The ABCD study: understanding the development of risk for mental and physical health outcomes.
Nicole R. Karcher,M Deanna +1 more
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TLDR
How the Adolescent Brain Cognitive Development Study was designed to elucidate factors associated with the development of negative mental and physical health outcomes is outlined and a selective overview of results emerging from the ABCD Study is provided.About:
This article is published in Neuropsychopharmacology.The article was published on 2021-01-01 and is currently open access. It has received 109 citations till now. The article focuses on the topics: Mental health & Population.read more
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Neuroimaging profiling identifies distinct brain maturational subtypes of youth with mood and anxiety disorders
TL;DR: In this article , the authors applied Heterogeneity Through Discriminative Analysis (HYDRA) to measures of regional brain morphometry, neurite density, and intracortical myelination to identify subtypes of youth, aged 9-10 years, with mood and anxiety disorders.
Journal ArticleDOI
Mapping Complex Brain Torque Components and Their Genetic Architecture and Phenomic Associations in 24,112 Individuals
TL;DR: In this article, the authors systematically analyzed all relevant components of the most prominent structural asymmetry -brain torque (BT) and their relationships with potential genetic and nongenetic modifiers in a sample comprised of 24,112 individuals from 6 cohorts.
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Specificity of Associations between Parental Psychopathology and Offspring Brain Structure
Matthew Mattoni,Helene J. Hopman,Adefunke Omosefe DadeMatthews,Sandra S. M. Chan,Thomas M. Olino +4 more
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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.
TL;DR: In this paper , structural MRI data from the Adolescent Brain and Cognitive Development (ABCD) dataset was used to predict gender and identify gender-related changes in brain structure. And the results showed that gender prediction accuracy is exceptionally high with training epochs > 200 and that this accuracy increases with age.
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Accounting for Temporal Variability in Functional Magnetic Resonance Imaging Improves Prediction of Intelligence
TL;DR: In this article , a deep neural network involving bi-directional long short-term memory (bi-LSTM) approach was proposed to predict intelligence scores based on region level fMRI time series as well as dynamic functional connectivity.
References
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Power failure: why small sample size undermines the reliability of neuroscience
Katherine S. Button,John P. A. Ioannidis,Claire Mokrysz,Brian A. Nosek,Jonathan Flint,Emma S J Robinson,Marcus R. Munafò +6 more
TL;DR: It is shown that the average statistical power of studies in the neurosciences is very low, and the consequences include overestimates of effect size and low reproducibility of results.
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