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Documentation to highlight situations or studies where multi-echo or tedana are specifically useful
Summary
Several developers discussed adding a section to the documentation that highlights situations or specific studies that demonstrate where multi-echo fMRI in general or specific methods have been shown to be useful. This could be a either a "case studies" or "killer apps" section.
Additional Detail
I've open this issue as a place for people to suggest content that could go into this section until someone actually turns this content into a cohesive section of the documentation.
Next Steps
- Suggest case studies or papers that exist
- Suggest things that where we known multi-echo fMRI can help or thing it can help, but where you don't know of any validation studies yet.
- Compile all this info into a new section of the documentation.
Just to get some case examples started:
- Long task designs Separating slow BOLD from non-BOLD baseline drifts using multi-echo fMRI 10.1016/j.neuroimage.2014.10.051 Can potentially distinguish slow drifts from scanner noise from slows drifts that are central to neuropharmacology or learning studies.
- Reducing dropout in ventral regions Making cardiac gated fMRI more realistic Evaluation of multi-echo ICA denoising for task based fMRI studies: Block designs, rapid event-related designs, and cardiac-gated fMRI 10.1016/j.neuroimage.2016.07.049 Benefits of multi-echo fMRI for brain-stem imaging and with cardiac gated fMRI.
- Paradigm free mapping methods Quantitative Deconvolution of fMRI Data with Multi-echo Sparse Paradigm Free Mapping 10.1007/978-3-030-00931-1_36 Multi-echo information helps a sparse deconvolution method become more reliable
- TSNR or CNR boosts 8-10% boost in contrast to noise across a massively repeated task just with the optimal combination of echos and more with denoising. https://fim.nimh.nih.gov/presentations/effects-multi-echo-based-denoising-reliability-massively-repeated-block-design-task & https://fim.nimh.nih.gov/presentations/effect-multi-echo-denoising-amount-data-required-see-wide-spread-activity
- Non-aggressive paradigms can be accelerated slightly (or perhaps not at all) to get SNR boost from echo combination
- Something with task correlated motion, in which pure motion regressors could be harmful.
The quest for the best: The impact of different EPI sequences on the sensitivity of random effect fMRI group analyses https://doi.org/10.1016/j.neuroimage.2015.10.071
In the Conclusion :
We note activation studies of the orbitofrontal cortex affected by susceptibility artifacts as an important exception, since multi-echo EPI provides superior sensitivity as compared to their single echo counterparts.
@handwerkerd should we include uses of multi-echo combined with other things, like physio or phase data?
I'm not sure where to file something like this, but this paper is interesting in using ultra high res, 7T multiecho fmri as means to examine layer profiles. https://www.sciencedirect.com/science/article/abs/pii/S1053811911001984?via%3Dihub One interesting finding for me was that different layers have different optimal echo times, and this can be related to myeline content.