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Post-hoc physiological waveform extraction from motion estimation in simultaneous multislice (SMS) functional MRI

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Summary
This summary is machine-generated.

High-resolution motion estimation in functional MRI (fMRI) reveals physiological signals. This method extracts respiration and cardiac data with higher accuracy than standard techniques, offering new insights into brain motion.

Keywords:
cardiaceffective sample ratemultiband (MB)physiologypost-processingrespiration

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Area of Science:

  • Neuroimaging
  • Physiological signal processing

Background:

  • Motion estimation is crucial for functional MRI (fMRI) preprocessing.
  • Standard fMRI software estimates motion parameters to correct for head movement.
  • Motion estimation time courses contain valuable physiological information.

Purpose of the Study:

  • To develop a high-resolution motion estimation technique (HighRes) for fMRI.
  • To extract physiological signals (respiration, cardiac) from fMRI motion data at higher bandwidth.
  • To validate the HighRes method using resting-state fMRI data.

Main Methods:

  • Estimated motion parameters separately for simultaneously acquired slices and combined them for high temporal resolution.
  • Applied the HighRes method to resting-state fMRI data.
  • Validated extracted physiological signals against respiration belt and pulse oximeter data.

Main Results:

  • Achieved effective sampling rates of 15.5 Hz and 11.4 Hz with HighRes.
  • Extracted respiration waveforms with significantly higher accuracy than standard motion parameters.
  • Successfully extracted cardiac waveforms, despite TR values typically too slow for cardiac sampling.

Conclusions:

  • HighRes motion traces provide insights into subject motion at higher frequencies than standard methods.
  • The technique can recover accurate respiration signals.
  • This method may reveal additional complexity in brain motion.