DeKang Yuan

TL;DR: In this article, Pearson's correlations among 161 variables representing constructs from all questionnaires and tasks from the Adolescent Brain and Cognitive Development Study® baseline data were used to describe the distribution of effect sizes across multiple instruments, consider factors qualifying the effect size distribution and identify examples as benchmarks for various effect sizes.

TL;DR: A complicated relationship between DMN/DAN anticorrelation and demographics, neuropsychological function, and psychiatric problems is examined in the largest sample to date of 9- to 10-year-old children.

TL;DR: The authors used multimodal neuroimaging assessments to identify generalizable brain correlates of current body mass index (BMI) and predictors of pathological weight gain (i.e., beyond normative development) one year later.

TL;DR: This paper responds to a recent critique of the fMRI Stop task being used in the Adolescent Brain Cognitive Development (ABCD) study by noting that satisfying race model assumptions is a pernicious challenge for Stop task designs but also that the race model is quite robust against violations of its assumptions.

TL;DR: The Brain Predictability Toolbox (BPt) as mentioned in this paper represents a unified framework of machine learning (ML) tools designed to work with both tabulated data (e.g., brain derived, psychiatric, behavioral, and physiological variables) and neuroimaging specific data.