I’m struggling with the following problem/challenge:
For a multiple kernel analysis (MKL) based on fMRI data I would like to take the AAL atlas and its brain regions. In doing so, the MKL generates a separate kernel for each brain region. Now, I don’t want to have all AAL regions included but a small subset of it. Does someone knows how to manipulate the AAL atlas root info ? The aim is to treat the modified atlas like a normal atlas but with fewer regions included. (I can’t solve this with a mask approach).
many thanks for your help! mike
can be solved with custom atlas made with BrainSuite
I also have a question regarding atlases, if possible kindly check my question on ‘Brain Network Analysis’
or here is the question
- 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.