Taro Toyoizumi

Affiliations: 
RIKEN Brain Science Institute, Wakō-shi, Saitama-ken, Japan 
Area:
Computational Neuroscience
Google:
"Taro Toyoizumi"
Mean distance: 13.31 (cluster 17)
 
SNBCP
Cross-listing: Computational Biology Tree

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Publications

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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
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
Sharpee TO, Destexhe A, Kawato M, et al. (2016) 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54
Tajima S, Yanagawa T, Fujii N, et al. (2015) Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. Plos Computational Biology. 11: e1004537
Toyoizumi T, Kaneko M, Stryker MP, et al. (2014) Modeling the dynamic interaction of Hebbian and homeostatic plasticity. Neuron. 84: 497-510
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