not influence results, nor did the presence of comorbid psychiatric disorders (all p>0·5)., Interpretation: With the largest dataset to date, we add new knowledge about bilateral amygdala, accumbens, and hippocampus reductions in ADHD. We extend the brain maturation delay theory for ADHD to include subcortical structures and refute medication effects on brain volume suggested by earlier meta-analyses. Lifespan analyses suggest that, in the absence of well powered longitudinal studies, the ENIGMA cross-sectional sample across six decades of ages provides a means to generate hypotheses about lifespan trajectories in brain phenotypes., Funding: National Institutes of Health., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Despite modern antiretroviral therapy, HIV-associated sensory neuropathy affects over 50 % of HIV patients. The clinical expression of HIV neuropathy is highly variable: many individuals report few symptoms, but about half report distal neuropathic pain (DNP), making it one of the most prevalent, disabling, and treatment-resistant complications of HIV disease. The presence and intensity of pain is not fully explained by the degree of peripheral nerve damage, making it unclear why some patients do, and others do not, report pain. To better understand central nervous system contributions to HIV DNP, we performed a cross-sectional analysis of structural magnetic resonance imaging volumes in 241 HIV-infected participants from an observational multi-site cohort study at five US sites (CNS HIV Anti-Retroviral Treatment Effects Research Study, CHARTER). The association between DNP and the structural imaging outcomes was investigated using both linear and nonlinear (Gaussian Kernel support vector) multivariable regression, controlling for key demographic and clinical variables. Severity of DNP symptoms was correlated with smaller total cerebral cortical gray matter volume (r = -0.24; p = 0.004). Understanding the mechanisms for this association between smaller total cortical volumes and DNP may provide insight into HIV DNP chronicity and treatment-resistance.

Structural MRI allows unparalleled in vivo study of the anatomy of the developing human brain. For more than two decades, MRI research has revealed many new aspects of this multifaceted maturation process, significantly augmenting scientific knowledge gathered from postmortem studies. Postnatal brain development is notably protracted and involves considerable changes in cerebral cortical, subcortical, and cerebellar structures, as well as significant architectural changes in white matter fiber tracts (see [12]). Although much work has described isolated features of neuroanatomical development, it remains a critical challenge to characterize the multidimensional nature of brain anatomy, capturing different phases of development among individuals. Capitalizing on key advances in multisite, multimodal MRI, and using cross-validated nonlinear modeling, we demonstrate that developmental brain phase can be assessed with much greater precision than has been possible using other biological measures, accounting for more than 92% of the variance in age. Further, our composite metric of morphology, diffusivity, and signal intensity shows that the average difference in phase among children of the same age is only about 1 year, revealing for the first time a latent phenotype in the human brain for which maturation timing is tightly controlled., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Understanding the genetic and environmental contributions to measures of brain structure such as surface area and cortical thickness is important for a better understanding of the nature of brain-behavior relationships and changes due to development or disease. Continuous spatial maps of genetic influences on these structural features can contribute to our understanding of regional patterns of heritability, since it remains to be seen whether genetic contributions to brain structure respect the boundaries of any traditional parcellation approaches. Using data from magnetic resonance imaging scans collected on a large sample of monozygotic and dizygotic twins in the Vietnam Era Twin Study of Aging, we created maps of the heritability of areal expansion (a vertex-based area measure) and cortical thickness and examined the degree to which these maps were affected by adjustment for total surface area and mean cortical thickness. We also compared the approach of estimating regional heritability based on the average heritability of vertices within the region to the more traditional region-of-interest (ROI)-based approach. The results suggested high heritability across the cortex for areal expansion and, to a slightly lesser degree, for cortical thickness. There was a great deal of genetic overlap between global and regional measures for surface area, so maps of region-specific genetic influences on surface area revealed more modest heritabilities. There was greater inter-regional variability in heritabilities when calculated using the traditional ROI-based approach compared to summarizing vertex-by-vertex heritabilities within regions. Discrepancies between the approaches were greatest in small regions and tended to be larger for surface area than for cortical thickness measures. Implications regarding brain phenotypes for future genetic association studies are discussed.

Cortical surface area measures appear to be functionally relevant and distinct in etiology, development, and behavioral correlates compared with other size characteristics, such as cortical thickness. Little is known about genetic and environmental influences on individual differences in regional surface area in humans. Using a large sample of adult twins, we determined relative contributions of genes and environment on variations in regional cortical surface area as measured by magnetic resonance imaging before and after adjustment for genetic and environmental influences shared with total cortical surface area. We found high heritability for total surface area and, before adjustment, moderate heritability for regional surface areas. Compared with other lobes, heritability was higher for frontal lobe and lower for medial temporal lobe. After adjustment for total surface area, regionally specific genetic influences were substantially reduced, although still significant in most regions. Unlike other lobes, left frontal heritability remained high after adjustment. Thus, global and regionally specific genetic factors both influence cortical surface areas. These findings are broadly consistent with results from animal studies regarding the evolution and development of cortical patterning and may guide future research into specific environmental and genetic determinants of variation among humans in the surface area of particular regions.

Cognitive control of thoughts, actions and emotions is important for normal behaviour and the development of such control continues throughout childhood and adolescence. Several lines of evidence suggest that response inhibition is primarily mediated by a right-lateralized network involving inferior frontal gyrus (IFG), presupplementary motor cortex (preSMA), and subthalamic nucleus. Though the brain's fibre tracts are known to develop during childhood, little is known about how fibre tract development within this network relates to developing behavioural control. Here we examined the relationship between response inhibition, as measured with the stop-signal task, and indices of regional white matter microstructure in typically-developing children. We hypothesized that better response inhibition performance would be associated with higher fractional anisotropy (FA) in fibre tracts within right IFG and preSMA after controlling for age. Mean FA and diffusivity values were extracted from right and left IFG and preSMA. As hypothesized, faster response inhibition was significantly associated with higher FA and lower perpendicular diffusivity in both the right IFG and the right preSMA, possibly reflecting faster speed of neural conduction within more densely packed or better myelinated fibre tracts. Moreover, both of these effects remained significant after controlling for age and whole brain estimates of these DTI parameters. Interestingly, right IFG and preSMA FA contributed additively to the prediction of performance variability. Observed associations may be related to variation in phase of maturation, to activity-dependent alterations in the network subserving response inhibition, or to stable individual differences in underlying neural system connectivity., (Copyright (c) 2009 Elsevier Ltd. All rights reserved.)

The medial temporal lobe (MTL) consists of several regions thought to be involved in learning and memory. However, the degree of functional specialization among these regions remains unclear. Previous studies have demonstrated effects of both content and processing stage, but findings have been inconsistent. In particular, studies have suggested that the perirhinal cortex is more involved in object processing than spatial processing, while other regions such as the parahippocampal cortex have been implicated in spatial processing. In this study, functional magnetic resonance imaging (fMRI) optimized for the MTL region was used to probe MTL activation during intentional encoding of object identities or positions. A region of interest analysis showed that object encoding evoked stronger activation than position encoding in bilateral perirhinal cortex, temporopolar cortex, parahippocampal cortex, hippocampus and amygdala. Results also indicate an unexpected significant correlation in activation level between anterior and posterior portions in both the left parahippocampal cortex and left hippocampus. Exploratory analysis did not show any regional content effects during preparation and rehearsal stages. These results provide additional evidence for functional specialization within the MTL, but were less clear regarding the specific nature of content specificity in these regions.

The application of advances in biomedical computing to medical imaging research is enabling scientists to conduct quantitative clinical imaging studies using data collected across multiple sites to test new hypotheses on larger cohorts, increasing the power to detect subtle effects. Given that many research groups have valuable existing (legacy) data, one goal of the Morphometry Biomedical Informatics Research Network (BIRN) Testbed is to assess the feasibility of pooled analyses of legacy structural neuroimaging data in normal aging and Alzheimer's disease. The present study examined whether such data could be meaningfully reanalyzed as a larger combined data set by using rigorous data curation, image analysis, and statistical modeling methods; in this case, to test the hypothesis that hippocampal volume decreases with age and to investigate findings of hippocampal asymmetry. This report describes our work with legacy T1-weighted magnetic resonance (MR) and demographic data related to normal aging that have been shared through the BIRN by three research sites. Results suggest that, in the present application, legacy MR data from multiple sites can be pooled to investigate questions of scientific interest. In particular, statistical analyses suggested that a mixed-effects model employing site as a random effect best fits the data, accounting for site-specific effects while taking advantage of expected comparability of age-related effects. In the combined sample from three sites, significant age-related decline of hippocampal volume and right-dominant hippocampal asymmetry were detected in healthy elderly controls. These expected findings support the feasibility of combining legacy data to investigate novel scientific questions.

Due to the increasing need for subject privacy, the ability to deidentify structural MR images so that they do not provide full facial detail is desirable. A program was developed that uses models of nonbrain structures for removing potentially identifying facial features. When a novel image is presented, the optimal linear transform is computed for the input volume (Fischl et al. [2002]: Neuron 33:341-355; Fischl et al. [2004]: Neuroimage 23 (Suppl 1):S69-S84). A brain mask is constructed by forming the union of all voxels with nonzero probability of being brain and then morphologically dilated. All voxels outside the mask with a nonzero probability of being a facial feature are set to 0. The algorithm was applied to 342 datasets that included two different T1-weighted pulse sequences and four different diagnoses (depressed, Alzheimer's, and elderly and young control groups). Visual inspection showed none had brain tissue removed. In a detailed analysis of the impact of defacing on skull-stripping, 16 datasets were bias corrected with N3 (Sled et al. [1998]: IEEE Trans Med Imaging 17:87-97), defaced, and then skull-stripped using either a hybrid watershed algorithm (Ségonne et al. [2004]: Neuroimage 22:1060-1075, in FreeSurfer) or Brain Surface Extractor (Sandor and Leahy [1997]: IEEE Trans Med Imaging 16:41-54; Shattuck et al. [2001]: Neuroimage 13:856-876); defacing did not appreciably influence the outcome of skull-stripping. Results suggested that the automatic defacing algorithm is robust, efficiently removes nonbrain tissue, and does not unduly influence the outcome of the processing methods utilized; in some cases, skull-stripping was improved. Analyses support this algorithm as a viable method to allow data sharing with minimal data alteration within large-scale multisite projects., ((c) 2007 Wiley-Liss, Inc.)

Performance of automated methods to isolate brain from nonbrain tissues in magnetic resonance (MR) structural images may be influenced by MR signal inhomogeneities, type of MR image set, regional anatomy, and age and diagnosis of subjects studied. The present study compared the performance of four methods: Brain Extraction Tool (BET; Smith [2002]: Hum Brain Mapp 17:143-155); 3dIntracranial (Ward [1999] Milwaukee: Biophysics Research Institute, Medical College of Wisconsin; in AFNI); a Hybrid Watershed algorithm (HWA, Segonne et al. [2004] Neuroimage 22:1060-1075; in FreeSurfer); and Brain Surface Extractor (BSE, Sandor and Leahy [1997] IEEE Trans Med Imag 16:41-54; Shattuck et al. [2001] Neuroimage 13:856-876) to manually stripped images. The methods were applied to uncorrected and bias-corrected datasets; Legacy and Contemporary T1-weighted image sets; and four diagnostic groups (depressed, Alzheimer's, young and elderly control). To provide a criterion for outcome assessment, two experts manually stripped six sagittal sections for each dataset in locations where brain and nonbrain tissue are difficult to distinguish. Methods were compared on Jaccard similarity coefficients, Hausdorff distances, and an Expectation-Maximization algorithm. Methods tended to perform better on contemporary datasets; bias correction did not significantly improve method performance. Mesial sections were most difficult for all methods. Although AD image sets were most difficult to strip, HWA and BSE were more robust across diagnostic groups compared with 3dIntracranial and BET. With respect to specificity, BSE tended to perform best across all groups, whereas HWA was more sensitive than other methods. The results of this study may direct users towards a method appropriate to their T1-weighted datasets and improve the efficiency of processing for large, multisite neuroimaging studies., (Copyright (c) 2005 Wiley-Liss, Inc.)

The very high sensitivity and specificity of odor identification tasks in discriminating between Alzheimer's patients and normals suggests that they reflect the presence of underlying neuropathology. Significant neuropathological changes are seen in areas critical to processing olfactory information, even in the early stages of Alzheimer's disease (AD). The current study was designed to investigate whether performance on olfactory tasks (odor threshold and odor identification) was related to volumetric MRI measures of mesial temporal areas central to olfactory information processing and important in the neuropathology of AD. Participants were 8 male and 5 female patients with probable AD, and 10 male and 12 female normal age-matched controls, diagnosed at the UCSD Alzheimer's Disease Research Center. The study investigated correlations between volumetric measures of hippocampus, the parahippocampal gyrus and the amygdala, and the psychophysical measures of olfactory function. Robust relationships were observed between mesial temporal lobe volumes and olfactory functional measures. The finding of a strong relationship between left hippocampal volume and performance on the odor identification task (r = .85) is compatible with a left-hemisphere superiority for verbally mediated olfactory tasks. The findings suggest a neural substrate for the breakdown in functional performance on verbally mediated odor identification tasks in Alzheimer's disease and suggest the utility of quantitative MRI measures and psychophysical performance in the assessment of AD. These results support the potential clinical utility of inclusion of odor identification tests in diagnostic batteries for detecting AD.

Here we report on detailed three-dimensional quantitative maps of brain surface and gray matter density asymmetry patterns during normal adolescent development and show how these anatomical features of the brain are disrupted as a result of prenatal exposure to large quantities of alcohol. We studied two independent samples of normally developing children, adolescents, and young adults, totaling 83 subjects from two different research groups, and compared them to 21 individuals with heavy prenatal alcohol exposure. Surface-based image analysis techniques allowed us to match cortical anatomy across subjects and between hemispheres based on manually delineated sulcal landmarks. Quantitative maps of brain surface asymmetry reveal prominent peri-Sylvian hemispheric differences in which the superior temporal and inferior parietal cortices are shifted backward in the left relative to the right hemisphere in both normal and alcohol-exposed subjects. Cortical surface gray matter asymmetry, mapped here in adolescent populations, is most prominent in the posterior inferior temporal lobes (right greater than left), and this effect does not differ between groups of normally developing children, adolescents, or young adults. Alcohol-exposed individuals show a significant reduction in this asymmetry, whether studied with surface-based or more traditional volumetric region of interest analyses. This region of cortex, near the junction of Brodmann's areas 21, 22, and 37, primarily subserves language functions that are known to be impaired on average in the alcohol-exposed subjects. Our findings elucidate regional patterns of brain surface and gray matter asymmetry during normal development and may contribute to a more comprehensive understanding of the neural substrates of cognitive dysfunction after heavy prenatal alcohol exposure.

Background and aimsRecently, 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 settingCross-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).CasesCases 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.MeasurementsGraph theory metrics of segregation and integration were used to summarize SCN.FindingsMirroring 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.ConclusionStructural 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.

Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of behavior. Previous studies suggested that FC patterns derived from task fMRI paradigms, which we refer to as task-based FC, are better correlated with individual differences in behavior than resting-state FC, but the consistency and generalizability of this advantage across task conditions was not fully explored. Using data from resting-state fMRI and three fMRI tasks from the Adolescent Brain Cognitive Development Study ® (ABCD), we tested whether the observed improvement in behavioral prediction power of task-based FC can be attributed to changes in brain activity induced by the task design. We decomposed the task fMRI time course of each task into the task model fit (the fitted time course of the task condition regressors from the single-subject general linear model) and the task model residuals, calculated their respective FC, and compared the behavioral prediction performance of these FC estimates to resting-state FC and the original task-based FC. The FC of the task model fit was better than the FC of the task model residual and resting-state FC at predicting a measure of general cognitive ability or two measures of performance on the fMRI tasks. The superior behavioral prediction performance of the FC of the task model fit was content-specific insofar as it was only observed for fMRI tasks that probed similar cognitive constructs to the predicted behavior of interest. To our surprise, the task model parameters, the beta estimates of the task condition regressors, were equally if not more predictive of behavioral differences than all FC measures. These results showed that the observed improvement of behavioral prediction afforded by task-based FC was largely driven by the FC patterns associated with the task design. Together with previous studies, our findings highlighted the importance of task design in eliciting behaviorally meaningful brain activation and FC patterns.

ImportanceHereditary hemochromatosis (HH) is an autosomal recessive genetic disorder that leads to iron overload. Conflicting results from previous research has led some to believe the brain is spared the toxic effects of iron in HH.ObjectiveTo test the association of the strongest genetic risk variant for HH on brainwide measures sensitive to iron deposition and the rates of movement disorders in a substantially larger sample than previous studies of its kind.Design, setting, and participantsThis cross-sectional retrospective study included participants from the UK Biobank, a population-based sample. Genotype, health record, and neuroimaging data were collected from January 2006 to May 2021. Data analysis was conducted from January 2021 to April 2022. Disorders tested included movement disorders (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10], codes G20-G26), abnormalities of gait and mobility (ICD-10 codes R26), and other disorders of the nervous system (ICD-10 codes G90-G99).ExposuresHomozygosity for p.C282Y, the largest known genetic risk factor for HH.Main outcomes and measuresT2-weighted and T2* signal intensity from brain magnetic resonance imaging scans, measures sensitive to iron deposition, and clinical diagnosis of neurological disorders.ResultsThe total cohort consisted of 488 288 individuals (264 719 female; ages 49-87 years, largely northern European ancestry), 2889 of whom were p.C282Y homozygotes. The neuroimaging analysis consisted of 836 individuals: 165 p.C282Y homozygotes (99 female) and 671 matched controls (399 female). A total of 206 individuals were excluded from analysis due to withdrawal of consent. Neuroimaging analysis showed that p.C282Y homozygosity was associated with decreased T2-weighted and T2* signal intensity in subcortical motor structures (basal ganglia, thalamus, red nucleus, and cerebellum; Cohen d >1) consistent with substantial iron deposition. Across the whole UK Biobank (2889 p.C282Y homozygotes, 485 399 controls), we found a significantly increased prevalence for movement disorders in male homozygotes (OR, 1.80; 95% CI, 1.28-2.55; P = .001) but not female individuals (OR, 1.09; 95% CI, 0.70-1.73; P = .69). Among the 31 p.C282Y male homozygotes with a movement disorder, only 10 had a concurrent HH diagnosis.Conclusions and relevanceThese findings indicate increased iron deposition in subcortical motor circuits in p.C282Y homozygotes and confirm an increased association with movement disorders in male homozygotes. Early treatment in HH effectively prevents the negative consequences of iron overload in the liver and heart. Our work suggests that screening for p.C282Y homozygosity in high-risk individuals also has the potential to reduce brain iron accumulation and to reduce the risk of movement disorders among male individuals who are homozygous for this mutation.

To determine the impact of genetic variants on the brain, we used genetically informed brain atlases in genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136 children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post hoc combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk. Opposing gradations of decreased surface area and increased thickness were associated with common inversion polymorphisms. Inferior frontal regions, encompassing Broca's area, which is important for speech, were enriched for human-specific genomic elements. Thus, a mixed genetic landscape of conserved and human-specific features is concordant with brain hierarchy and morphogenetic gradients.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.

ObjectiveSome studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.MethodsWe analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.ResultsThere was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.ConclusionPrior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P

Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.

ObjectiveNeuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies.MethodsCortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707).ResultsIn the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample.ConclusionsSubtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.

Despite great interest in using magnetic resonance imaging (MRI) for studying the effects of genes on brain structure in humans, current approaches have focused almost entirely on predefined regions of interest and had limited success. Here, we used multivariate methods to define a single neuroanatomical score of how William's Syndrome (WS) brains deviate structurally from controls. The score is trained and validated on measures of T1 structural brain imaging in two WS cohorts (training, n = 38; validating, n = 60). We then associated this score with single nucleotide polymorphisms (SNPs) in the WS hemi-deleted region in five cohorts of neurologically and psychiatrically typical individuals (healthy European descendants, n = 1863). Among 110 SNPs within the 7q11.23 WS chromosomal region, we found one associated locus (p = 5e-5) located at GTF2IRD1, which has been implicated in animal models of WS. Furthermore, the genetic signals of neuroanatomical scores are highly enriched locally in the 7q11.23 compared with summary statistics based on regions of interest, such as hippocampal volumes (n = 12,596), and also globally (SNP-heritability = 0.82, se = 0.25, p = 5e-4). The role of genetic variability in GTF2IRD1 during neurodevelopment extends to healthy subjects. Our approach of learning MRI-derived phenotypes from clinical populations with well-established brain abnormalities characterized by known genetic lesions may be a powerful alternative to traditional region of interest-based studies for identifying genetic variants regulating typical brain development.

Structural neuroimaging measures based on magnetic resonance imaging have been at the forefront of imaging genetics. Global efforts to ensure homogeneity of measurements across study sites have enabled large-scale imaging genetic projects, accumulating nearly 50K samples for genome-wide association studies (GWAS). However, not many novel genetic variants have been identified by these GWAS, despite the high heritability of structural neuroimaging measures. Here, we discuss the limitations of using heritability as a guidance for assessing statistical power of GWAS, and highlight the importance of discoverability-which is the power to detect genetic variants for a given phenotype depending on its unique genomic architecture and GWAS sample size. Further, we present newly developed methods that boost genetic discovery in imaging genetics. By redefining imaging measures independent of traditional anatomical conventions, it is possible to improve discoverability, enabling identification of more genetic effects. Moreover, by leveraging enrichment priors from genomic annotations and independent GWAS of pleiotropic traits, we can better characterize effect size distributions, and identify reliable and replicable loci associated with structural neuroimaging measures. Statistical tools leveraging novel insights into the genetic discoverability of human traits, promises to accelerate the identification of genetic underpinnings underlying brain structural variation.

This study investigates the relationship between variability in cortical surface area and thickness of the pars opercularis of the inferior frontal gyrus and motor-inhibitory performance on a stop-signal task in a longitudinal, typically developing cohort of children and adolescents. Linear mixed-effects models were used to investigate the hypotheses that (1) cortical thinning and (2) a relatively larger cortical surface area of the bilateral pars opercularis of the inferior frontal gyrus would predict better performance on the stop-signal task in a cohort of 110 children and adolescents 4-13 years of age, with one to four observations (totaling 232 observations). Cortical thickness of the bilateral opercular region was not related to inhibitory performance. However, independent of age, gender, and total cortical surface area, relatively larger cortical surface area of the bilateral opercular region of the inferior frontal gyrus was associated with better motor-inhibitory performance. Follow-up analyses showed a significant effect of surface area of the right pars opercularis, but no evidence for an effect of area of left pars opercularis, on motor-inhibitory performance. These findings are consistent with the previous work in adults showing that cortical morphology of the pars opercularis is related to inhibitory functioning. It also expands upon this literature by showing that, in contrast to earlier work highlighting the importance of cortical thickness of this region in adults, relative cortical surface area of the pars opercularis may be related to developing motor-inhibitory functions during childhood and adolescence. Relationships between cortical phenotypes and individual differences in behavioral measures may vary across the lifespan.

One of the most salient long-term implications of a childhood diagnosis of ADHD is an increased risk for substance use, abuse, or dependence in adolescence and adulthood. The extent to which cannabis use affects ADHD-related alterations in brain functional organization is unknown, however. To address this research gap, we recruited a sample of 75 individuals aged 21-25 years with and without a childhood diagnosis of ADHD Combined Type, who were either frequent users or non-users of cannabis. These participants have been followed longitudinally since age 7-9.9 years as part of a large multi-site longitudinal study of ADHD, the Multimodal Treatment Study of Children with ADHD (MTA). We examined task-independent intrinsic functional connectivity (iFC) within 9 functional networks using a 2 × 2 design, which compared four groups of participants: (1) individuals with a childhood diagnosis of ADHD who currently use cannabis (n = 23); (2) individuals with ADHD who do not currently use cannabis (n = 22); (3) comparisons who currently use cannabis (n = 15); and (4) comparisons who do not currently use cannabis (n = 15). The main effects of childhood ADHD were primarily weakened iFC in networks supporting executive function and somatomotor control. Contrary to expectations, effects of cannabis use were distinct from those of diagnostic group and no interactions were observed. Exploratory brain-behavior analyses suggested that ADHD-related effects were primarily linked with poorer neurocognitive performance. Deficits in the integrity of functional networks supporting executive function and somatomotor control are consistent with the phenotypic and neurocognitive features of ADHD. Our data suggest that cannabis use does not exacerbate ADHD-related alterations, but this finding awaits replication in a larger sample. Longitudinal neuroimaging studies are urgently required to delineate the neurodevelopmental cascade that culminates in positive and negative outcomes for those diagnosed with ADHD in childhood.

The brain's serotonergic system plays a crucial role in the processing of emotional stimuli, and several studies have shown that a reduced serotonergic neurotransmission is associated with an increase in amygdala activity during emotional face processing. Prolonged recreational use of ecstasy (3,4-methylene-dioxymethamphetamine [MDMA]) induces alterations in serotonergic neurotransmission that are comparable to those observed in a depleted state. In this functional magnetic resonance imaging (fMRI) study, we investigated the responsiveness of the amygdala to emotional face stimuli in recreational ecstasy users as a model of long-term serotonin depletion. Fourteen ecstasy users and 12 non-using controls underwent fMRI to measure the regional neural activity elicited in the amygdala by male or female faces expressing anger, disgust, fear, sadness, or no emotion. During fMRI, participants made a sex judgement on each face stimulus. Positron emission tomography with 11C-DASB was additionally performed to assess serotonin transporter (SERT) binding in the brain. In the ecstasy users, SERT binding correlated negatively with amygdala activity, and accumulated lifetime intake of ecstasy tablets was associated with an increase in amygdala activity during angry face processing. Conversely, time since the last ecstasy intake was associated with a trend toward a decrease in amygdala activity during angry and sad face processing. These results indicate that the effects of long-term serotonin depletion resulting from ecstasy use are dose-dependent, affecting the functional neural basis of emotional face processing.

Sensitivity to global visual motion has been proposed as a signature of brain development, related to the dorsal rather than ventral cortical stream. Thresholds for global motion have been found to be elevated more than for global static form in many developmental disorders, leading to the idea of "dorsal stream vulnerability." Here we explore the association of global motion thresholds with individual differences in children's brain development, in a group of typically developing 5- to 12-year-olds. Good performance was associated with a relative increase in parietal lobe surface area, most strongly around the intraparietal sulcus and decrease in occipital area. In line with the involvement of intraparietal sulcus, areas in visuospatial and numerical cognition, we also found that global motion performance was correlated with tests of visuomotor integration and numerical skills. Individual differences in global form detection showed none of these anatomical or cognitive correlations. This suggests that the correlations with motion sensitivity are unlikely to reflect general perceptual or attentional abilities required for both form and motion. We conclude that individual developmental variations in global motion processing are not linked to greater area in the extrastriate visual areas, which initially process such motion, but in the parietal systems that make decisions based on this information. The overlap with visuospatial and numerical abilities may indicate the anatomical substrate of the "dorsal stream vulnerability" proposed as characterizing neurodevelopmental disorders.

Brain structural development continues throughout adolescence, when experimentation with alcohol is often initiated. To parse contributions from biological and environmental factors on neurodevelopment, this study used baseline National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) magnetic resonance imaging (MRI) data, acquired in 674 adolescents meeting no/low alcohol or drug use criteria and 134 adolescents exceeding criteria. Spatial integrity of images across the 5 recruitment sites was assured by morphological scaling using Alzheimer's disease neuroimaging initiative phantom-derived volume scalar metrics. Clinical MRI readings identified structural anomalies in 11.4%. Cortical volume and thickness were smaller and white matter volumes were larger in older than in younger adolescents. Effects of sex (male > female) and ethnicity (majority > minority) were significant for volume and surface but minimal for cortical thickness. Adjusting volume and area for supratentorial volume attenuated or removed sex and ethnicity effects. That cortical thickness showed age-related decline and was unrelated to supratentorial volume is consistent with the radial unit hypothesis, suggesting a universal neural development characteristic robust to sex and ethnicity. Comparison of NCANDA with PING data revealed similar but flatter, age-related declines in cortical volumes and thickness. Smaller, thinner frontal, and temporal cortices in the exceeds-criteria than no/low-drinking group suggested untoward effects of excessive alcohol consumption on brain structural development.

Response inhibition deficits are widely believed to be at the core of Attention-Deficit Hyperactivity Disorder (ADHD). Several studies have examined neural architectural correlates of ADHD, but research directly examining structural correlates of response inhibition is lacking. Here we examine the relationship between response inhibition as measured by a Go/No Go task, and cortical surface area and thickness of the caudal inferior frontal gyrus (cIFG), a region implicated in functional imaging studies of response inhibition, in a sample of 114 young adults with and without ADHD diagnosed initially during childhood. We used multiple linear regression models to test the hypothesis that Go/No Go performance would be associated with cIFG surface area or thickness. Results showed that poorer Go/No Go performance was associated with thicker cIFG cortex, and this effect was not mediated by ADHD status or history of substance use. However, independent of Go/No Go performance, persistence of ADHD symptoms and more frequent cannabis use were associated with thinner cIFG. Go/No Go performance was not associated with cortical surface area. The association between poor inhibitory functioning and thicker cIFG suggests that maturation of this region may differ in low performing participants. An independent association of persistent ADHD symptoms and frequent cannabis use with thinner cIFG cortex suggests that distinct neural mechanisms within this region may play a role in inhibitory function, broader ADHD symptomatology, and cannabis use. These results contribute to Research Domain Criteria (RDoC) by revealing novel associations between neural architectural phenotypes and basic neurobehavioral processes measured dimensionally.

ObjectiveThe aims of the current study were to determine whether children with the 6 different APOE ε genotypes show differences in gray matter maturation, particularly for those with ε4 and ε2 alleles, which are associated with poorer outcomes in many neurologic disorders.MethodsA total of 1,187 healthy children (aged 3-20 years, 52.1% boys, 47.9% girls) with acceptable data from the cross-sectional Pediatric Imaging Neurocognition and Genetics Study were evaluated for the effects of 6 APOE ε genotypes on macroscopic and microscopic cortical and subcortical gray matter structures (measured with 3-tesla MRI and FreeSurfer for automated morphometry) and on cognition (NIH Toolbox).ResultsAmong APOE ε4 carriers, age-related changes in brain structures and cognition varied depending on genotype, with the smallest hippocampi in ε2ε4 children, the lowest hippocampal fractional anisotropy in younger ε4ε4 children, the largest medial orbitofrontal cortical areas in ε3ε4 children, and age-dependent thinning of the entorhinal cortex in ε4ε4 children. Younger ε4ε4 children had the lowest scores on executive function and working memory, while younger ε2ε4 children performed worse on attention tasks. Larger parietal gyri in the younger ε2ε4 children, and thinner temporal and cingulate isthmus cortices or smaller hippocampi in the younger ε4ε4 children, predicted poorer performance on attention or working memory.ConclusionsOur findings validated and extended prior smaller studies that showed altered brain development in APOE ε4-carrier children. The ε4ε4 and ε2ε4 genotypes may negatively influence brain development and brain aging at the extremes of age. Studying APOE ε polymorphisms in young children may provide the earliest indicators for individuals who might benefit from early interventions or preventive measures for future brain injuries and dementia.

ObjectiveThe aims of the current study were to determine whether children with the 6 different APOE ε genotypes show differences in gray matter maturation, particularly for those with ε4 and ε2 alleles, which are associated with poorer outcomes in many neurologic disorders.MethodsA total of 1,187 healthy children (aged 3-20 years, 52.1% boys, 47.9% girls) with acceptable data from the cross-sectional Pediatric Imaging Neurocognition and Genetics Study were evaluated for the effects of 6 APOE ε genotypes on macroscopic and microscopic cortical and subcortical gray matter structures (measured with 3-tesla MRI and FreeSurfer for automated morphometry) and on cognition (NIH Toolbox).ResultsAmong APOE ε4 carriers, age-related changes in brain structures and cognition varied depending on genotype, with the smallest hippocampi in ε2ε4 children, the lowest hippocampal fractional anisotropy in younger ε4ε4 children, the largest medial orbitofrontal cortical areas in ε3ε4 children, and age-dependent thinning of the entorhinal cortex in ε4ε4 children. Younger ε4ε4 children had the lowest scores on executive function and working memory, while younger ε2ε4 children performed worse on attention tasks. Larger parietal gyri in the younger ε2ε4 children, and thinner temporal and cingulate isthmus cortices or smaller hippocampi in the younger ε4ε4 children, predicted poorer performance on attention or working memory.ConclusionsOur findings validated and extended prior smaller studies that showed altered brain development in APOE ε4-carrier children. The ε4ε4 and ε2ε4 genotypes may negatively influence brain development and brain aging at the extremes of age. Studying APOE ε polymorphisms in young children may provide the earliest indicators for individuals who might benefit from early interventions or preventive measures for future brain injuries and dementia.

The many subcomponents of the human cortex are known to follow an anatomical pattern and functional relationship that appears to be highly conserved between individuals. This suggests that this pattern and the relationship among cortical regions are important for cortical function and likely shaped by genetic factors, although the degree to which genetic factors contribute to this pattern is unknown. We assessed the genetic relationships among 12 cortical surface areas using brain images and genotype information on 2,364 unrelated individuals, brain images on 466 twin pairs, and transcriptome data on 6 postmortem brains in order to determine whether a consistent and biologically meaningful pattern could be identified from these very different data sets. We find that the patterns revealed by each data set are highly consistent (p

Anxiety is a risk factor for many adverse neuropsychiatric and socioeconomic outcomes, and has been linked to functional and structural changes in the ventromedial prefrontal cortex (VMPFC). However, the nature of these differences, as well as how they develop in children and adolescents, remains poorly understood. More effective interventions to minimize the negative consequences of anxiety require better understanding of its neurobiology in children. Recent research suggests that structural imaging studies may benefit from clearly delineating between cortical surface area and thickness when examining these associations, as these distinct cortical phenotypes are influenced by different cellular mechanisms and genetic factors. The present study examined relationships between cortical surface area and thickness of the VMPFC and a self-report measure of anxiety (SCARED-R) in 287 youths aged 7-20 years from the Pediatric Imaging, Neurocognition, and Genetics (PING) study. Age and gender interactions were examined for significant associations in order to test for developmental differences. Cortical surface area and thickness were also examined simultaneously to determine whether they contribute independently to the prediction of anxiety. Anxiety was negatively associated with relative cortical surface area of the VMPFC as well as with global cortical thickness, but these associations diminished with age. The two cortical phenotypes contributed additively to the prediction of anxiety. These findings suggest that higher anxiety in children may be characterized by both delayed expansion of the VMPFC and an altered trajectory of global cortical thinning. Further longitudinal studies will be needed to confirm these findings.

BackgroundBoth Attention Deficit Hyperactivity Disorder (ADHD) and chronic cannabis (CAN) use have been associated with brain structural abnormalities, although little is known about the effects of both in young adults.MethodsParticipants included: those with a childhood diagnosis of ADHD who were CAN users (ADHD_CAN; n=37) and non-users (NU) (ADHD_NU; n=44) and a local normative comparison group (LNCG) who did (LNCG_CAN; n=18) and did not (LNCG_NU; n=21) use CAN regularly. Multiple regressions and MANCOVAs were used to examine the independent and interactive effects of a childhood ADHD diagnosis and CAN group status and age of onset (CUO) on subcortical volumes and cortical thickness.ResultsAfter controlling for age, gender, total brain volume, nicotine use, and past-year binge drinking, childhood ADHD diagnosis did not predict brain structure; however, persistence of ADHD was associated with smaller left precentral/postcentral cortical thickness. Compared to all non-users, CAN users had decreased cortical thickness in right hemisphere superior frontal sulcus, anterior cingulate, and isthmus of cingulate gyrus regions and left hemisphere superior frontal sulcus and precentral gyrus regions. Early cannabis use age of onset (CUO) in those with ADHD predicted greater right hemisphere superior frontal and postcentral cortical thickness.DiscussionYoung adults with persistent ADHD demonstrated brain structure abnormalities in regions underlying motor control, working memory and inhibitory control. Further, CAN use was linked with abnormal brain structure in regions with high concentrations of cannabinoid receptors. Additional large-scale longitudinal studies are needed to clarify how substance use impacts neurodevelopment in youth with and without ADHD.

Based on the Huttenlocher lecture, this article describes the need for a more integrative scientific paradigm for addressing important questions raised by key observations made over 2 decades ago. Among these are the early descriptions by Huttenlocher of variability in synaptic density in cortex of postmortem brains of children of different ages and the almost simultaneous reports of cortical volume reductions on MR imaging in children and adolescents. In spite of much progress in developmental neurobiology, developmental cognitive neuroscience, and behavioral and imaging genetics, we still do not know how these early observations relate to each other. It is argued that large scale, collaborative research programs are needed to establish the associations between behavioral differences among children and imaging biomarkers, and to link the latter to cellular changes in the developing brain. Examples of progress and challenges remaining are illustrated with data from the Pediatric Imaging, Neurocognition, and Genetics Project (PING).

We here describe a multimodality neuroimaging containing data from healthy volunteers and patients, acquired within the Lundbeck Foundation Center for Integrated Molecular Brain Imaging (Cimbi) in Copenhagen, Denmark. The data is of particular relevance for neurobiological research questions related to the serotonergic transmitter system with its normative data on the serotonergic subtype receptors 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4 and the 5-HT transporter (5-HTT), but can easily serve other purposes. The Cimbi database and Cimbi biobank were formally established in 2008 with the purpose to store the wealth of Cimbi-acquired data in a highly structured and standardized manner in accordance with the regulations issued by the Danish Data Protection Agency as well as to provide a quality-controlled resource for future hypothesis-generating and hypothesis-driven studies. The Cimbi database currently comprises a total of 1100 PET and 1000 structural and functional MRI scans and it holds a multitude of additional data, such as genetic and biochemical data, and scores from 17 self-reported questionnaires and from 11 neuropsychological paper/computer tests. The database associated Cimbi biobank currently contains blood and in some instances saliva samples from about 500 healthy volunteers and 300 patients with e.g., major depression, dementia, substance abuse, obesity, and impulsive aggression. Data continue to be added to the Cimbi database and biobank.

Little is known about how genetic variation contributes to neuroanatomical variability, and whether particular genomic regions comprising genes or evolutionarily conserved elements are enriched for effects that influence brain morphology. Here, we examine brain imaging and single-nucleotide polymorphisms (SNPs) data from ∼2,700 individuals. We show that a substantial proportion of variation in cortical surface area is explained by additive effects of SNPs dispersed throughout the genome, with a larger heritable effect for visual and auditory sensory and insular cortices (h(2)∼0.45). Genome-wide SNPs collectively account for, on average, about half of twin heritability across cortical regions (N=466 twins). We find enriched genetic effects in or near genes. We also observe that SNPs in evolutionarily more conserved regions contributed significantly to the heritability of cortical surface area, particularly, for medial and temporal cortical regions. SNPs in less conserved regions contributed more to occipital and dorsolateral prefrontal cortices.

BackgroundBrain abnormalities in adolescent heavy drinkers may result from alcohol exposure, or stem from pre-existing neural features.MethodsThis longitudinal morphometric study investigated 40 healthy adolescents, ages 12-17 at study entry, half of whom (n=20) initiated heavy drinking over the 3-year follow-up. Both assessments included high-resolution magnetic resonance imaging. FreeSurfer was used to segment brain volumes, which were measured longitudinally using the newly developed quantitative anatomic regional change analysis (QUARC) tool.ResultsAt baseline, participants who later transitioned into heavy drinking showed smaller left cingulate, pars triangularis, and rostral anterior cingulate volume, and less right cerebellar white matter volumes (p

The neuregulin-1 (NRG1) gene is one of the best-validated risk genes for schizophrenia, and psychotic and bipolar disorders. The rs6994992 variant in the NRG1 promoter (SNP8NRG243177) is associated with altered frontal and temporal brain macrostructures and/or altered white matter density and integrity in schizophrenic adults, as well as healthy adults and neonates. However, the ages when these changes begin and whether neuroimaging phenotypes are associated with cognitive performance are not fully understood. Therefore, we investigated the association of the rs6994992 variant on developmental trajectories of brain macro- and microstructures, and their relationship with cognitive performance. A total of 972 healthy children aged 3-20 years had the genotype available for the NRG1-rs6994992 variant, and were evaluated with magnetic resonance imaging (MRI) and neuropsychological tests. Age-by-NRG1-rs6994992 interactions and genotype effects were assessed using a general additive model regression methodology, covaried for scanner type, socioeconomic status, sex and genetic ancestry factors. Compared with the C-carriers, children with the TT-risk-alleles had subtle microscopic and macroscopic changes in brain development that emerge or reverse during adolescence, a period when many psychiatric disorders are manifested. TT-children at late adolescence showed a lower age-dependent forniceal volume and lower fractional anisotropy; however, both measures were associated with better episodic memory performance. To our knowledge, we provide the first multimodal imaging evidence that genetic variation in NRG1 is associated with age-related changes on brain development during typical childhood and adolescence, and delineated the altered patterns of development in multiple brain regions in children with the T-risk allele(s).

Animal data show that cortical development is initially patterned by genetic gradients largely along three orthogonal axes. We previously reported differences in genetic influences on cortical surface area along an anterior-posterior axis using neuroimaging data of adult human twins. Here, we demonstrate differences in genetic influences on cortical thickness along a dorsal-ventral axis in the same cohort. The phenomenon of orthogonal gradations in cortical organization evident in different structural and functional properties may originate from genetic gradients. Another emerging theme of cortical patterning is that patterns of genetic influences recapitulate the spatial topography of the cortex within hemispheres. The genetic patterning of both cortical thickness and surface area corresponds to cortical functional specializations. Intriguingly, in contrast to broad similarities in genetic patterning, two sets of analyses distinguish cortical thickness and surface area genetically. First, genetic contributions to cortical thickness and surface area are largely distinct; there is very little genetic correlation (i.e., shared genetic influences) between them. Second, organizing principles among genetically defined regions differ between thickness and surface area. Examining the structure of the genetic similarity matrix among clusters revealed that, whereas surface area clusters showed great genetic proximity with clusters from the same lobe, thickness clusters appear to have close genetic relatedness with clusters that have similar maturational timing. The discrepancies are in line with evidence that the two traits follow different mechanisms in neurodevelopment. Our findings highlight the complexity of genetic influences on cortical morphology and provide a glimpse into emerging principles of genetic organization of the cortex.

Adolescence is characterized by significant neuromaturation, including extensive cortical thinning, particularly in frontal regions. The goal of this study was to examine the behavioral correlates of neurostructural development in early adolescence. Participants were 185 healthy 12- to 14-year-olds (44% female) recruited from local schools. Participants completed a comprehensive neuropsychological test battery and magnetic resonance imaging session. Cortical surface reconstruction and thickness estimates were performed via FreeSurfer. Age and cortical thickness were negatively correlated in 10 brain regions, 7 of which were in frontal areas (β = −.15 to −.25, ps ≤ .05). Hierarchical linear regressions examined the influence of cortical thickness on working memory, attention, verbal learning and memory, visuospatial functioning, spatial planning and problem solving, and inhibition, controlling for age and intracranial volume. Thinner parietal cortices predicted better performances on tests of verbal learning and memory, visuospatial functioning, and spatial planning and problem solving (β = −.14 to −.24, ps ≤ .05). Age, spanning from 12 to 14 years, accounted for up to 6% of cortical thickness, suggesting substantial thinning during early adolescence, with males showing more accelerated thinning than females between ages 12 and 14. For both males and females, thinner parietal association cortices corresponded with better neurocognitive functioning above and beyond age alone.

MRI alterations in the cerebral white (WM) and gray matter (GM) are common in HIV infection, even during successful combination antiretroviral therapy (CART), and their pathophysiology and clinical significance are unclear. We evaluated the association of these alterations with recovery of CD4+ T cells. Seventy-five HIV-infected (HIV+) volunteers in the CNS HIV Anti-Retroviral Therapy Effects Research study underwent brain MRI at two visits. Multi-channel morphometry yielded volumes of total cerebral WM, abnormal WM, cortical and subcortical GM, and ventricular and sulcal CSF. Multivariable linear regressions were used to predict volumetric changes with change in current CD4 and detectable HIV RNA. On average, the cohort (79 % initially on CART) demonstrated loss of total cerebral WM alongside increases in abnormal WM and ventricular volumes. A greater extent of CD4 recovery was associated with increases in abnormal WM and subcortical GM volumes. Virologic suppression was associated with increased subcortical GM volume, independent of CD4 recovery. These findings suggest a possible link between brain alterations and immune recovery, distinct from the influence of virologic suppression. The association of increasing abnormal WM and subcortical GM volumes with CD4+ T cell recovery suggests that neuroinflammation may be one mechanism in CNS pathogenesis.