No abstract

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets.

Highlights ADHD symptoms relate differently to brain activity across executive function tasks. Hyperactivity and inattention show unique and overlapping relations to brain activity. Activity in sensory and default mode network regions related to ADHD symptoms. Dimensional and categorical models of ADHD reveal different effects.

English Learners (ELs), students from non‐English‐speaking backgrounds, are a fast‐growing, understudied, group of students in the U.S. with unique learning challenges. Cognitive flexibility—the ability to switch between task demands with ease—may be an important factor in learning for ELs as they have to manage learning in their non‐dominant language and access knowledge in multiple languages. We used functional MRI to measure cognitive flexibility brain activity in a group of Hispanic middle school ELs (N = 63) and related it to their academic skills. We found that brain engagement during the cognitive flexibility task was related to both out‐of‐scanner reading and math measures. These relationships were observed across the brain, including in cognitive control, attention, and default mode networks. This work suggests the real‐world importance of cognitive flexibility for adolescent ELs, where individual differences in brain engagement were associated with educational outcomes.

Executive function (EF) and social function are both critical skills that continue to develop through adolescence and are strongly predictive of many important life outcomes. Longstanding empirical and theoretical work has suggested that EF shapes social function. However, there is little empirical work on this topic in adolescence, despite both EF and social function continuing to mature into early adulthood (e.g., Bauer et al., 2017). Further, adolescence might be a phase of life where social interactions can shape EF. We tested the longitudinal relation between EF and social function across adolescence utilizing a sample of 99 individuals (8–19 years) from the greater Austin area tested annually for 3 consecutive years. Although EF showed significant improvement in that span, the social function was largely consistent over age. Cross-lagged panel models revealed a bidirectional relation, such that Year 1 EF predicted social function in Year 2, and social function at Years 1 and 2 predicted EF in Year 3. When examining different components of social function, social motivation in earlier adolescence seemed to most consistently predict future EF outcomes, relative to other social functions. Our findings advance the field’s theoretical understanding of how these two critical skills might develop alongside one another over adolescent development with particular emphasis on the role of social motivation on EF maturation.