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Applying correction for multiple seeds

September 30, 2019, 9:20 am
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Dear CONN experts, 

I´m doing a Seed to voxel analysis with CONN. I have 12 Seeds, and I´d like to correct for multiple Seeds in addition to the whole brain FDR correction. 
Could you please confirm if the way I´m doing it is right?

I just divided 0.05 by 12, resulting in 0,00416. Then, when I click on 'Results explorer' I set the cluster threshold to p < 0,00416 (cluster-size p-FDR corrected). Is this form correct or there is a better way to implement this correction?

Thank you in advance for your help, 

Diana Lopez-Barroso
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Multivariate regression beta maps z-transformation?

October 1, 2019, 4:26 am
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Hi there,

I have used Conn to run a multivariate seed based analysis to look at the unique correlation of 1 seed, while correcting for two other seeds. As output in the first level analysis I get the BETA maps per subject and source. However, to continue to second level analysis, I have to z-transform these regression coefficients, right? The only way I can find to do so, is by dividing it by the standard deviation. However, where can I find these variance maps/SDs? Is there an option in conn toolbox to output these files? 

Thank you,

Margo
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Cohen's d in comparison of 2 independent samples

October 1, 2019, 1:12 pm
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Dear Alfonso,

Could you please clarify for a non-specialist in statistics,

As far as I have understood, you are writing about Cohen's d in comparison of 2 independent samples (patients vs. controls). Why is not Cohen's d computed in the following way: d = [b]2[/b]T / sqrt(dof)? Everywhere in the literature T is multiplied by 2 in independent samples T-test, e.g.:

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.
Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4:863. doi:10.3389/fpsyg.2013.00863

Lots of excuses if the question is strange. Thank you very much for your tool, it's very helpful.

Yours sincerely,
Yana


[i]Originally posted by Alfonso Nieto-Castanon:[/i][quote]Dear Julian,

Generally effect sizes in REX displays correspond to contrast values, or linear combinations of regressor coefficients, from your secod-level general linear model. For your analyses, looking at patient-control differences in connectivity, those effect sizes (approximately 0.05 in your results)  will be interpretable as average differences in Fisher-transformed correlation values between the patients and control groups. If you prefer to report Cohen's d, in your case that can be easily computed from your analysis T-stats and dofs as d = T / sqrt(dof) (e.g. T=4.11 and dof probably 54 or 52, not totally sure, so Cohen's d in this case is going to be around 0.5 or a "medium-size" effect)

Hope this helps
Alfonso
[i]Originally posted by Julian Roessler:[/i][quote]Dear Alfonso

I have a question about the meaning of the effect size (the y-axis in the REX Results GUI). Is this effect size in the sense of cohen's d? Or how should the effect size value be interpreted? Because we get nice significant results, but with a very small effect size - as you can see on the picture I added below.

The analysis we did, was thanks to your help and is described here in detail: https://www.nitrc.org/forum/forum.php?thread_id=7145&forum_id=1144

Kind regards
Julian[/quote][/quote]
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Extract data / import values from ICA results

October 2, 2019, 6:22 am
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Dear CONN users

I have problems figuring out which values are automatically extracted from ICA results. After loading the spm.mat file (second level results) in REX the software seems to extract data from the following first level files:

[b]BETA_Subject*_Condition*_Measure*_Component*.nii[/b]

However, it is not clear to me what these images represent.

Any help would be highly appreciated. I searched the whole archive, however, couldn't find an answer

Thank you very much

Felix
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One group - 3 sessions

October 2, 2019, 1:21 pm
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Hi all,

I have got 30 healthy participants (no patient group). I am testing the test-retest reliability of a new MRI protocol. Each participant was scanned 3 times, a few weeks apart, which, I guess, translates into 3 "sessions" in the CONN toolbox. (My hypothesis is that my resting-state data will be the same across the three timepoints). However, how many "conditions" should I choose in the toolbox? 1 or 3?

Thank you!
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ROI masks - odd display

October 3, 2019, 11:47 am
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Some of the ROIs in my atlases are bilateral, such as MTG. I use fslmaths to threshold, and fslroi to extract the left and right areas to separate files. When I display them in fsleyes, they look find. When they are displayed in conn toolbox, they are shown on half the brain, either the left or right hemisphere, and on the appropriate side.

Also, the Reference point coordinates in conn don't match the MNI coordinates in FSLeyes.

Are these things something I should be concerned about?[code]fslmaths MTG_bilateral.nii.gz -thr 50 MTG_50[/code][code]fslroi MTG_50.nii.gz MTG_50_L 90 -1 0 -1 0 -1[/code]
[img]https://i.imgur.com/hXcwNp7.png[/img]

[img]https://i.imgur.com/8hjc4w9.png[/img]
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RE: Save 2nd-level ROI-to-ROI connectivity matrix

October 3, 2019, 2:16 pm
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Hi Alfonso,

I have a follow-up on this question regarding test statistics in ROI-ROI analysis. I'm currently testing differences in ROI-ROI connectivity (among 12 ROIs) between three groups, controlling for three covariates with a between-subjects contrast of [1 -1 0 0 0 0; 0 1 -1 0 0 0]. I'm interested in the omnibus test for each ROI, which I understand to be a multivariate ancova (three groups, three covariates, 11 outcomes per ROI). When I open the results explorer, each ROI has an "X" test statistic with 22 degrees of freedom. I imagine this is a chi-square value based on the p value, so I am wondering what test is being performed? I would've expected something like a Wilks Lambda from a mancova. Would appreciate any help on this!

Bruce
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Contrast definition

October 4, 2019, 12:05 pm
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Hi, apologies if this has been asked before however I need some clarification on my resting-state contrasts. I have two groups [autism spectrum disorder (ASD) vs. typical development (TD)]. I am wanting to look at how behavioral covariates are associated with functional connectivity while controlling for average motion across the [u]entire[/u] sample (I will look at the groups individually after), however depending on my approach I get radically different results.

[b]Approach A[/b]
[i]3 second level covariates:[/i][list][*]sample_ids (1's for both ASD and TD)[*]behavioral_measure[*]average_motion (average of the 6 motion parameters generated in pre-processing for both ASD and TD)[/list]
Contrast: [0 1 0]

[b]Approach B[/b]
5 second level covariates:[list][*]ASD_ids[*]TD_ids[*]behavioral_measure[*]ASD_average_motion [*]TD_average_motion[/list]Contrast: [0 0 1 0 0]

Approach A gives me a huge amount of results (suspiciously large amount) whereas approach B gives me few results but potentially more reliable. Does anyone have any advice on which is the correct way to do this? My intuition is that approach B makes more logical sense as it controls for the potential differences between the two groups.

Any help would be appreciated. Thanks,
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RE: first level threshold

October 4, 2019, 2:15 pm
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Hello!

Just wanted to follow up from my last post about whether anybody has had any luck with finding a way to produce multiple-corrected maps at the first-level?

Thanks!
Kaitlin
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Centrality measuring methods comparision

October 5, 2019, 3:24 am
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Hi there,

I want to know can I compare centrality measuring methods in this toolbox and/or what are the other research topics that I can explore in functional connectivity using this toolbox. 

Thank you in advance.


Best Regards,

Sadam Hussain
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Visualizing results from a pre-generated thresholded T-map

October 5, 2019, 4:20 pm
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I have a thresholded t-map generated from an SPM run, and I'd like to use CONN toolbox to generate figures; is there any way to do this without working through the setup and pipeline? I am wondering if there is a way to bypass directly to visualizing a t-map from a .nii file.
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Preprocessing HCP data in native space

October 8, 2019, 12:49 am
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Hi,

I would like to use the unprocessed data of the rsMRI from the HCP. I also want to see the result overlayed over the native structural T1 images. Can somebody help me with the choices in the preprocessing steps, please? One thing more. The HCP has RL and LR fMRI data for each run. How to deal with them in the preprocessing steps?

Thanks

Mudathir
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Non-rigid reflection along x-axis for custom ROIs

October 8, 2019, 4:07 pm
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Dear Alfonso & community,

I am running analyses in CONN where I perform a flipping of the hemispheres for a subset of participants (non-rigid reflection along x-axis (x/y/z to -x/y/z)) for the structural as well as functional data. This successfully flips the data. However, I am using custom ROI labels (created in Freesurfer, inputted to CONN as .nii files normalized to the MNI space) and these custom ROI labels are [b]not[/b] flipped when I flip the structural/functional data. Hence, my question: Is there a way to flip these custom ROIs in CONN to match the non-rigid reflection transformation (so the custom labels "follows" the exact same transformation as the rest of the data)?

Thank you!
Greta
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Combining Brodmanns areas for ROI - Measure1 and measure2 output

October 9, 2019, 7:02 am
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Hello! 

I am performing a seed-to-voxel analyses with one seed (dorsolateral prefrontal cortex) combining Brodmann's areas 9 and 46. I have defined the between-sources contrast as [1 0:0 1]. I have 3 groups: affected patients, non-affected patients and healthy controls with imaging at one timepoint. I have defined my between-subjects contrast for a one-way ANOVA as [-1 1 0; 0 -1 1]. The results for the one-way ANOVA are clear; however when I run post-hoc analyses (between-subjects contrasts: [1 -1]) to determine which groups the significant difference is between, in results explorer, when I import the values it gives me two outputs for each significant cluster labelled as "coordinates_Measure1" and "coordinates_Measure2". This did not happen for the seeds defined using one Brodmann area so I am assuming this is due to my combination of 2 Brodmanns areas. When I compare the connectivity values for the same significant cluster _measure1 and _measure2, they are not the same. 

Any advise on how to combine into one ROI or how to interpret this output? 

Thank you!
Mikaela
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Second-level analyses – controlling for age and sex between-subjects contrast

October 9, 2019, 7:03 am
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Hello,
I am trying to figure out how to define the between-subjects contrast in order to control for age and sex in my analyses. I have three groups of interest: affected patients, unaffected patients and healthy controls and would like to run a one-way ANCOVA to determine if there is a difference between these 3 groups while controlling for age and sex. I only have one timepoint of imaging.
Thank you!
Mikaela
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Obtaining correlation coefficients from a ROI-to-ROI analysis

October 9, 2019, 7:13 am
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Dear CONN experts,
we analyzed a resting-state data set on a healthy control sample, and we defined 12 ROIs.
We would like to obtain correlation coefficients for each individual ROI with all the others, for every subject separately.
Could you please guide how to do this (assuming it is possible). We tried looking through the results explorer, but haven't had much success so far.

Thank you in advance!
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RE: CONN 18a. Error in importing SPM.mat

October 10, 2019, 10:28 am
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Hi all,

I also get the same error using conn 17.c after importing my data preprocessed in SPM:

ERROR: Subject 1 Session 1 condition 1 contains onset times beyond the end of the scanning session
ERROR: Subject 1 Session 1 condition 2 contains onset times beyond the end of the scanning session
ERROR: Subject 1 Session 1 condition 3 contains onset times beyond the end of the scanning session

Has anyone found a way to fix this?

Thank you,
Pauline
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ROI-to-ROI matrix

October 11, 2019, 1:41 am
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Dear conn experts,

I'm having some trouble interpreting the effect sizes in the ROI-to-ROI results. To get an overview, I've been extracting the ROI-to-ROI matrix in terms of two-tailed T-values or as beta-values.

Do the beta values still represent Z-transformed Pearson correlation coefficients in the second-level results, and how are they to be interpreted?

Is it possible to extract a ROI-to-ROI matrix with correlation coefficients ranging from -1 to 1?


Best wishes

Andreas
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Denoising destroys preprocessed nifti output

October 13, 2019, 10:24 pm
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Dear forum,

I am working with the conn_batch system in order to preprocess and denoise my fmri data for further analysis steps.
My preprocessing steps inherit:
- structural_segment
- functional_segment
- functional_art
- functional_coregister_affine
- functional_smooth

After the last smoothing my fmri data looks fine and ready to be denoised.
Here for I use linear detrending and denoising for the standard conpounds: wm, gw, cfs and realignment.
After that i convert the matc file to a nifti file.

However, the ouput nifti of this denoising steps is cut off by around half the brainheight in x-y-plane. The nifti cotains values, but those are equal to the "not in the brain" voxels.

No need to say, that those results are useless for any further analysis.

Can anybody comment on this kind of error? Anyone experienced the same ? Anyone knows how to fix it, since I tried a whole day and night and couldnt find the reason for this mischief....

Greetings and all the best
Daniel
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RE: Seed Based Analysis - Conceptual Question

October 14, 2019, 6:58 am
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Hi paul,

I am struggling with the same issue, has it been resolved ?
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