Smoothed dense data for XCP-D computations

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Hello,

I wanted to reach out regarding a question I have about the way XCP-D generates parcellations and correlation matrices. I selected “Neuro Questions” but this could also be a “Software Support” question; pardon me for any conflict.

We have been working on processing HCPD datasets with the XCP-D pipeline and our research group noted that the parcellations and correlation matrices are computed using unsmoothed dense data in XCP-D. Is there a way to enable XCP-D to compute the parcellations and correlation matrices using smoothed dense data instead of unsmoothed data?

For reference, I do have an argument (–smoothing 2) that incorporates Gaussian smoothing kernel and applies it to the denoised BOLD data. But it appears that this may not be relevant for computing the parcellations and correlation matrices using smoothed dense data. It would be great if you could let us know whether there are any options in XCP-D that can use smoothed dense data for computing parcellations and correlation matrices.

Thanks,
Saptarshi

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Hi @ssinha,

It is not recommended to do any atlas based operations (connectivity, time series, etc) with smoothed data as the averaging within parcels serves the same function (without signal contamination from adjoining parcels). Thus we do not allow this as an option.

Best,
Steven

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