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Effective Preprocessing Procedures Virtually Eliminate Distance-Dependent Motion Artifacts in Resting State FMRI.

Hang Joon Jo1, Stephen J Gotts2, Richard C Reynolds3

  • 1Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892-1148, USA.

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Summary
This summary is machine-generated.

Head motion artifacts in resting-state fMRI (rs-fMRI) are a concern. Global Signal Regression (GSReg) can worsen motion-induced biases, while WMeLOCAL preprocessing minimizes motion sensitivity.

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Area of Science:

  • Neuroimaging
  • Functional Magnetic Resonance Imaging (fMRI)

Background:

  • Artifacts in resting-state fMRI (rs-fMRI) arise from head motion, physiology, and hardware.
  • Head motion is a significant source of artifact, biasing correlations between brain regions based on their distance.
  • Common artifact correction methods include censoring motion-corrupted time points and Global Signal Regression (GSReg).

Purpose of the Study:

  • To investigate the impact of Global Signal Regression (GSReg) on motion-related artifacts in rs-fMRI.
  • To evaluate different rs-fMRI preprocessing strategies for their sensitivity to head motion.

Main Methods:

  • Replication of previously reported head-motion bias in correlation coefficients using Power et al. (2012) data.
  • Comparison of various rs-fMRI preprocessing models, including GSReg and WMeLOCAL.
  • Assessment of motion sensitivity and dependence on censoring levels for different preprocessing approaches.

Main Results:

  • Head motion introduces artifactual biases in correlation coefficients.
  • GSReg exacerbates the distance-dependent bias caused by head motion.
  • Correlation estimates after GSReg are more susceptible to motion and censoring.

Conclusions:

  • The choice of rs-fMRI preprocessing significantly influences the impact of motion artifacts on correlation estimates.
  • The WMeLOCAL denoising approach, a subset of ANATICOR, demonstrates minimal sensitivity to motion.
  • WMeLOCAL reduces the dependence of correlation results on censoring, offering a more robust analysis.