cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15154/1528316
title: Differences in cortical morphology and child internalizing or externalizing problems: accounting for the co-occurrence

description: Background: Childhood internalizing and externalizing problems frequently co-occur. Many studies report neural correlates of either internalizing or externalizing problems, but few account for their co-occurrence. We aimed to assess specific cortical substrates of these psychiatric problems.

Methods: We used data from 9,635 children aged 9-11 years in the baseline Adolescent Brain Cognitive Development Study. Internalizing and externalizing problem composite scales scores were derived from the Child Behavior Checklist. We standardized FreeSurfer-derived volumes of 68 cortical regions. We examined internalizing and externalizing problems separately and jointly (covariate-adjustment) in relation to cortical volumes, with and without adjusting for total brain volume (TBV) in multivariate linear regressions adjusted for demographics and multiple comparisons. We fit bifactor models to confirm the consistency of patterns exploring specific internalizing and specific externalizing problems. Sensitivity analyses included a vertex-wide analysis and a replication in another large population-based study.

Results: In separate TBV-unadjusted analyses, externalizing and internalizing problems were associated with smaller cortical volumes. If adjusted for externalizing behavior, however, larger cortical volumes were associated with internalizing problems, while smaller cortical volumes remained associated with externalizing problems after adjustment for internalizing problems. The bifactor model produced similar results, which were consistently replicated in another pre-adolescent neuroimaging sample. These associations likely represent global effects: adjusting for TBV rendered most associations non-significant. Vertex-wise analyses confirmed global patterns.

Conclusion: Our results suggest that internalizing and externalizing problems have globally opposing, and non-specific associations with cortical morphology in childhood, which are only apparent if analyses account for their co-occurrence.
DOI: 10.15154/1528319
title: Childhood Maltreatment in Females Is Associated with Enhanced Fear Acquisition and an Overgeneralization of Fear.

description: Childhood maltreatment may alter fear neurocircuitry, which results in pathological anxiety and depression. One alteration of fear-related behaviors that has been observed in several psy-chiatric populations is an overgeneralization of fear. Thus, we examined the association between childhood maltreatment and fear generalization in a non-clinical sample of young adults. Two hundred and ninety-one participants underwent differential fear conditioning in a fear-potentiated startle paradigm. One visual stimulus (CS+), but not another (CS-), was associ-ated with an aversive airblast to the throat (US) during acquisition. The next day, participants were tested for their fear responses to the CS+, CS-, and several generalization stimuli (GS) without the presence of the US. Participants also completed questionnaires that assessed symp-toms of childhood maltreatment, anxiety, depression, and post-traumatic stress disorder (PTSD). Participants reporting high childhood maltreatment (n = 71; 23 males, 48 females) exhibited sig-nificantly greater anxiety, depression, and symptoms of PTSD than participants reporting low childhood maltreatment (n = 220; 133 males, 87 females). Females reporting high childhood maltreatment demonstrated significantly enhanced fear learning and greater fear generalization, based on their fear-potentiated startle responses. Our findings suggest that childhood maltreat-ment may sex-dependently influence the development of fear neurocircuitry and result in great-er fear generalization in maltreated females.
DOI: 10.15154/1528321
title: Developmental Milestones of Infancy and Associations with Later Childhood Neurodevelopmental Outcomes in the Adolescent Brain Cognitive Development (ABCD) Study

description: The age at attaining infancy developmental milestones has been associated with later neurodevelopmental outcomes, but evidence from large and diverse samples is lacking. We investigated this by analyzing data of 5360 singleton children aged 9–10 from 17 states in the US enrolled in the Adolescent Brain Cognitive Development (ABCD) study during 2016–2020. Delays in four milestones (first roll over, unaided sitting, unaided walking, and speaking first words) were defined using the 90th percentile of age at attainment reported by children’s biological mothers. Childhood neurocognitive function was measured by research assistants using the NIH toolbox, and children reported their behavioral problems using the Brief Problem Monitor. Linear mixed-effects models were employed to investigate the association between delays in single or multiple milestones and childhood neurobehavioral outcomes. Delays in first roll over, unaided sitting, or walking were associated with poorer childhood neurocognitive function, while delay in speaking first words was associated with both poorer neurocognitive function and behavioral problems. Children who had delays in both motor and language milestones had the worst neurocognitive function and behavioral outcomes. Our results suggest that delays in motor and language milestone attainment during infancy are predictive of childhood neurobehavioral outcomes.
DOI: 10.15154/1528326
title: Predicting multilingual effects on executive function and individual connectomes in children: An ABCD study

description: While there is a substantial amount of work studying multilingualism’s effect on cognitive functions, little is known about how the multilingual experience modulates the brain as a whole. In this study, we analyzed data of over 1,000 children from the Adolescent Brain Cognitive Development (ABCD) Study to examine whether monolinguals and multilinguals differ in executive function, functional brain connectivity, and brain–behavior associations. We observed significantly better performance from multilingual children than monolinguals in working-memory tasks. In one finding, we were able to classify multilinguals from monolinguals using only their whole-brain functional connectome at rest and during an emotional n-back task. Compared to monolinguals, the multilingual group had different functional connectivity mainly in the occipital lobe and subcortical areas during the emotional n-back task and in the occipital lobe and prefrontal cortex at rest. In contrast, we did not find any differences in behavioral performance and functional connectivity when performing a stop-signal task. As a second finding, we investigated the degree to which behavior is reflected in the brain by implementing a connectome-based behavior prediction approach. The multilingual group showed a significant correlation between observed and connectome-predicted individual working-memory performance scores, while the monolingual group did not show any correlations. Overall, our observations suggest that multilingualism enhances executive function and reliably modulates the corresponding brain functional connectome, distinguishing multilinguals from monolinguals even at the developmental stage.
DOI: 10.15154/1528328
title: Functional Connectivity Stability: A Signature of Neurocognitive Development and Psychiatric Problems in Children

description: Brain functional connectivity has been shown to provide a type of fingerprint for adult subjects. However, most studies tend to focus on the connectivity strength rather than its stability across scans. In this study, we performed for the first time a large-scale analysis of within-individual stability of functional connectivity (FC) using 9071 children from the Adolescent Brain Cognitive Development database. Functional network connectivity (FNC) was extracted via a fully automated independent component analysis framework. We found that children's FNC is robust and stable with high similarity across scans and serves as a fingerprint that can identify an individual child from a large group. The robustness of this finding is supported by replicating the identification in the two-year follow-up session and between longitudinal sessions. More interestingly, we discovered that the within-individual FNC stability was predictive of cognitive performance and psychiatric problems in children, with higher FNC stability correlating with better cognitive performance and fewer dimensional psychopathology. The overall results indicate that the FNC of children also shows reliable within-individual stability, acting as a fingerprint for distinguishing participants, regardless of significant growth and development in the children's brain. FC stability can be a valuable imaging marker to predict early cognitive and psychiatric behaviors in children.
DOI: 10.15154/1528329
title: Prediction of Gender from Longitudinal MRI data via Deep Learning on Adolescent Data Reveals Unique Patterns Associated with Brain Structure and Change over a Two-year Period

description: Deep learning algorithms for predicting neuroimaging data have shown considerable promise in various applications. Prior work has demonstrated that deep learning models that take advantage of the data's 3D structure can outperform standard machine learning on several learning tasks. However, most prior research in this area has focused on neuroimaging data from adults. Within the Adolescent Brain and Cognitive Development (ABCD) dataset, a large longitudinal development study, we examine structural MRI data to predict gender and identify gender-related changes in brain structure. Results demonstrate that gender prediction accuracy is exceptionally high (>97%) with training epochs > 200 and that this accuracy increases with age. Brain regions identified as the most discriminative in the task under study include predominantly frontal areas and the temporal lobe. When evaluating gender predictive changes specific to a two-year increase in age, a broader set of visual, cingulate, and insular regions are revealed. Our findings show a robust gender-related structural brain change pattern, even over a small age range. This suggests that it might be possible to study how the brain changes during adolescence by looking at how these changes are related to different behavioral and environmental factors.
DOI: 10.15154/1528330
title: 'Harmless' adversarial network harmonization approach for removing site effects and improving reproducibility in neuroimaging studies

description: Multi-site collaboration, which gathers together samples from multiple sites, is a powerful way to overcome the small-sample problem in the neuroimaging field and has the potential to discover more robust and reproducible biomarkers. However, confounds among the datasets caused by various site-specific factors may dramatically reduce the cross-site reproducibility performance. To properly remove confounds while improving cross-site task performances, we propose a maximum classifier discrepancy generative adversarial network (MCD-GAN) that combines the advantages of generative models and maximum discrepancy theory. The mechanisms of MCD-GAN and how it harmonizes the dataset are visualized using simulated data. The performance of MCD-GAN was also compared with state-of-the-art methods (e.g., ComBat, cycle-GAN) within Adolescent Brain Cognitive Development (ABCD) dataset. Result demonstrates that the proposed MCD-GAN can effectively improve the cross-site gender classification performance by harmonizing site effects. Our proposed framework is also suitable for various classification/prediction tasks and is promising to facilitate the cross-site reproducibility of neuroimaging studies.
DOI: 10.15154/1528335
title: Generalization of cortical MOSTest genome-wide associations within and across samples

description: Genome-Wide Association studies have typically been limited to univariate analysis in which a single outcome measure is tested against millions of variants. Recent work demonstrates that a Multivariate Omnibus Statistic Test (MOSTest) is well powered to discover genomic effects distributed across multiple phenotypes. Applied to cortical brain MRI morphology measures, MOSTest has resulted in a drastic improvement in power to discover loci when compared to established approaches (min-P). One question that arises is how well these discovered loci replicate in independent data. Here we perform 10 times cross validation within 34,973 individuals from UK Biobank for imaging measures of cortical area, thickness and sulcal depth (>1,000 dimensionality for each). By deploying a replication method that aggregates discovered effects distributed across multiple phenotypes, termed PolyVertex Score (MOSTest-PVS), we demonstrate a higher replication yield and comparable replication rate of discovered loci for MOSTest (# replicated loci: 242-496, replication rate: 96-97%) in independent data when compared with the established min-P approach (# replicated loci: 26-55, replication rate: 91-93%). An out-of-sample replication of discovered loci was conducted with a sample of 4,069 individuals from the Adolescent Brain Cognitive Development® (ABCD) study, who are on average 50 years younger than UK Biobank individuals. We observe a higher replication yield and comparable replication rate of MOSTest-PVS compared to min-P. This finding underscores the importance of using well-powered multivariate techniques for both discovery and replication of high dimensional phenotypes in Genome-Wide Association studies.
DOI: 10.15154/1528338
title: Recalibrating expectations about effect size: A multi-method survey of effect sizes in the ABCD study

description: Effect sizes are commonly interpreted using heuristics established by Cohen (e.g., small: r = .1, medium r = .3, large r = .5), despite mounting evidence that these guidelines are mis-calibrated to the effects typically found in psychological research. This study's aims were to 1) describe the distribution of effect sizes across multiple instruments, 2) consider factors qualifying the effect size distribution, and 3) identify examples as benchmarks for various effect sizes. For aim one, effect size distributions were illustrated from a large, diverse sample of 9/10-year-old children. This was done by conducting Pearson's correlations among 161 variables representing constructs from all questionnaires and tasks from the Adolescent Brain and Cognitive Development Study® baseline data. To achieve aim two, factors qualifying this distribution were tested by comparing the distributions of effect size among various modifications of the aim one analyses. These modified analytic strategies included comparisons of effect size distributions for different types of variables, for analyses using statistical thresholds, and for analyses using several covariate strategies. In aim one analyses, the median in-sample effect size was .03, and values at the first and third quartiles were .01 and .07. In aim two analyses, effects were smaller for associations across instruments, content domains, and reporters, as well as when covarying for sociodemographic factors. Effect sizes were larger when thresholding for statistical significance. In analyses intended to mimic conditions used in "real-world" analysis of ABCD data, the median in-sample effect size was .05, and values at the first and third quartiles were .03 and .09. To achieve aim three, examples for varying effect sizes are reported from the ABCD dataset as benchmarks for future work in the dataset. In summary, this report finds that empirically determined effect sizes from a notably large dataset are smaller than would be expected based on existing heuristics.
DOI: 10.15154/1528359
title: Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology

description: The disconnection hypothesis of schizophrenia proposes that symptoms of the disorder arise as a result of aberrant functional integration between segregated areas of the brain. The concept of metastability characterizes the coexistence of competing tendencies for functional integration and functional segregation in the brain, and is therefore well suited for the study of schizophrenia. In this study, we investigate metastability as a candidate neuromechanistic biomarker of schizophrenia pathology, including a demonstration of reliability and face validity.

Group-level discrimination, individual-level classification, pathophysiological relevance, and explanatory power were assessed using two independent case-control studies of schizophrenia, the Human Connectome Project Early Psychosis (HCPEP) study (controls n=82, non-affective psychosis n=53) and the Cobre study (controls n=71, cases n=59). In this work we extend Leading Eigenvector Dynamic Analysis (LEiDA) to capture specific features of dynamic functional connectivity and then implement a novel approach to estimate metastability. We used non-parametric testing to evaluate group-level differences and a naïve Bayes classifier to discriminate cases from controls. 

Our results show that our new approach is capable of discriminating cases from controls with elevated effect sizes relative to published literature, reflected in an up to 76% area under the curve (AUC) in out-of-sample classification analyses. Additionally, our new metric showed explanatory power of between 81-92% for measures of integration and segregation. Furthermore, our analyses demonstrated that patients with early psychosis exhibit intermittent disconnectivity of subcortical regions with frontal cortex and cerebellar regions, introducing new insights about the mechanistic bases of these conditions. 

Overall, these findings demonstrate reliability and face validity of metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.
DOI: 10.15154/1528367
title: Genetic risk, parental history, and suicide attempts in a diverse sample of US adolescents

description: Background: Adolescent suicide is a major health problem in the US marked by a recent increase in risk of suicidal behavior among Black/African American youth. While genetic factors partly account for familial transmission of suicidal behavior, it is not clear whether polygenic risk scores of suicide attempt can contribute to suicide risk classification.

Objectives: To evaluate the contribution of a polygenic risk score for suicide attempt (PRS-SA) in explaining variance in suicide attempt by early adolescence.

Methods: We studied N = 5,214 non-related youth of African and European genetic ancestry from the Adolescent Brain Cognitive Development (ABCD) Study (ages 8.9–13.8 years) who were evaluated between 2016 and 2021. Regression models tested associations between PRS-SA and parental history of suicide attempt/death with youth-reported suicide attempt. Covariates included age and sex.

Results: Over three waves of assessments, 182 youth (3.5%) reported a past suicide attempt, with Black youth reporting significantly more suicide attempts than their White counterparts (6.1 vs. 2.8%, p < 0.001). PRS-SA was associated with suicide attempt [odds ratio (OR) = 1.3, 95% confidence interval (CI) 1.1–1.5, p = 0.001]. Parental history of suicide attempt/death was also associated with youth suicide attempt (OR = 3.1, 95% CI, 2.0–4.7, p < 0.001). PRS-SA remained significantly associated with suicide attempt even when accounting for parental history (OR = 1.29, 95% CI = 1.1–1.5, p = 0.002). In European ancestry youth (n = 4,128), inclusion of PRS-SA in models containing parental history explained more variance in suicide attempt compared to models that included only parental history (ΔR2 = 0.7%, p = 0.009).

Conclusions: Findings suggest that PRS-SA may be useful for youth suicide risk classification in addition to established risk factors.
DOI: 10.15154/1528398
title: The interaction between age and sleep quality impacts cognition

description: Background: The association between sleep quality and cognition is widely established but the role of the aging process on this relationship is largely unknown. 
Purpose: To examine how age impacts the sleep-cognition relationship and determine critical age ranges when sleep is most strongly associated with cognition. This investigation could help identify individuals at risk for sleep-related cognitive impairment. 
Methods: Sample included 711 individuals (59.66 ± 14.91, 55.7 % female) who were assessed for sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and cognition as part of the Human Connectome Project Aging (HCP-A). 
Results: There was a significant interaction term between the PSQI and non-linear age term (age2) on Trail Making Test B (TMT-B) (p = 0.02) and NIH Toolbox (TB) crystallized cognition (p = 0.02), with critical age ranges at ages 50-75 for TMT-B and ages 66-70 for crystallized cognition. 
Conclusions: The relationship between sleep quality and cognitive performance may be modified by age. Furthermore, middle-age to early older adulthood may be the most vulnerable to sleep-related cognitive impairment.
DOI: 10.15154/1528403
title: Decoding Age-specific Changes in Brain Functional Connectivity Using a Sliding-window Based Clustering Method

description: Functional magnetic resonance imaging (fMRI) permits detailed study of human brain function. Understanding the age-specific development of neural circuits in the typically developing brain may help us generate new hypotheses for developmental psychopathologies. Functional connectivity (FC), defined as the statistical associations between two brain regions, has been widely used in estimating functional networks from fMRI data. Previous research has shown that the evolution of FC does not follow a linear trend, particularly from childhood to young adulthood. Thus, this work aims to detect the nuanced FC changes with age from the non-linear curves and identify age-period-specific FC development patterns. We proposed a sliding-window based clustering approach to identify refined age interval of FC development. We used resting-state fMRI (rs-fMRI) data from the human connectome project-development (HCP-D), which recruited children, adolescents, and young adults aged from 5 to 21 years. Our analyses revealed different developmental patterns of resting-state FC by sex. In general, females matured earlier than males, but males had a faster development rate during age 100 -120 months. We identified four developmental phases: network construction in late childhood, segregation and integration construction in adolescence, network pruning in young adulthood, and a unique phase in males -- U-shape development. In addition, we investigated the sex effect on the slopes of FC-age correlation. Males had higher slopes during late childhood and young adulthood. These results inform trajectories of normal FC development, information that can in the future be used to pinpoint when development might go awry in neurodevelopmental disorders.
DOI: 10.15154/1528411
title: Parent Perceptions of Caregiver-Mediated Telemedicine Tools for Assessing Autism Risk in Toddlers

description: Telemedicine tools have potential for increasing access to diagnostic services for children with autism spectrum disorder (ASD). Past work has utilized tele-assessment procedures in which remote psychologists observe administration of interactive screening instruments by trained, on-site providers. Although promising, this approach relies on two clinicians, limiting its efficiency and scalability. The present study examined the use, acceptability, and parents' perceptions of two caregiver-mediated tools for assessing ASD risk in toddlers, in which remote clinicians guided parents to complete interactive screening activities with their children. Most parents found tele-assessment to be comfortable, and many reported liking the parent-led nature of these tools. Parents also offered constructive feedback, which was used to modify the tele-assessment process for future study.