I am interested in analysing time-frequency plots. I have multiple trials for each subject. I am planning to generate time-freq plots mostly for small clusters of sensors (size would depend upon the computational limit). As I was going through the tutorial https://neuroimage.usc.edu/brainstorm/Tutorials/ChannelFile#Multiple_runs_and_head_positions
You have three options if you consider grouping information from multiple runs:
Method 1: Process all the runs separately and average between runs at the source level: The more accurate option, but requires more work, computation time and storage.
Method 2: Ignore movements between runs: This can be acceptable if the displacements are really minimal, less accurate but much faster to process and easier to manipulate.
Method 3: Co-register properly the runs using the process Standardize > Co-register MEG runs: Can be a good option for displacements under 2cm.
Warning: This method has not be been fully evaluated on our side, use at your own risk. Also, it does not work correctly if you have different SSP projectors calculated for multiple runs.
I came across the warning for method 3. Thus, wanted to check if there has been any evaluation of it.