Python is increasingly becoming common-place in the analysis of neuroimaging data. This course will familiarize attendees with how one can manipulate and transform neuroimaging data using Python s neuroimaging packages (nibabel, nilearn). We will begin with first developing 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. The final component of the course will involve performing 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.
Teacher: SciNet Team
Date: Wed, 26 Jun 2019 - 1:30 pm