Dear Alfonso, dear CONN users,
I would like to use the rshrf toolbox to deconvolve the haemodynamic response function: https://github.com/compneuro-da/rsHRF
Unfortunately, it requires a bandpass filter to work. I have thus two options to apply in an analysis pipeline with CONN:
* Either after preprocessing, thus CONN would receive as input functional files already bandpass filtered images (and hrf deconvolved). Can this impact the CompCor denoising or is this OK?
* Either after CONN denoising, but then I have no idea how I can make CONN use the denoised+deconvolved files instead of just denoised, as CONN provides no way to specify custom additional post-processing steps (feature request? ;-) ). However, even if there was a way to do it after denoising, I think the denoising can remove important information to estimate the hrf, so this is probably not the best avenue (but that's only my thoughts?).
Does someone have any suggestion of what would be the best avenue, or the most correct technically?
Thank you very much in advance!
Best regards,
Stephen
I would like to use the rshrf toolbox to deconvolve the haemodynamic response function: https://github.com/compneuro-da/rsHRF
Unfortunately, it requires a bandpass filter to work. I have thus two options to apply in an analysis pipeline with CONN:
* Either after preprocessing, thus CONN would receive as input functional files already bandpass filtered images (and hrf deconvolved). Can this impact the CompCor denoising or is this OK?
* Either after CONN denoising, but then I have no idea how I can make CONN use the denoised+deconvolved files instead of just denoised, as CONN provides no way to specify custom additional post-processing steps (feature request? ;-) ). However, even if there was a way to do it after denoising, I think the denoising can remove important information to estimate the hrf, so this is probably not the best avenue (but that's only my thoughts?).
Does someone have any suggestion of what would be the best avenue, or the most correct technically?
Thank you very much in advance!
Best regards,
Stephen