Jun Tani

Photo of Jun Tani
Jun Tani
Dr. Eng. (Sophia University Tokyo)
MSc (University of Michigan, Ann Arbor, USA)
BSc (Waseda University, Tokyo)
tani1216jp at gmail.com



  • Sony Computer Science Laboratories Inc., Tokyo, Japan
  • Riken Brain Science Institute, Saitama, Japan
  • Korean Advanced Institute of Science and Technology (KAIST), Daejeon, Korea


Selected Publications


Journal Articles

  • Choi, M., & Tani, J. (2017). Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model. accepted in Neural Computation.
  • Murata, S., Yamashita, Y., Arie, H., Ogata, T., Sugano, S., & Tani, J. (2015). Learning to perceive the world as probabilistic or deterministic via interaction with others: a neuro-robotics experiment. IEEE Transactions on Neural Networks and Learning Systems, (4), 830-848. DOI: 10.1109/TNNLS.2015.2492140
  • Tani, J. (2014). Self-Organization and Compositionality in Cognitive Brains: A Neuro-Robotics Study. Proceedings of the IEEE, Special Issue on Cognitive Dynamic Systems, 102(4), 586-605.
  • Namikawa, J., Nishimoto, R., & Tani, J.(2011). A neurodynamic account of spontaneous behaviour”, PLoS Computational Biology, Vol. 7, Issue 10, e1002221.
  • Yamashita, Y., & Tani, J. (2008). Emergence of functional hierarchy in a multiple timescale neural network model: a humanoid robot experiment. PLoS Computational Biology, Vol.4, Issue.11, e1000220.
  • Sugita, Y., & Tani, J. (2005). Learning semantic combinatoriality from the interaction between linguistic and behavioral processes. Adaptive Behavior, 13(1), 33-52.
  • Tani, J., Ito, M., & Sugita, Y. (2004). Self-organization of distributedly represented multiple behavior schemata in a mirror system: Reviews of robot experiments using RNNPB. Neural Networks, 17, 1273-1289.
  • Tani, J., & Nolfi, S. (1999). Learning to perceive the world as articulated: an approach for hierarchical learning in sensory-motor systems. Neural Networks, 12, 1131-1141.
  • Tani, J. (1998). An interpretation of the ‘Self’ from the dynamical systems perspective: a constructivist approach. Journal of Consciousness Studies, 5(5/6), 516-542.
  • Tani, J. (1996). Model-based learning for mobile robot navigation from the dynamical systems perspective. IEEE Trans. on Syst. Man and Cybern. Part B-Cybernetics, 26(3), 421-436.
  • Tani, J., & Fukumura, N. (1995). Embedding a grammatical description in deterministic chaos: an experiment in recurrent neural learning. Biological Cybernetics, 72, 365-370.

Lecture video: https://www.youtube.com/watch?v=lKIZdP5WnlE

Recent Lectures

  • Tani, J. A Proposal of a Novel Variational Bayes Recurrent Neural Network Model Under Predictive Coding and Active Inference Frameworks. Consciousness Club Tokyo, Tokyo, Japan, February 7 (2020). Video
  • Tani, J. Cognitive Neurorobotics Study Using Frameworks of Predictive Coding and Active Inference. BMW Group, Munich, Germany, December 18 (2019).
  • Tani, J. Actions, Symbols and Selves as Self-Organizing Dynamic Phenomena: a View from Neurorobotics study. CHAIN INTERNATIONAL SYMPOSIUM Adventures in Consciousness Science: Exploring the Crossover between Philosophy, Neuroscience, AI, and Robotics, Sapporo, Japan, November 10 (2019).
  • Tani, J. An account of the development of cognitive minds using predictive coding and active inference frameworks. ATR Brain Information Communication Research Laboratory Group Symposium, Kyoto, Japan, October 30 (2019).
  • Tani, J. Accounting social cognitive mechanisms by the framework of predictive coding and active inference: a synthetic experimental study using robotics interaction platforms. Keynote speech, 7th International Conference on Human-Agent Interaction (HAI2019), Kyoto, Japan, October 8 (2019).
  • Tani, J. Emergence in Neurorobotics Experimental Studies. Riken Robotics Retreat, Kyoto, Japan, September 13 (2019).
  • Tani, J. ロボット構成論的アプローチで考える身体的自己と物語的自己について, 第19回Kフォーラム, Takayama, Japan, August 22-24 (2019).
  • Tani, J. How can compositionality develop through self-exploration and supervised tutoring? Fourth International Workshop on Intrinsically-Motivated Open-ended Learning (IMOL2019), Frankfurt, Germany, July 1-3 (2019).
  • Tani, J. Generating goal-directed planning images using frameworks of predictive coding and active inference: Agency and object constancy. NII Shonam Meeting, Language as Goal-Directed Sequential Behavior: Computational Theories, Brain Mechanisms, Evolutionary Roots, Shonan, Japan, May 21 (2019).
  • Tani, J. Accounts of the development of embodied cognition using predictive coding and active inference frameworks. Marcus Wallenberg International Symposium on Affective and Developmental Processes in Cognitive and Autonomous Systems - Augmenting Deep Learning using Neural Dynamics and Predictive Coding, Gothenburg, Sweden, May 6 (2019).