title: Decoding of Covert Vowel Articulation Using Electroencephalography Cortical Currents.
abstract: With the goal of providing assistive technology for the communication impaired, we proposed electroencephalography (EEG) cortical currents as a new approach for EEG-based brain-computer interface spellers. EEG cortical currents were estimated with a variational Bayesian method that uses functional magnetic resonance imaging (fMRI) data as a hierarchical prior. EEG and fMRI data were recorded from ten healthy participants during covert articulation of Japanese vowels /a/ and /i/, as well as during a no-imagery control task. Applying a sparse logistic regression (SLR) method to classify the three tasks, mean classification accuracy using EEG cortical currents was significantly higher than that using EEG sensor signals and was also comparable to accuracies in previous studies using electrocorticography. SLR weight analysis revealed vertices of EEG cortical currents that were highly contributive to classification for each participant, and the vertices showed discriminative time series signals according to the three tasks. Furthermore, functional connectivity analysis focusing on the highly contributive vertices revealed positive and negative correlations among areas related to speech processing. As the same findings were not observed using EEG sensor signals, our results demonstrate the potential utility of EEG cortical currents not only for engineering purposes such as brain-computer interfaces but also for neuroscientific purposes such as the identification of neural signaling related to language processing.
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of TechnologyYokohama, Japan; Department of Functional Brain Research, National Center of Neurology and Psychiatry, National Institute of NeuroscienceTokyo, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and PsychiatryTokyo, Japan.
authors.forename: Natsue
authors.initials: N
authors.lastname: Yoshimura
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of TechnologyYokohama, Japan; Department of Functional Brain Research, National Center of Neurology and Psychiatry, National Institute of NeuroscienceTokyo, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and PsychiatryTokyo, Japan.
authors.forename: Atsushi
authors.initials: A
authors.lastname: Nishimoto
authors.affiliation: Department of Neurosurgery, Osaka University Medical School Osaka, Japan.
authors.forename: Abdelkader Nasreddine
authors.initials: AN
authors.lastname: Belkacem
authors.affiliation: Department of Electronics and Mechatronics, Tokyo Polytechnic University Atsugi, Japan.
authors.forename: Duk
authors.initials: D
authors.lastname: Shin
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of Technology Yokohama, Japan.
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Kambara
authors.affiliation: Department of Functional Brain Research, National Center of Neurology and Psychiatry, National Institute of NeuroscienceTokyo, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and PsychiatryTokyo, Japan; Precursory Research for Embryonic Science and Technology, Japan Science and Technology AgencyTokyo, Japan.
authors.forename: Takashi
authors.initials: T
authors.lastname: Hanakawa
authors.affiliation: Precision and Intelligence Laboratory, Tokyo Institute of TechnologyYokohama, Japan; Department of Advanced Neuroimaging, Integrative Brain Imaging Center, National Center of Neurology and PsychiatryTokyo, Japan; Solution Science Research Laboratory, Tokyo Institute of TechnologyYokohama, Japan.
authors.forename: Yasuharu
authors.initials: Y
authors.lastname: Koike
keywords: brain-computer interfaces; electoencephalography; functional magnetic resonance imaging; inverse problem; silent speech