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Hemodynamic response function (HRF) variability confounds resting-state fMRI functional connectivity.

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Hemodynamic response function variability (HRFv) can create false functional connectivity (FC) in resting-state fMRI (rs-fMRI). Ignoring HRFv may lead to inaccurate brain network findings, suggesting deconvolution is crucial for reliable FC estimation.

Keywords:
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Area of Science:

  • Neuroimaging
  • Functional Connectivity Analysis
  • Brain Network Dynamics

Background:

  • Resting-state fMRI (rs-fMRI) estimates functional connectivity (FC) by analyzing spontaneous brain activity.
  • The hemodynamic response function (HRF) models the relationship between neural activity and the fMRI signal.
  • Variability in the HRF (HRFv) across brain regions is influenced by neural and non-neural factors, potentially confounding FC estimates.

Purpose of the Study:

  • To investigate whether HRF variability confounds functional connectivity (FC) estimates in resting-state fMRI (rs-fMRI).
  • To test the hypothesis that HRFv introduces inaccuracies in brain network analyses, particularly within the default-mode network.

Main Methods:

  • Simulations were used to model the impact of HRFv on FC with known ground truth.
  • rs-fMRI data from 47 healthy participants acquired at 7T were analyzed.
  • Two analysis pipelines were compared: one with hemodynamic deconvolution (DC) to minimize HRFv, and one without (NDC, ignoring HRFv).

Main Results:

  • Simulations demonstrated that HRFv can alter FC by up to 50%.
  • Analysis of rs-fMRI data revealed potential false connectivities, primarily between different brain lobes, attributable to HRFv.
  • A double exponential relationship was observed between HRFv magnitude and its impact on FC, with significant mean/median errors (30.5%/11.5%) in FC estimates.

Conclusions:

  • Ignoring HRFv in rs-fMRI analysis can lead to the identification of false functional connectivity.
  • FC findings derived from data where HRFv is not accounted for should be interpreted with caution.
  • Employing deconvolution techniques is recommended to minimize HRFv and improve the reliability of FC estimates.