help
help > RE: weighted-GLM and effect of task in denoising step
Jan 29, 2021 02:01 PM | Alfonso Nieto-Castanon - Boston University
RE: weighted-GLM and effect of task in denoising step
Hi Andrew,
Yes, your interpretation is perfectly correct, the reasoning is simply that the task effect which you are correcting for during denoising (when entering task effects in the confounds list) is the "main" task effect (the constant activation that all of the events of one type/condition are sharing on average) while the connectivity results that you want to measure (e.g. as in a beta-series correlation approach) is the correlation among ROIs in the event-to-event differences/variability in these responses (disregarding the constant/average response across all those events).
Hope this helps
Alfonso
Originally posted by Andrew Lynn:
Yes, your interpretation is perfectly correct, the reasoning is simply that the task effect which you are correcting for during denoising (when entering task effects in the confounds list) is the "main" task effect (the constant activation that all of the events of one type/condition are sharing on average) while the connectivity results that you want to measure (e.g. as in a beta-series correlation approach) is the correlation among ROIs in the event-to-event differences/variability in these responses (disregarding the constant/average response across all those events).
Hope this helps
Alfonso
Originally posted by Andrew Lynn:
Hi all,
I am running a weighted-GLM task-based functional connectivity analysis across several condition using an event-related design. Could someone help clarify (or point me to literature) as to why I would included the effect of task in the denoising step as is indicated on the CONN toolbox website (see attached)?
My understanding is that for the connectivity analysis the event is convolved with an HRF function and the weighted-GLM is similar to a beta-series correlation approach. In that instance I am concerned that removing the effect of task in the denoising step may be removing the very signal I want to capture and correlate across ROIs.
Is this line of reasoning correct? Or is there a justification for including these task effects in the denoising step for an event-related task-based connectivity analysis?
Andrew
I am running a weighted-GLM task-based functional connectivity analysis across several condition using an event-related design. Could someone help clarify (or point me to literature) as to why I would included the effect of task in the denoising step as is indicated on the CONN toolbox website (see attached)?
My understanding is that for the connectivity analysis the event is convolved with an HRF function and the weighted-GLM is similar to a beta-series correlation approach. In that instance I am concerned that removing the effect of task in the denoising step may be removing the very signal I want to capture and correlate across ROIs.
Is this line of reasoning correct? Or is there a justification for including these task effects in the denoising step for an event-related task-based connectivity analysis?
Andrew
Threaded View
| Title | Author | Date |
|---|---|---|
| Andrew Lynn | Jan 27, 2021 | |
| Alfonso Nieto-Castanon | Jan 29, 2021 | |