Cortical current source estimation from electroencephalography in combination with near-infrared spectroscopy as a hierarchical prior

Takatsugu Aihara, Yusuke Takeda, Kotaro Takeda, Wataru Yasuda, Takanori Sato, Yohei Otaka, Takashi Hanakawa, Manabu Honda, Meigen Liu, Mitsuo Kawato, Masa aki Sato, Rieko Osu

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

Previous simulation and experimental studies have demonstrated that the application of Variational Bayesian Multimodal EncephaloGraphy (VBMEG) to magnetoencephalography (MEG) data can be used to estimate cortical currents with high spatio-temporal resolution, by incorporating functional magnetic resonance imaging (fMRI) activity as a hierarchical prior. However, the use of combined MEG and fMRI is restricted by the high costs involved, a lack of portability and high sensitivity to body-motion artifacts. One possible solution for overcoming these limitations is to use a combination of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). This study therefore aimed to extend the possible applications of VBMEG to include EEG data with NIRS activity as a hierarchical prior. Using computer simulations and real experimental data, we evaluated the performance of VBMEG applied to EEG data under different conditions, including different numbers of EEG sensors and different prior information. The results suggest that VBMEG with NIRS prior performs well, even with as few as 19 EEG sensors. These findings indicate the potential value of clinically applying VBMEG using a combination of EEG and NIRS.

Original languageEnglish
Pages (from-to)4006-4021
Number of pages16
JournalNeuroImage
Volume59
Issue number4
DOIs
Publication statusPublished - 2012 Feb 15
Externally publishedYes

Keywords

  • Electroencephalography (EEG)
  • Near-infrared spectroscopy (NIRS)
  • Variational Bayesian Multimodal EncephaloGraphy (VBMEG)

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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