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000904407 1001_ $$0P:(DE-Juel1)187419$$aHeunis, Stephan$$b0$$eCorresponding author
000904407 245__ $$aThe effects of multi-echo fMRI combination and rapid T*-mapping on offline and real-time BOLD sensitivity
000904407 260__ $$aOrlando, Fla.$$bAcademic Press$$c2021
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000904407 520__ $$aA variety of strategies are used to combine multi-echo functional magnetic resonance imaging (fMRI) data, yet recent literature lacks a systematic comparison of the available options. Here we compare six different approaches derived from multi-echo data and evaluate their influences on BOLD sensitivity for offline and in particular real-time use cases: a single-echo time series (based on Echo 2), the real-time T2*-mapped time series (T2*FIT) and four combined time series (T2*-weighted, tSNR-weighted, TE-weighted, and a new combination scheme termed T2*FIT-weighted). We compare the influences of these six multi-echo derived time series on BOLD sensitivity using a healthy participant dataset (N = 28) with four task-based fMRI runs and two resting state runs. We show that the T2*FIT-weighted combination yields the largest increase in temporal signal-to-noise ratio across task and resting state runs. We demonstrate additionally for all tasks that the T2*FIT time series consistently yields the largest offline effect size measures and real-time region-of-interest based functional contrasts and temporal contrast-to-noise ratios. These improvements show the promising utility of multi-echo fMRI for studies employing real-time paradigms, while further work is advised to mitigate the decreased tSNR of the T2*FIT time series. We recommend the use and continued exploration of T2*FIT for offline task-based and real-time region-based fMRI analysis. Supporting information includes: a data repository (https://dataverse.nl/dataverse/rt-me-fmri), an interactive web-based application to explore the data (https://rt-me-fmri.herokuapp.com/), and further materials and code for reproducibility (https://github.com/jsheunis/rt-me-fMRI).
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000904407 7001_ $$0P:(DE-HGF)0$$aBreeuwer, Marcel$$b1
000904407 7001_ $$0P:(DE-HGF)0$$aCaballero-Gaudes, César$$b2
000904407 7001_ $$0P:(DE-HGF)0$$aHellrung, Lydia$$b3
000904407 7001_ $$0P:(DE-HGF)0$$aHuijbers, Willem$$b4
000904407 7001_ $$0P:(DE-HGF)0$$aJansen, Jacobus FA$$b5
000904407 7001_ $$0P:(DE-HGF)0$$aLamerichs, Rolf$$b6
000904407 7001_ $$0P:(DE-HGF)0$$aZinger, Svitlana$$b7
000904407 7001_ $$0P:(DE-HGF)0$$aAldenkamp, Albert P$$b8
000904407 773__ $$0PERI:(DE-600)1471418-8$$a10.1016/j.neuroimage.2021.118244$$gVol. 238, p. 118244 -$$p118244 -$$tNeuroImage$$v238$$x1053-8119$$y2021
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