TY  - JOUR
AU  - Heunis, Stephan
AU  - Breeuwer, Marcel
AU  - Caballero-Gaudes, César
AU  - Hellrung, Lydia
AU  - Huijbers, Willem
AU  - Jansen, Jacobus FA
AU  - Lamerichs, Rolf
AU  - Zinger, Svitlana
AU  - Aldenkamp, Albert P
TI  - The effects of multi-echo fMRI combination and rapid T*-mapping on offline and real-time BOLD sensitivity
JO  - NeuroImage
VL  - 238
SN  - 1053-8119
CY  - Orlando, Fla.
PB  - Academic Press
M1  - FZJ-2021-05977
SP  - 118244 -
PY  - 2021
AB  - A 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).
LB  - PUB:(DE-HGF)16
C6  - pmid:34116148
UR  - <Go to ISI:>//WOS:000679333800006
DO  - DOI:10.1016/j.neuroimage.2021.118244
UR  - https://juser.fz-juelich.de/record/904407
ER  -