Removing evoked response for AEC functional connectivity analyses

Dear Brainstorrm community,

I have some ERP data. I am interested in calculating the functional connectivity between a scout and the remaining regions using amplitude envelope correlation.

Reading up on the idea of removing the evoked response from event-related data when wanting to calculate connectivity (such as the Wang et al. 2008 ' Estimating Granger causality after stimulus onset: A cautionary note'), it seems as though there are mixed thoughts as to doing so.

Could anyone suggest as to what the current opinion is on this process? With regards to AEC, I could only find resting state papers, so there's no paper I can reference to with regards to task-based connectivity and the removal of the evoked response.

I plan on trying both and comparing the results, but without much precedence, I am thinking going forward with this analysis, I may stick with not removing the evoked response.

Any input would be greatly appreciated.
Best,
Paul

@rmleahy @hossein27en @Sylvain @Marc.Lalancette @peterd ?

I don't believe there is consensus on the question, because the neural mechanisms involved are still unknown. Be aware of edge effects due to using band-pass filters when applying AEC: they can confound the outcome when included in the AEC time window. This can be critical is you apply AEC on short ERP segments, such as trials. You may want to consider expanding the duration of ERP epochs, if possible, or better: bandpass filter your raw data in the frequency bands where you want to compute AEC and then re-epoch the data into trials -- more cumbersome but less prone to method artifacts.

Keep us posted!