AFNI Message Board

Dear AFNI users-

We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:

https://discuss.afni.nimh.nih.gov

Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.

The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.

Sincerely, AFNI HQ

History of AFNI updates  

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January 26, 2015 09:59AM
Hi Kara,

>
> Does the same rule apply with surface-based data?

Yes.

> I used a target FWHM of 4mm during my
> preprocessing. I then ran individual level GLMs
> using 3dDeconvolve and a group analysis using
> 3dttest++. Then to determine my cluster threshold,
> given my uncorrected and corrected p-values of
> interest, I ran slow_surf_clustsim.py. It sets
> the blur to 4mm by default. Is there a reason this
> smoothing value should be different than the
> original target FWHM?

I am not sure what you mean by that. The smoothness used in slow_surf_clustsim.py should be the same as the one you applied to your data. The smoothing command in slow_surf_clustsim.py should closely mirror what one uses in the processing. The choice of the level of smoothness depends on many factors such as the degree of alignment between subjects, the SNR of the data, and the size of responses expected. Hard to tell what is appropriate for your study, but smoothness from 4 to 8 is common. Now note that with -target_fwhm 4, you are smoothing to 4mm rather than by an additional 4mm FWHM, so that would be less smoothness than commonly used in the literature.

>
> Also, I did go back and calculate the smoothness
> of the individual-level residuals (errts data)
> using 3dFWHMx for each participant and the average
> is essentially 4mm, if anything its lower (3.9mm).

You mean in the volume errts? I am a little confused here. Assuming you mapped time series from volumes to the surface early on, say after volume registration, then your error time series should be defined on the surface, so if you want to estimate the smoothness of the residuals you should do that with SurfFWHM . The answers should be close to the target FWHM but not necessarily the same.

>
>
> Can someone please let me know if I am missing
> something? Or perhaps how best to justify my
> choices to reviewers?

Of 4mm? There is nothing wrong with smoothing a little bit, as that would preserve high spatial resolution in your data, at the expense of more noise perhaps but there is nothing wrong with that since you are correcting for FWE in the end.

cheers,
Ziad


>
> Thanks in advance,
> Kara
Subject Author Posted

estimating spatial smoothness for surface data

kblacker January 23, 2015 09:43AM

Re: estimating spatial smoothness for surface data

ziad January 26, 2015 09:59AM

Re: estimating spatial smoothness for surface data

kblacker January 26, 2015 11:57AM