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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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The problem is the following:
no yes
A 37 37
AV 37 37
V 37 0
You don't have any data for the combination of "V" and "yes".
by
gang
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AFNI Message Board
Maegan,
One possibility is that a lot of data variability was not accounted for in the model; thus, the high spatial correlation could lead to a small cluster size threshold. Are you trying to assess the contrast between two conditions? If possible, try 3dttest++ with either '-Clustsim' or '-ETAC', and see if the results are more reasonable.
Another option is to adopt a
by
gang
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AFNI Message Board
Yue,
One possibility is that something is not structured properly in the file table.txt. See if you could use the 3dMVM validator to sort it out:
by
gang
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AFNI Message Board
> When I tried to run my data using this method we got errors while doing the t-test since there were too many censored-out vectors.
Are you talking about t-test at the subject or group level? Could you show your script?
by
gang
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AFNI Message Board
Thanks for providing a clear context.
> a little more emphasis is placed on type II error compared to fMRI in the research arena but type I error is still of significant concern
We probably all agree that it would make more sense to keep some kind of balance between the two sides of the coin. I don't have any definite suggestion to your question, but I would like to say that the sta
by
gang
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AFNI Message Board
> How do I investigate if it is a positive or negative relation though? If I extract the betas and correlate those with the covariate
> they do not always correlate significantly (sometimes trendlines are even flat and correlation coefficients are close to zero!).
> Now I am aware this is there as a result of a correlation... but how do I investigate it further?
Visualizing data wit
by
gang
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AFNI Message Board
Sarah,
Are you trying to use 3dANOVA and 3dMVM to build the same model and perform the same analysis? In other words, do you just have one condition: face-shape? If so, remove "condition" and try something like
3dMVM -prefix 3dMVM_PPG -jobs 24 \
-bsVars group \
-num_glt 3 \
-gltLabel 1 'HC-PT' -gltCode 1 'group : 1*HC -1*PT' \
-gltLabel 2 'HC-TC'
by
gang
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AFNI Message Board
Dane,
> One thought our team had in response to your concerns was running Seed-to-whole brain FC correlations analysis using onlyve
> non-overlapping/interleaved portions of our condition of interest for the seed signal to avoid the modeling/deconvolution issue.
> Would there be any conceptual issues to looking for correlations of this partial signal (e.g. without many of the HDR t
by
gang
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AFNI Message Board
Hi Dane,
> the root of difficulty is for untangling the condition's task-based signals
A typical FMRI experiment is designed to have many trials per condition. The BOLD response tends to vary substantially from trial to trial. For example, see Fig. 8B in this paper, Figs 4 and 13 in this paper. In other words, simply removing the average effect for a condition would not achieve the
by
gang
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AFNI Message Board
Dane,
I still think that it would be difficult, if not impossible, to reliably separate effects at the trial level across different conditions. Unfortunately I'm not an expert on "effective connectivity", but it remains to be seen as to how much an autoregressive structural equation modeling approach, as demonstrated in the paper you linked, could robustly reveal regarding inter
by
gang
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AFNI Message Board
Xiyue,
Some of the R-related AFNI programs (3dMVM, 3dLMEr, 3dLMEr, RBA, ...) currently work only on Mac OS version 10.12.x. If downgrading your Mac OS is not preferable, perform this kind of analysis on a Linux computer.
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gang
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AFNI Message Board
Dane,
Do you mind providing some details about the experimental design? How many tasks/conditions? Under what condition/task are you trying to perform the seed-based correlation analysis?
> 3dSynthesize is being used here (with the matrix output from that activation 3dDeconvolve) to help isolate specific conditions of
> interest (by removing the other conditions, motion, and censors)
by
gang
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AFNI Message Board
> thresholded at p < .001
Is it possible that the excessively conservative thresholding is the cause for the pixelation?
by
gang
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AFNI Message Board
In the second image, what values are you showing? And what threshold is adopted? What would it look like if you set a low threshold? Is this some kind of seed-based correlation analysis based on trial-level effect estimates at the subject level?
by
gang
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AFNI Message Board
I have no problem running your script. What AFNI version do you have?
afni -ver
by
gang
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AFNI Message Board
Maria,
Change
-gltCode 1 'group : 1*Dep-1*DepAnx' \
to (add a space before -1)
-gltCode 1 'group : 1*Dep -1*DepAnx' \
by
gang
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AFNI Message Board
Monira,
Considering the number of input files, I suspect one possibility is that the computer ran out of memory. Test your script with a small number (e.g., 4) of subjects, and see if it works. If it does, you may need to find a computer with a larger memory.
by
gang
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AFNI Message Board
> when we report this method in our paper, can we say it's single-subject repeated measure ANOVA? Is there any
> paper you know that used this method before and I could read it as an example?
I don't think you need a specific reference to justify your modeling approach. ANOVA simply means that the data have a structure of two or higher dimensions. Such dimensions can be subjec
by
gang
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AFNI Message Board
Lingyan,
To convince yourself, add two or more separate lines like the following in 3dDeconvolve:
-gltsym 'SYM: +a1 -a2 \ +a2 -a3 \ +a3 -a4 \ +a4 -a5 \ +a5 -a6 \ +a6 -a7 \ +a7 -a8 \ +a8 -a9'
-gltsym 'SYM: +a1 -a2 \ +a1 -a3 \ +a1 -a4 \ +a1 -a5 \ +a1 -a6 \ +a1 -a7 \ +a1 -a8 \ +a1 -a9'
...
and check if you get the same F-stat value.
by
gang
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AFNI Message Board
Try this:
1) Find the degrees of freedom for the t-stat sub-brick using a command like this (assuming the sub-brick number is 9):
3dAttribute BRICK_STATAUX myFile+tlrc'[9]'
The last number is the degrees of freedom.
2) Compute the critical value corresponding to the p-value of, for example, 0.05 (DF is the degrees of freedom from 1) above):
cdf -p2t fitt 0.05 DF
3) Fi
by
gang
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AFNI Message Board
With 9 conditions, there are 36 possible pairwise contrasts; however, among them there are only 8 independent ones. So, any set of 8 independent pairwise contrasts would be fine to obtain the conventional "omnibus" inference in this case. For example, you can also go with
-gltsym 'SYM: +a1 -a2 \ +a1 -a3 \ +a1 -a4 \ +a1 -a5 \ +a1 -a6 \ +a1 -a7 \ +a1 -a8 \ +a1 -a9'
by
gang
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AFNI Message Board
> My experiment has 9 different conditions, let's say it's a1, a2, ... a9
Suppose that the labels for those 9 conditions are a1, a2, ..., a9. In your 3dDeconvolve script, add something like
-gltsym 'SYM: +a1 -a2 \ +a2 -a3 \ +a3 -a4 \ +a4 -a5 \ +a5 -a6 \ +a6 -a7 \ +a7 -a8 \ +a8 -a9'
-fout -tout
by
gang
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AFNI Message Board
Could you provide more context? Is your goal to make inference on one subject or at the group level? What is your research hypothesis about those three regions?
> My goal is to summarize the language-related activation clusters in a clean and statistically relevant manner.
It's difficult to define a clean manner because statistics is meant to measure and reveal uncertainty, not cert
by
gang
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AFNI Message Board
> is there a way to indicate the single subject Pthr to run through group level analysis? That is, only include voxels
> that are significant at the single level in the group level analysis?
Would this be like cherry-picking?
> it doesn't seem accurate to run a group level analysis on a non-thresholded single subject file.
In what sense it's not accurate?
> If
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gang
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AFNI Message Board
> I've been using 3dANOVA3 -type 4 to achieve this, but I was wondering if there is a way to include 3dClustim in a similar way to 3dttest (-Clustim)?
In this case you can directly use 3dttest++ on each of the contrasts you're interested.
> I'm not sure if this is the best approach, but my plan is to use 3dANOVA to generate Condition*TIme interaction maps with the F-sta
by
gang
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AFNI Message Board
> I provide all subjects as input and write the results into one .1D or .txt file. In this case, each subject’s values
> are added as a new column. The result is a file that contains as many columns as subjects.
Suppose that your 1D file is called Philipp.1D. I offer two approaches --
1) If the number of columns in Philipp.1D is N and N is not large, try
1dcat Philipp.1D'[0]&
by
gang
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AFNI Message Board
Hi Paul,
> how the shared variance in age and HVA could relate to the imaging indices?
How to quantify the relatedness in this context? One approach is to use the coefficient of determination R^2 in a regression model that measures the proportion of the variation in the response variable Z that is predictable from the explanatory variable(s).
With two explanatory variables X and Y, y
by
gang
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AFNI Message Board