Shigeru Shinomoto, Ph.D.
Affiliations: | Kyoto University, Kyōto-shi, Kyōto-fu, Japan |
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Publications
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| Endo D, Kobayashi R, Bartolo R, et al. (2021) A convolutional neural network for estimating synaptic connectivity from spike trains. Scientific Reports. 11: 12087 |
| Kobayashi R, Kurita S, Kurth A, et al. (2019) Reconstructing neuronal circuitry from parallel spike trains. Nature Communications. 10: 4468 |
| Kass RE, Amari SI, Arai K, et al. (2018) Computational Neuroscience: Mathematical and Statistical Perspectives. Annual Review of Statistics and Its Application. 5: 183-214 |
| Fujita K, Medvedev A, Koyama S, et al. (2018) Identifying exogenous and endogenous activity in social media Physical Review E. 98 |
| Onaga T, Shinomoto S. (2016) Emergence of event cascades in inhomogeneous networks. Scientific Reports. 6: 33321 |
| Mochizuki Y, Onaga T, Shimazaki H, et al. (2016) Similarity in Neuronal Firing Regimes across Mammalian Species. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 36: 5736-47 |
| Kostal L, Shinomoto S. (2016) Efficient information transfer by Poisson neurons. Mathematical Biosciences and Engineering : Mbe. 13: 509-20 |
| Yamanaka Y, Amari S, Shinomoto S. (2015) Microscopic instability in recurrent neural networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 91: 032921 |
| Mochizuki Y, Shinomoto S. (2014) Analog and digital codes in the brain. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 89: 022705 |
| Kim H, Shinomoto S. (2014) Estimating nonstationary inputs from a single spike train based on a neuron model with adaptation. Mathematical Biosciences and Engineering : Mbe. 11: 49-62 |