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Related Experiment Video

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Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
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Resting-State Functional Connectivity Estimated With Hierarchical Bayesian Diffuse Optical Tomography.

Takatsugu Aihara1,2, Takeaki Shimokawa2, Takeshi Ogawa3

  • 1Graduate School of Human and Environmental Studies, Kyoto University, Kyoto, Japan.

Frontiers in Neuroscience
|February 22, 2020
PubMed
Summary
This summary is machine-generated.

A new hierarchical Bayesian (HB) algorithm for diffuse optical tomography (DOT) accurately estimates resting-state functional connectivity (RSFC). This method offers a more accessible and portable alternative to fMRI for brain imaging research.

Keywords:
diffuse optical tomography (DOT)hierarchical Bayesian estimation algorithmminimum norm algorithmnear-infrared spectroscopy (NIRS)resting-state functional connectivity (RSFC)

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Area of Science:

  • Neuroimaging
  • Biomedical Engineering
  • Computational Neuroscience

Background:

  • Resting-state functional connectivity (RSFC) is crucial for understanding brain function.
  • Functional magnetic resonance imaging (fMRI) is the standard for RSFC but has limitations (cost, portability, contraindications).
  • Diffuse optical tomography (DOT) using functional near-infrared spectroscopy (fNIRS) offers a portable, non-invasive alternative measuring hemodynamic changes.

Purpose of the Study:

  • To evaluate a novel hierarchical Bayesian (HB) algorithm for DOT in estimating RSFC.
  • To compare the HB DOT algorithm's performance against existing DOT algorithms using fMRI as a reference.
  • To assess the HB DOT algorithm's accuracy and reproducibility in mapping brain connectivity.

Main Methods:

  • Acquired 10-minute resting-state data from 20 healthy males using both 3T fMRI and high-density NIRS (96 long, 56 short source-detector channels).
  • Implemented and evaluated a hierarchical Bayesian (HB) DOT algorithm for reconstructing brain activity.
  • Compared the HB DOT algorithm with two prevailing DOT algorithms, using fMRI data as the ground truth for RSFC.

Main Results:

  • The HB DOT algorithm demonstrated superior performance in estimating RSFC compared to existing DOT algorithms.
  • The HB algorithm showed higher similarity to fMRI-derived RSFC data.
  • The HB algorithm exhibited improved inter-run reproducibility for RSFC estimation.

Conclusions:

  • The hierarchical Bayesian DOT algorithm is a promising tool for accurate and reproducible RSFC estimation.
  • This HB DOT approach provides a viable, non-invasive, and portable alternative to fMRI for brain connectivity studies.
  • The findings support the clinical and research potential of advanced DOT algorithms for neuroimaging.