EEG/MEG Signal Processing, Modeling and Equipment Development.
Main Lab Location:
588-2, Iwaoka, Iwaoka-cho, Nishi-ku, Kobe, Hyougo 651-2492, Japan
My research interest is neuroscience and engineering using non-invasive brain imaging methods, in particular electroencephalography (EEG) and magnetoencephalography (MEG).
Recently, Brain ICTs, such as BMI technology, have progressed rapidly. However, many of these technologies can be used only in laboratories or hospitals. The aim of my research is to establish Brain ICTs that improve the quality of daily life.
One of my research topics is the development of a novel system that can easily measure brain activity in naturalistic environments. I have already developed a mobile-wireless EEG device that enables measurement of brain activity in electrically noisy environments. Moreover, to improve the usability of the EEG device, I have developed a dry flexible electrode which enables EEG measurement without conductive pastes. I am advancing this development based on collaboration between government, industry and academia, and the EEG device and flexible electrode are already launched by Japanese companies.
Another research topic of my lab is the development of novel signal processing techniques to extract brain information from EEG/MEG data in electrically noisy environments. I use techniques such as time-frequency analysis, machine learning, and Bayes’ inference. In many cases, I first verify the novel signal processing techniques using low-noise MEG system, and then implement the techniques in the mobile-wireless EEG system. I am developing applications which can assist people not only in medical services but also in education and communication by using the EEG system in which the signal processing techniques are implemented.
The other research topic is the study of dynamics of EEG/MEG. Currently, understanding the waveforms of EEG/MEG is based on empirical rules in many cases. Knowledge of the dynamics is especially useful to understand EEG/MEG waveforms.
Naruse, Y., Takiyama, K., Okada, M. & Umehara, H. Statistical method for detecting phase shifts in alpha rhythm from human electroencephalogram data. Physical Review E 87, 042708 (2013)
Naruse, Y., Takiyama, K., Okada, M. & Murata, T. Inference in alpha rhythm phase and amplitude modeled on Markov random field using belief propagation from electroencephalograms. Phys. Rev. E 82, 011912 (2010)
Naruse, Y., Matani, A., Miyawaki, Y. & Okada, M. Influence of coherence between multiple cortical columns on alpha rhythm: A computational modeling study. Hum. Brain Mapp. 31, 703-715 (2010)
Naruse, Y., Matani, A., Hayakawa, T. & Fujimaki, N. Influence of seamlessness between pre- and post-stimulus alpha rhythms on visual evoked potential. NeuroImage 32, 1221-1225 (2006)