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On time delay estimation and sampling error in resting-state fMRI.

Ryan V Raut1, Anish Mitra1, Abraham Z Snyder2

  • 1Departments of Radiology, Washington University, St. Louis, MO, 63110, USA.

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Summary
This summary is machine-generated.

Resting-state fMRI (rsfMRI) connectivity and time delays are affected by sampling variability. Shorter scans limit accuracy, especially for time delay estimation, necessitating careful data analysis strategies.

Keywords:
Functional connectivityHead motionLagReliabilitySampling errorTime delay estimation

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Area of Science:

  • Neuroimaging
  • Computational Neuroscience

Background:

  • Resting-state functional magnetic resonance imaging (rsfMRI) signals reflect electrophysiological infra-slow activity (<0.1 Hz).
  • Pairwise correlations (functional connectivity, FC) and temporal delays in rsfMRI signals describe spatiotemporal dynamics.

Purpose of the Study:

  • To investigate factors influencing sampling variability in time delay estimation (TDE) and FC.
  • To assess the impact of data quantity and quality on TDE and FC accuracy in rsfMRI.

Main Methods:

  • Analysis of surrogate fMRI time series to isolate effects on TDE and FC.
  • Examination of real 30-minute rsfMRI data to evaluate sampling error.
  • Investigation of motion artifact impact on sampling error and TDE/FC.

Main Results:

  • Both TDE and FC accuracy are sensitive to data quantity, with TDE being more affected.
  • Lower correlation magnitudes and sampling rates impact TDE accuracy.
  • Exclusion of motion-corrupted data can worsen sampling error, highlighting a bias-variance tradeoff.

Conclusions:

  • Sampling error is a significant challenge for rsfMRI TDE and FC, particularly with limited scan durations.
  • Strategies for motion handling, error characterization, and mitigation are crucial for reliable lag-based analyses.
  • Careful consideration of data quantity and quality is essential for robust rsfMRI analysis.