Dear AFNI Gurus,

I hope you are enjoying this special time of the year even though it is a very different year.

I have a question regarding the pre-processing of resting-state data, especially with respect to bandpassing.

This resting-state-note states that the data should be bandpassed if physio recordings are not available. Unfortunately, we did not collect any physio recordings, hence suggesting that we should bandpass. However, the associated data loss is a concern for me - our TR is 2, meaning that we would lose 60% of DoF.

Paul's answer in the topic quick question about bandpassing stated that to avoid bandpassing and the loss of DoF, highpass filtering can be achieved by regressing out the polynomials. Does that mean "-regress_polort" should be included in the afni_proc.py command?

Additionally, I was wondering whether there is also a possible substitute for the lowpass filtering? After consulting the resting-state note, it seems that processing the data using example 11 might be suitable for e.g. resting-state functional connectivity analysis. However, this pre-processing example includes neither bandpassing nor the regress_polort option. Could you please explain to me why this is still suitable for the resting-state analysis and how high and low frequency noise are removed from the final dataset? Paul's answer to this post on Conducting bandpassing in one step with versus in two steps states that bandpassing should be done in the regression model, but I am not sure whether it can only be achieved using "-regress_bandpass" or whether a combination of using "-regress_polort" and other options could have a similar effect in removing high and low-frequency noise from the data without having to bandpass it (and hence lose 60% of DoF).

Related to this, we also collected data from the same participants watching short video clips. We used the same scanning parameters, but the main analysis method we would like to use there is Intersubject correlation. Do the same rules regarding bandpassing apply there given that EPIs acquired under naturalistic stimulation are usually pre-processed like resting-state data?

Any further clarification about this would be highly appreciated!

Many thanks in advance for your help and best regards,
Stef