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

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Peter Molfese
June 29, 2015 11:37PM
I suspect folks use the 8mm smoothing kernel in SPM because it's the default. That said, there are some suggestions for using a larger kernel to play nicely with the Random Field Theory multiple comparison correction (which AFNI does not do). In general I see everything from smoothing the size of 1 voxel to nearly 3 voxels. So if you had a 3mm isotropic voxel size, you might use anything from 3mm to nearly 9mm. There's a decent review on MindHive here.

Whichever size you use will impact the amount of smoothing in the data estimated by 3dFWHMx and the necessary cluster size needed for statistical significance in 3dClustSim.
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Default smoothing kernel using uber_subject.py

neurobie June 29, 2015 06:54PM

Re: Default smoothing kernel using uber_subject.py

Peter Molfese June 29, 2015 11:37PM