Using humanoid robots to study human behavior

Our understanding of human behavior advances as our humanoid robotics work progresses-and vice versa. This team's work focuses on trajectory formation and planning, learning from demonstration, oculomotor control and interactive behaviors. They are programming robotic behavior based on how we humans “program” behavior in-or train-each other

Changes in the Japanese Currency System due to the Interactions in East Asia from the 15th to the 17th Centuries

第3回AAWH （アジア世界史学会）報告集 : シンガポール・南洋理工大学2015年5月29～31日Project leader : Professor MOMOKI Shiro Graduate School of Letters, Osaka UniversityMigration, Trade and Exchange around the Peripheral East Asia研究者・教員・市民のための新しい歴史学入門（平成26-29年度科学研究費補助金・基盤研究（A）・課題番号26244034)研究代表者 桃木至朗（大阪大学大学院文学研究科教授）JSPS Grant-in-Aid for Scientific Research (Scientific Research A : “ Creating new research guides to history for professional researchers, teachers and citizens ” Project No.26244034 for the fiscal years 2014-2017)Papers presented at the Third AA WH (Asian Association of World Historians) : Singapore: Nanyang Technological University, May 29-31, 201

Minimal distance transformations between links and polymers: Principles and examples

The calculation of Euclidean distance between points is generalized to one-dimensional objects such as strings or polymers. Necessary and sufficient conditions for the minimal transformation between two polymer configurations are derived. Transformations consist of piecewise rotations and translations subject to Weierstrass-Erdmann corner conditions. Numerous examples are given for the special cases of one and two links. The transition to a large number of links is investigated, where the distance converges to the polymer length times the mean root square distance (MRSD) between polymer configurations, assuming curvature and non-crossing constraints can be neglected. Applications of this metric to protein folding are investigated. Potential applications are also discussed for structural alignment problems such as pharmacophore identification, and inverse kinematic problems in motor learning and control.Comment: Submitted to J. Phys.:Condens. Matte

Functional MRI neurofeedback training on connectivity between two regions induces long-lasting changes in intrinsic functional network

Motor or perceptual learning is known to influence functional connectivity between brain regions and induce short-term changes in the intrinsic functional networks revealed as correlations in slow blood-oxygen-level dependent (BOLD) signal fluctuations. However, no cause-and-effect relationship has been elucidated between a specific change in connectivity and a long-term change in global networks. Here, we examine the hypothesis that functional connectivity (i.e., temporal correlation between two regions) is increased and preserved for a long time when two regions are simultaneously activated or deactivated. Using the connectivity-neurofeedback training paradigm, subjects successfully learned to increase the correlation of activity between the lateral parietal and primary motor areas, regions that belong to different intrinsic networks and negatively correlated before training under the resting conditions. Furthermore, whole-brain hypothesis-free analysis as well as functional network analyses demonstrated that the correlation in the resting state between these areas as well as the correlation between the intrinsic networks that include the areas increased for at least 2 months. These findings indicate that the connectivity-neurofeedback training can cause long-term changes in intrinsic connectivity and that intrinsic networks can be shaped by experience-driven modulation of regional correlation

Boosting perceptual learning by fake feedback

AbstractHow does the brain control its sensory plasticity using performance feedback? We examined this question using various types of fake feedback in perceptual learning paradigm. We demonstrated that fake feedback indicating a larger performance improvement facilitated learning compared with genuine feedback. Variance of the fake feedback modulated learning as well, suggesting that feedback uncertainty can be internally evaluated. These results were explained by a computational model which controlled the learning rate of the visual system based on Bayesian estimation of performance gradient incorporating an optimistic bias. Our findings suggest that sensory plasticity might be controlled by high-level cognitive processes