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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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I am working on a surface-based analysis. I followed the example 8 from AFNI proc.py, and have used 3dttest++ on the results. I would like to perform a cluster correction for this data. I ran slow_surf_clustsim.py but got vastly different cluster sizes per hemisphere (1071 for the left hemisphere and 249 for the right). Given my understanding of slow_surf_clustsim this doesn't make any sense
by
usaelzler
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AFNI Message Board
I am still working on this and was wondering if anyone had any suggestions, since I feel like I'm missing something quite obvious.
Is the appropriate approach to convert the 3dttest++ output (i.e. twominuszero_lh.niml.dset) to a volumetric dataset using 3dSurf2Vol? I was under the impression that one of the purposes of doing the surface-based analysis directly through afni_proc.py was so
by
usaelzler
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AFNI Message Board
I am attempting to do a surface based analysis of an n-back task (2 back minus 0 back conditions), and I am having trouble piecing together the appropriate procedure through the docs.
I manually edited the skull-stripping in FreeSurfer, then converted the edited brainmask file to a surface via:
@SUMA_Make_Spec_FS -NIFTI -fspath ./subject_ID -sid ./subject_ID
Then, I followed example 8 (b
by
usaelzler
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AFNI Message Board
Thanks for the advice!
I re-ran this using 3dttest:
3dttest++ -prefix reg_Young_3dttest \
-mask Mask_Young+tlrc \
-covariates Covariates.txt \
-nomeans \
-center NONE \
-setA Subj \
137 /stats.137_PathInt_nt_tcat2+tlrc'[8]' \
143 /stats.143_PathInt_nt_tcat2+tlrc'[8]' \
147 /stats.147_PathInt_nt_tcat2+tlrc'[8]' \
159 /stats.159_PathInt_nt_tcat2+tlrc
by
usaelzler
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AFNI Message Board
I am trying to look at the correlation between the BOLD response and performance on a single outcome measure using 3dMVM. I have done this using 3dRegAna, but the results show huge clusters of activation outside of the brain, so I am attempting to use 3dMVM with a group mask.
When I run:
3dMVM -prefix reg_Young_mvm \
-bsVars 1 \
-vVars 'Perf' \
-qVars 'Perf' \
-Mask ma
by
usaelzler
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AFNI Message Board