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Hi Kersten,
Thank you for your response. Am I able to do ROI analysis (following
whole-brain analysis) using the mris_preproc and mris_surf2surf outputs (which
I am currently using for whole-brain analysis)?
I was under the impression that aparcstats2table output is simplest for ROI
parcellation, so I used that to prep the data.
Best,
Daniel
From: freesurfer-boun...@nmr.mgh.harvard.edu
<freesurfer-boun...@nmr.mgh.harvard.edu> On Behalf Of Diers, Kersten /DZNE
Sent: January 7, 2025 8:51 AM
To: freesurfer@nmr.mgh.harvard.edu
Subject: Re: [Freesurfer] Fwd: LME pipeline for individual ROIs
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Hello,
I am not sure if there is a right or wrong here; personally, I'd do a single
whole-brain analysis, and apply ROIs only as the very last step, correcting for
multiple comparisons within each ROI and for the number of ROIs. I would not
expect fundamental differences between this approach and your approach, though.
FDR2 may be more sensitive than FDR, but not necessarily in all circumstances.
Hope this helps,
Kersten
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Hello FreeSurfer experts,
I am using a mass-univariate pipeline to assess cortical thickness changes
longitudinally at a regional level (based on the D-K atlas), and have been
following this thread: MailScanner has detected a possible fraud attempt from
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My pipeline is set up so that lme_mass_fit, lme_mass_F, and lme_mass_FDR are
all run independently in a for-loop for each individual ROI, rather than
altogether. Is this correct? As well, would using FDR2 be more advantageous
than FDR?
Best,
Daniel Bondi
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