This course introduces students to best practices for processing neuroimaging data with a focus on data organization and campus computing resources. We begin with software and account setup, and a discussion of neuroimaging data formats (DICOM, NIfTI, GIFTI, and CIFTI). Subsequently, we explore data sharing and reproducibility with an emphasis on the BIDS standard for naming and organizing neuroimaging data and a review of version control tools and containerization with Docker and Singularity. Before introducing individual data processing pipelines, we spend two weeks learning the High Performance Computing Cluster: especially the job submission system (SLURM) and Globus for effective data transfer. In the second part of the class, students will use containerized applications to process data: We begin with conversion of DICOM data to BIDS, then learn about quality assessment tools (e.g. MRIQC), and fmri preprocessing (fmriprep) and analysis tools (GIFT). We conclude with a discussion of DWI preprocessing tools (QSIprep).
Course Credits
3