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Plos One|June 28, 2016
Development of a Portable Motor Learning Laboratory (PoMLab)Ken Takiyama, Masahiro ShinyaJournal of Biomechanics|February 20, 2024
Guidelines for balancing the number of trials and the number of subjects to ensure the statistical power to detect variability - Implication for gait studiesMasahiro Shinya, Ken TakiyamaScientific Reports|April 30, 2020
Larger, but not better, motor adaptation ability inherent in medicated Parkinson's disease patients revealed by a smart-device-based studyKen Takiyama, Takeshi Sakurada, Masahiro Shinya, et al.Neural Networks : the Official Journal of the International Neural Network Society|June 3, 2017
Bayesian geodesic path for human motor controlKen TakiyamaFrontiers in Computational Neuroscience|February 21, 2015
Context-dependent memory decay is evidence of effort minimization in motor learning: a computational studyKen TakiyamaPhysical Review. E|June 15, 2016
Bayesian estimation inherent in a Mexican-hat-type neural networkKen TakiyamaNeural Computation|February 9, 2011
Detection of hidden structures in nonstationary spike trainsKen Takiyama, Masato OkadaScientific Reports|February 14, 2020
A data-driven approach to decompose motion data into task-relevant and task-irrelevant components in categorical outcomeDaisuke Furuki, Ken TakiyamaFrontiers in Sports and Active Living|January 19, 2024
Speed-dependent modulations of asymmetric center of body mass trajectory in the gait of above-knee amputee subjectsKen Takiyama, Hikaru YokoyamaPageof 9