Javid Dadashkarimi

Whether using large-scale projects---like the Human Connectome Project (HCP), the Adolescent Brain Cognitive Development (ABCD) study, Healthy Brain Network (HBN), and the UK Biobank---or pooling together several smaller studies, open-source, publicly available datasets allow for unprecedented sample sizes and promote generalization efforts. Overall, releasing preprocessing data can enhance participant privacy, democratize science, and lead to unique scientific discoveries. But releasing preprocessed data also limits the choices available to the end-user. For connectomics, this is especially true as connectomes created from different atlases (i.e., ways of dividing the brain into distinct regions) are not directly comparable. In addition, there exist several atlases with no gold standards, and more being developed yearly, making it unrealistic to have processed, open-source data available from all atlases. To address these limitations, as part of my PhD with Dustin Scheinost --MINDS lab -- and Amin Karbasi -- IID lab --, we propose Cross Atlas Remapping via Optimal Transport (CAROT) to find a mapping between two atlases, allowing data processed from one atlas to be directly transformed into a connectome based on another atlas without needing raw data.