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Hoarding behavior is prevalent in children and adolescents, yet clinicians do not routinely inquire about it and youth may not spontaneously report it due to stigma. It is unknown whether hoarding behavior, over and above obsessive-compulsive symptoms (OCS), is associated with major clinical factors in a general youth population. This observational study included N = 7054 youth who were not seeking help for mental health problems (ages 11–21, 54% female) and completed a structured interview that included evaluation of hoarding behavior and OCS, as a part of the Philadelphia Neurodevelopmental Cohort between November 2009 and December 2011. We employed regression models with hoarding behavior and OCS (any/none) as independent variables, and continuous (linear regression) or binary (logistic regression) mental health measures as dependent variables. All models covaried for age, sex, race, and socioeconomic status. A total of 374 participants endorsed HB (5.3%), most of which reported additional OCS (n = 317). When accounting for OCS presence, hoarding behavior was associated with greater dimensional psychopathology burden (i.e., higher P-factor) (β = 0.19, p <.001), and with poorer functioning (i.e., lower score on the child global assessment scale) (β = − 0.07, p <.001). The results were consistent when modeling psychopathology using binary variables. The results remained significant in sensitivity analyses accounting for count of endorsed OCS and excluding participants who met criteria for obsessive-compulsive disorder (n = 210). These results suggest that hoarding behavior among youth is associated with poorer mental health and functioning, independent of OCS. Brief hoarding-behavior assessments in clinical settings may prove useful given hoarding behavior's stigma and detrimental health associations. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study is to scrutinize whether psychopathology symptom networks differ between those with and without lifetime: treatment seeking, treatment and treatment of longer duration. Methods: We created non‐exclusive groups of subjects with versus without lifetime treatment seeking, treatment and treatment of mid‐long‐term duration. We estimated Ising models and carried out network comparison tests (NCTs) to compare (a) overall connectivity and (b) network structure. Furthermore, we examined node strength. We used propensity score matching (PSM) to minimize potential confounding by indication for service use. Results: Based on data from 9,172 participants, there were no statistically significant differences in overall connectivity and network structure in those with versus without lifetime: treatment seeking (p =.75 and p =.82, respectively), treatment (p =.63 and p =.49, respectively) and treatment of mid‐longterm duration (p =.15 and p =.62, respectively). Notably, comparing networks with versus without service use consistently revealed higher node strength in 'obsessions' and 'aggression' and lower node strength in 'elevated mood' in all networks with service use. Conclusions: Findings suggest that after adjusting for potential confounding by indication for service use, there was no indication of an association in overall connectivity or network structure for lifetime treatment seeking, treatment and treatment of longer duration. However, selected structurally important symptoms differed consistently in all three comparisons. Our findings highlight the potential of network analysis methods to examine treatment mechanisms and outcomes. Specifically, more granular network characteristics on the node level may complement and enrich traditional outcomes in clinical research. [ABSTRACT FROM AUTHOR]

Evidence shows that reports of psychopathology symptoms by youth and their caregiver informants differ. To quantify youth-caregiver discrepancies in psychopathology symptoms and factors associated with such discrepancies, we investigated differences in how youth and their caregivers rated psychopathology symptoms. The sample (N = 5094) was extracted from the Philadelphia Neurodevelopmental Cohort, a community-based sample of youth and included participants ages 11-17 years old with both youth and caregiver reported symptom scores. Across psychopathology symptoms, youth-caregiver concordance was poor to fair (Cohens kappa for symptom items ranged between 0.03–0.41). Psychosis symptoms had the lowest concordance—Cohen's kappa ranged from 0.03 to 0.17 across psychosis symptoms. Discrepancies between youth and caregiver symptom reports were greater than average for Black youth and for youth of low socioeconomic status; discrepancies were also higher than average in youth with any psychiatric disorder when compared to typically developing youth. Network analysis of difference scores obtained by subtracting youth symptom scores from caregiver reported symptom scores showed that network connectivity (i.e., correlated difference scores) was sparsest for psychosis spectrum compared to other psychiatric disorders. Using a large sample, we show that youth and their caregiver informants tend to report psychopathology symptoms differently. Youth-caregiver discrepancies were the most pronounced for Black youth and youth of low socio-economic status. Race and socioeconomic status contribute to significant differences in how youth and their caregivers report such symptoms and are important factors that should be accounted for to facilitate accurate mental health symptom assessment and evaluation. [ABSTRACT FROM AUTHOR]

Background: Assessment of risks of illnesses has been an important part of medicine for decades. We now have hundreds of 'risk calculators' for illnesses, including brain disorders, and these calculators are continually improving as more diverse measures are collected on larger samples. Methods: We first replicated an existing psychosis risk calculator and then used our own sample to develop a similar calculator for use in recruiting 'psychosis risk' enriched community samples. We assessed 632 participants age 8–21 (52% female; 48% Black) from a community sample with longitudinal data on neurocognitive, clinical, medical, and environmental variables. We used this information to predict psychosis spectrum (PS) status in the future. We selected variables based on lasso, random forest, and statistical inference relief; and predicted future PS using ridge regression, random forest, and support vector machines. Results: Cross-validated prediction diagnostics were obtained by building and testing models in randomly selected sub-samples of the data, resulting in a distribution of the diagnostics; we report the mean. The strongest predictors of later PS status were the Children's Global Assessment Scale; delusions of predicting the future or having one's thoughts/actions controlled; and the percent married in one's neighborhood. Random forest followed by ridge regression was most accurate, with a cross-validated area under the curve (AUC) of 0.67. Adjustment of the model including only six variables reached an AUC of 0.70. Conclusions: Results support the potential application of risk calculators for screening and identification of at-risk community youth in prospective investigations of developmental trajectories of the PS. [ABSTRACT FROM AUTHOR]

Background: Traumatic stressful events (TSEs) are among the most studied risk factors for subsequent schizotypal symptoms. However, specificity and aggregate effects of trauma exposure on schizotypal symptoms remain unclear. This study investigates these relationships among a community-based sample of US adolescents.Material and Methods: A sub-sample of 426 adolescents (51.6% female) from the Philadelphia Neurodevelopmental Cohort study were selected for longitudinal follow-up based on presence (n = 209) or absence (n = 217) of psychosis spectrum symptoms (PSS). At baseline, they completed assessments of demographic, TSEs, other psychopathology (e.g., PSS, anxiety, depression, and behavioral disorder) and family history of psychopathology. Schizotypal symptom dimensions (cognitive-perceptual, interpersonal and disorganized) were evaluated approximately two years later.Results: More than half of adolescents experienced at least one type of TSE. Adolescents with assaultive trauma reported about 1.5 times as many symptoms on all three schizotypal symptom dimensions, compared to adolescents with non-assaultive TSE, adjusting for demographic and family history variables. No statistical significance was found after further adjusting for other baseline psychopathology (p > 0.05). There was a significant aggregate effect of TSEs on cognitive-perceptual symptoms with small effect size (p < 0.001, Cohen's f2 = 0.034).Conclusions: We found evidence of an association between aggregate TSEs and cognitive-perceptual symptoms, but trauma type was not associated with schizotypal symptom dimensions when controlling for potential confounders. Our findings highlight the importance of considering aggregate TSE effects and potential confounds when examining associations between TSEs and schizotypy. Trauma and psychosis spectrum screening may be important in the effort to provide trauma-informed care. [ABSTRACT FROM AUTHOR]

Brain iron is vital to multiple aspects of brain function, including oxidative metabolism, myelination, and neurotransmitter synthesis. Atypical iron concentration in the basal ganglia is associated with neurodegenerative disorders in aging and cognitive deficits. However, the normative development of brain iron concentration in adolescence and its relationship to cognition are less well understood. Here, we address this gap in a longitudinal sample of 922 humans aged 8-26 years at the first visit (M = 15.1, SD = 3.72; 336 males, 486 females) with up to four multiecho T2* scans each. Using this sample of 1236 imaging sessions, we assessed the longitudinal developmental trajectories of tissue iron in the basal ganglia. We quantified tissue iron concentration using R2* relaxometry within four basal ganglia regions, including the caudate, putamen, nucleus accumbens, and globus pallidus. The longitudinal development of R2* was modeled using generalized additive mixed models (GAMMs) with splines to capture linear and nonlinear developmental processes. We observed significant increases in R2* across all regions, with the greatest and most prolonged increases occurring in the globus pallidus and putamen. Further, we found that the developmental trajectory of R2* in the putamen is significantly related to individual differences in cognitive ability, such that greater cognitive ability is increasingly associated with greater iron concentration through late adolescence and young-adulthood. Together, our results suggest a prolonged period of basal ganglia iron enrichment that extends into the midtwenties, with diminished iron concentration associated with poorer cognitive ability during late adolescence. [ABSTRACT FROM AUTHOR]

Adolescence is characterized by rapid development of executive function. Working memory (WM) is a key element of executive function, but it is not known what brain changes during adolescence allow improved WM performance. Using a fractal «-back fMRI paradigm, we investigated brain responses to WM load in 951 human youths aged 8 -22 years. Compared with more limited associations with age, WM performance was robustly associated with both executive network activation and deactivation of the default mode network. Multivariate patterns of brain activation predicted task performance with a high degree of accuracy, and also mediated the observed age-related improvements in WM performance. These results delineate a process of functional maturation of the executive system, and suggest that this process allows for the improvement of cognitive capability seen during adolescence. [ABSTRACT FROM AUTHOR]

The spatial layout of large-scale functional brain networks differs between individuals and is particularly variable in the association cortex, implicated in a broad range of psychiatric disorders. However, it remains unknown whether this variation in functional topography is related to major dimensions of psychopathology in youth. The authors studied 790 youths ages 8 to 23 years who had 27 minutes of high-quality functional magnetic resonance imaging data as part of the Philadelphia Neurodevelopmental Cohort. Four correlated dimensions were estimated using a confirmatory correlated traits factor analysis on 112 item-level clinical symptoms, and one overall psychopathology factor with 4 orthogonal dimensions were extracted using a confirmatory factor analysis. Spatially regularized nonnegative matrix factorization was used to identify 17 individual-specific functional networks for each participant. Partial least square regression with split-half cross-validation was conducted to evaluate to what extent the topography of personalized functional networks encodes major dimensions of psychopathology. Personalized functional network topography significantly predicted unseen individuals' major dimensions of psychopathology, including fear, psychosis, externalizing, and anxious-misery. Reduced representation of association networks was among the most important features for the prediction of all 4 dimensions. Further analysis revealed that personalized functional network topography predicted overall psychopathology (r = 0.16, permutation testing p <.001), which drove prediction of the 4 correlated dimensions. These results suggest that individual differences in functional network topography in association networks is related to overall psychopathology in youth. Such results underscore the importance of considering functional neuroanatomy for personalized diagnostics and therapeutics in psychiatry. [ABSTRACT FROM AUTHOR]

Objective: Deficits in executive function (EF) are common in neuropsychiatric disorders, but the specificity of these deficits remains unclear. The aim of the present study was to elucidate the pattern of EF impairment across psychopathologies in children and adolescents. Associations among components of EF with dimensions of psychopathology, including an overall psychopathology factor, were assessed.Method: Participants (8-21 years) were from the Philadelphia Neurodevelopmental Cohort (N = 9,498). Data from a structured clinical screening interview were reduced to 5 dimensional domains using factor analyses: overall psychopathology, anxious-misery, fear, externalizing, and psychosis. EF components of attentional vigilance, response inhibition, conceptual flexibility, and working memory were assessed. Associations of clinical dimensions with general EF ability and with specific EF components were examined.Results: EF ability showed common and domain-specific associations with clinical symptoms. General EF was directly associated with the general psychopathology, anxious-misery, and psychosis domains but not with the fear or externalizing domains. For the EF subcomponents, differences emerged in the magnitude and direction of the association between components and clinical domains. Poorer EF was typically associated with increased symptoms across clinical domains; however, in some instances, better EF ability was associated with greater symptom burden, particularly in the fear domain.Conclusion: EF has widespread associations with psychopathology in youth. Findings showed some overlap in the type of EF impairment across clinical phenotypes, as indicated by similar patterns of associations between some clinical symptoms and EF. However, findings also showed domain-specific associations with EF that differed across EF components and clinical domains. [ABSTRACT FROM AUTHOR]

Background Adolescence is a critical period for emotional maturation and is a time when clinically significant symptoms of anxiety and depression increase, particularly in females. However, few studies relate developmental differences in symptoms of anxiety and depression to brain development. Cerebral blood flow is one brain phenotype that is known to have marked developmental sex differences. Methods We investigated whether developmental sex differences in cerebral blood flow mediated sex differences in anxiety and depression symptoms by capitalizing on a large sample of 875 youths who completed cross-sectional imaging as part of the Philadelphia Neurodevelopmental Cohort. Perfusion was quantified on a voxelwise basis using arterial spin-labeled magnetic resonance imaging at 3T. Perfusion images were related to trait and state anxiety using general additive models with penalized splines, while controlling for gray matter density on a voxelwise basis. Clusters found to be related to anxiety were evaluated for interactions with age, sex, and puberty. Results Trait anxiety was associated with elevated perfusion in a network of regions including the amygdala, anterior insula, and fusiform cortex, even after accounting for prescan state anxiety. Notably, these relationships strengthened with age and the transition through puberty. Moreover, higher trait anxiety in postpubertal females was mediated by elevated perfusion of the left amygdala. Conclusions Taken together, these results demonstrate that differences in the evolution of cerebral perfusion during adolescence may be a critical element of the affective neurobiological characteristics underlying sex differences in anxiety and mood symptoms. [ABSTRACT FROM AUTHOR]

Background Diffusion tensor imaging (DTI) is applied in investigation of brain biomarkers for neurodevelopmental and neurodegenerative disorders. However, the quality of DTI measurements, like other neuroimaging techniques, is susceptible to several confounding factors (e.g., motion, eddy currents), which have only recently come under scrutiny. These confounds are especially relevant in adolescent samples where data quality may be compromised in ways that confound interpretation of maturation parameters. The current study aims to leverage DTI data from the Philadelphia Neurodevelopmental Cohort (PNC), a sample of 1601 youths with ages of 8–21 who underwent neuroimaging, to: 1) establish quality assurance (QA) metrics for the automatic identification of poor DTI image quality; 2) examine the performance of these QA measures in an external validation sample; 3) document the influence of data quality on developmental patterns of typical DTI metrics. Methods All diffusion-weighted images were acquired on the same scanner. Visual QA was performed on all subjects completing DTI; images were manually categorized as Poor, Good, or Excellent. Four image quality metrics were automatically computed and used to predict manual QA status: Mean voxel intensity outlier count (MEANVOX), Maximum voxel intensity outlier count (MAXVOX), mean relative motion (MOTION) and temporal signal-to-noise ratio (TSNR). Classification accuracy for each metric was calculated as the area under the receiver-operating characteristic curve (AUC). A threshold was generated for each measure that best differentiated visual QA status and applied in a validation sample. The effects of data quality on sensitivity to expected age effects in this developmental sample were then investigated using the traditional MRI diffusion metrics: fractional anisotropy (FA) and mean diffusivity (MD). Finally, our method of QA is compared with DTIPrep. Results TSNR (AUC = 0.94) best differentiated Poor data from Good and Excellent data. MAXVOX (AUC = 0.88) best differentiated Good from Excellent DTI data. At the optimal threshold, 88% of Poor data and 91% Good/Excellent data were correctly identified. Use of these thresholds on a validation dataset (n = 374) indicated high accuracy. In the validation sample 83% of Poor data and 94% of Excellent data was identified using thresholds derived from the training sample. Both FA and MD were affected by the inclusion of poor data in an analysis of an age, sex and race matched comparison sample. In addition, we show that the inclusion of poor data results in significant attenuation of the correlation between diffusion metrics (FA and MD) and age during a critical neurodevelopmental period. We find higher correspondence between our QA method and DTIPrep for Poor data, but we find our method to be more robust for apparently high-quality images. Conclusion Automated QA of DTI can facilitate large-scale, high-throughput quality assurance by reliably identifying both scanner and subject induced imaging artifacts. The results present a practical example of the confounding effects of artifacts on DTI analysis in a large population-based sample, and suggest that estimates of data quality should not only be reported but also accounted for in data analysis, especially in studies of development. [ABSTRACT FROM AUTHOR]

The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale study of child development that combines neuroimaging, diverse clinical and cognitive phenotypes, and genomics. Data from this rich resource is now publicly available through the Database of Genotypes and Phenotypes (dbGaP). Here we focus on the data from the PNC that is available through dbGaP and describe how users can access this data, which is evolving to be a significant resource for the broader neuroscience community for studies of normal and abnormal neurodevelopment. [ABSTRACT FROM AUTHOR]

Abstract: The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale, NIMH funded initiative to understand how brain maturation mediates cognitive development and vulnerability to psychiatric illness, and understand how genetics impacts this process. As part of this study, 1445 adolescents ages 8–21 at enrollment underwent multimodal neuroimaging. Here, we highlight the conceptual basis for the effort, the study design, and the measures available in the dataset. We focus on neuroimaging measures obtained, including T1-weighted structural neuroimaging, diffusion tensor imaging, perfusion neuroimaging using arterial spin labeling, functional imaging tasks of working memory and emotion identification, and resting state imaging of functional connectivity. Furthermore, we provide characteristics regarding the final sample acquired. Finally, we describe mechanisms in place for data sharing that will allow the PNC to become a freely available public resource to advance our understanding of normal and pathological brain development. [Copyright &y& Elsevier]

Abstract: Several recent reports in large, independent samples have demonstrated the influence of motion artifact on resting-state functional connectivity MRI (rsfc-MRI). Standard rsfc-MRI preprocessing typically includes regression of confounding signals and band-pass filtering. However, substantial heterogeneity exists in how these techniques are implemented across studies, and no prior study has examined the effect of differing approaches for the control of motion-induced artifacts. To better understand how in-scanner head motion affects rsfc-MRI data, we describe the spatial, temporal, and spectral characteristics of motion artifacts in a sample of 348 adolescents. Analyses utilize a novel approach for describing head motion on a voxelwise basis. Next, we systematically evaluate the efficacy of a range of confound regression and filtering techniques for the control of motion-induced artifacts. Results reveal that the effectiveness of preprocessing procedures on the control of motion is heterogeneous, and that improved preprocessing provides a substantial benefit beyond typical procedures. These results demonstrate that the effect of motion on rsfc-MRI can be substantially attenuated through improved preprocessing procedures, but not completely removed. [Copyright &y& Elsevier]

Abstract: The ventral striatum (VS) is a critical brain region for reinforcement learning and motivation. Intrinsically motivated subjects performing challenging cognitive tasks engage reinforcement circuitry including VS even in the absence of external feedback or incentives. However, little is known about how such VS responses develop with age, relate to task performance, and are influenced by task difficulty. Here we used fMRI to examine VS activation to correct and incorrect responses during a standard n-back working memory task in a large sample (n=304) of healthy children, adolescents and young adults aged 8–22. We found that bilateral VS activates more strongly to correct than incorrect responses, and that the VS response scales with the difficulty of the working memory task. Furthermore, VS response was correlated with discrimination performance during the task, and the magnitude of VS response peaked in mid-adolescence. These findings provide evidence for scalable intrinsic reinforcement signals during standard cognitive tasks, and suggest a novel link between motivation and cognition during adolescent development. [Copyright &y& Elsevier]