CiNet Hosoda Group

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Welcome to Hosoda group, CiNet

We explore "What is self, what is human, and what is life," and develop brain-inspired AI.

  • Our group was launched in September 2021. We are currently working mainly on mathematical models and fMRI experiments.

Research

The specific research themes are as follows. We welcome bringing themes and collaborative research.

  • Hebbian-inspired One-shot learning for deep-neural-network models
  • Simulating Eureka effect in visual object recognition using artificial neural network.
  • Whole-brain fMRI analysis of Eureka effect in visual object recognition
  • Enhancing Eureka ability of humans (collaborative research with Nittono Laboratory, Osaka University)
  • Fluctuation-driven super energy-saving computer
  • Construction of AI with “Self”

    • Members

    We enjoy deep discussions with these members

  • Kazufumi Hosoda; Senior Researcher (PI) [Prof in Kobe-U]
  • Chanseok Lim; Researcher
  • Komaki Kunishige; Research technician
  • Keigo Nishida; Collaborative researcher [Postdoc in Riken]
  • Wataru Miyamori; Trainee
  • Misako Kimura; Internship trainee
  • Tsutomu Murata; Senior Researcher (Advisor)
  • Izumi Ohzawa; Invited Specialist (Advisor) [Prof Emeritus in Osaka-U]
  • Kunihiko Kaneko; Invited Specialist (Advisor) [Prof Emeritus in Tokyo-U, Prof in Niels Bohr Inst]

    • Publications

    Preprints

  • Kazufumi Hosoda, Keigo Nishida, Shigeto Seno, Tomohiro Mashita, Hideki Kashioka, Izumi Ohzawa, "It's DONE: Direct ONE-shot learning with Hebbian weight imprinting", arXiv, Art. no. arXiv:2204.13361, Jun. 2022

    • Peer-reviewed

  • Yusuke Morito, Tsutomu Murata, “Accumulation System: Distributed Neural Substrates of Perceptual Decision Making Revealed by fMRI Deconvolution,” J. Neurosci., vol. 42, no. 24, pp. 4891?4912, Jun. 2022, doi: 10.1523/JNEUROSCI.1062-21.2022. (*draw journal attention: J Neurosci 42: 8596?8598, 2022)
  • Kazufumi Hosoda, Shigeto Seno, Tsutomu Murata, "Simulating reaction time for Eureka effect in visual object recognition using artificial neural network.", in Proceedings of The 17th International Conference on Knowledge, Information and Creativity Support Systems (KICSS2022), Kyoto, Japan, 2022 (*Best Crowd Award)

    • Patents

  • Japanese patent 2022-146887
  • Japanese patent 2022-107734

    • Access & Contact

    E-mail: hosodak at nict.go.jp
    〒565-0871  1-4 Yamadaoka, Suita City, Osaka, 565-0871
    Center for Information and Neural Networks (CiNet)
    (in Osaka university)