About Our Lab

In our laboratory, we conduct research activities in groups and individually based on self-designed brain measurement experiments. We use non-invasive methods such as magnetoencephalography (MEG) and magnetic resonance imaging (MRI) to measure brain activity. Since neuroscience is an interdisciplinary field and therefore requires a variety of background knowledge, we provide an in-depth study of the mechanisms of the brain as well as related fields such as engineering, physiology, psychology, and computational theory. If you want to study brain function measurement, brain information analysis, and biological signal processing, this is the laboratory for you.

For details, please visit this page and S-face interview.

In the first half of our seminar meeting, students present papers and book chapters, and in the second half, we give lectures on measurement and analysis methods of brain information, create and analyze sensory stimuli to be used in experiments, discuss group research, and present the progress of the group and individual researches. Please feel free to contact us if you would like to attend the seminar (brain[at]sfc.keio.ac.jp).

Our Environment

In our laboratory, we are able to use the most advanced brain measurement devices. For example, we use magnetoencephalography (MEG) and magnetic resonance imaging (MRI) at an external institution (e.g., Chiba Research Center, Tokyo Denki University, where the faculty member in charge was the MEG maintenance supervisor). It is a great privilege to have access to these facilities as an undergraduate student.

For Applicants

We accept students from other universities, other departments and other laboratories at any time. If you are interested in brain research, please feel free to contact us (brain[at]sfc.keio.ac.jp) if you are thinking of continuing your studies or have any questions.

To Prospective New Students

Our laboratory is always accepting new students who wish to enroll. If you are interested in brain research and our laboratory, please feel free to contact us (brain[at]sfc.keio.ac.jp).

Steps to Join the Seminar

To ensure a smooth start to your participation in the research seminar, we ask that you prepare by following the steps below. If you have any questions, please do not hesitate to ask.

1. Literature Review:

   First, to deepen your foundational knowledge of EEG research, please read "Introduction to EEG Analysis" (Japanese book). Chapters 1, 2, and Sections 1 and 2 of Chapter 4 are particularly important as they form the basis of our research. If possible, reading Sections 1 and 2 of Chapter 5 will further enhance your understanding.

2. Software Preparation:

   We use the following software in our research. Please install them in advance.

   • MATLAB (2020b or later): This is an essential tool for data analysis in the lab. It is available under a Keio University license. Please obtain it by logging into keio.jp, then navigating to "Services" → "Software License Acquisition System". Please also install the following toolboxes:
     • Simulink
     • Bioinformatics Toolbox
     • Fixed-Point Designer
     • Parallel Computing Toolbox
     • Signal Processing Toolbox
     • Statistics and Machine Learning Toolbox
   • EEGLAB (Advanced): A powerful toolbox for EEG analysis that runs on MATLAB. Detailed installation instructions are provided in "Introduction to EEG Analysis".
   • MNE-Python (Advanced): A Python-based library for EEG and MEG analysis. Please install this as needed.
3. Completion of Research Ethics Training:

   Adherence to research ethics is essential for anyone conducting research. Please complete the e-learning course following the steps below and submit your certificate of completion via email.

   1. Access K-Support and from the "Apps" menu, select "Research" → "Application for Research Ethics and Compliance Education e-Learning Account".
   2. Take the Keio University researcher course in the "APRIN e-learning Program" (the "Science and Engineering" course is recommended).
   3. After completion, please send the certificate of completion (in PDF format) to the lab's email address.

References

The following materials are useful references for beginners learning about the brain and conducting research. Please refer to them as needed.

• Eric R. Kandel (Author), John D. Koester (Author), Sarah H. Mack (Author), Steven A. Siegelbaum (Author). Principles of Neural Science, Sixth Edition. McGraw Hill / Medical, 2021, 1696p.
• Yasutsugu Miyashita (Supervisor), Eric R. Kandel (Author), John D. Koester (Author), Sarah H. Mack (Author), Steven A. Siegelbaum (Author). Kandel's Principles of Neural Science, 2nd Edition. Medical Science International, 2022, 1700p.
• Mark F. Bear (Author), Barry W. Connors (Author), Michael A. Paradiso (Author), Satoshi Fujii (Supervisor, Translator). Color Edition Bear, Connors, Paradiso Neuroscience: Exploring the Brain, Revised Edition. Nishimura Shoten, 2021, 788p.
• Neil R. Carlson (Author), Melissa A. Birkett (Author), Katsuki Nakamura (Supervisor, Translator). Carlson's Physiology of Behavior - Brain and Behavior - Original 13th Edition. Maruzen Publishing, 2022, 777p.
• Mike X Cohen (Author). Analyzing Neural Time Series Data: Theory and Practice. The MIT Press, 2014, 600p.
• Kazuo Hiraki (Editor), Noriaki Kanayama (Editor), Takanori Kochiyama (Author), Atsushi Matsumoto (Author), Makoto Miyakoshi (Author). Introduction to EEG Analysis Windows 10 Compatible Edition: Mastering EEGLAB and SPM. University of Tokyo Press, 2020, 224p.
• Satoru Miyauchi (Author), Shoko Hoshi (Author), Iwao Kanno (Author), Shinya Kuriki (Author), Hironobu Tokuno (Editor). Brain Imaging. 2016, 256p. (Brain Science Lecture 3).
• Tsunehiro Takeda (Author), The Institute of Electronics, Information and Communication Engineers (Editor). Brain Engineering. Corona Publishing, 2003, 220p. (Electronics and Information Communication Lecture Series, D-24)
• Hiroshi Harashima. Brain Tan. NTS, 2005, 162p.
• Mark Lutz (Author). Learning Python. Oreilly & Associates Inc, 2013, 1540p.
• Nobukatsu Takai (Author). Introduction to MATLAB. Kogakusha, 2002, 215p.