|Testing computational models of learning from social, real, and fictive feedback in human and nonhuman primates
||Associate Professor, School of Medicine, Kansai Medical University
This project effectively combines computational and experimental approaches in order to gain insight into neural mechanisms of learning from real, fictive, and social feedback. The Japanese side will test the neurobiological plausibility of computational models on the basis of behavioral and electrophysiological data in nonhuman primates, while the German side will test it on the basis of behavioral, electroencephalographic, and functional neuroimaging data in humans. The use of complementary methods in two primate species will lead to a better generalizability of the models and to a deeper understanding of neural mechanisms for learning and decision-making.
||Professor, Faculty of Natural Sciences, Otto-von-Guericke Universität Magdeburg
|Decoding of in vivo two-photon imaging data in mouse motor cortex
||Head, Computational Neuroscience Laboratories, Advanced Telecommunications Research Institute International
This project aims to revel the computational principle of local neural circuits that prepare and generate motor behavior. The Japanese group performs data analysis using machine-learning models, and the German group conducts two-photon calcium imaging of the mouse motor cortex. This collaboration combining cellular-level neural imaging and computational modeling will lead to a quantitative understanding of local neural circuits for motor behavior.
||Junior group leader, Center for Integrative Neuroscience, University of Tübingen
|The development of the functional organization in visual cortex
||Professor, Department of Molecular Physiology, Graduate School of Medical Sciences, Kyushu University
In this study, we aim to identify candidate mechanisms of cortical reorganization from a quantitative comparison between model and experiment. The Japanese group will perform two-photon calcium imaging of large populations of neurons in the developing mouse visual cortex to study how the functional organization changes during normal development. The German group will develop a computational circuit model. Through complementary efforts, we expect to identify candidate mechanisms of cortical reorganization during development.
||Fellow, Frankfurt Institute for Advanced Studies and Professor, Department of Computer Science and Mathematics, Goethe University
|Autonomous learning of active depth perception: from neural models to humanoid robots
||Assistant Professor, School of Information Science, Japan Advanced Institute of Science and Technology
The main aim of our collaborative research aims to develop a neurally plausible model of the development of binocular depth perception in human infants and other mammals and use it to model normal and abnormal visual development in various binocular vision pathologies or under unnatural rearing conditions and design a new active perception model for robotics by endowing robots with an autonomously learning and fully self-calibrating binocular vision system. To synthesize the development model of binocular depth perception in human infants, the Japanese team will design the model from an engineering perspective and use it to implement on a humanoid robot, while the German team will investigate the model from a neurophysiological and biological perspective. It is expected that this may ultimately inspire new forms of autonomous learning and self-calibration for robots and clinical intervention.
||Professor, Neuroscience Department, Frankfurt Institute for Advanced Studies