Taro Toyoizumi
Affiliations: | RIKEN Brain Science Institute, Wakō-shi, Saitama-ken, Japan |
Area:
Computational NeuroscienceGoogle:
"Taro Toyoizumi"Mean distance: 13.31 (cluster 17) | S | N | B | C | P |
Cross-listing: Computational Biology Tree
Parents
Sign in to add mentor| Shun-ichi Amari | grad student | RIKEN BSI | |
| Wulfram Gerstner | grad student | RIKEN BSI | |
| Larry F. Abbott | post-doc | RIKEN BSI | |
| Kenneth D. Miller | post-doc | RIKEN BSI |
Children
Sign in to add trainee| Satohiro Tajima | post-doc | RIKEN BSI | |
| Yu Terada | post-doc | RIKEN Center for Brain Science | |
| Sakyasingha Dasgupta | post-doc | 2015- | RIKEN BSI |
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Publications
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| Terada Y, Toyoizumi T. (2024) Chaotic neural dynamics facilitate probabilistic computations through sampling. Proceedings of the National Academy of Sciences of the United States of America. 121: e2312992121 |
| Shimizu G, Yoshida K, Kasai H, et al. (2021) Computational roles of intrinsic synaptic dynamics. Current Opinion in Neurobiology. 70: 34-42 |
| Kuśmierz Ł, Ogawa S, Toyoizumi T. (2020) Edge of Chaos and Avalanches in Neural Networks with Heavy-Tailed Synaptic Weight Distribution. Physical Review Letters. 125: 028101 |
| Humble J, Hiratsuka K, Kasai H, et al. (2019) Intrinsic Spine Dynamics Are Critical for Recurrent Network Learning in Models With and Without Autism Spectrum Disorder. Frontiers in Computational Neuroscience. 13: 38 |
| Buckley CL, Toyoizumi T. (2018) A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback. Plos Computational Biology. 14: e1005926 |
| Kuśmierz Ł, Isomura T, Toyoizumi T. (2017) Learning with three factors: modulating Hebbian plasticity with errors. Current Opinion in Neurobiology. 46: 170-177 |
| Tajima S, Mita T, Bakkum DJ, et al. (2017) Locally embedded presages of global network bursts. Proceedings of the National Academy of Sciences of the United States of America |
| Keck T, Toyoizumi T, Chen L, et al. (2017) Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 372 |
| Newton AJH, Seidenstein AH, McDougal RA, et al. (2017) 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Bmc Neuroscience. 18 |
| Lankarany M, Heiss JE, Lampl I, et al. (2016) Simultaneous Bayesian Estimation of Excitatory and Inhibitory Synaptic Conductances by Exploiting Multiple Recorded Trials. Frontiers in Computational Neuroscience. 10: 110 |