Can continuous task-based MEGA-PRESS be treated as block fMRS, and analyzed with Gannet?

Ask Anything!
1

Hi all, I would appreciate some advice on a block fMRS design.

I am considering acquiring single-voxel MEGA-PRESS MRS from vmPFC while participants perform an typical instrumental learning / approach–avoidance task continuously during the scan. The task includes reward, punishment, and neutral conditions, and it the entire acquisition window will be treated as one task block.

My two main questions are:

  1. Can this design reasonably capture task-related neurochemical changes?
    In other words, if the participant performs the task throughout the whole MRS acquisition, can the resulting spectrum be interpreted as reflecting the neurochemical state during ongoing task engagement, rather than just a nonspecific average?
  2. Can such data be analyzed with Gannet?
    If I treat one continuous MEGA-PRESS acquisition as one complete task block and analyze the averaged edited spectrum, is Gannet an appropriate tool? Or would task-based / blocked fMRS be better handled with another analysis pipeline for example like fMRI?

Any suggestions or relevant experience would be greatly appreciated. Thank you!

2

Hi @jmy_psy,

  1. I would direct you to @PGMM for his input, and also check out his 2018 paper.
  2. Gannet currently doesn’t perform out-of-the-box dynamic analyses on edited MRS data, but it will once version 4 is released (release date TBD). But it can analyze blocks of data if you have separate acquisitions. You just need to use the correct command syntax. Please reach out if this is something you want to explore (mam4041@med.cornell.edu). Also, Gannet would only be appropriate for analyzing GABA-edited data, so if Glu/Glx was your interest, you have to use another toolkit. FSL-MRS does natively support dynamic MRS data/analyses, I believe. It would be worth chatting to @wclarke about that.

Mark

3

@jmy_psy Happy to talk 2D fitting and fMRS analysis if you are interested in it. You could take a look at GitHub - wtclarke/fsl_mrs_fmrs_demo: Fitting fMRS data in FSL-MRS - ISMRM 2022 · GitHub or https://onlinelibrary.wiley.com/doi/10.1002/mrm.30001 for more information on this.