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Updated: May 26, 2026

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
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TRACC-PHYSIO: Time-Domain Resolution-Aligned Cross-Correlation to Estimate PHYSIOlogical Coupling and Time Delays in

Adam M Wright1,2, Jianing Zhang1, Yunjie Tong2

  • 1Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.

Magnetic Resonance in Medicine
|May 24, 2026
PubMed
Summary

A new method, TRACC-PHYSIO, accurately measures cardiac and respiratory pulsations in dynamic MRI scans. This framework quantifies physiological coupling and pulse delays, crucial for understanding neurofluid circulation.

Keywords:
cardiac and respiratory pulsationscoupling strengthdynamic diffusion‐weighted imaging (dynDWI)functional MRI (fMRI)neurofluid dynamicspulse time delays

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Area of Science:

  • Medical Imaging
  • Physiological Monitoring
  • Neuroscience

Background:

  • Cardiac and respiratory pulsations significantly influence neurofluid circulation.
  • Assessing these pulsations typically requires fast MRI, which is often unachievable in standard dynamic acquisitions.
  • Existing methods struggle to resolve temporal dynamics in slowly sampled dynamic MRI.

Purpose of the Study:

  • To validate TRACC-PHYSIO, a novel framework for assessing cardiac and respiratory brain pulsations in slowly sampled dynamic MRI.
  • To establish a method for quantifying physiological coupling and time delays in dynamic MRI data.
  • To enable the study of neurofluid dynamics in a wider range of MRI acquisitions.

Main Methods:

  • TRACC-PHYSIO, a Time-domain Resolution-Aligned Cross-Correlation framework, was systematically validated.
  • The method uses external cardiac and respiratory waveforms as references for time-shifted cross-correlation.
  • Key metrics derived include Peak Coupling Coefficient (Peak CorrCoeff) for coupling strength and TimeDelay for relative pulse arrival time.

Main Results:

  • In vivo fMRI demonstrated a strong association between TRACC-derived Peak CorrCoeff and spectrum-derived physiological bandpower (Pearson r > 0.90).
  • Simulations across various repetition times (TRs) and acquisition durations showed minimal mean bias and low temporal errors for both Peak CorrCoeff and TimeDelay.
  • The framework successfully estimated physiological coupling and time delays in simulated dynamic MR signals.

Conclusions:

  • TRACC-PHYSIO is a validated time-domain framework for quantifying cardiac and respiratory coupling strength in dynamic MRI.
  • The method enables the estimation of millisecond-scale relative pulse delays in standard dynamic MR acquisitions.
  • TRACC-PHYSIO overcomes limitations of fast imaging requirements for assessing physiological pulsations in the brain.