RIKEN BRAIN SCIENCE INSTITUTE (RIKEN BSI)

Faculty Detail / 研究室詳細

Naotaka Fujii, M.D., Ph.D.

- Our goal is to reveal neural mechanisms of adaptive social behavior at network level.

Adaptive Intelligence

Team Leader

Visiting Professor, Graduate School of Frontier Sciences, The University of Tokyo

Social brain function, Brain machine interface

Naotaka  Fujii

Research Area

Adaptive intelligence is an ability that allows all of living organisms to make adaptive behavior in environment. This is an innate biological function that creates novel state of relationship from old state between self and other/environment, which may provide maximal benefit to self with minimal risk, through interactive communication. Such novel relationships are generated at every moment and everywhere in the world and are built into relationship network made by enormous amount of previously established relationships. Our brain can understand rules of behavior at the moment that are described in the network structure and make adaptive behavior. Our team pursues understanding brain mechanism in terms of cognitive functions based on relationships. The mechanism will be incorporated into artificial support system for better communication between people.

Selected Publications View All

  1. 1

    Fujii N, Hihara S, Nagasaka Y, and Iriki A: "Social state representation in prefrontal cortex.", Soc Neurosci, 4(1), 73-84 (2009)

  2. 2

    Fujii N, Hihara S, and Iriki A: "Social cognition in premotor and parietal cortex.", Soc Neurosci, 3(3-4), 250-60 (2008)

  3. 3

    Fujii N, Abla D, Kudo N, Hihara S, Okanoya K, and Iriki A: "Prefrontal activity during koh-do incense discrimination.", Neurosci Res, 59(3), 257-64 (2007)

  4. 4

    Fujii N, Hihara S, and Iriki A: "Dynamic social adaptation of motion-related neurons in primate parietal cortex.", PLoS One, 2(4), e397 (2007)

  5. 5

    Takenaka K, Nagasaka Y, Hihara S, Nakahara H, Iriki A, and Kuniyoshi Y and Fujii N: "Linear discrimination analysis of monkey's behavior in alternative free choice task", Journal of Robotics and Mechatronics, 19(4), 416-422 (2007)

Press Releases View All