ABCD Study and Course Motivation

The Adolescent Brain Cognitive Development (ABCD) Study® is the largest long-term study of brain development and child health in the United States. The National Institutes of Health (NIH) funded leading researchers in the fields of adolescent development and neuroscience to conduct this ambitious project. The ABCD Research Consortium consists of a Coordinating Center, a Data Analysis, Informatics & Resource Center, and 21 research sites across the country, which have invited 11,878 children ages 9-10 to join the study. Researchers will track their biological and behavioral development through adolescence into young adulthood. ABCD protocol summaries describe the physical, cognitive, social, emotional, environmental, behavioral, and academic assessments, as well as multimodal neuroimaging and biospecimen collection for hormonal, genetic, epigenetic, environmental exposure, and substance use analysis.

One goal of the multisite, longitudinal ABCD Study® is to create a unique data resource for the entire scientific community by embracing an open science model. However, an increasing body of evidence points to some issues in reproducibility in biomedical or life sciences. The issue of lack of reproducibility has been now described in several scientific domains, and for several years raising concerns in the scientific community. ReproNim, a Center for Reproducible Neuroimaging Computation, aims to help researchers achieve more reproducible data analysis workflows and outcomes. ReproNim has developed a curriculum that will give researchers the information, tools and practices to perform repeatable and efficient research, and a map of where to find the resources for deeper practical training.

Our ABCD-ReproNim course was designed to provide a comprehensive background to the ABCD dataset while delivering hands-on, interactive instruction to enable rigorous and reproducible data analyses. To this end, we have assembled an interdisciplinary team of instructors and evaluators that includes ABCD Study® Investigators, ReproNim team members and collaborators, and non-ABCD/ReproNim researchers. Success will result in the generation of a cadre of investigators that are well trained in the ways that support efficient, re-executable design and FAIR practices, use of the ABCD (and other) data resources.

ABCD-ReproNim is supported by an award from the National Institute of Drug Abuse (R25-DA051675).

Course Philosophy

Most educational programs around neuroimaging rely on intensive teaching over a short period, typically ranging from one day to two weeks. Reproducible analytics, a topic not taught in traditional university curricula, requires absorbing a significant amount of diverse technology-oriented content. Hackathons or unconferences, are increasingly well-attended around neuroimaging and other conferences. These events, by their design, often self-select individuals who are already knowledgeable in many of the areas spanning data science and are often not suited for training. However, mastery of computational technologies is a challenging task for students to complete in a one- to two-week immersive hackathon or workshop. Our experience suggests that learning, conceptual consolidation, and computational skill development does not optimally occur over a short intensive period of time. As instructors, we know it is common to spend a significant portion of a hack week on didactic instruction.

Thus, the ABCD-ReproNim team seeks to create a new form of an inverted classroom for workshops and hackathons.

Course Design

Due to the COVID-19 global pandemic, the ABCD-ReproNim Course will be virtual and include both asynchronous and synchronous activities. Using the “flipped classroom” approach, our goal is to slow down the didactic teaching process so that it occurs over a 13-week semester and with a curated set of teaching objectives. The online course will include pre-recorded video presentations and a weekly live Q&A with ABCD and ReproNim experts. Additional course readings will be provided to enhance and reinforce online lessons, and open-access data-based exercises will be assigned to ensure learning objectives are met. Students will use this time to learn content and gain skills, allowing the ABCD-ReproNim team to evaluate progress and determine if any students need additional support or assistance.

Once students have ample time to learn and master the proposed data analytic skills, they will have the opportunity to put those skills to use during the 5-day hands-on data-intensive Project Week. Students will self-organize into small, collaborative learning groups and develop proposals for data analysis or resource development projects. During Project Week, they will apply the skills learned and work towards completion of their project activities and also learn to contribute to open source software.

With this educational design, ABCD-ReproNim intends to fill the needs between a typical NIH T32 program and an immersive summer school. The increased number of hours spent on training through instructor-based and assignment-based pedagogy is expected to provide a better grounding for participants before the week-long Project Week, focused on innovating around ABCD data.

Student Participation

Similar to the successful model of Neuromatch Academy, ABCD-ReproNim students may participate as either Observer or Enrolled students. An unlimited number of Observer students are welcome to view the pre-recorded lectures, participate in NeuroStars discussions, and access course materials. A hands-on data exercise will be made available each week to review and reinforce course content while developing practical skills in reproducible neuroimaging analyses. Enrolled students will receive additional direct support from ABCD-ReproNim Teaching Assistants and data exercises will be graded to assess achievement of course learning objectives. Enrolled students will receive an ABCD-ReproNim Certificate of Completion at the end of the course that may be listed on their CV or resume.

There are no registration fees for ABCD-ReproNim.