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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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Hi,
I need your help with understanding how to interpret the stats about censored TRs at the bottom of the output of preprocessing.
As you can see, I have 500 TRs and 3 regressors of interests. When I look at the number of TR per stims, the sum is 168+166+294=628. This is a number which is greater than 500. How is that possible?
One options is that it could have something to do with the o
by
giono
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AFNI Message Board
Hi Gang,
Thank you for suggesting this analysis.
I ran it, but I am still puzzled about some aspects:
1) The terms "(Oxytocin|subject)" and "(Pleasantness|subject)" that you suggest are to be interpreted as random slope of oxytocin (and pleasantness) across subjects with correlated intercept? How does that change the regression equation?
2) I have a significant inter
by
giono
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AFNI Message Board
We would like to investigate all the main effects and interactions of the qualitative and quantitative variables of interest (Session, Velocity, Pleasantness and Oxytocin).
For instance, we see a main effect of pleasantness that we are trying to better understand.
by
giono
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AFNI Message Board
Dear AFNI experts,
To further my understanding and reporting of a set of results I’ve been working with, I am checking one of the results from a 3dLME analysis using Excel. My design entails two within-subject factors (Session and Velocity) each with two levels, two quantitative variables of interest (Pleasantness and Oxytocin) and one quantitative covariate of no interest (Movement). Further
by
giono
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AFNI Message Board
Hi again,
I have a follow up to my previous questions.
In the end I had a design with two within factors (2 levels each) and 3 covariates.
Let's say I observe clusters for the F test of one covariate. I would interpret that as: those voxels covary with the covariate. How do I investigate if it is a positive or negative relation though? If I extract the betas and correlate those with the
by
giono
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AFNI Message Board
Dear colleagues,
I have a few questions about the 3dLME.
My design is originally a 2x2 with two within-subject factors (Session: T1, T2) and Velocity (Slow, Fast).
I realized that one of the two sessions make subjects moving significantly more than the other (this was quantified with average movement per TR).
Therefore, in order to exclude that the motion, even after motion correction, coul
by
giono
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AFNI Message Board
Hi Rick,
Thanks.
Yes, I do have problems to work with it, since next command is:
1deval -a seed_neuro.1D -b GAM.1d -expr 'a*b'
where a is the output of the FALTUNG and this produces an output that is a file with a unique 0 instead of 456 values.
by
giono
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AFNI Message Board
Dear AFNI experts,
I am running a PPI analysis, but when I run the following command:
3dTfitter -RHS seed_BOLD.1D -FALTUNG GAM.1D seed_neuro.1D 012 0 \
the output file seed_neuro.1D is actually a 3D file, with the following structure:
# <AFNI_3D_dataset
# self_idcode = ...
# ni_type = "456*float"
etc-....
This is quite strange, since the same scripts worked for m
by
giono
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AFNI Message Board
Thanks!
> If those contrast make sense to you, do it with 3dttest++ as a two-sample t-test (the covariatecan be added too).
If I understood correctly, I cannot do that, since each group (e.g A1 and B2) includes different subjects and will have a different covariate file. 3dttest++ do not handle two Covariate files, right?
> The conjunction among those 4 conditions? If so,
> w
by
giono
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AFNI Message Board
Perfect thanks:
I guess that, after I add the demeaned data into the table, I don't need to use the qVarCenters option, right? (Which means that it will still use the global mean as centering value).
I have two related questions:
1) How do I test the difference between levels of each factor? My design is Agent (within: A,B) x Order (between: 1,2).
Order 1: A1 B1
Ord
by
giono
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AFNI Message Board
Thanks, that sounds good.
In case my prior knowledge would bring me to assume that the covariate would be affected also by the between subject factor, should I do demeaning 4 times?
by
giono
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AFNI Message Board
Thanks for this.
> How are you modeling the random effects? With a random intercept or both random intercept and slope?
I have started with both random intercept and slope, but then I have tried also with each on its own (only slope, only intercept) and the one with only intercept seems to be a bit different (less activation in all clusters) from the other two which do not differ. How d
by
giono
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AFNI Message Board
3dLME - 5 years ago
Hi,
I have ran a 3dLME on my data. My factorial design includes a within subject factor (Agent), a between subject factor (Order) and a Covariate for which subjects have a value for each of the 2 levels of the within subject factors. Now I have two questions that are crucial to correctly report the results of this analysis:
1. When a correspondent analysis (Mixed Linear Model) is carried in
by
giono
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AFNI Message Board
Dear AFNI users,
I am planning to run a PPI analysis and I was looking at Gang's pipeline beforehand.
My main doubt is about the Reconvolve phase, where the waver command is used. Specifically:
waver -GAM -peak 1 -${TR} ${sub_TR} -input Inter_neu${cond}${cc}${sd}.1D -numout ${n_tp} > Inter_hrf${cond}${cc}${sd}.1D
My question is about the input for TR (or dt or sub_TR). My TR=
by
giono
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AFNI Message Board
Hi,
I have a question regarding beta extraction. I got a significant activation in a cluster from a paired-t test with a covariate. How should I proceed to get beta values that take in account the covariate?
I have tried the following approach, but the t-test run on the resulting values did not turn significant as expected:
I started by extracting “raw” betas for each condition I included
by
giono
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AFNI Message Board