Kazuhisa Shibata, Ph. D

English/Japanese


Common words in the abstracts of my papers (created by Wordle)
Associate Professor
Department of Psychology

Contact Information

shibata at lit.nagoya-u.ac.jp (Nagoya University)
kazuhisa.shibata at gmail.com (gmail)


Research Interests

  • Learning
  • Attention
  • Decision making
  • Subliminal process
  • Bayesian theory


Publications

  • International journals
    1. The effects of feature attention on pre-stimulus cortical activity in the human visual systemKazuhisa Shibata, Noriko Yamagishi, Naokazu Goda, Taku Yoshioka, Okito Yamashita, Masa-aki Sato, and Mitsuo Kawato, Cerebral Cortex, 2008, 18(7):1664-1675.
    2. Boosting perceptual learning by fake feedbackKazuhisa Shibata, Noriko Yamagishi, Shin Ishii, and Mitsuo Kawato, Vision Research, 2009, 49(21):2574-2585. (Evaluated by Faculty of 1000 Biology)
    3. Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentationKazuhisa Shibata, Takeo Watanabe, Yuka Sasaki, and Mitsuo Kawato, Science, 2011, 334(6061):1413-1415.
    4. Monocular deprivation boosts long-term visual plasticityKazuhisa Shibata, Mitsuo Kawato, Takeo Watanabe, and Yuka Sasaki, Current Biology, 2012, 22(9):R291-292.
    5. Preference suppression caused by misattribution of task-irrelevant subliminal motionKazuhisa Shibata and Takeo Watanabe, Proceedings of the Loyal Society B, 2012, 279(1742):3443-8.
    6. Resetting capacity limitations revealed by long-lasting elimination of attentional blink through training, Hoon Choi, Li-Hung Chang, Kazuhisa Shibata, Yuka Sasaki, and Takeo Watanabe, Proceedings of the National Academy of Sciences of USA, 2012, 109(30):12242-12247.
    7. Decoding Reveals Plasticity in V3A as a Result of Motion Perceptual LearningKazuhisa Shibata, Li-Hung Chang, Dongho Kim, Jose E. Nanez Sr, Yukiyasu Kamitani, and Takeo Watanabe, Yuka Sasaki, PLoS One, 2012, 7(8): e44003.
    8. Two-stage model in perceptual learning: toward a unified theoryKazuhisa Shibata, Dov Sagi, and Takeo Watanabe, Annals of the NY Academy of Sciences, 2014, 1316:18-28.
    9. Age-related declines of stability in visual perceptual learning, Li-Hung Chang, Kazuhisa Shibata, George J. Andersen, Yuka Sasaki, and Takeo Watanabe, Current Biology, 2014, 24(24):2926-2929.
    10. A small number of abnormal brain connections predicts adult autism spectrum disorder, Noriaki Yahata, Jun Morimoto, Ryuichiro Hashimoto, Giuseppe Lisi, Kazuhisa Shibata, Yuki Kawakubo, Hitoshi Kuwabara, Miho Kuroda, Takashi Yamada, Fukuda Megumi, Hiroshi Imamizu, José E. Náñez Sr, Hidehiko Takahashi, Yasumasa Okamoto, Kiyoto Kasai, Nobumasa Kato, Yuka Sasaki, Takeo Watanabe, and Mitsuo Kawato, Nature Communications, 2016, 7:11254.
    11. Neuroimaging Evidence for 2 Types of Plasticity in Association with Visual Perceptual LearningKazuhisa Shibata, Yuka Sasaki, Mitsuo Kawato, Takeo Watanabe, Cerebral Cortex, 2016, 26(9):3681-3689.
    12. Learning to associate orientation with color in early visual areas by associative decoded fMRI neurofeedback, Kaoru Amano, Kazuhisa Shibata, Mitsuo Kawato, Yuka Sasaki, Takeo Watanabe, Current Biology, 2016, 26(14):1861-1866.
    13. Differential activation patterns in the same brain region led to opposite emotional statesKazuhisa Shibata, Takeo Watanabe, Mitsuo Kawato, Yuka Sasaki, PLoS Biology, 2016, 14(9): e1002546.
    14. Neural predictors of evaluative attitudes towards celebrities, Keise Izuma, Kazuhisa Shibata, Kenji Matsumoto, Ralph Adolphs, Social Cognitive and Affective Neuroscience, 2016, Advanced online publication.
    15. Fear reduction without fear through reinforcement of neural activity that bypasses conscious exposure, Ai Koizumi, Kaoru Amano, Aurelio Cortese, Kazuhisa Shibata, Wako Yoshida, Ben Seymour, Mitsuo Kawato, Hakwan Lau, Nature Human Behavior, 2016, 1:0006.
  • International conferences
    1. Feature attention modulates activity within feature-sensitive visual areas before stimulus onset: An fMRI constrained MEG study, Kazuhisa Shibata, Noriko Yamagishi, Naokazu Goda, Taku Yoshioka, Okito Yamashita, Masa-aki Sato, and Mitsuo Kawato, Society for Neuroscience Annual Meeting, Oct. 2006, Atlanta, USA (Poster presentation).
    2. Applying a sparse classifier method to MEG data decoding of attention experiment, Okito Yamashita, Kazuhisa Shibata, Noriko Yamagishi, Masa-aki Sato, International Conference on Biomagnetism, Aug. 2006, Vancouver, Canada (Poster presentation).
    3. Boosting perceptual learning by feedback manipulation, Kazuhisa Shibata, Shin Ishii, Noriko Yamagishi, and Mitsuo Kawato, Vision Sciences Society Annual Meeting, May 2008, Florida, USA (Talk presentation).
    4. Preference bias is induced by task-irrelevant motion only if it is weak, Kazuhisa Shibata, Takeo Watanabe, Vision Sciences Society Annual Meeting, May 2010, Florida, USA (Poster presentation).
    5. Decoding reveals sensory plasticity in V3A with motion perceptual learning, Kazuhisa Shibata, Li-Hung Chang, Yuka Sasaki, Dongho Kim, Jose E. Nanez, Sr., Yukiyasu Kamitani, Takeo Watanabe, Society for Neuroscience Annual Meeting, Nov. 2010, San Diego, USA (Poster presentation).
    6. Misattribution of unconscious visuo-motor conflict to preferential decision, Kazuhisa Shibata, Takeo Watanabe, Vision Sciences Society Annual Meeting, May 2011, Florida, USA (Poster presentation).
    7. Ventral lateral prefrontal areas reflect an influence of past experiences of weak signals on perceptual decision making, Shigeaki Nishina, Dongho Kim, Kazuhisa Shibata, Ji-Won Bang, Gojko Zaric, José Náñez, Yuka Sasaki, Takeo Watanabe, Vision Sciences Society Annual Meeting, May 2011, Florida, USA (Poster presentation).
    8. Greater effect of less visible signals on implicit probability learning in perceptual decision making, Shigeaki Nishina, Dongho Kim, Kazuhisa Shibata, Yuka Sasaki, Takeo Watanabe, The 15th annual meeting of the ASSC, June 2011, Kyoto, Japan (Poster presentation).
    9. Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation, Kazuhisa Shibata, Yuka Sasaki, Mitsuo Kawato, and Takeo Watanabe, Vision Sciences Society Annual Meeting, May 2012, Florida, USA (Talk presentation).
    10. Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation, Kazuhisa Shibata, Yuka Sasaki, Mitsuo Kawato, and Takeo Watanabe, Association for Scientific Study of Consciousness, July 2012, Brighton, UK (Talk presentation).
    11. Inducing behavioral modification by decoded neurofeedback, Kazuhisa Shibata, Annual meeting of the Japan Neuroscience Society, September 2012, Nagoya, Japan (Invited talk presentation).
    12. Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation, Kazuhisa Shibata, Yuka Sasaki, Mitsuo Kawato, and Takeo Watanabe, Society for Neuroscience, October 2012, New Orleans, USA (Poster presentation).
    13. Perceptual learning is associated with different types of plasticity at different stages - revealed by fMRI, Kazuhisa Shibata, Yuka Sasaki, Mitsuo Kawato, and Takeo Watanabe, Vision Sciences Society Annual Meeting, May 2013, Florida, USA (Talk presentation).
    14. Human facial preferences are changed at the mercy of online neurofeedback, Kazuhisa Shibata, Yuka Sasaki, Mitsuo Kawato, and Takeo Watanae, Society for Neuroscience, Novemeber 2013, San Diego, USA (Poster presentation).
    15. Human facial preferences are changed at the mercy of decoded fMRI neurofeedback, Kazuhisa Shibata, Yuka Sasaki, Mitsuo Kawato, and Takeo Watanabe, Vision Sciences Society Annual Meeting, May 2014, Florida, USA (Talk presentation).
    16. The neural mechanism of stabilization of perceptual learning revealed by the concentration of excitatory and inhibitory neurotransmitter, Kazuhisa Shibata, Maro Machizawa, Edward Walsh, Ji Won Bang, Li-Hung Chang, Aaron Berard, Qingleng Tan, Yuka Sasaki, and Takeo Watanabe, Vision Sciences Society Annual Meeting, May 2015, Florida, USA (Poster presentation).
  • Awards
    1. Uehara Memorial Foundation, Postdoctal Fellowship, 2009.
  • Other publications (Reviews)
    1. Kazuhisa Shibata, Reinforcement learning and reward system in the brain, Bussei Kenkyu, 2006, 87(3):467-72.
    2. Kazuhisa Shibata, Computational neuroscience and computational biology, Bussei Kenkyu, 2006, 87(3):473-77.
    3. Kazuhisa Shibata, Lecture by Yukiyasu Kamitani in ASCONE - The Bayesian perception, Japanese Neural networks, 2007, 14(4):313-8.
    4. Kazuhisa Shibata, Takeo Watanabe, Perceptual learning, consciousness, and psychiatry, Japanese Journal of Clinical Psychiatry, 2011, 40(4).
    5. Kazuhisa Shibata, Decoded neurofeedback method (DecNef), Clinical Neuroscience, 2012, 30(9):1070-1
    6. Kazuhisa Shibata, A new neuroscientific approach using decoded neurofeedback (DecNef), Clinical Neurology, 2012, 52:1185-7
  • Invited talks
    1. University College London, Mar. 2008, London, UK.
    2. International Conference of Perceptual Learning, Oct. 2008, Beijin, China.
    3. Meeting for Memory and Cognition, Hosei University, Apr. 2010, Tokyo, Japan.
    4. Experimental Psychology Meering for Young researchers in Kansai, Dec. 2010, Osaka, Japan.
    5. Symposium in National Institute of Physiological Sciences: Toward Understanding Visual Perception, October 2012, Okazaki, Japan.
    6. International Conference of Perceptual Learning, Dec. 2012, Nara, Japan.
    7. Columbia University, Aug. 2013, New York, USA.
    8. Princeton University, Mar. 2014, Princeton, USA.
    9. International Conference of Perceptual Learning, Aug. 2014, Vevey, Switzerland.
    10. Yale University, Sep. 2014, New Haven, USA.
    11. Dartmouth College, Feb. 2015, Hanover, USA.
    12. University of Reading, Oct. 2015, Reading, UK.
    13. University of Cambridge, Oct. 2015, Cambridge, UK.
    14. University of York, Nov. 2015, York, UK.
    15. Korea Advanced Institute of Science and Technology, Sep. 2016, Daejeon, Korea.
    16. Kochi University of Technology, Sep. 2016, Kochi, Japan.
    17. RIKEN Brain Science Institutes, Oct. 2016, Saitama, Japan.
    18. Kyoto University, Nov. 2016, Kyoto, Japan.

Research skills

  • Experience on psychophysical experiments in vision, decision making, motor control
  • Measurement (online/offline fMRI, MRS, MEG, EEG) and analyses (SPM, FreeSurfer, BrainVoyager, Turbo-BrainVoyager, LC Model, EEGLab) of neuroimaging data
  • Brain decoding using various statistical methods (Support Vector Machine, Sparse Logistic Regression, etc)
  • Computational theory and simulation
  • Programing (MATLAB since 2003, C/C++ since 2000, and VB, Perl, and SQL since 2002, etc)


Collaborators, Mentors, and Supervisors


Career


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