Help for connectivity pipeline

[hossein27en]

@yuwenh

@Francois

To my knowledge, there are still no tools working correctly for connectivity analysis on unconstrained source models (3 dipoles with orthogonal directions for each 3D location). Therefore, I recommend doing your source analysis with constrained locations and constrained orientations.

@hossein27en Can you confirm?

I confirm.

@Francois

(6) And, somehow the options for the type of connectivity seem not matching the tutorial documentaiton onine, so I don't know which connectivity analysis is the best for me to go for? If I am interested in examining the degree of of phase synchronisation, or something like 'lagged coherence' or 'phase lag index', which one is the one to go for I wonder? And what parameters should I use?
(7) Finally, how can I subtract connectivity between trial conditions? I assume I can then average the sum of these differences for each subject, right?

This part is still under construction.
@hossein27 might be able to address some of your questions.

As @Francois said, we are working on the tutorial for connectivity analysis. We might add some general guidelines for choosing a method, but it completely depends on your project. Based on what you said, I would say better start with the "lagged-coherence".

While you have had one matrix for each condition (average of matrices of all trials) and each subject, you can subtract two conditions and then have a difference matrix for each subject and you can do statistical analysis on that. Check here:

Connectivity Tutorial and Methods Development on BST

Dear Alfredo, Many thanks for your valuable points. regarding your questions: Granger causality is a good approach to differentiate between the source and the sink of information flow. The performance of GC depends on how accurate is the underlying model and assumptions. Also, the interpretation is not very easy when we have more than two signals in our model. That is why we only have bi-variate functions. However, If you have few sources it should have satisfactory results. We are workin…

Imaginary Coherency Output - Time Average

So, If I understood correctly, you want to plot the average of connectivity spectrum (Frequency by time) among all pairs of a N x N matrix? Paul, first of all, you need to use a measure which produces that 4-D structure (channels x channels x time x frequency band). Right now, you can use time-resolved coherence. You can specify the time window and frequency resolution. Make sure to select overlap as large as possible so you would have a better temporal resolution. When you computed the connec…

• Hossein