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MEPrep: A robust pipeline for multi-echo fMRI denoising and preprocessing.

Zhishun Wang1,2, Feng Liu1,2, Rachel Marsh1,2

  • 1The Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, United States.

Imaging Neuroscience (Cambridge, Mass.)
|April 9, 2026
PubMed
Summary
This summary is machine-generated.

Introducing MEPrep, a new pipeline for multi-echo fMRI data. It uses preICA and ME-ICA to significantly reduce noise, improving data quality and analysis reliability for researchers.

Keywords:
NipypefMRIPrepfunctional connectomeindependent component analysis (ICA)multi-echo functional MRI (ME-fMRI)tedana

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Area of Science:

  • Neuroimaging
  • Functional Magnetic Resonance Imaging (fMRI)
  • Signal Processing

Background:

  • Multi-echo fMRI enhances BOLD signal quality by mitigating motion and susceptibility artifacts.
  • Multi-echo independent component analysis (ME-ICA) excels at separating BOLD signals from noise compared to traditional methods.
  • Existing pipelines lack advanced denoising steps for raw multi-echo data.

Purpose of the Study:

  • To introduce preICA, a novel ICA-based denoising method for raw multi-echo fMRI data.
  • To integrate preICA and ME-ICA into a robust preprocessing pipeline, MEPrep.
  • To evaluate MEPrep's efficacy in denoising multi-echo fMRI data.

Main Methods:

  • Developed preICA, an ICA-based denoising step applied before echo combination.
  • Integrated preICA and ME-ICA into the fMRIPrep framework, creating the MEPrep pipeline.
  • Validated MEPrep on a resting-state multi-echo fMRI dataset.

Main Results:

  • MEPrep significantly improved denoising efficacy compared to existing methods.
  • Key improvements included enhanced T2* model fitting, reduced motion artifacts, and increased signal-to-noise ratio.
  • Functional connectivity reliability and Shannon entropy were also improved, indicating better signal preservation.

Conclusions:

  • MEPrep, integrating preICA and ME-ICA, offers superior noise suppression for multi-echo fMRI.
  • The pipeline enhances data quality while preserving neurobiological signal complexity.
  • MEPrep provides a scalable, open-source solution for reproducible multi-echo fMRI preprocessing.