I am totally new here and I have little knowledge of brain network analysis.
Kindly help me out with the following(where can I learn these topics/ how to do them?)
Pre-process some open-source functional magnetic resonance imaging (fMRI) data sets and estimate networks from atlases such as AAL and Gordon.
For the above data sets, create a R/Python script that reads in each of the data sets and then estimates some graph summary statistics such as small worldness, modularity, clustering coefficients, etc for some of the networks.
- I recommend using fMRIPrep to preprocess fMRI data sets.
- Then you can use the python toolbox Nilearn to create the atlas networks and extract graph theory metrics
Both of these tools are well-documented, and several users on this forum use one or both of them. Hope this helps!
Adding networkx to the stack for network measures.
Thank you for the answer but, actually, I am totally new to the fMRI field and have no idea how to use fmriprep or Nilearn.
If there is a video I can refer to or any material, it would be great.
The websites I linked have setup instructions, but here’s a series of videos on fmriprep https://youtube.com/playlist?list=PLIQIswOrUH6_szyxn9Fy-2cxd3vjlklde
The Nilearn website has plenty of tutorials too.