Dear Team,
Pardon if my question are so basic!
I have recently trained a Hidden Markov Model (HMM) using fMRI time series data for brain state classification using python. The time series were extracted using the AAL atlas, which contains 116 regions. From this HMM analysis, I obtained group means and covariance matrices, with shapes (6, 116) and (6, 116, 116), respectively—where the 6 represents the number of states.
I would like to visualize these results using Nilearn, and I am seeking your advice on the following:
- What is the recommended approach for plotting spatial maps based on these group means and covariance matrices with Nilearn? Could you please give a insight for using the nilearn for this task?
- Do I need to ensure that the resolution of the parcellation matches the resolution of the atlas data?
- Does the AAL atlas indeed have a default resolution of 2 mm?
- Given that AAL is a volumetric parcellation, how should I incorporate this into Nilearn’s visualization functionality?
Any guidance or suggestions you could provide would be greatly appreciated.
Kind regards,
Elvin