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Related Experiment Video

Updated: Jan 8, 2026

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Motion-corrected eye tracking improves gaze accuracy during visual fMRI experiments.

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|December 18, 2025
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Summary
This summary is machine-generated.

We developed Motion-Corrected Eye Tracking (MoCET) to precisely track human eye movements during functional Magnetic Resonance Imaging (fMRI) scans. This method corrects head motion drift, improving gaze accuracy for cognitive studies.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Biomedical Engineering

Background:

  • High-precision eye tracking is crucial for understanding cognition.
  • Functional Magnetic Resonance Imaging (fMRI) presents challenges for accurate eye tracking due to head motion.
  • Head shifts cause data drift and gaze inaccuracies in fMRI eye tracking.

Purpose of the Study:

  • To introduce a novel method for correcting eye tracking drift in fMRI.
  • To enhance the accuracy and precision of gaze estimation during fMRI scans.
  • To enable more robust investigations of naturalistic vision and cognition using fMRI.

Main Methods:

  • Developed Motion-Corrected Eye Tracking (MoCET) technique.
  • Utilized head motion parameters from fMRI preprocessing to correct eye tracking drift.
  • Applied MoCET retrospectively to existing fMRI datasets without additional hardware.

Main Results:

  • MoCET significantly improves the accuracy of gaze estimation compared to conventional detrending.
  • The method offers superior spatial and temporal precision over existing magnetic resonance-based eye trackers.
  • Demonstrated effective drift correction using fMRI head motion data.

Conclusions:

  • MoCET overcomes a critical limitation in integrating eye tracking with fMRI.
  • This technique enables precise investigation of naturalistic vision and cognition in fMRI.
  • MoCET facilitates more reliable and accurate eye movement analysis in neuroimaging research.