NITRC NITRC Community Forum: open-discussion

RE: Connectivity question

Patrick Bedard — Fri, 13 Mar 2026 16:05:26 GMT

<p>ok thanks , </p>
<p>I was afraid this would be the case!!</p>
<p>I did chopped the timeseries ans selected specific blocks (frames); but now I have less timepoints and the data is not continuous anymore, so it's harder to do causality analysis, say like Granger or some other time-varying FC</p>

RE: Connectivity question

Rodolphe Nenert — Fri, 13 Mar 2026 15:49:37 GMT

<p>Different numbers of timepoints can matter because the connectivity estimates from longer series are usually more stable. I would not fix that by upsampling. A better approach is to compute connectivity from matched portions of the task across all subjects (for example the same blocks or the first common segment), convert correlations to Fisher z, and then compare groups at the second level. You can include the number of usable frames as a covariate only as a secondary sensitivity analysis, but not as the main solution if scan length is essentially confounded with group.</p>

RE: Connectivity question

Patrick Bedard — Fri, 13 Mar 2026 2:58:42 GMT

<p>Anna, </p>
<p>Thanks for responding!</p>
<p>I don't want to split the timeseries, I want to use all the timepoints (volumes) available. <br>But, this creates the issue of having many more timepoints for a group vs the other and so the correlations will be calculated with different number of timepoints.  </p>
<p>Just to be sure I'm cler, the correlation between ROI for the controls would be based on 480 timepoints while the correlation for the patients would be based on 240 timepoints. Then I'd compare between groups those correlations.</p>
<p>Is this a problem that these correlations are based on different timeseries length?</p>
<p>best</p>
<p>patrick</p>

RE: Connectivity question

Anna Farmer — Wed, 11 Mar 2026 16:42:56 GMT

<p>Patrick, </p>
<p>I mainly work with resting state fMRI, but I have a suggestion for addressing your issue. You can always use fslsplit to split out the time series into individual volumes and then use fslmerge to merge the volumes you want back into one file for analysis. You could script this so it manually removes the extra volumes from the end of the time series in your patients. </p>
<p>Hope this helps, </p>
<p>Anna </p>

Connectivity question

Patrick Bedard — Tue, 10 Mar 2026 18:48:35 GMT

<div>Hello expert,</div>
<div> </div>
<div>I have a question about fMRI connectivity analysis.</div>
<div>I’m trying to see if connectivity differs between groups of patient and controls, in a set of ROI.</div>
<div> </div>
<div>Say I'd use correlation </div>
<div> </div>
<div>My issue is that the fMRI timeseries are much longer for the control than patients, about 2 times longer, so more timepoints (~480 vs ~250); it's a feature of the task they were doing, the patients got fatigued much earlier. So, the correlation for the controls would be computed with more timepoints than the correlation of the patients.</div>
<div> </div>
<div>-1-</div>
<div>So, my question is since the number of timepoints differ substantially between the groups, is this a problem for group analysis? I would compare the correlation between groups with a t-test for example.</div>
<div> </div>
<div>-2-</div>
<div>If this an issue, is there a way out? Maybe up-sampling the patient time series or some other methods?</div>
<div> </div>
<div> </div>
<div>thansk a lot</div>
<div>patrick</div>
<div> </div>
<div> </div>

Loading AnalyzIR data into SPM

Henry Brice — Wed, 26 Nov 2025 20:57:42 GMT

<p>I want to use the gPPI module in SPM in order to run a task-based functional connectivity analysis om fNIRS data.</p>
<p>I have used the AnalyzIR (Huppert) toolbox to process the data, so I have the motion-corrected HbO and HbR timeseries arranged in ROI space, but I can't work out how to output that preprocessed data in a format that I can read into SPM, or any in-depth explanation of the data structure that the gPPI package wants to read in.</p>
<p>I'd be very grateful for any tips or tricks to get this to work.</p>
<p>Henry</p>

Data access on NITRC

NITRC Moderator — Mon, 10 Nov 2025 20:19:57 GMT

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