Members

Person in charge

Staffs

  • Rin Kuriyama, Project Researcher
  • Kaaya Akira, Technical Staff
  • Yukiko Miyadera, Technical Staff
  • Daisuke Ichimura, Adjunct Research Scientist (Researcher @ AIST)
  • Taira Kobayashi, Adjunct Research Scientist (Assistant Professor @ Yamaguchi University)

FY2026

Alumni

FY2025

  • Mao Iwata, Technical Staff
  • Rin Kuriyama (D4)
    • JSPS Research Fellowship for Young Scientists DC1 (FY2022 – FY2024)
    • FY2025 Student Award
    • FY2023 Student Award
    • FY2021 Student Award
    • FY2019 Meguro Award
    • Rin Kuriyama, Hideyuki Yoshimura, Tadashi Yamazaki. A theory of cerebellar learning as a spike-based reinforcement learning in continuous time and space. PNAS Nexus, 4(10): pgaf302, 2025. (10 pages).
    • Rin Kuriyama, Claudia Casellato, Egidio D’Angelo, Tadashi Yamazaki. Real-time simulation of a cerebellar scaffold model on graphics processing units. Frontiers in Cellular Neuroscience 15: 623552, 2021.
    • Rin Kuriyama*, Kaaya Akira*, Laura Green, Beatriz Herrera, Kael Dai, Mari Iura, Gilles Gouaillardet, Asako Terasawa, Taira Kobayashi, Jun Igarashi, Anton Arkhipov, Tadashi Yamazaki (*: equally contributed). Microscopic-Level Mouse Whole Cortex Simulation Composed of 9 Million Biophysical Neurons and 26 Billion Synapses on the Supercomputer Fugaku. in The International Conference for High Performance Computing, Networking, Storage and Analysis (SC ’25), November 16–21, 2025, St Louis, MO, USA. ACM, New York, NY, USA, 11 pages. doi: 10.1145/3712285.3759819.
    • Rin Kuriyama, Hideyuki Yoshimura, Tadashi Yamazaki. Cerebellar spiking network model as a reinforcement learning machine.  Annual Meeting of Society for Neuroscience (Neuroscience2024) , October 5-9, 2024, Chicago, USA.
    • Rin kuriyama, Hideyuki Yoshimura, Tadashi Yamazaki. A cerebellar spiking network model as a reinforcement learning machine. The 33rd Annual Meeting of the Japanese Neural Network Society (JNNS2023), September 4-6, 2023, Tokyo. Conference Encouragement Award. 
    • Rin Kuriyama, Hideyuki Yoshimura, Ryohei Hoashi, Tadashi Yamazaki. Developing a spiking network model of the cerebellum as a reinforcement learning machine. Annual Meeting of Society for Neuroscience (Neuroscience2022) , November 12-16, 2022, San Diego, USA  (Hybrid).
    • Rin Kuriyama, Hideyuki Yoshimura, Ryohei Hoashi, Tadashi Yamazaki. Implementation of a cerebellar spiking neural network as a reinforcement learning module. NEURO2022, Jun 30 – July 3, 2022,Okinawa (Hybrid).
    • Rin Kuriyama, Tadashi Yamazaki. Realtime simulation of a cerebellar scaffold model on a GPU. 30th Annyal Meeting of Japanese Neural Network Society (JNNS2020), December 2-5, 2020, Online.
    • Student in Hackathon on cerebellum modeling (January 15–17, 2020, Pavia, Italy)
    • Student in School of Brain Cells & Circuits “Camillo Golgi” (August 27–September 1, 2019, Erice, Italy)
  • Takeki Mukaida (M2)
  • Nanako Wakasugi (M2)
  • Mitsuru Inoue (M2)

FY2024

FY2023

  • Masahumi Ikeyama (B4)

FY2022

  • Shu Omura (M2)
  • Ryo Maeoka (M2)
  • Kaoru Shiga (B4)
    • Master course student at University of Kyoto since April 2023

FY2021

FY2020

FY2019

  • Hiroshi Yamaura, Research Scientist
    • Hiroshi Yamaura, Jun Igarashi, Tadashi Yamazaki. A spiking network model of the cerebrocerebellar communication loop. 27th Annual Conference of Japanese Neural Network Society (JNNS2017), Sep 20-22, 2017, Kitakyushu International Conference Center.
    • Hiroshi Yamaura, Jun Igarashi, Tadashi Yamazaki. Scalable simulation of cerebellar corticonuclear microcomplexes using a tile-based neural network simulator on K supercomputer. 41th Annual Meeting of Japan Neuroscience Society (Neuroscience2018 Kobe), July 26-29, 2018, Kobe.
    • Hiroshi Yamaura, Tadashi Yamazaki. Purkinje cells in a cerebellar neural network model acquire climbing fiber driven activity modulation for accurate movements. The 48th Annual Meeting of Society for Neuroscience (Neuroscience2018) , November 3-7, 2018, San Diego, USA.
    • Hiroshi Yamaura, Jun Igarashi, Tadashi Yamazaki. Building a spiking network model of the cerebellum on K computer using NEST and MONET simulators. Computational Neuroscience (CNS*2019), July 13-17 2019, Barcelona,Spain.
  • Daisuke Ichimura (D3)
    • Postdoctoral fellow at the Advanced Institute of Science and Technology (AIST) since December 2020
    • Received FY2019 Student Award
    • Received FY2016 Meguro Award
    • Received FY2014 Student Award
    • Daisuke Ichimura, Tadashi Yamazaki. A Pathological Condition Affects Motor Modules in a Bipedal Locomotion Model. Frontiers in Neurorobotics 13:79, 2019.
    • Daisuke Ichimura, Satoshi Yano, Tadashi Yamazaki. Computer simulation of a cerebellar-musculoskeletal model for bipedal locomotion with feedback compensation of foot contact. IEICE Transactions on Information and Systems (Japanese Edition) Vol.J100-D No.8 pp.808-816, 2017.
    • Daisuke Ichimura, Satoshi Yano, Tadashi Yamazaki. Dynamical simulation of a brain-musculoskeletal system for rehabilitation. 8th Motor Control Workshop. Aug 7-9, 2014, Tsukuba University.
    • Daisuke Ichimura, Tadashi Yamazaki. Computer simulation of a brain-musculoskeletal dynamical model for bipedal walking towards personalized rehabilitation. Neuroscience 2015, October 17-21, 2015, Chicago, USA.
    • Daisuke Ichimura, Tadashi Yamazaki. Parameter tuning for stable bipedal walking of a neuromusculoskeletal model by genetic algorithms. Annual Meeting of Society for Neuroscience (Neuroscience) 2016, November 12-16, San Diego, USA.
    • Daisuke Ichimura, Tadashi Yamazaki. Computer simulation of a pathological walk using a small humanoid robot. 27th Annual Conference of Japanese Neural Network Society (JNNS2017), Sep 20-22, 2017, Kitakyushu International Conference Center.
    • Daisuke Ichimura, Tadashi Yamazaki. Simulation Study of Bipedal Locomotion using Motor Modules.The 28th Annual Conference of the Japanese Neural Network Society (JNNS2018), October 24-27, 2018, OIST, Okinawa.
    • Daisuke Ichimura, Tadashi Yamazaki. Simulation study of bipedal walking based on motor modules of synergistic muscle activations. The 48th Annual Meeting of Society for Neuroscience (Neuroscience2018) , November 3-7, 2018, San Diego, USA.
    • Daisuke Ichimura, Tadashi Yamazaki. Neuromusculoskeletal model for bipedal locomotion under a pathological condition. Computational Neuroscience (CNS*2019), July 13-17, 2019, Barcelona, Spain.
    • Daisuke Ichimura, Tadashi Yamazaki. Simulation of bipedal locomotion in normal and pathological conditions. 29th Annual Conference of Japanese Neural Network Society. September 3–6, 2019, Tokyo Tech.
    • Yui ICHIKAWA, Daisuke ICHIMURA, Rie ASADA, Tadashi YAMAZAKI. Classification of caretakers’ trajectory: A time-series classifier approach. IEICE Technical Report NC2019-78(2020-03), Technical Committee on Neurocomputing, March 5, 2020, Tokyo (the meeting was cancelled)
  • Hideyuki Yoshimura (M2)
    • Ph.D. Student of Okinawa Institute of Science and Technology Graduate School, JP since April 2020
    • Hideyuki Yoshimura, Hiroki Kurashige, Tadashi Yamazaki. Real-time Reinforcement Learning Using a Spiking Neuron Network Model of Basal Ganglia. 2018 GPU Technology Conference (GTC), March 26-29, 2018, San Jose, California.
    • Hideyuki Yoshimura, Tadashi Yamazaki. Online reinforcement learning by a spiking network model of the basal ganglia. NICE (Neuro-Inspired Computational Elements) 2019 Workshop. March 26–28, 2019, Albany, NY.
    • Hideyuki Yoshimura, Tadashi Yamazaki. Developing a spiking neuron network model of the basal ganglia performing reinforcement learning. Computational Neuroscience (CNS*2019), July 13-17, 2019, Barcelona, Spain.
    • Hideyuki Yoshimura, Tadashi Yamazaki. Purely spike-based implementation of temporal difference error and state-value function in reinforcement learning. 29th Annual Conference of Japanese Neural Network Society. September 3–6, 2019, Tokyo Tech.
  • Taro Sunagawa (M2)
    • Internship at Dwango AI Lab (October 2018 – March 2019)
    • Selected as a student in Nengo Summer School (Jun 9-21, 2019 at Ontario, Canada)
    • Taro Sunagawa, Tadashi Yamazaki. Integration of a reinforcement learning module in REACH model for adaptive arm control. Computational Neuroscience (CNS*2019), July 13-17, 2019, Barcelona, Spain.
    • Taro Sunagawa, Kosuke Miyoshi, Hiroshi Yamakawa, Tadashi Yamazaki. Extention of REACH model with an actor-critic model and its application to adaptive arm control. 29th Annual Conference of Japanese Neural Network Society. September 3–6, 2019, Tokyo Tech.
  • Rie Asada, Technical Staff
    • Yui ICHIKAWA, Daisuke ICHIMURA, Rie ASADA, Tadashi YAMAZAKI. Classification of caretakers’ trajectory: A time-series classifier approach. IEICE Technical Report NC2019-78(2020-03), Technical Committee on Neurocomputing, March 5, 2020, Tokyo (the meeting was cancelled)
  • Yui Ichikawa, Technical Staff
    • Yui ICHIKAWA, Daisuke ICHIMURA, Rie ASADA, Tadashi YAMAZAKI. Classification of caretakers’ trajectory: A time-series classifier approach. IEICE Technical Report NC2019-78(2020-03), Technical Committee on Neurocomputing, March 5, 2020, Tokyo (the meeting was cancelled)

FY2018

  • Hiroki Kurashige, Research Scientist (Tenure-track lecturer of Tokai University since November 2018)
  • Wataru Furusho (M2)
    • Received FY2018 Meguro Award
    • Wataru Furusho, Tadashi Yamazaki. Implementation of Learning Mechanisms on a Cat-scale Cerebellar Model and its Simulation. 26th International Conference on Artificial Neural Networks (ICANN) 2017. 2017年9月11-14日, Sardinia, Italy.
    • Wataru Furusho, Tadashi Yamazaki. Speeding up the cat-scale artificial cerebellum for online learning. 27th Annual Conference of Japanese Neural Network Society (JNNS2017), Sep 20-22, 2017, Kitakyushu International Conference Center.
    • Wataru Furusho, Tadashi Yamazaki. Development of a Monkey-Scale Artificial Cerebellum with Online Learning Capability and its simulation on Supercomputer Gyoukou. The 28th Annual Conference of the Japanese Neural Network Society (JNNS2018), October 24-27, 2018, OIST, Okinawa.
    • Wataru Furusho, Tadashi Yamazaki. Development of large-scale artificial cerebellum and its petaflops simulation on PEZY-SC2 processor. The 48th Annual Meeting of Society for Neuroscience (Neuroscience2018) , November 3-7, 2018, San Diego, USA.

FY2017

  • Tsukasa Tsuyuki (M2)
    • Received FY2015 Meguro Award
    • 2017 Kobe HPC Spring School student
    • 2016 Kobe HPC Summer School student
    • Tsukasa Tsuyuki, Yuki Yamamoto, Tadashi Yamazaki. Computer simulation of neuron models with spatial structure on graphics processing units. Advances in Neuroinformatics 2016, May 28–29, 2016, RIKEN.
    • Tsukasa Tsuyuki, Yuki Yamamoto, Tadashi Yamazaki. Efficient numerical simulation of neuron models with spatial structure on graphics processing units. Neuroinformatics 2016, September 3-4, 2016, Reading, UK.
    • Tsukasa Tsuyuki, Yuki Yamamoto, Tadashi Yamazaki. Efficient numerical simulation of neuron models with spatial structure on graphics processing units. A. Hirose et al. (Eds.): ICONIP 2016, Part IV, LNCS 9950, pp. 279–285, 2016. DOI: 10.1007/978-3-319-46681-1 34
    • Tsukasa Tsuyuki, Yuki Yamamoto, Tadashi Yamazaki. Multi compartment model simulation of cerebellar granule layer. 27th Annual Conference of Japanese Neural Network Society (JNNS2017), Sep 20-22, 2017, Kitakyushu International Conference Center.

FY2016

  • Ohki Katakura (M2)
    • Ph.D. Student of University of Hertfordshire, UK since October 2018
    • Received FY2016 Student Award
    • Received FY2014 Meguro Award
    • Accepted as a student in 2014 JNNS Autumn Schoool for Computational Neuroscience (ASCONE)
    • Ohki Katakura, Tadashi Yamazaki. Feedback signals improve robustness of the representation of time (Oral presentation). 24th Annual Conference of Japanese Neural Network Society (JNNS2014), Aug 27-29, 2014, Future University Hakodate, Hokkaido.
    • Ohki Katakura, Tadashi Yamazaki. A theoretical model for robust representation of the passage of time by feedback signals. Neuroscience 2015, October 17-21, 2015, Chicago, USA.
    • Ohki Katakura, Tadashi Yamazaki. Computational model of the cerebellum and the basal ganglia for interval timing learning. A. Hirose et al. (Eds.): ICONIP 2016, Part IV, LNCS 9950, pp. 244–251, 2016. DOI: 10.1007/978-3-319-46681-1 30
    • Ohki Katakura, Tadashi Yamazaki. A unified model of the cerebellum and the basal ganglia for temporal information processing. Annual Meeting of Society for Neuroscience (Neuroscience) 2016, November 12-16, San Diego, USA.

FY2015

FY2014

  • Shusei Yasumuro (B4)

FY2013