Center for Functional MRI In the Department of Radiology

Multi-echo Simultaneous Multi-slice (MESMS) High Performance fMRI


A major need in the analysis of Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI) data is the ability to distinguish BOLD related signals from non-BOLD related signals, such as those due to physiological fluctuations or head motion.  Previous studies1 have shown that the amplitude of the BOLD signal variations has a linear dependence on echo time (TE), whereas the amplitude of the non-BOLD signal variations does not.

Kundu et al2 3 extended this observation to Independent Component Analysis (ICA) of multi-echo fMRI data, where ICA components that display TE dependencies are considered BOLD signals; ICA components that do not display TE dependencies are considered noise and thus removed from the fMRI data. This fMRI denoising method, known as multi-echo ICA (ME-ICA), has been shown to robustly detect motion and other non-BOLD related signals, and to significantly improve signal to noise ratio and functional connectivity estimates (see Figure).

At Center for fMRI (CFMRI) we provide an accelerated multi-echo simultaneous multi-slice (MESMS) protocol that is capable of acquiring full brain multi-echo fMRI data with a TR of ~ 1sec.

MEMS image

Note that the MESMS protocol requires the use of the Nova Medical 32 channel head coil.

1 Peltier SJ, Noll DC, T2* dependence of low frequency functional connectivity, Neruoimage, 2002; 16(4)

2 Kundu P et al, Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI. Neuroimage, 2012;60(3)

3 Kundu P et al, Integrated strategy for improving functional connectivity mapping using multi-echo fMRI, PNAS, 2013; 110(40)

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