Table of Contents
This section describes how to generate macroscale gradient mapping from the output matrices of micapipe. The matrices are the same as in the Main output matrices tutorial.
For this tutorial we will map each modality of a single subject using BrainSpace, a
python based library.
Additionally the libraries
nibabel will be used.
As in previous examples, we will use the subject
01 from the MICs dataset, and all paths will be relative to the subject directory or
out/micapipe/sub-HC001_ses01/ and the atlas
The first step is to set the python environment and all the variables relative to the subject you’re interested to visualize.