Biology subjects

Barch, D. M.

Publications and source records attributed to Barch, D. M..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Associations between parenting and cognitive and language abilities at age 2 depend on prenatal exposure to disadvantage

ObjectiveTo investigate whether parenting and/or neonatal brain volumes mediate the associations between prenatal social disadvantage (PSD) and cognitive/language abilities; and whether these mechanisms vary by level of disadvantage. Study DesignPregnant women were recruited from obstetric clinics in St Louis, Missouri. PSD encompassed access to social (e.g., education) and material (e.g., income-to-needs, health insurance, area deprivation, and nutrition) resources during pregnancy. Neonates underwent brain magnetic resonance imaging. Mother-child dyads (N=202) returned at age 1 for parenting measures and at age 2 for cognition/language assessments (Bayley-III). Generalized additive and mediation models tested hypotheses. ResultsGreater PSD was nonlinearly associated with poorer cognitive/language scores. The relation between parenting and cognition/language was moderated by PSD, such that supportive and non-supportive parenting behaviors only related to cognition/language in children with low PSD. Further, parenting mediations differed by level of PSD, such that both supportive and non-supportive parenting mediated PSD-cognition/language associations in children with low PSD, but not in children with high PSD. PSD-associated reductions in neonatal subcortical grey matter ({beta}=.19, q=.03), white matter ({beta}=.23, q=.02), and total brain volume ({beta}=.18, q=.03) were associated with lower cognition, but they did not mediate PSD-cognition associations. ConclusionsParenting moderates and mediates associations between PSD and early cognitive and language development, but only in families with lower levels of social disadvantage. These findings, while correlational, suggest that there may be a critical threshold of disadvantage, below which mediating or moderating factors become less effective, highlighting the importance of reducing disadvantage as primary prevention.

neuroscience↗

bioRxiv2024

Higher amplitudes of visual networks are associated with trait but not state- depression.

Despite depression being a leading cause of global disability, neuroimaging studies have struggled to identify replicable neural correlates of depression or explain limited variance. This challenge may, in part, stem from the intertwined state (current symptoms; variable) and trait (general propensity; stable) experiences of depression. Here, we sought to disentangle state from trait experiences of depression by leveraging a longitudinal cohort and stratifying individuals into four groups: those in remission ( trait depression group), those with large longitudinal severity changes in depression symptomatology ( state depression group), and their respective matched control groups (total analytic n=1,030). We hypothesized that spatial network organization would be linked to trait depression due to its temporal stability, whereas functional connectivity between networks would be more sensitive to state-dependent depression symptoms due to its capacity to fluctuate. We identified 15 large-scale probabilistic functional networks from resting-state fMRI data and performed group comparisons on the amplitude, connectivity, and spatial overlap between these networks, using matched control participants as reference. Our findings revealed higher amplitude in visual networks for the trait depression group at the time of remission, in contrast to controls. This observation may suggest altered visual processing in individuals predisposed to developing depression over time. No significant group differences were observed in any other network measures for the trait-control comparison, nor in any measures for the state-control comparison. These results underscore the overlooked contribution of visual networks to the psychopathology of depression and provide evidence for distinct neural correlates between state and trait experiences of depression.

neuroscience↗

bioRxiv2024

A Data-Driven Latent Variable Approach to Validating the Research Domain Criteria (RDoC) Framework

Despite the widespread use of the Research Domain Criteria (RDoC) framework in psychiatry and neuroscience, recent studies suggest that the RDoC is insufficiently specific or excessively broad relative to the underlying brain circuitry it seeks to elucidate. To address these concerns, we employed a latent variable approach using bifactor analysis. We examined 84 whole-brain task-based fMRI (tfMRI) activation maps from 19 studies with 6,192 participants. A curated subset of 37 maps with a balanced representation of RDoC domains constituted the training set, and the remaining held-out maps formed the internal validation set. External validation was conducted using 36 peak coordinate activation maps from Neurosynth, using terms of RDoC constructs as seeds for topic meta-analysis. Here, we show that a bifactor model incorporating a task-general domain and splitting the cognitive systems domain better fits the examined corpus of tfMRI data than the current RDoC framework. We also identify the domain of arousal and regulatory systems as underrepresented. Our data-driven validation supports revising the RDoC framework to reflect underlying brain circuitry more accurately.

neuroscience↗

bioRxiv2023

Functional parcellation of the neonatal brain

The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that adult- and older infant-derived parcels are a poor fit with neonatal data, emphasizing the need for neonatal-specific parcels. We next derive a set of 283 cortical surface parcels from a sample of n=261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies. HIGHLIGHTSO_LINeonatal cortical surface parcels derived based on abrupt changes in functional connectivity (FC) were highly homogenous and were validated in external neonatal datasets. C_LIO_LIBorders between cortical parcels were smoother (less abrupt) in group-average neonatal data compared to adults, likely due to increased heterogeneity in boundary location across individual neonates. C_LIO_LIParcels derived from adults and older infants show poor fit with neonatal resting-state FC data, underscoring the need for a neonatal-specific parcellation. C_LI

neuroscience↗

bioRxiv2023

Prenatal environment is associated with the pace of cortical network development over the first three years of life

Environmental influences on brain structure and function during early development have been well-characterized. In pre-registered analyses, we test the theory that socioeconomic status (SES) is associated with differences in trajectories of intrinsic brain network development from birth to three years (n = 261). Prenatal SES is associated with developmental increases in cortical network segregation, with neonates and toddlers from lower-SES backgrounds showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between SES and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. SES-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results yield key insight into the timing and directionality of associations between the early environment and trajectories of cortical development.

neuroscience↗

bioRxiv2023

Uncovering and mitigating bias in large, automated MRI analyses of brain development

Large, population-based MRI studies of adolescents promise transformational insights into neurodevelopment and mental illness risk 1, 2. However, MRI studies of youth are especially susceptible to motion and other artifacts 3, 4. These artifacts may go undetected by automated quality control (QC) methods that are preferred in high-throughput imaging studies, 5 and can potentially introduce non-random noise into clinical association analyses. Here we demonstrate bias in structural MRI analyses of children due to inclusion of lower quality images, as identified through rigorous visual quality control of 11,263 T1 MRI scans obtained at age 9-10 through the Adolescent Brain Cognitive Development (ABCD) Study6. Compared to the best-rated images (44.9% of the sample), lower-quality images generally associated with decreased cortical thickness and increased cortical surface area measures (Cohens d 0.14-2.84). Variable image quality led to counterintuitive patterns in analyses that associated structural MRI and clinical measures, as inclusion of lower-quality scans altered apparent effect sizes in ways that increased risk for both false positives and negatives. Quality-related biases were partially mitigated by controlling for surface hole number, an automated index of topological complexity that differentiated lower-quality scans with good specificity at Baseline (0.81-0.93) and in 1,000 Year 2 scans (0.88-1.00). However, even among the highest-rated images, subtle topological errors occurred during image preprocessing, and their correction through manual edits significantly and reproducibly changed thickness measurements across much of the cortex (d 0.15-0.92). These findings demonstrate that inadequate QC of youth structural MRI scans can undermine advantages of large sample size to detect meaningful associations.

neuroscience↗

bioRxiv2022

A mind-body interface alternates with effector-specific regions in motor cortex

Primary motor cortex (M1) has been thought to form a continuous somatotopic homunculus extending down precentral gyrus from foot to face representations1,2. The motor homunculus has remained a textbook pillar of functional neuroanatomy, despite evidence for concentric functional zones3 and maps of complex actions4. Using our highest precision functional magnetic resonance imaging (fMRI) data and methods, we discovered that the classic homunculus is interrupted by regions with sharpy distinct connectivity, structure, and function, alternating with effector-specific (foot, hand, mouth) areas. These inter-effector regions exhibit decreased cortical thickness and strong functional connectivity to each other, and to prefrontal, insular, and subcortical regions of the Cingulo-opercular network (CON), critical for executive action5 and physiological control6, arousal7, and processing of errors8 and pain9. This interdigitation of action control-linked and motor effector regions was independently verified in the three largest fMRI datasets. Macaque and pediatric (newborn, infant, child) precision fMRI revealed potential cross-species analogues and developmental precursors of the inter-effector system. An extensive battery of motor and action fMRI tasks documented concentric somatotopies for each effector, separated by the CON-linked inter-effector regions. The inter-effector regions lacked movement specificity and co-activated during action planning (coordination of hands and feet), and axial body movement (e.g., abdomen, eyebrows). These results, together with prior work demonstrating stimulation-evoked complex actions4 and connectivity to internal organs (e.g., adrenal medulla)10, suggest that M1 is punctuated by an integrative system for implementing whole-body action plans. Thus, two parallel systems intertwine in motor cortex to form an integrate-isolate pattern: effector-specific regions (foot, hand, mouth) for isolating fine motor control, and a mind-body interface (MBI) for the integrative whole-organism coordination of goals, physiology, and body movement.

neuroscience↗

bioRxiv2022

Neurodevelopmental Patterns of Early Postnatal White Matter Maturation Represent Distinct Underlying Microstructure and Histology

During the early postnatal period, cerebral white matter undergoes rapid maturation through a complex series of interrelated cellular and histogenetic processes. Accurately quantifying these processes is important for improving understanding of early brain development, developmental abnormalities related to prematurity, and neurodevelopmental diseases. Past efforts have used magnetic resonance imaging (MRI) to track these developmental processes in vivo. However, most previous studies have relied on single imaging modality data and have often been limited by small samples and analytics that do not evaluate complex multivariate imaging patterns. Here, we applied an advanced unsupervised multivariate pattern analysis technique, non-negative matrix factorization (NMF), to T2w/T1w signal ratio maps from a large cohort of newborns (Developing Human Connectome Project [dHCP], n=342), revealing patterns of synchronous white matter maturation. These patterns showed divergent age-related maturational trajectories and differential susceptibility to premature birth, which were replicated in an independent large sample of newborns (Early Life Adversity, Biological Embedding, and Risk for Developmental Precursors of Mental Disorders [eLABE], n=239). Furthermore, we showed that T2w/T1w signal variations in white matter maturational patterns are explained by differential contributions of white matter microstructure indices (i.e., free water content and neurite density index) derived from neurite orientation dispersion and density imaging (NODDI) modeling of diffusion-weighted MRI. Finally, we demonstrated how white matter maturation patterns relate to distinct histological features by comparing our findings with postmortem late fetal/early postnatal brain tissue staining. Together, these results delineate a novel MRI representation of white matter microstructural and histological reorganization during the early postnatal development.

neuroscience↗

bioRxiv2021

Reliability and Stability Challenges in ABCD Task fMRI Data

Trait stability of measures is an essential requirement for individual differences research. Functional MRI has been increasingly used in studies that rely on the assumption of trait stability, such as attempts to relate task related brain activation to individual differences in behavior and psychopathology. However, recent research using adult samples has questioned the trait stability of task-fMRI measures, as assessed by test-retest correlations. To date, little is known about trait stability of task fMRI in children. Here, we examined within-session reliability and longitudinal stability of task-fMRI using data from the Adolescent Brain Cognitive Development (ABCD) Study using its tasks focused on reward processing, response inhibition, and working memory. We also evaluated the effects of factors potentially affecting reliability and stability. Reliability and stability [quantified via an intraclass correlation (ICC) that focuses on rank consistency] was poor in virtually all brain regions, with an average ICC of .078 and .054 for short (within-session) and long-term (between-session) ICCs, respectively, in regions of interest (ROIs) historically-recruited by the tasks. ICC values in ROIs did not exceed the poor cut-off of .4, and in fact rarely exceeded .2 (only 5.9%). Motion had a pronounced effect on estimated ICCs, with the lowest motion quartile of participants having a mean reliability/stability three times higher (albeit still poor) than the highest motion quartile. Regions with stronger activation tended to show higher ICCs, with the absolute value of activity and reliability/stability correlating at .53. Across regions, the magnitude of age-related longitudinal (between-session) changes positively correlated with the longitudinal stability of individual differences, which suggests developmental change was not necessarily responsible for poor stability. Poor reliability and stability of task-fMRI, particularly in children, diminishes potential utility of fMRI data due to a drastic reduction of effect sizes and, consequently, statistical power for the detection of brain-behavior associations. This essential issue needs to be addressed through optimization of preprocessing pipelines and data denoising methods.

neuroscience↗

bioRxiv2020

Smaller Hippocampal Volume among Black and Latinx Youth Living in High-Stigma Contexts

BackgroundTo determine whether being raised in a stigmatizing context influences neurodevelopment in children. MethodsWe drew data from one of the first national, multi-site neuroimaging studies with substantial variability in sociopolitical contexts: the Adolescent Brain and Cognitive Development study (N=11,534; M=9.9 years). We measured structural stigma surrounding gender, race, and Latinx ethnicity using objective state-level indicators of social policies and prejudicial attitudes and individual-level experiences of perceived discrimination, and examined associations with two neural markers: hippocampal volume and amygdala reactivity to threat. ResultsIn a pre-registered analysis, we find that Black (B=-57.27, p=0.025) and Latinx (B=-41.02, p=0.037) youths raised in higher-stigma environments have smaller hippocampal volume than youths raised in low-stigma contexts, controlling for demographics and family socioeconomic status. This association was marginal among girls (p=0.082). The magnitude of the observed difference in hippocampal volume between high and low structural stigma contexts was equivalent to a $20,000 difference in annual family income. Stigmatizing environments were unrelated to hippocampal volume in non-stigmatized youth, providing evidence of specificity. Perceived discrimination was unrelated to hippocampal volume among any of the stigmatized groups. No associations between individual or structural forms of stigma and amygdala reactivity to threat were observed in the stigmatized groups. ConclusionsWe provide novel evidence that an objective measure of stigma at the contextual level (structural stigma) may have a stronger influence on neurodevelopment than subjective perceptions of stigma measured at the individual level, suggesting that contextual approaches may yield new insights into neurodevelopment.

neuroscience↗

bioRxiv2020

Meaningful Effects in the Adolescent Brain Cognitive Development Study

The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and childrens health in the United States. A cohort of n= 11,880 children aged 9-10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

neuroscience↗

bioRxiv2020

Towards Reproducible Brain-Wide Association Studies

Magnetic resonance imaging (MRI) continues to drive many important neuroscientific advances. However, progress in uncovering reproducible associations between individual differences in brain structure/function and behavioral phenotypes (e.g., cognition, mental health) may have been undermined by typical neuroimaging sample sizes (median N=25)1,2. Leveraging the Adolescent Brain Cognitive Development (ABCD) Study3 (N=11,878), we estimated the effect sizes and reproducibility of these brain-wide associations studies (BWAS) as a function of sample size. The very largest, replicable brain-wide associations for univariate and multivariate methods were r=0.14 and r=0.34, respectively. In smaller samples, typical for brain-wide association studies (BWAS), irreproducible, inflated effect sizes were ubiquitous, no matter the method (univariate, multivariate). Until sample sizes started to approach consortium-levels, BWAS were underpowered and statistical errors assured. Multiple factors contribute to replication failures4-6; here, we show that the pairing of small brain-behavioral phenotype effect sizes with sampling variability is a key element in wide-spread BWAS replication failure. Brain-behavioral phenotype associations stabilize and become more reproducible with sample sizes of N{gap}2,000. While investigator-initiated brain-behavior research continues to generate hypotheses and propel innovation, large consortia are needed to usher in a new era of reproducible human brain-wide association studies.

neuroscience↗

bioRxiv2020

Brain Network Mechanisms of Visual Shape Completion

Visual shape completion represents object shape, size, and number from spatially segregated edges. Despite being extensively investigated, the processs underlying brain regions, networks, and functional connections are still not well understood. To shed light on the topic, we scanned (fMRI) healthy adults during rest and during a task in which they discriminated pac-man configurations that formed or failed to form visually completed shapes (illusory and fragmented condition, respectively). Task activation differences (illusory-fragmented), resting-state functional connectivity, and multivariate pattern differences were identified on the cortical surface using 360 predefined parcels and 12 functional networks composed of such parcels. Brain activity flow mapping (ActFlow) was used to evaluate the likely involvement of resting-state connections for shape completion. We identified 34 differentially-active parcels including a posterior temporal region, PH, whose activity was consistent across all 20 observers. Significant task regions primarily occupied the secondary visual network but also incorporated the frontoparietal, dorsal attention, default mode, and cingulo-opercular networks. Each parcels task activation difference could be modeled via its resting-state connections with the remaining parcels (r=.62, p<10-9), suggesting that such connections undergird shape completion. Functional connections from the dorsal attention network were key in modeling activation differences in the secondary visual network and across all remaining networks. Taken together, these results suggest that shape completion relies upon a distributed but densely interconnected network coalition that is centered in the secondary visual network, coordinated by the dorsal attention network, and inclusive of at least three other networks. HighlightsO_LIShape completion differentially activates regions distributed across five networks C_LIO_LIThe secondary visual network plays the clearest role in shape completion C_LIO_LIDorsal attention functional connections likely coordinate activity across networks C_LIO_LIPosterior temporal region, PH, played a highly consistent role in completion C_LI

neuroscience↗

bioRxiv2019

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity

Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., motion parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (> 0.1 Hz, here referred to as HF-motion), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0 - 2.5 s.) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 - 2.5 s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is relatively trait-like and more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants. Highlights- Single-band fMRI motion traces show factitious high-frequency content (HF-motion) - The magnitude of HF-motion relates to age and other demographic factors - HF-motion elevates framewise displacement (FD) and causes data loss - Substantial fMRI data can be recovered from censoring by filtering motion traces - Filtering motion traces reduces motion artifacts in functional connectivity

neuroscience↗

bioRxiv2019

The genetic architecture of human brainstem structures and their involvement in common brain disorders

Brainstem regions support critical bodily functions, yet their genetic architectures and involvement in brain disorders remain understudied. Here, we examined volumes of brainstem structures using magnetic resonance imaging in 43,353 individuals. In 27,034 genotyped healthy participants, we identified 16 genetic loci associated with whole brainstem volume and 10, 23, 3, and 9 loci associated with volumes of the midbrain, pons, superior cerebellar peduncle, and medulla oblongata, respectively. These loci were mapped to 305 genes, including genes linked to brainstem development and common brain disorders. We detected genetic overlap between the brainstem volumes and eight psychiatric and neurological disorders. Using imaging data from 16,319 additional individuals, we observed differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinsons disease. Together, our results provide new insights into the genetic underpinnings of brainstem structures and support their involvement in common brain disorders.

neuroscience↗

bioRxiv2019

Behavioral and neural signatures of working memory in childhood

Working memory function changes across development and varies across individuals. The patterns of behavior and brain function that track individual differences in working memory during development, however, are not well understood. Here we establish associations between working memory, cognitive abilities, and functional MRI activation in data from over 4,000 9-10-year-olds enrolled in the Adolescent Brain Cognitive Development study, an ongoing longitudinal study in the United States. Behavioral analyses reveal robust relationships between working memory, short-term memory, language skills, and fluid intelligence. Analyses relating out-of-scanner working memory performance to memory-related fMRI activation in an emotional n-back task demonstrate that frontoparietal activity in response to an explicit memory challenge indexes working memory ability. Furthermore, this relationship is domain-specific, such that fMRI activation related to emotion processing during the emotional n-back task, inhibitory control during a stop-signal task, and reward processing during a monetary incentive delay task does not track memory abilities. Together these results inform our understanding of the emergence of individual differences in working memory and lay the groundwork for characterizing the ways in which they change across adolescence.

neuroscience↗

bioRxiv2019

Delineating and validating higher-order dimensions of psychopathology in the Adolescent Brain Cognitive Development (ABCD) study

Hierarchical dimensional systems of psychopathology promise more informative descriptions for understanding risk and predicting outcome than traditional diagnostic systems, but it is unclear how many major dimensions they should include. We delineated the hierarchy of childhood and adult psychopathology and validated it against clinically-relevant measures. Participants were 4,524 9- and 10-year-old children and their parents from the Adolescent Brain Cognitive Development (ABCD) study. Factor analyses on items from the Child Behavior Checklist and Adult Self-Report characterized a dimensional hierarchy. We examined the familial aggregation of the psychopathology dimensions, and the ability of different factor solutions to account for risks factors, social, educational and cognitive functioning, and physical and mental health service utilization. A hierarchical structure with a general psychopathology ( p) factor at the apex and five specific factors (internalizing, somatoform, detachment, neurodevelopmental, and externalizing) emerged in children. Adult factors were similar, but externalizing behaviors separated into disinhibited and antagonistic factors. Child and parent p-factors correlated highly (r=.61, P<.001), and smaller but significant correlations emerged for convergent dimensions between parents and children after controlling for p-factors (r=.10-20, P<.001). A model with childhood p-factor alone explained mental health service utilization (R2=.13, P<.001), but up to five dimensions provided incremental validity to account for developmental risk and current functioning (R2=.03-.20, P<.001). In this first investigation comprehensively mapping the psychopathology hierarchy in children and adults, we delineated a hierarchy of higher-order dimensions associated with a range of clinically-relevant validators. These findings hold important implications for psychiatric nosology and future research in this sample.

epidemiology↗

bioRxiv2018

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The ABCD Study is a collaborative effort, including a Coordinating Center, 21 data acquisition sites across the United States, and a Data Analysis and Informatics Center (DAIC). The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data will provide a resource of unprecedented scale and depth for studying typical and atypical development. Here, we describe the baseline neuroimaging processing and subject-level analysis methods used by the ABCD DAIC in the centralized processing and extraction of neuroanatomical and functional imaging phenotypes. Neuroimaging processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI.\n\nHighlightsO_LIAn overview of the MRI processing pipeline for the ABCD Study\nC_LIO_LIA discussion on the challenges of large, multisite population studies\nC_LIO_LIA methodological reference for users of publicly shared data from the ABCD Study\nC_LI

neuroscience↗