Journal articles describing multi-echo methods


Multi-echo preprocessing software

tedana requires data that has already been preprocessed for head motion, alignment, etc.

AFNI can process multi-echo data natively as well as apply tedana denoising through the use of To see various implementations, start with Example 12 in the help

fmriprep can also process multi-echo data, but is currently limited to using the optimally combined timeseries. For more details, see the fmriprep workflows page.

Currently SPM and FSL do not natively support multi-echo fmri data processing.

Other software that uses multi-echo fMRI

tedana represents only one approach to processing multi-echo data. Currently there are a number of methods that can take advantage of or use the information contained in multi-echo data. These include:

  • 3dMEPFM: A multi-echo implementation of ‘paradigm free mapping’, that is
    detection of neural events in the absence of a prespecified model. By
    leveraging the information present in multi-echo data, changes in relaxation
    time can be directly estimated and more events can be detected.
    For more information, see the following paper.
  • Bayesian approach to denoising: An alternative approach to separating out
    BOLD and non-BOLD signals within a Bayesian framework is currently under
  • Multi-echo Group ICA: Current approaches to ICA just use a single run of
    data in order to perform denoising. An alternative approach is to use
    information from multiple subjects or multiple runs from a single subject
    in order to improve the classification of BOLD and non-BOLD components.
  • Dual Echo Denoising: If the first echo can be collected early enough,
    there are currently methods that take advantage of the very limited BOLD
    weighting at these early echo times.
  • qMRLab: This is a MATLAB software package for quantitative magnetic
    resonance imaging. While it does not support ME-fMRI, it does include methods
    for estimating T2*/S0 from high-resolution, complex-valued multi-echo GRE
    data with correction for background field gradients.

Publications using multi-echo fMRI

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