Dear Francois,
Many thanks for answering all the questions and you valuable feedback.
Are these some power measures, computed for a specific frequency band?
No these are not any power measures. I have 800sec MEG signal and I source localised. The activation you are seeing is an activation at one particular point in time. My ultimate aim is to get resting state source time series in 68 parcellation regions and then look at the connectivity (basically, functional connectivity in source space instead of sensor space).
I have one more question. Sorry if I am bothering you.
- I do not have .pos file which contains head positions so I used only 3 fudicial points to position the MEG helmet and here is the image ( 3 different subjects). How can I correct them?
Regards,
Sri.
What MEG system is this?
The NAS/RPA/LPA points you placed in the MRI look reasonable, so it means that the issue in on the side of the NAS/RPA/LPA points from the MEG files.
Subject A and B: It could be that the what you see is really the positions of the subjects' head in the MEG. It happens that the people are not positioned properly.
Subject C: The position of the head was not acquired correctly at the time of acquisition.
In both cases, there is nothing you can do to "fix" it.
If the subject's brain was far from the MEG sensors, there is no way to create recordings after acquisiton.
If the positions of the head localization coils were not acquired correctly at the time of the MEG recordings, there is no way to reconstruct this information later.
Apologies for the delayed response. I am using CTF system.
Many thanks for answering this question.
For C, it looks like the pre-localization failed and it used the default position (the default "default position" looks like that, but it can be changed in the settings in your system's xdb file). A bad pre-localization may also be the case for A or B, though those look like possible head positions. I recommend looking at correcting the initial position if you use continuous head localization. This is a recent addition to Brainstorm for CTF data. See the tutorial: https://neuroimage.usc.edu/brainstorm/Tutorials/HeadMotion
