NITRC CONN : functional connectivity toolbox Forum: help

Sliding Window Analysis Storage

sfeuer45 — Mon, 21 Sep 2026 15:23:08 GMT

Hello,
I have been trying to perform sliding window analysis using CONN after successfully completing gPPI analysis. With eight subjects, I attempted to complete sliding window analysis, where the window length is 20 TRs (pretty standard according to <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/brb3.1255">Savva et al 2019)</a> and the window shift is 4 TRs (much higher than standard, because I was trying to avoid storage issues and this results in less windows). 
The result was 53 windows each for three sessions, across eight participants. I suppose this is quite a few, but this is less than I would expect if I stuck with standard values for window shift. However, when I ran 1st-level SBC analysis utilizing these windows, it took up 1.1 TB of storage on my machine.
This feels like a lot for such a widely-used method and would prevent me from doing any further analysis. Is it possible that I performed the analysis incorrectly? Or have others had this issue with sliding window analysis taking up a lot of storage? Happy to clarify any other parameters I used.

Error "Index exceeds the number of array elements. Index must not exceed 2." in preprocessing step

Hyunjun Park — Mon, 21 Sep 2026 11:56:08 GMT

Dear users,

I'm preprocessing my fMRI datasets using CONN connectivity.
My datasets consist of two sessions and two different conditions were assigned to each session.
I designed the script for it. While uploading images and setting up conditions were okay, I got the error message below during the preprocessing. Would you mind letting me know how I can fix this error, or sharing any previous posts regarding it, please?

---------------------------- [ Error Message ] ----------------------------
Step 7/7: Updating Denoising variables
Index exceeds the number of array elements. Index must not exceed 2.

Error in conn_process (line 1226)
for n1=1:N2, CONN_x.Preproc.variables.dimensions{N1+n1}=max(CONN_x.Preproc.variables.dimensions{N1+n1},size(x2.data{n1},2)*ones(1,2)); end
^^^^^^^^^^^
Error in conn_process (line 55)
case 'setup', conn_disp(['CONN: RUNNING SETUP STEP']); conn_process([0:4,4.5,5]);
^^^^^^^^^^^^^^^^^^^^^^^^^
Error in conn_batch (line 1361)
conn_process Setup;
^^^^^^^^^^^^
Error in GBA_prepro_Batch_v1 (line 29)
conn_batch('filename', projectFile, ...
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

------------------------------------------------------------------------

RE: Error using cellfun

Francesc Xavier Aymerich — Mon, 21 Sep 2026 8:15:01 GMT

Hi Spencer,
Thanks for your reply. I solved it updating the conn_process.m file from github repository. In the new version arrayfun function was used instead cellfun and it works
Xavier

RE: Error using cellfun

Spencer Upton — Sat, 19 Sep 2026 14:44:48 GMT

Here is a link to the solution.

Forum

(https://www.nitrc.org/forum/forum.php?thread_id=15994&forum_id=1144)

Code link

(https://github.com/alfnie/conn/blob/master/conn_process.m)

RE: Error using cellfun

Spencer Upton — Sat, 19 Sep 2026 11:50:28 GMT

I am having this same issue.

RE: preprocessing data issues

Omar Maximo — Fri, 18 Sep 2026 18:28:27 GMT

Hi,

Here's something I noticed across all versions I have used:

When I processed subjects with 3 timepoints, I noticed that it only created a mean image for the first timepoint and not for the remaining 2 but still created outputs. Is CONN using a mean image from timepoint 1 to correct for motion and coregistration for the other 2 sessions? Why isn't CONN creating a mean image for each timepoint and using them accordingly? or is it creating a mean image across all sessions?

There is also an issue when you have multiple T1w images. When you tell CONN that you have multiple images, then it only preprocess subjects with one timepoint and get errors for the other subjects with multiple errors. Then, when I change the setting to one scan per subject, then the errors go away. But then again, that brings me back to my first point.

Single vs. session-specific T1 images in a repeated-measures pre/post rs-fMRI study

Liliana Kataryne — Tue, 15 Sep 2026 23:42:34 GMT

I am analyzing a repeated-measures resting-state fMRI study and I would appreciate your advice regarding the structural images.
We have 22 participants who completed three experimental visits. In each visit, resting-state fMRI and a T1-weighted image were acquired both PRE and POST intervention. Therefore, each participant has six resting-state acquisitions and six corresponding T1-weighted images.
No anatomical changes are expected between these time points, since this is an acute intervention study.
For preprocessing in CONN, would you recommend using one T1-weighted image as the structural reference for all six resting-state sessions of each participant, or using the corresponding T1-weighted image for each session (session-specific structurals)?
I have seen your previous comments suggesting that a single structural image may be sufficient when no structural changes are expected across repeated measurements, but I was unsure whether the same recommendation would apply to this PRE/POST design.
Thank you very much for your help!
Best, Liliana

2nd-level ROI-to-ROI results restricted to ROIs from separate 1st-level analysis

Tyler Reekes — Tue, 15 Sep 2026 19:09:01 GMT

I am running into an issue with the 2nd-level results GUI for ROI-to-ROI analyses, specifically when using the "Group analysis results: individual ROIs" option. (CONN version 25.b.)
I have a seed ROI of interest that I am analyzing against the full set of 400 Schaefer atlas ROIs. In one 1st-level analysis, the seed is analyzed against all 400 Schaefer ROIs. I then created a separate 1st-level analysis using the same seed but restricted the target ROIs to only those belonging to the DMN.
The problem occurs when viewing the 2nd-level ROI-to-ROI results. The original analysis containing all 400 Schaefer ROIs appears to be restricted to only the ROIs included in the separate DMN-only analysis. In other words, the 400-ROI analysis is displayed as though it were the DMN-restricted analysis. This occurs even though the two analyses were set up separately at the 1st level.
I have checked the corresponding SPM files, and they appear to contain the correct dimensions/matrices (i.e., the expected number of ROIs for each analysis). Thus, it seems that the underlying first/second-level files may be correct, but the results displayed in the CONN GUI are not corresponding to the appropriate analysis. I have also tried deleting the corresponding 1st-level analysis files and rerunning the analyses, but this does not resolve the issue in the Results GUI.
Is there a specific file, or results cache that controls the ROI selection displayed in the 2nd-level ROI-to-ROI single ROI analysis GUI? Or, is there a recommended way to completely reset/rebuild the 2nd-level ROI-to-ROI results so that each analysis uses its own ROI set?
I would be happy to provide screenshots of the setup/results GUI, or examples of the relevant SPM files/matrices if helpful.

Error using cellfun

Francesc Xavier Aymerich — Sun, 13 Sep 2026 10:55:49 GMT

Dear users,
I have found an error when processing (apply and continue from denoising & Quality control)
ERROR DESCRIPTION:   Error using cellfun Input #2 expected to be a cell array, was double instead.
Error in conn_process (line 2015)  enames=cellfun(@(nroi)arrayfun(@(n)sprintf('%s_%d',names{nroi},n),1:size(data{nroi},2),'uni',0),1:numel(data),'uni',0);  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Error in conn_process (line 69)  case {'preprocessing_gui','denoising_gui'}, conn_disp(['CONN: RUNNING DENOISING STEP']); conn_process([1.5,2,6:9],varargin{:});  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Error in conn (line 7931)  conn_process('denoising_gui'); ispending=false;  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Error in conn_menumanager (line 125)  feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ CONN25.b SPM25 + DAiSS DEM FieldMap MEEGtools Matlab v.2026a
Please help me. I can't continue with the analysis
Best regards,
Xavier

preprocessing data issues

Jose Maximo — Fri, 11 Sep 2026 19:28:36 GMT

Hi,
I recently preprocessed some resting state data and when I looked at the MNI transformed EPI images, some looked odd (see attached image). For example, this subject's timepoint 2 image looks that its shifted (bottom image looks rotated on the y-axis) and many more look like that (positions are different).
I used the latest conn toolbox (25a, I believe) along with SPM25.
I will re-preprocess my data using the previous CONN version, which never had issues as far as I remember.
Thanks.