Optimizing Resting-State MEG Functional Connectivity Analysis: Epoch Length and Overlapping Strategies

Dear All,

We want to calculate the functional connectivity (at the source level) from resting-state MEG recordings using envelope correlation / Hilbert transform.
At the moment, it's basically running the analysis for the entire 240 seconds, as shown in the screenshot below.
However data that is invalid for a certain period of time (such as 55 to 58 seconds) due to artifact removal processing cannot be analyzed normally.
We would like to ask for your opinion on the appropriate method and approach to deal with this situation.

(1) As a basic idea to do the analysis, what is the advantage of overlapping time windows when doing a growing correlation analysis at rest?

(2) Which strategy is more desirable: adopting a shorter epoch length (e.g., 5 seconds) to include the majority of the original data (235s) without increasing the number of analysis results through overlap, or determining the epoch length (e.g., 600 ms * 3 epochs for inclusion, and 600 ms * 1 epoch for exclusion) to maximize the increase in analysis results with a 50% overlap strategy?

Thanks in advance.

Best regards,

If you mark certain segments with BAD event flags during the data review process, I believe they might not be included in the connectivity analyses. Please compare the connectivity outcomes with and without marking BAD events.

Thank you for replying, @Sylvain

I have marked an artifact as a BAD event because it clearly affected the results of the analysis when it was recorded.
Should we still consider the results if we did not mark such a case?
Thank you so much.

I am not sure I understand your question, sorry. If you deemed the data segment as BAD based on data quality, you don't want to include it in subsequent analyses for sure.

I’m sorry that this question is not easy to understand. Thank you for trying to understand.
The first thing I wanted to discuss in this question was the benefits and things to be careful about when conducting an envelope correlation analysis of resting brain activity with a sliding window.
Best regards, and thank you in advance for your time.