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This study introduces a novel BOLD perturbation model to computationally separate dynamic brain responses from static background in fMRI signals. The method enables precise mapping of brain activity by reconstructing magnetic sources for improved functional analysis.

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Area of Science:

  • Neuroimaging
  • Biophysics
  • Computational Neuroscience

Background:

  • Functional magnetic resonance imaging (fMRI) is crucial for understanding brain activity.
  • Separating dynamic Blood-Oxygen-Level-Dependent (BOLD) signals from static background noise is a key challenge in fMRI analysis.
  • Existing methods often struggle to isolate subtle BOLD responses for accurate functional mapping.

Purpose of the Study:

  • To develop and validate a computational model for separating dynamic BOLD responses from static background in fMRI data.
  • To enable precise forward fMRI signal analysis and inverse mapping of brain functional activity.
  • To reconstruct intrinsic brain magnetic sources for enhanced functional mapping.

Main Methods:

  • A BOLD perturbation model (χ = χ0 + δχ) was employed to represent brain activity.
  • Complex division was used to extract BOLD phase signals (δP) from T2* images.
  • Inverse problem-solving reconstructed BOLD magnetic perturbations (δχ) and full brain magnetic susceptibility (χ) distributions.
  • Temporal correlation analysis was applied for functional mapping of 4D task BOLD fMRI datasets.

Main Results:

  • Demonstrated the BOLD perturbation model's efficacy in phase signal separation and magnetic source reconstruction using high-field (7T) and low-field (3T) fMRI data.
  • Reconstructed intrinsic brain magnetic sources (χ and δχ) from fMRI phase signals.
  • Task fMRI experiments revealed bidirectional BOLD χ perturbations during task performance, visualized by the δχ-depicted functional map.

Conclusions:

  • The BOLD perturbation model successfully separates fMRI phase signals and enables inverse mapping for pure BOLD δχ reconstruction.
  • This facilitates intrinsic functional χ mapping and provides a novel brain tissue image for scrutinizing BOLD responses.
  • Automatic function/structure co-localization is achieved for detailed analysis of brain tissue idiosyncrasy.