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Correcting MEG Artifacts Caused by Overt Speech.

Omid Abbasi1, Nadine Steingräber1, Joachim Gross1,2,3

  • 1Institute for Biomagnetism and Biosignal Analysis, University of Münster, Münster, Germany.

Frontiers in Neuroscience
|June 25, 2021
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Summary
This summary is machine-generated.

This study addresses artifacts in magnetoencephalography (MEG) during speech production, particularly those from head movements. A novel artifact rejection method successfully removes these distortions, improving brain activity analysis for speech research.

Keywords:
MEGhead movementmovement artifactregression analysissignal space projectionspeech production

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Area of Science:

  • Neuroscience
  • Biophysics
  • Speech Science

Background:

  • Magnetoencephalography (MEG) is crucial for understanding speech production dynamics.
  • Speech production generates artifacts (e.g., from head movements) that contaminate MEG signals.
  • Existing methods struggle to effectively remove these speech-induced artifacts.

Purpose of the Study:

  • To characterize speech-related artifacts, focusing on head movements, in MEG data.
  • To develop and validate an artifact rejection approach for MEG during speech production.
  • To improve the quality of neurophysiological signals recorded during speech tasks.

Main Methods:

  • Recorded MEG data from 11 healthy participants during syllable pronunciation at varying loudness.
  • Extracted head position and orientation data during speech production.
  • Applied a combined regression analysis and signal space projection (SSP) approach for artifact removal.

Main Results:

  • Louder speech correlated with increased head movements and greater MEG signal distortions.
  • The proposed artifact rejection method effectively removed speech-related artifacts.
  • Underlying neurophysiological signals were successfully retrieved after artifact correction.

Conclusions:

  • Head movements during speech production significantly distort MEG recordings.
  • The developed regression and SSP-based artifact rejection approach is effective for MEG speech studies.
  • This method facilitates research into the neural basis of speech production using MEG.