| Prospective errors determine motor learning K Takiyama, M Hirashima, D Nozaki Nature communications 6 (1), 5925, 2015 | 73 | 2015 |
| Recovery in stroke rehabilitation through the rotation of preferred directions induced by bimanual movements: a computational study K Takiyama, M Okada PLoS One 7 (5), e37594, 2012 | 25 | 2012 |
| Decomposing motion that changes over time into task-relevant and task-irrelevant components in a data-driven manner: application to motor adaptation in whole-body movements D Furuki, K Takiyama Scientific Reports 9 (1), 7246, 2019 | 23 | 2019 |
| Maximization of learning speed in the motor cortex due to neuronal redundancy K Takiyama, M Okada PLoS computational biology 8 (1), e1002348, 2012 | 23 | 2012 |
| Context-dependent memory decay is evidence of effort minimization in motor learning: a computational study K Takiyama Frontiers in Computational Neuroscience 9, 4, 2015 | 21 | 2015 |
| Speed-dependent and mode-dependent modulations of spatiotemporal modules in human locomotion extracted via tensor decomposition K Takiyama, H Yokoyama, N Kaneko, K Nakazawa Scientific reports 10 (1), 680, 2020 | 19 | 2020 |
| Development of a portable motor learning laboratory (PoMLab) K Takiyama, M Shinya PLoS One 11 (6), e0157588, 2016 | 16 | 2016 |
| Balanced motor primitive can explain generalization of motor learning effects between unimanual and bimanual movements K Takiyama, Y Sakai Scientific Reports 6 (1), 23331, 2016 | 16 | 2016 |
| Statistical method for detecting phase shifts in alpha rhythm from human electroencephalogram data Y Naruse, K Takiyama, M Okada, H Umehara Physical Review E 87 (4), 042708, 2013 | 16 | 2013 |
| Detection of hidden structures in nonstationary spike trains K Takiyama, M Okada Neural computation 23 (5), 1205-1233, 2011 | 16 | 2011 |
| Exact inference in discontinuous firing rate estimation using belief propagation K Takiyama, K Katahira, M Okada Journal of the Physical Society of Japan 78 (6), 064003, 2009 | 16 | 2009 |
| Inference in alpha rhythm phase and amplitude modeled on Markov random field using belief propagation from electroencephalograms Y Naruse, K Takiyama, M Okada, T Murata Physical review E 82 (1), 011912, 2010 | 15 | 2010 |
| Optimizing motor decision-making through competition with opponents K Ota, M Tanae, K Ishii, K Takiyama Scientific reports 10 (1), 950, 2020 | 14 | 2020 |
| Influence of switching rule on motor learning K Ishii, T Hayashi, K Takiyama Scientific Reports 8 (1), 13559, 2018 | 11 | 2018 |
| Detecting the relevance to performance of whole-body movements D Furuki, K Takiyama Scientific Reports 7 (1), 15659, 2017 | 11 | 2017 |
| A data-driven approach to decompose motion data into task-relevant and task-irrelevant components in categorical outcome D Furuki, K Takiyama Scientific Reports 10 (1), 2422, 2020 | 9 | 2020 |
| Speed-and mode-dependent modulation of the center of mass trajectory in human gaits as revealed by Lissajous curves K Takiyama, H Yokoyama, N Kaneko, K Nakazawa Journal of biomechanics 110, 109947, 2020 | 8 | 2020 |
| Sensorimotor transformation via sparse coding K Takiyama Scientific Reports 5 (1), 9648, 2015 | 7 | 2015 |
| Effort-dependent effects on uniform and diverse muscle activity features in skilled pitching T Hashimoto, K Takiyama, T Miki, H Kobayashi, D Nasu, T Ijiri, M Kuwata, ... Scientific Reports 11 (1), 8211, 2021 | 5 | 2021 |
| Larger, but not better, motor adaptation ability inherent in medicated Parkinson’s disease patients revealed by a smart-device-based study K Takiyama, T Sakurada, M Shinya, T Sato, H Ogihara, T Komatsu Scientific Reports 10 (1), 7113, 2020 | 5 | 2020 |
