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Problem with first-level analysis main CONN GUI when using different template files.

June 7, 2019, 2:08 pm
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Hello Alfonso and CONN users,

I'm new in CONN.
I pre-processed my data set in CONN, and I have used a different template . I am using the pediatric template (http://www.bic.mni.mcgill.ca/~vfonov/nihpd/obj1/). I actually have gray/white/CSF pediatric tissue probability maps, as well as a pediatric T1 template and I use these maps in CONN/SPM12. As in SPM12 the tissue probability maps should be entered as a single 4d-file, so I created an additional "other" probability map and merged all four classes into a single map using the following commands:

spm_imcalc({'grey.nii','white.nii','csf.nii'},'other.nii','max(0,1-i1-i2-i3)');
spm_file_merge({'grey.nii','white.nii','csf.nii','other.nii'},'TPM.nii');

(As mentioned in "Pediatric Template" topic).

I use the default preprocessing pipeline and when I am prompted with the (Segment/normalize/resample settings) window I specify the the TPM.nii file for the pediatric template.

I have noticed that dimensions of the functional Nifti files after pre-processing are (91,109,91) and but the dimensions of my template is (197,233,189), Also the dimensions of normalized structural images after preprocessing  are different with my template (warped images).

Can you please advise me? Could that be the issue ? 
what are the necessary changes which I should consider when using my template file?

Any Help is much appreciated,
Hengameh
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Problem with first-level analysis main CONN GUI when using different template files.

June 7, 2019, 8:04 pm
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Hello Alfonso and CONN users,

I'm new in CONN.
I pre-processed and analyzed my data set in CONN, and I have used a different template. I am using the pediatric template.
As mentioned in "pediatric template" topic, that in SPM12 the tissue probability maps should be entered as a single 4d-file, I created an additional "other" probability map with probability values 1-p1-p2-p3  and merge all four classes into a single map using the following commands:

spm_imcalc({'grey.nii','white.nii','csf.nii'},'other.nii','max(0,1-i1-i2-i3)');
spm_file_merge({'grey.nii','white.nii','csf.nii','other.nii'},'TPM.nii');

I used the default preprocessing pipeline and in the (Segment/normalize/resample settings) window I specified the the TPM.nii file for the pediatric template.

I have noticed that dimensions of the functional Nifti files after pre-processing are (91,109,91) but the dimensions of my template are (197,233,189), Also the dimensions of  the warped structural images (wWM,wCSF,wGM) are different with my template.

Can you please advise on how to fix it? 
when Iuse my template, What are the necessary changes which I should consider in CONN ?

Any Help is much appreciated,
Hengameh
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RE: Problem with second-level analysis main CONN GUI & result explorer display , when using different template and atlas files.

June 8, 2019, 5:09 am
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[color=#000000]me?
[/color][i]Originally posted by Mohammad Iyas Kawas:[/i][quote]Thank you Alfonso,

I am using the Mayo clinic adult life span template and atlas. 
I use the default preprocessing pipeline and when I am prompted with the (Segment/normalize/resample settings) window I specify the the TPM file for the mayo clinic template. 

And in setup>ROI I use the corresponding atlas too (an 122 ROI modified AAL atlas that is coregistered the template.)

In Setup>Options I also Use the (GM+WM) Brain mask created from and provided with the template as my explicit analysis mask.

And when I reach the 2nd level analysis display I specify the reference T1 for this template also and then I specify the Atlas too.

All the files (TPM, T1, Atlas, and mask are co-registered) and I download them as such.

NOTE: I did one thing that seems to have corrected the labeling issue in the GUI's display, which is I modified the .txt file associated with my atlas as it started the first line with a 0_unknown and then started listing the ROI's starting from the second line 1_precentral,....... (as you can see in the attached image). I changed the .txt file for the atlas to be very similar to the .txt file of the default conn atlas. (this fixed the display, but I didn't rerun the Setup or rerun the analysis as the for ROI to ROI analysis CONN seems to have generated the seeds correctly from the Atlas file. Do you think I need to rerun the Setup and analysis?)

Also, I understand from you that if the analysis Mask has different dimensions but is properly co-registered to the TPM file CONN will handle it correctly ? 
Hope this is correct and that the analysis is not affected by these issues.

Many thanks,
Mohammad Kawas[/quote][quote]Hello Mohammad Kawas[/quote][quote]I have the same problem.  I am using the pediatric template.[/quote][quote]I used the default preprocessing pipeline and in the (Segment/normalize/resample settings) window I specified the the TPM.nii file for the pediatric template. I have noticed that dimensions of the functional Nifti files after pre-processing are (91,109,91) but the dimensions of my template are (197,233,189), Also the dimensions of the warped structural images (wWM,wCSF,wGM) are different with my template.[/quote][quote]I didn't understand is it a problem or not? What should I do?[/quote][quote]Would you please advise me?[/quote][quote]Thanks in advance,[/quote][quote]Hengameh
[/quote]
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error in step 5/7: importing ROI data

June 9, 2019, 3:36 am
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Hi

I was running conn for connectivity analysis. i incurred the following error.
I tried re installing conn and running the project again. but the same error occured.
Could i get some help in this.


step 5/7: Importing ROI data
ERROR DESCRIPTION:

Scalar structure required for this assignment.
Error in conn_process (line 694)
V0.fname=regexprep(Vmask{nroi}{nses},',\d+$','');
Error in conn_process (line 16)
case 'setup', conn_disp(['CONN: RUNNING SETUP STEP']); conn_process([0:4,4.5,5]);
Error in conn (line 5262)
else conn_process(processname); ispending=false;
Error in conn_menumanager (line 120)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN18.b
SPM12 + DEM FieldMap MEEGtools
Matlab v.2019a
project: CONN18.a
storage: 44.4Gb available




thanks
Ashwini
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RE: Y axis scale changes during plotting scatterplots for connectivity results

June 9, 2019, 3:58 am
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[color=#000000]Hi[/color]

[color=#000000]I do not know the details of how SPM creates these plots but my guess would be that you may be plotting the data from nearby but not exactly the same voxel locations. A more robust way to create these plots would be to first extract the connectivity values aggregated across all voxels within your cluster of interest, instead of selecting a single voxel (e.g. this can be done using the 'extract values' button in CONN's results explorer window), and then simply plotting those connectivity values against your behavioral covariate (e.g. this can be done using [i]Tools.Calculator [/i]in CONN) [/color]

[color=#000000]Hope this helps[/color]
[color=#000000]Alfonso[/color]
[i]Originally posted by konstantina ki:[/i][quote]Hi Alfonso!

I am doing a resting-state functional connectivity analysis with a behavioural covariate (i.e.,  I want to see if my behavioural variable affects the RS seed-based connectivity amongst individuals). To visualise my second-level results, I click on SPM button in the CONN results display option.
To show the scatterplot of connectivity against the behavioural variable, I select plot->fitted responses --> predicted-->against variable and I select my behavioural contrast generated by CONN.

What I notice is that the scale of y axis (the connectivity values) can change from time to time. Although the pattern of the points seems to remain the same, it seems that some times y axis is expanded and sometimes is reduced. This can lead to few values becoming negative for example - despite the pattern of the points being similar.
This occurs even if I do not select 'recompute second level' but just 'load existing values'.

I cannot understand why this happens and what I can do to prevent SPM or CONN from doing this.
I assume that these are arbitrary units and so it shouldn't matter, right? 
I need to be able to produce the same plots on every execution.

Can you please help?

Thanks,
Konstantina[/quote]
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error in imprting ROI data

June 10, 2019, 12:31 am
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Hi,

I'm trying to create new ROIs and got an error message in the step 5/7: importing ROI data.
ROIs were extracted from seed to voxel analysis. I created "...ROI. img" data file by clicking "Export mask."
Last time I successfully imported another ROIs, so I'm confused.
I appreciate your help.

Thank you.

Aya

ERROR DESCRIPTION:

Error using spm_sample_vol
File too small.
Error in rex>rex_do (line 811)
if ~isempty(allxyz1), dall = spm_sample_vol(params.VF(i),allxyz1(1,:),allxyz1(2,:),allxyz1(3,:),0); end %XYZ1{r}{nclusters}(1,:),XYZ1{r}{nclusters}(2,:),XYZ1{r}{nclusters}(3,:),0);
Error in rex (line 180)
[params.ROIdata,params.ROInames,params.ROIinfo.basis,params.ROIinfo.voxels,params.ROIinfo.files,params.ROIinfo.select,params.ROIinfo.trans]=rex_do(params,1);
Error in conn_rex (line 8)
[varargout{1:nargout}]=rex(varargin{:});
Error in conn_process (line 867)
[data{nroi1},namesroi{nroi},params]=conn_rex(Vsourcethis,Vmask{nroi}{min(nses,nsesstemp)},'summary_measure','mean','conjunction_mask',mask,'level',level,'scaling',scalinglevel,'select_clusters',0,'covariates',entercovariates,'fsanatomical',fsanatomical,'output_type',outputtype,'output_rex',filenamerex,'output_folder',filepath);
Error in conn_process (line 16)
case 'setup', conn_disp(['CONN: RUNNING SETUP STEP']); conn_process([0:4,4.5,5]);
Error in conn (line 5262)
else conn_process(processname); ispending=false;
Error in conn_menumanager (line 120)
feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});
CONN18.b
SPM12 + Anatomy DEM FieldMap MEEGtools Masking aal cat12 iVAC
Matlab v.2016a
project: CONN17.a
storage: 2294.6Gb available
spm @ /home/araya/spm12
conn @ /home/araya/conn
SUGGESTIONS:
Potential corrupt or incomplete volume. Try revising or regenerating source volumes
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RE: Weird cut-off activation map single subject

June 11, 2019, 11:48 am
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Just to update on this issue, in the end, we did find that the fov for the single patient cut off the cerebellum, whereas for controls it was fully present. So in the end, we had to workaround this issue by making a custom brainmask with this part of the cerebellum masked out, and we added a seed in the cerebellum that we would regress as a covariate of nuisance, in order to ensure that this part of the brain would be neither used as a seed nor as a target. This allowed us to get correct results in the end, since the super high z values in this buggy regions were hiding everything else.
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RE: duplicate connections exporting table

June 11, 2019, 10:30 pm
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Hi Alfonso,
I can live with duplicates. It makes sense that if I select all rois in the graph explorer I will get both region A to region B and Region B to Region A in the output table . However, not all the ROIs are duplicated (see 381-89) and not all of the ROIs have the same calculated FDR values (see 188 to 146 and the same connection 146 to 188). 

188 146 -3.99 0.0001 0.0419
146 188 -3.99 0.0001 0.0399
271 68 -3.96 0.0001 0.0476
68 271 -3.96 0.0001 0.0476
381 89 -3.94 0.0001 0.0064

I am using conn 17a. I have enclosed two new screen shots. Why would 381 to 89 be significant but not 89 to 381?

all the very best,
Jen
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RE: Error while importing ROI data

June 12, 2019, 3:03 am
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Hello Forum Users, Hello Boris

I have the same error-message with CONN 18b.

@boris: Did you maybe solve it?

@forum: or can anybody help me?

Best regards,
Andrea
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Extracting ROI info into correlation matrix

June 12, 2019, 8:55 am
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Hello all,
Apologies if this is a no-brainer, this is my first time using Conn. I've followed the FAQ in terms of extracting the Fisher-transformed Z scores from the resultsROI_ConditionXX.mat file. However, I'm such a newbie with Matlab that I'm not sure how to get everything out of the resultsROI (names, scores, etc.) file into a correlation matrix or heatmap. How does one do this? Or is it best to do a correlation matrix for each subject?
Thanks!!
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Documentation on conn_batch_humanconnectomeproject.m

June 12, 2019, 1:53 pm
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Hi all,

I am wondering if there is documentation on the reasoning for running specific steps in the script provided for processing and analyzing ICA-FIX data from the Human Connectome Project (conn_batch_humanconnectomeproject.m).

Thank you!

Georgia
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Contrast weights for between-sources comparisons

June 13, 2019, 5:16 am
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Hi Alfonso and others


I'm unsure about contrast weights in between-sources comparisons - thanks for any pointers!

If I compare e.g. 4 frontal against 2 parietal ROIs in a t-test, my weights vector should be [1 1 1 1 -2 -2] in order to sum to zero. The CON* images in the folder results/secondlevel/(myanalysis) folder should then be the linear combination of the BETA* images for the corresponding ROIs (from the first-level analysis), weighted by my contrast vector.

Is this correct?

Best wishes, 

Eugeno
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RE: Inconsistent ROI-ROI results

June 14, 2019, 12:42 am
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Hi Alfonso and CONN experts,

Following up on this question from a few years ago, it seems that primarily the gPPI modelling in the CONN toolbox (and all other gPPI toolboxes) is still directional, do you know if there is any way yet to circumvent this and get a symmetric ROIxROI correlation matrix for task-based connectivity in CONN or using another tool?

If not, do you know if it is acceptable to calculate the average based on RegionA - RegionB and RegionB - RegionA in order to obtain a approximate measure of this? Or can one pick only the strongest connection as is done in DWI?

I was also wondering why it is important to use bivariate regression as opposed to bivariate correlation for gPPI models (as is recommended in the manual)? I am asking this as I noticed that I get the same matrices from selecting gPPI and bivariate correlation and examining the matrices found in /results/firstlevel/SBC_01/results...ROI_Condition001.mat and if I use the graph theory toolbox, set my threshold to 0, select correlation coefficients, then select "export data" and view results.Z. Does this mean that the graph theory option calculates bivariate correlations even in the case of gPPI and is this still a valid measure of connectivity in this case or is it also not recommended to use graph theory analyses on gPPI data? Lastly, I also noticed in the results.Z matrices the values are all positive values even if I select two-way in the gui, is there a reason for these correlations being expressed as only positive in the graph theory portion of the toolbox? 

My ultimate aim is to produce large network-based correlation matrices (ideally symmetric) for specific task condition contrasts that I can use post-hoc to examine large-scale connectivity associated with specific functions. I know I can do this for each ROI individually using the  the "import values" option at the second-level covariate and could build my own matrix this way but was wondering if there was another way (such as using the graph theory toolbox) to explore large-scale networks within the gPPI framework.

Thank you so much for your time and thank you for making such a great multipurpose connectivity toolbox!

Isabella
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1st-level t-tests script

June 14, 2019, 8:28 am
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Dear Alfonso, dear community,

I extended a script that Alfonso provided in 2014 to do 1st-level t-tests. The scripts now allows to freely choose what conditions to use, and what t-test contrast to perform (so it's possible to perform multi-conditions contrasts like [-2 -1 0 1 2] with 5 conditions).

The script can be found here: https://github.com/lrq3000/csg_mri_pipelines/blob/master/analysis/fmri/various/conn_1stlevel_ttest.m

Hope this can be useful,
Best regards,
Stephen
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Co-registration ROI with structural data

June 14, 2019, 11:14 am
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Hello,

I am a new user of Conn, and I have a question regarding ROI.
I want to process data with brain lesions. In order to do so, I wanted to add a ROI with a mask of the entire brain without the lesion.
These ROIs are not in the MNI space.
Should I co-register these ROIs (drawn on the original MPR T1) with the initial data, or after the pre-processing steps?
If I need to co-register the pre-processed data with my ROIs, where is the pre-processed MPR T1 saved?

Thanks a lot for your help!
Best,
Mickael
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graphical display options for connectome ring

June 15, 2019, 11:36 am
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Is there a way to suppress certain connections on the circle diagram (ROI-to_ROI effects) to aid in visualizing specific aspects of the diagram?

For example, how i would display just inter-hemispheric connections suppressing the between hemispheric connections.  Could you please let me know what script is run to create this circle diagram? 
Thanks
Jen
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RE: Installation fault

June 16, 2019, 10:32 am
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Same error here with Matlab R2018a.  I copied and pasted my spm12 folder with conn 18.b into the R2019a update 2 folder and added spm folder to path, cd'd -> conn and it seems to be working fine.
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how long Intrinsic connectivity (ICC) takes

June 16, 2019, 7:35 pm
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Hi all,

I'm running ICC with the resting state data from 100 subjects, however, it only takes about 20min, can it running so fast? or is any step wrong?

My analysis steps are as follows:

Setup >>
Basic- 100 subjects
Structural - not input images (because the data has been preprocessed)
Functional - preprocessed data
ROIs - grey, white, CSF
Conditions - rest (entire session)
Covariates 1st-level - none
Covariates 2nd-level - three groups
Options - Voxel-Voxel, check all output files, default setup for others 
Preprocessing - none

Denoising>>
Confounds - White, CSF, further filtered 0.009-0.08, Simultaneous

first-level Analyses >>
Voxel-to-Voxel - IntrinsicConnectivity, Normalization, inf

it's weird only takes 20min to running ICC, does anybody know if there's anything wrong with my setup?

Thanks in advance,
Rabby
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About Compcor

June 18, 2019, 2:55 am
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Hi everyone,

Does anyone know that the aCompCor in CONN calculates PCA based on raw data in wm/csf or considering the [i]conditions[/i] and [i]covariates[/i] input in SETUP session? I found that it does not exclude the voxels that highly correlated to the task function when calculating PCA so I had this concern.

Thanks!

Adler
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Missing single subject first-level results for seemingly arbitrary ROIs/sessions

June 18, 2019, 4:03 am
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Dear all,

I am trying to perform a seed-to-voxel connectivity analysis with subject-specific but session-invariate ROIs (12/subject, several sessions for each subject). In the first-level results window, connectivity results are missing for certain ROIs only in certain individuals and in certain scan sessions (=conditions) and the "source timeseries" box does not show any timeseries signal in these cases. Consequently, my N is off in the second-level results...

The ROIs are all located correctly within the functional images (and anatomically in the structural grey matter mask at each session, for that matter). I tried to re-run the analysis including pre-processing, but to no avail.

Has anyone noticed similarly strange behavior? Where can I start the debugging?

Best regards,
Johann Philipp Zöllner
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