I used mne_compute_raw_inverse on averaged data, with 36 labels per
hemisphere in my --labeldir. My resulting fif file has 72 time series,
which I imagine are the average of the activations in each label. I
was wondering how I can map the channel number (e.g. lh-Jz 075096)
back to label name. I found the page in the manual that describes this
channel name, but I couldn't understand how to map it back to my label
file.
Also, is there a way to run the command above for multiple sets at the
same time, creating just one .fif file with several sets in it? I'm
currently going around it by using for loops, but it'd be nice if I
could do everything with just one command.
I used mne_compute_raw_inverse on averaged data, with 36 labels per
hemisphere in my --labeldir. My resulting fif file has 72 time
series, which I imagine are the average of the activations in each
label. I was wondering how I can map the channel number (e.g. lh-Jz
075096) back to label name. I found the page in the manual that
describes this channel name, but I couldn't understand how to map it
back to my label file.
The newest MNE version 2.6.1 contains mne_read_label_file function
which you can use to read label files. To find which label the vertex
number (in your case 75096) is in do the following:
1. Load all the labels from your labeldir.
2. Using the 'intersect' Matlab function determine which label has the
vertex of interest. If the labels are not overlapping, there should be
only one such label.
Also, is there a way to run the command above for multiple sets at
the same time, creating just one .fif file with several sets in it?
I'm currently going around it by using for loops, but it'd be nice
if I could do everything with just one command.
Unfortunately, you need multiple runs of the program to process
multiple sets.