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Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
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MEG current source reconstruction using a meta-analysis fMRI prior.

Keita Suzuki1, Okito Yamashita2

  • 1Department of Computational Brain Imaging, ATR Neural Information Analysis Laboratories, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan; Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma 630-0192, Japan.

Neuroimage
|April 11, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for magnetoencephalography (MEG) source reconstruction using meta-analysis functional MRI (fMRI) data. This approach enhances accuracy without increasing measurement costs or subject burden.

Keywords:
Hierarchical Bayesian methodMEG inverse problemMeta-analysisSource reconstructionfMRI

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Area of Science:

  • Neuroscience
  • Biophysics
  • Medical Imaging

Background:

  • Magnetoencephalography (MEG) noninvasively measures brain activity by mapping magnetic fields to cortical sources.
  • Current source reconstruction in MEG is an ill-posed inverse problem due to limited sensor data.
  • Functional MRI (fMRI) data can constrain MEG source reconstruction but requires additional measurements and subject effort.

Purpose of the Study:

  • To develop a cost-effective method for MEG current source reconstruction.
  • To investigate the utility of meta-analysis fMRI data as a spatial constraint for MEG.
  • To improve the accuracy of MEG source localization without additional in-person data acquisition.

Main Methods:

  • Utilized meta-analysis fMRI data synthesized from existing literature.
  • Integrated meta-analysis fMRI data as prior information in hierarchical Bayesian estimation.
  • Performed realistic simulations and applied to experimental face recognition task data.

Main Results:

  • Meta-analysis fMRI data improved current source reconstruction performance compared to low-quality individual fMRI and conventional methods.
  • Qualitative analysis of face recognition task data showed similar group analysis results using meta-analysis fMRI data.
  • The proposed method enhances MEG source reconstruction accuracy without additional measurement costs.

Conclusions:

  • Meta-analysis fMRI data offers a viable and cost-effective alternative to individual fMRI for MEG source reconstruction.
  • The method shows promise for modalities with lower measurement costs, like optically pumped magnetometers.
  • This approach advances noninvasive neuroimaging by improving source localization accuracy and accessibility.