I’m planning to calculate the PLV connectivity. Please, can you check my pipeline because I am afraid to miss something.
Import EEG signals into BrainStorm (already preprocessed in Eeglab)
Import digitized positions of electrodes (we want to use default anatomy + individual electrode coordinates)
Visually check the electrodes location (it was Ok, but a little far from the head surface, so I project them on the surface) ----->
Project electrodes on the head surface
Compute noise covariance
Compute head model with the ICBM152 template.
Computed sources with dSPM
There is the question: do I need to calculate phase locking value 1xN directly on my source files (so scouts time series will be calculated on the fly if I select the option " scout function: before ")
OR do I need to do some previous manipulations with scouts? And only after that use these values for connectivity estimation.
It would be great if you can take me a hint, how should I perform statistical analyses of PLV values (I have 6 different conditions).
Visually check the electrodes location (it was Ok, but a little far from the head surface, so I project them on the surface)
If you have the electrodes positions but no anatomy, the recommended procedure is to warp the default anatomy to match the head shape: https://neuroimage.usc.edu/brainstorm/Tutorials/TutWarping
This is designed to work with dense surfaces of head points, not for low-resolution EEG caps. But if you have >= 128 electrodes, it might work decently. Try it on a few subjects.
If this approach doesn't work, you may consider using the same standard electrodes positions for all your participants. Importing the individual electrode positions + projecting them on the default anatomy might introduce important biases between subjects. There is not mechanism that would ensure that this projection performs similarly across participants.
There is the question: do I need to calculate phase locking value 1xN directly on my source files
This should work.
I select the option " scout function: before "
Note that we don't have any guidelines to give regarding the choice of this option (before / after).
There is no consensus in the community regarding these tools. These are still considered experimental features, you need to clearly understand what you are doing in order to use them correctly.
do I need to do some previous manipulations with scouts?
"But if you have >= 128 electrodes, it might work decently. Try it on a few subjects."
Yes, I have 128 electrodes. SO do you recommend use WARP function?Ok, I will try.
" do I need to do some previous manipulations with scouts?
I'm not sure what manipulations you refer to?"
I meant do I need to choose scouts at first, then to calculate time-series for them, and then calculate connectivity between scouts.
But as I understand it is OK if I will use individual sources to determine PLV connectivity and at the same time choose ROIs (in the same working window).
I want to calculate 1*N connectivity between fusiform gyrus and all other areas during the recognizing the visual words stimuly.
Can I ask another question,
when I make a warping of all the heads, at the end I will still have to bring all the heads to one tempalate ? to calculate the statistical difference between the groups
I recommend you try, and see whether the result looks satisfying to you.
Note that before this warping, you may need to adjust manually the positions of the electrodes, so that they look centered on the head surface of the template.
This is also difficult to reproduce identically between participants, and may introduce some biases, but at least you can't alter the relative positions of the electrodes within the cap.
I meant do I need to choose scouts at first, then to calculate time-series for them, and then calculate connectivity between scouts.
But as I understand it is OK if I will use individual sources to determine PLV connectivity and at the same time choose ROIs (in the same working window).
You can double-check: both approaches should give the same results.
when I make a warping of all the heads, at the end I will still have to bring all the heads to one template ?
At what point and how do I do this?
Could you please check if everything was done correctly?
I am sorry, this is my first attempt to measure connectivity using Brainstorm.
In addition, one more question:
if I choose 1*N paradigm the calculation goes for one ROI and for all other brain points (not scouts! but 1 * 15000 points).
How can I fix it?
I calculated sources with Current density map, but I'm worried that I can`t see any activity on the picture. At any time. Can it be possible?
Use the amplitude slider? Navigate in time?
I'd recommend you follow carefully all the introduction tutorials using the example dataset provided before trying to do anything on your own data: https://neuroimage.usc.edu/brainstorm/Tutorials
After that I computed PLV connectivity with these parameters (on a pic.) and I got a graph that looks quite realistic.
It looks quite noisy...
Could you please check if everything was done correctly?
No, unfortunately I can't help you validate that you did everything correctly. The only advice I can give would be to stick to either something that is clearly documented in the Brainstorm online tutorials, or to a processing pipeline clearly documented in an article you trust.
if I choose 1*N paradigm the calculation goes for one ROI and for all other brain points (not scouts! but 1 * 15000 points). How can I fix it?
Use Process2 and the [AxB] version of the process.
