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RIKEN Center for Advanced Intelligence Project

Information Integration for Neuroscience Team

Team Leader: Motoaki Kawanabe (D.Eng.)
Motoaki  Kawanabe(D.Eng.)

In the aging and high-stress society of recent years, the number of people who suffer from mental disorders continues to increase year after year, and inflating medical expenses become a critical social issue as well. Towards creation of a novel brain/mental health management framework to prevent serious disorder, we are developing necessary key technologies such as brain state estimation methods by integrating everyday multi-sensor data with brain information, and robust EEG analysis techniques using fMRI data.

Main Research Field

Neuroscience & Behavior

Related Research Fields

Engineering / Computer Science

Research Subjects

  • Robust Analysis Techniques for Multi-modal Brain Data
  • Daily Life Monitoring by Multi-sensors
  • Management of Brain and Mental Health

Selected Publications

Papers with an asterisk(*) are based on research conducted outside of RIKEN.
  1. Hirayama, J., Hyvärinen, A., and Kawanabe, M.:
    “SPLICE: Fully tractable hierarchical extension of ICA with pooling”
    Proceedings of the 34th International Conference on Machine Learning, (2017).
  2. Hirayama, J., Hyvärinen, A., Kiviniemi, V., Kawanabe, M., and Yamashita, O.:
    “Characterizing variability of modular brain connectivity with constrained principal component analysis”
    PLOS ONE, Vol. 11, e0168180 (2016).
  3. *Hyvärinen, A., Hirayama, J., Kiviniemi, V., and Kawanabe,M.:
    “Orthogonal connectivity factorization: Interpretable decomposition of variability in correlation matrices”
    Neural Computation, Vol.28, pp. 445-484 (2016).
  4. *Morioka, H., Kanemura, A., Hirayama, J., Shikauchi, M., Ogawa, T., Ikeda, S., Kawanabe, M., and Ishii, S.:
    “Learning a common dictionary for subject-transfer decoding with resting calibration”
    NeuroImage, Vol. 111, pp. 167-178 (2015).
  5. *Morioka, H., Kanemura, A., Morimoto, S., Yoshioka, T., Oba, S., Kawanabe, M., and Ishii, S.:
    “Decoding spatial attention by using cortical currents estimated from electroencephalography with near-infrared spectroscopy prior information”
    NeuroImage, Vol. 90, pp. 128-139 (2014).
  6. *Samek, W., Kawanabe, M., and Müller, K.-R.:
    “Divergence-based framework for common spatial patterns algorithms.”
    IEEE Reviews in Biomedical Engineering, Vol. 7, pp. 50-72 (2014).
  7. *Kawanabe, M., Samek, W., Müller, K.-R., and Vidaurre, C.:
    “Robust common spatial filters with a maxmin approach”
    Neural Computation, Vol. 26, pp. 349-376 (2014).
  8. *Binder, A., Müller, K.-R., and Kawanabe, M.:
    “On taxonomies for multi-class image categorization”
    International Journal of Computer Vision, Vol. 99, pp. 281-301 (2012).
  9. *Haufe, S., Tomioka, R., Nolte, G., Müller, K.-R., and Kawanabe, M.:
    “Modeling sparse connectivity between underlying brain sources for EEG/MEG”
    IEEE Transactions on Biomedical Engineering, Vol. 57, pp. 1954-1963 (2010).
  10. *Blankertz, B., Tomioka, R., Lemm, S., Kawanabe, M., and Müller, K.-R.:
    “Optimizing spatial filters for robust EEG single-trial analysis”
    IEEE Signal Processing Magazine, Vol.25, pp.41-56 (2008).

Contact information

2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto

Email: motoaki.kawanabe [at] riken.jp

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