[Neuroimaging] Obtaining power spectrum for each component

[Silvia Russo]

Hello!

I am relatively new to fMRI analysis and trying to use open-source python-based methods to do my work.
I am supposed to run single-subject ICA analysis on 25 subjects, identify 5 resting state networks and look at the averaged low frequency across networks in each subject. 

I am using preprocessed images from the human connectome project and running them through nilearn’s module DictLearn. 
I asked for 10 components (as the images are already preprocessed). 

I had three questions regarding this: 
Is it correct to create a ‘for’ loop that runs DictLearn on each of the 25 subjects and call this a single-subject analysis? If not, what would be a good way to do single-subject ICA without having to use FSL Melodic?
How can I automatically identify the specific network each component may represent? E.g. component 1 is 90% likely to represent the default mode network, component 2 is 92% likely to represent the salience network, etc
FSL automatically creates power spectrums for each component, how can you do the same in python?
Thank you so much for your help!
Silvia
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