Somatomotor disconnection links sleep duration with socioeconomic context, screen time, cognition, and psychopathology.

Background: Sleep is critical for healthy brain development and emotional wellbeing, especially during adolescence when sleep, behavior, and neurobiology are rapidly evolving. Theoretical reviews and empirical research have historically focused on how sleep influences mental health through its impact on brain systems. No studies have leveraged data-driven network neuroscience methods to uncover interpretable, brain-wide signatures of sleep duration in adolescence, their socio-environmental origins, or their consequences for cognition and mental health.

Functional brain network organization and multidomain resilience to neighborhood disadvantage in youth.

Though youth living in disadvantaged neighborhoods experience greater risk for poor behavioral and mental health outcomes, many go on to show resilience in the face of adversity. A few recent studies have identified neural markers of resilience in cognitive and affective brain networks, yet the broader network organization supporting resilience in youth remains unknown, particularly in relation to neighborhood disadvantage. Moreover, most studies have defined resilience as the absence of psychopathology, which does not consider growing evidence that resilience also includes positive outcomes across multiple domains (e.

Functional Brain Connectivity Predictors of Prospective Substance Use Initiation and Their Environmental Correlates.

Background: Early substance use initiation (SUI) places youth at substantially higher risk for later substance use disorders. Furthermore, adolescence is a critical period for the maturation of brain networks, the pace and magnitude of which are susceptible to environmental influences and may shape risk for SUI.

Methods: We examined whether patterns of functional brain connectivity during rest (rsFC), measured longitudinally during pre- and early adolescence, can predict future SUI.

Assessing neurocognitive maturation in early adolescence based on baby and adult functional brain landscapes.

Adolescence is a period of growth in cognitive performance and functioning. Recently, data-driven measures of brain-age gap, which can index cognitive decline in older populations, have been utilized in adolescent data with mixed findings. Instead of using a data-driven approach, here we assess the maturation status of the brain functional landscape in early adolescence by directly comparing an individual's resting-state functional connectivity (rsFC) to the canonical early-life and adulthood communities.

Socioeconomic resources in youth are linked to divergent patterns of network integration/segregation across the brain's transmodal axis.

Socioeconomic resources (SER) calibrate the developing brain to the current context, which can confer or attenuate risk for psychopathology across the lifespan. Recent multivariate work indicates that SER levels powerfully relate to intrinsic functional connectivity patterns across the entire brain. Nevertheless, the neuroscientific meaning of these widespread neural differences remains poorly understood, despite its translational promise for early risk identification, targeted intervention, and policy reform.

Flexible adaptation of task-positive brain networks predicts efficiency of evidence accumulation.

Efficiency of evidence accumulation (EEA), an individual's ability to selectively gather goal-relevant information to make adaptive choices, is thought to be a key neurocomputational mechanism associated with cognitive functioning and transdiagnostic risk for psychopathology. However, the neural basis of individual differences in EEA is poorly understood, especially regarding the role of largescale brain network dynamics. We leverage data from 5198 participants from the Human Connectome Project and Adolescent Brain Cognitive Development Study to demonstrate a strong association between EEA and flexible adaptation to cognitive demand in the "task-positive" frontoparietal and dorsal attention networks.

Functional brain connectivity predictors of prospective substance use initiation and their environmental correlates.

Background: Early substance use initiation (SUI) places youth at substantially higher risk for later substance use disorders. Furthermore, adolescence is a critical period for the maturation of brain networks, the pace and magnitude of which are susceptible to environmental influences and may shape risk for SUI.

Methods: We examined whether patterns of functional brain connectivity during rest (rsFC), measured longitudinally in pre-and-early adolescence, can predict future SUI.

Image response regression via deep neural networks.

Delineating associations between images and covariates is a central aim of imaging studies. To tackle this problem, we propose a novel non-parametric approach in the framework of spatially varying coefficient models, where the spatially varying functions are estimated through deep neural networks. Our method incorporates spatial smoothness, handles subject heterogeneity, and provides straightforward interpretations.

Data-driven, generalizable prediction of adolescent sleep disturbances in the multisite Adolescent Brain Cognitive Development Study.

Study Objectives: Sleep disturbances are common in adolescence and associated with a host of negative outcomes. Here, we assess associations between multifaceted sleep disturbances and a broad set of psychological, cognitive, and demographic variables using a data-driven approach, canonical correlation analysis (CCA).

Methods: Baseline data from 9093 participants from the Adolescent Brain Cognitive Development (ABCD) Study were examined using CCA, a multivariate statistical approach that identifies many-to-many associations between two sets of variables by finding combinations for each set of variables that maximize their correlation.

Socioeconomic resources in youth are linked to divergent patterns of network integration and segregation across the brain's transmodal axis.

Socioeconomic resources (SER) calibrate the developing brain to the current context, which can confer or attenuate risk for psychopathology across the lifespan. Recent multivariate work indicates that SER levels powerfully influence intrinsic functional connectivity patterns across the entire brain. Nevertheless, the neurobiological meaning of these widespread alterations remains poorly understood, despite its translational promise for early risk identification, targeted intervention, and policy reform.

Neighborhood poverty during childhood prospectively predicts adolescent functional brain network architecture.

Family poverty has been associated with altered brain structure, function, and connectivity in youth. However, few studies have examined how disadvantage within the broader neighborhood may influence functional brain network organization. The present study leveraged a longitudinal community sample of 538 twins living in low-income neighborhoods to evaluate the prospective association between exposure to neighborhood poverty during childhood (6-10 y) with functional network architecture during adolescence (8-19 y).

Generalizable prediction of childhood ADHD symptoms from neurocognitive testing and youth characteristics.

Childhood attention-deficit/hyperactivity disorder (ADHD) symptoms are believed to result from disrupted neurocognitive development. However, evidence for the clinical and predictive value of neurocognitive assessments in this context has been mixed, and there have been no large-scale efforts to quantify their potential for use in generalizable models that predict individuals' ADHD symptoms in new data. Using data drawn from the Adolescent Brain Cognitive Development Study (ABCD), a consortium that recruited a diverse sample of over 10,000 youth (ages 9-10 at baseline) across 21 U.

Differential Item Functioning in Reports of Delinquent Behavior Between Black and White Youth: Evidence of Measurement Bias in Self-Reports of Arrest in the Adolescent Brain Cognitive Development Study.

Youth self-reports are a mainstay of delinquency assessment; however, making valid inferences about delinquency using these assessments requires equivalent measurement across groups of theoretical interest. We examined whether a brief 10-item delinquency measure exhibited measurement invariance across non-Hispanic White ( = 6,064) and Black ( = 1,666) youth (ages 10-11 years old) in the Adolescent Brain Cognitive Development Study (ABCD Study®). We detected differential item functioning (DIF) in two items.

Evidence for embracing normative modeling.

In this work, we expand the normative model repository introduced in Rutherford et al., 2022a to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online platform for transferring these models to new data sources. We showcase the value of these models with a head-to-head comparison between the features output by normative modeling and raw data features in several benchmarking tasks: mass univariate group difference testing (schizophrenia versus control), classification (schizophrenia versus control), and regression (predicting general cognitive ability).

Socioeconomic resources are associated with distributed alterations of the brain's intrinsic functional architecture in youth.

Little is known about how exposure to limited socioeconomic resources (SER) in childhood gets "under the skin" to shape brain development, especially using rigorous whole-brain multivariate methods in large, adequately powered samples. The present study examined resting state functional connectivity patterns from 5821 youth in the Adolescent Brain Cognitive Development (ABCD) study, employing multivariate methods across three levels: whole-brain, network-wise, and connection-wise. Across all three levels, SER was associated with widespread alterations across the connectome.

Whether implicit attitudes exist is one question, and whether we can measure individual differences effectively is another.

Questions about measurement of individual differences in implicit attitudes, which have been the focus so far in this exchange, should be distinguished from more general questions about whether implicit attitudes exist and operate in our minds. Theorists frequently move too quickly from pessimistic results regarding the first set of questions to pessimistic conclusions about the second. That is, they take evidence that indirect measures such as the implicit association test (IAT) disappoint as individual difference measures and use it to (mistakenly) suggest that people do not in fact have implicit attitudes directed at stigmatized groups.

Will-powered: Synchronic regulation is the difference maker for self-control.

Philosophers, psychologists, and economists have reached the consensus that one can use two different kinds of regulation to achieve self-control. Synchronic regulation uses willpower to resist current temptation. Diachronic regulation implements a plan to avoid future temptation.

Task-general efficiency of evidence accumulation as a computationally-defined neurocognitive trait: Implications for clinical neuroscience.

Quantifying individual differences in higher-order cognitive functions is a foundational area of cognitive science that also has profound implications for research on psychopathology. For the last two decades, the dominant approach in these fields has been to attempt to fractionate higher-order functions into hypothesized components (e.g.

Charting brain growth and aging at high spatial precision.

Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources.

Widespread attenuating changes in brain connectivity associated with the general factor of psychopathology in 9- and 10-year olds.

Convergent research identifies a general factor ("P factor") that confers transdiagnostic risk for psychopathology. Large-scale networks are key organizational units of the human brain. However, studies of altered network connectivity patterns associated with the P factor are limited, especially in early adolescence when most mental disorders are first emerging.

Brain-wide functional connectivity patterns support general cognitive ability and mediate effects of socioeconomic status in youth.

General cognitive ability (GCA) is an individual difference dimension linked to important academic, occupational, and health-related outcomes and its development is strongly linked to differences in socioeconomic status (SES). Complex abilities of the human brain are realized through interconnections among distributed brain regions, but brain-wide connectivity patterns associated with GCA in youth, and the influence of SES on these connectivity patterns, are poorly understood. The present study examined functional connectomes from 5937 9- and 10-year-olds in the Adolescent Brain Cognitive Development (ABCD) multi-site study.

Impaired control in addiction involves cognitive distortions and unreliable self-control, not compulsive desires and overwhelmed self-control.

Impaired control in addiction involves a characteristic but obscure kind of partial control. Certain aspects of control over drug use are clearly reduced, reflected in difficulty cutting back and relapse. However, other aspects of control are clearly preserved, as reflected in substantial sensitivity to situational incentives-for example, the ability to defer use when needed.

The General Factor of Psychopathology in the Adolescent Brain Cognitive Development (ABCD) Study: A Comparison of Alternative Modeling Approaches.

Many models of psychopathology include a single general factor of psychopathology (GFP) or " factor" to account for covariation across symptoms. The Adolescent Brain Cognitive Development (ABCD) Study provides a rich opportunity to study the development of the GFP. However, a variety of approaches for modeling the GFP have emerged, raising questions about how modeling choices impact estimated GFP scores.

Validating dynamicity in resting state fMRI with activation-informed temporal segmentation.

Confirming the presence (or absence) of dynamic functional connectivity (dFC) states during rest is an important open question in the field of cognitive neuroscience. The prevailing dFC framework aims to identify dynamics directly from connectivity estimates with a sliding window approach, however this method suffers from several drawbacks including sensitivity to window size and poor test-retest reliability. We hypothesize that time-varying changes in functional connectivity are mirrored by significant temporal changes in functional activation, and that this coupling can be leveraged to study dFC without the need for a predefined sliding window.