Hello!

I thought I would try re-posting my question in case someone might be able to provide some insight. The full background/content of my question is below, but briefly I was hoping to gain some insight as to why it seems to be okay to use fsl_motion_outliers after you've done temporal filtering on a timeseries which includes motion-contaminated timepoints, when from my understanding doing temporal filtering on a timeseries with motion-contaminated time points could lead to ringing artifacts in the data which fsl_motion_outliers wouldn't correct per se.

Thank you for your time,
Katherine


---------- Forwarded message ----------
From: Katherine Lawrence
Date: 2016-06-22 16:15 GMT-07:00
Subject: Temporal Filtering and fsl_motion_outliers
To: [log in to unmask]


Hello!

I have a question about using fsl_motion_outliers to censor motion-contaminated timepoints from resting-state data. Here's my understanding of how to do this so far, followed by my question:

-FSL recommends using confound EVs from fsl_motion_outliers to take care of motion-contaminated time points instead of deleting the motion-contaminated time points.

-Based on the May 2014 thread, it seems like for seed-based analyses one should include the confound EVs from fsl_motion_outliers not in any preprocessing GLMs where we're regressing out the nusiance regressors to obtain residuals. Instead, we should include them in the same GLM as where we're including the seed's timeseries (and therefore the GLM where we are actually getting our betas of interest).

-So it sounds like preprocessing, including temporal filtering, should have already been run by the time the confound EVs from fsl_motion_outliers are included in the seed-based GLM above.

-However, Carp 2013 (NeuroImage) said that if you bandpass filter while you still have the 'bad' timepoints in your timeseries, the filtering may introduce ringing artifacts in the data, spreading the artifacts across time.

-I would therefore think that waiting to include regressors from fsl_motion_outliers until the seed-based GLM (and after bandpass filtering) would result in the motion-contaminated time points spreading their artifact to other time points during the bandpass filtering step. Therefore, even if the motion-contaminated time points themselves would be essentially censored by including a confound EV for them, there could still be motion-related noise in other time points.

I haven't been able to find any mentions of this sort of potential problem, though, which makes me think I might be missing something. Is my understanding of this whole situation correct? If not, what am I missing? If so, is there a reason to not be concerned about potential ringing from bandpass filtering the data? Just let me know if I haven't phrased anything clearly enough.

Thank you in advance,
Katherine