Motor learning and control based on the internal model. - Koji Ito; Jun Izawa; Toshiyuki Kondo (CDC, 2001)

Biological Robot Arm Motion through Reinforcement Learning. - Jun Izawa; Toshiyuki Kondo; Koji Ito (ICRA, 2002)

Motor learning model using reinforcement learning with neural internal model. - Jun Izawa; Toshiyuki Kondo; Koji Ito (ICRA, 2003)

Biological arm motion through reinforcement learning. - Jun Izawa; Toshiyuki Kondo; Koji Ito (Biol. Cybern., 2004)

MR Compatible Manipulandum with Ultrasonic Motor for fMRI Studies. - Jun Izawa; Takahiro Shimizu; Toshiyuki Aodai; Toshiyuki Kondo; Hiroaki Gomi; Shigeki Toyama; Koji Ito (ICRA, 2006)

Learning from Sensory and Reward Prediction Errors during Motor Adaptation. - Jun Izawa; Reza Shadmehr (PLoS Comput. Biol., 2011)

Analysis of extrinsic and intrinsic factors affecting event related desynchronization production. - Yohei Takata; Toshiyuki Kondo; Midori Saeki; Jun Izawa; Kotaro Takeda; Yohei Otaka; Koji Ito (EMBC, 2012)

Temporal changes of beta rhythms and rotation-related negativity reflect switches in motor imagery. - Hiroshi Yokoyama; Isao Nambu; Jun Izawa; Yasuhiro Wada (EMBC, 2014)

Modeling method in embodied-brain systems science. - Jun Ota 001; Hajime Asama; Toshiyuki Kondo; Hirokazu Tanaka; Shiro Yano; Jun Izawa; Shinya Aoi; Ryosuke Chiba (MHS, 2015)

A computational approach to detect a mete-learning of the cortical basis function during a motor adaptation study. - Daichi Sasaki; Jun Izawa; Masahiko Morita (MHS, 2015)

Robustness of Selective Desensitization Perceptron Against Irrelevant and Partially Relevant Features in Pattern Classification. - Tomohiro Tanno; Kazumasa Horie; Jun Izawa; Masahiko Morita (ICONIP (6), 2017)

Application of computational neuroscience to robotic rehabilitation: a conceptual study. - Jun Izawa (MHS, 2018)

Learning to control the other's body facilitates the embodied perspective taking. - Ryota Ishikawa; Kyohei Sasaki; Saho Ayabe-Kanamura; Jun Izawa (CogSci, 2019)

The Regret Motivated Reinforcement Learning. - Yihao Wu; Jun Izawa (MHS, 2021)

A small-scale robotic manipulandum for motor control study with rodents. - Takahisa Inoue; Shin Terada; Masanori Matsuzaki; Jun Izawa (Adv. Robotics, 2021)

Task-relevant and task-irrelevant variability causally shape error-based motor learning. - Lucas Rebelo Dal'Bello; Jun Izawa (Neural Networks, 2021)

Computational role of exploration noise in error-based de novo motor learning. - Lucas Rebelo Dal'Bello; Jun Izawa (Neural Networks, 2022)

Reward prediction errors, not sensory prediction errors, play a major role in model selection in human reinforcement learning. - Yihao Wu; Masahiko Morita; Jun Izawa (Neural Networks, 2022)

Study on High-Level Structure of cognition control construction in Exploration and Exploitation within Multi-Armed Bandit Model of Reinforcement Learning. - Jiaxing Tian; Jun Izawa (MHS, 2023)