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Sampling Rate Effects on Resting State fMRI Metrics.

Niko Huotari1,2, Lauri Raitamaa1,2, Heta Helakari1,2

  • 1Oulu Functional NeuroImaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.

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Summary

Low sampling rates in resting-state fMRI can cause aliasing of cardiorespiratory signals, affecting functional connectivity (FC). While conventional FC metrics are robust, dynamic analyses and cardiorespiratory signal aliasing are sensitive to sampling rates, especially at higher repetition times (TRs).

Keywords:
aliasingmagnetic resonance encephalographypulsationsquasi-periodic patternsresting state

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Area of Science:

  • Neuroimaging
  • Cardiorespiratory Physiology
  • Signal Processing

Background:

  • Resting-state functional magnetic resonance imaging (rs-fMRI) is crucial for understanding brain function.
  • Low sampling rates (long repetition times, TRs) in rs-fMRI can introduce aliasing artifacts from cardiorespiratory pulsations into the blood-oxygen-level-dependent (BOLD) signal.
  • These artifacts can potentially confound functional connectivity (FC) metrics, especially in the very low frequency (VLF) range.

Purpose of the Study:

  • To investigate the impact of varying sampling rates on established rs-fMRI functional connectivity (FC) metrics.
  • To assess the degree of cardiorespiratory signal aliasing across different sampling rates and acquisition schemes.
  • To evaluate the influence of sampling rate on both static and dynamic FC analyses.

Main Methods:

  • Ultra-fast fMRI data (TR 0.1 s) were downsampled to simulate various repetition times (TRs) from 0.3 s to 3 s.
  • Comparisons included echo-planar imaging (EPI) and interleaved slice acquisition against a 3D single-shot trajectory.
  • Analyses encompassed stationary (seed-based FC, ReHo, ICA) and dynamic (quasi-periodic patterns, QPP) metrics, alongside frequency domain analyses (FFT maps of VLF, respiratory, and cardiac power).

Main Results:

  • Conventional static FC metrics (e.g., seed-based connectivity, ICA) showed minimal changes across TRs from 0.1 s to 3 s.
  • Cardiorespiratory signal aliasing, particularly cardiac power into the respiratory band, was prominent at higher TRs (1-2 s) in central brain regions.
  • Dynamic analyses, such as VLF pulse detection in QPP, demonstrated a linear decrease in repeatability with increasing TRs, while benefiting from shorter TRs.

Conclusions:

  • Standard rs-fMRI FC metrics are generally robust to variations in TR within the 0.1 s to 3 s range.
  • Higher TRs (1-2 s) exacerbate cardiorespiratory aliasing, impacting frequency domain analyses and potentially dynamic FC measures.
  • Short TR acquisition is advantageous for dynamic rs-fMRI analyses and minimizing cardiorespiratory signal contamination.