| A small number of abnormal brain connections predicts adult autism spectrum disorder N Yahata, J Morimoto, R Hashimoto, G Lisi, K Shibata, Y Kawakubo, ... Nature communications 7 (1), 11254, 2016 | 296 | 2016 |
| Functional MRI neurofeedback training on connectivity between two regions induces long-lasting changes in intrinsic functional network F Megumi, A Yamashita, M Kawato, H Imamizu Frontiers in Human Neuroscience 9, 160, 2015 | 148 | 2015 |
| Energy landscape and dynamics of brain activity during human bistable perception T Watanabe, N Masuda, F Megumi, R Kanai, G Rees Nature communications 5 (1), 4765, 2014 | 119 | 2014 |
| Brain activity dynamics in human parietal regions during spontaneous switches in bistable perception F Megumi, B Bahrami, R Kanai, G Rees NeuroImage 107, 190-197, 2015 | 66 | 2015 |
| Can we predict real‐time fMRI neurofeedback learning success from pretraining brain activity? A Haugg, R Sladky, S Skouras, A McDonald, C Craddock, M Kirschner, ... Human brain mapping 41 (14), 3839-3854, 2020 | 33 | 2020 |
| Brain activity training apparatus and brain activity training system M Kawato, J Morimoto, N Yahata, R Hashimoto, M Fukuda, K Shibata, ... US Patent App. 14/438,962, 2015 | 25 | 2015 |
| Predictors of real-time fMRI neurofeedback performance and improvement–a machine learning mega-analysis A Haugg, FM Renz, AA Nicholson, C Lor, SJ Götzendorfer, R Sladky, ... Neuroimage 237, 118207, 2021 | 23 | 2021 |
| Energy landscape and dynamics of brain activity during human bistable perception. Nat. Commun. 5, 4765 T Watanabe, N Masuda, F Megumi, R Kanai, G Rees | 5 | 2014 |
| Determinants of Real-Time fMRI Neurofeedback Performance and Improvement–a Machine Learning Mega-Analysis A Haugg, FM Renz, AA Nicholson, C Lor, SJ Götzendorfer, R Sladky, ... bioRxiv, 2020.10. 21.349118, 2020 | 2 | 2020 |
Mitsuo KawatoATRBestätigte E-Mail-Adresse bei atr.jp
