College of Liberal Arts
The primary aims of this ongoing longitudinal study are to conduct a comprehensive investigation of brain development during adolescence and early adulthood and to determine how brain development is altered when individuals begin to use alcohol (as well as other drugs, such as marijuana) during this period. The researchers employ an extensive two-day data collection protocol at each study time point, consisting of behavioral assessments (interviews, questionnaires, computerized testing), brain magnetic resonance imaging (MRI; high resolution anatomical scans, several types of diffusion scans, spectroscopy, resting functional scans), and electroencephalography (EEG). They also have a one-time collection of genetic data (single-nucleotide polymorphisms). Data collection waves occur at two-year intervals and currently the researchers are completing their fifth assessment. In their analyses within and across these types of data, the researchers investigate the refinement of brain network connectivity during normal adolescent development and identify alterations due to alcohol and drug use. MSI resources are heavily used to achieve this “connectivity” aspect of this brain-behavior research, which relates directly to the goals of the Human Connectome Project.
Based on initial findings from this study, in 2019 the researchers began data collection on a targeted longitudinal study of 18-19 year old alcohol and/or cannabis users, employing an extensive MRI assessment that uses updated scanning techniques developed in the Human Connectome Project. These data will be processed and analyzed using MSI resources throughout 2020.
Finally, the Principal Investigator is a PI on the Adolescent Brain Cognitive Development (ABCD) study, the largest long-term (longitudinal) study of brain development and child health in the United States. this NIH-funded project spans 21 research sites across the country, and has enrolled over 12,000 children ages 9-10 years who will be assessed longitudinally through adolescence into young adulthood. Laboratory assessments include extensive behavioral testing as well as a lengthy MRI scanning session. Each data release from an assessment wave contains more than 30 TB of MRI data. Processing and analysis of MRI data from this study presents challenges never encountered previously, due to both the scale of the research and the complexity of the cutting-edge MRI scans that are employed. Currently the study is conducting its second full assessment wave, but most of the computing work involves finding better solutions for data storage and automated data preprocessing (identifying and correcting for various MRI artifacts, such as magnetic bias fields, head movement induced blurring and ringing, etc., prior to statistical modeling). The researchers expect to conduct multiple very large scale data processing runs in 2020, each involving as many as 40,000 individual MRI scans and millions of individual data points.