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Get familiar with how one can manipulate and transform neuroimaging data using Python s neuroimaging packages (nibabel, nilearn). Develop an understanding how MRI data is represented in Python and perform some hands-on tasks such as basic manipulation on both structural MR and functional MR. Then we will discuss the steps required to take minimally pre-processed MR data (fmriprep), to clean and workable data through the process of motion cleaning and dimensionality reduction. Finally, we will cover how to perform functional connectivity (FC) analysis to build a resting state connectivity matrix. All analyses will be performed using Jupyter notebooks in the spirit of reproducible and open science. E. Dickie, J. Jeyachandra, M. Joseph, J. Kai, O. Stanley 1 credits towards Scientific Computing 2 credits towards Data Science Enrolled: 84 (waitlist: 0); Attended: 13. Please note that you will need to be logged in to partake in most of the functionality of this site.Zoom info for the online events Login information for the cluster This course is part of the Virtual Summer Training Program. |
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