A method for selecting the bin size of a time histogram H Shimazaki, S Shinomoto Neural computation 19 (6), 1503-1527, 2007 | 647 | 2007 |
Kernel bandwidth optimization in spike rate estimation H Shimazaki, S Shinomoto Journal of computational neuroscience 29, 171-182, 2010 | 427 | 2010 |
Phase transitions in active rotator systems S Shinomoto, Y Kuramoto Progress of Theoretical Physics 75 (5), 1105-1110, 1986 | 307 | 1986 |
Local and grobal self-entrainments in oscillator lattices H Sakaguchi, S Shinomoto, Y Kuramoto Progress of Theoretical Physics 77 (5), 1005-1010, 1987 | 281 | 1987 |
Differences in spiking patterns among cortical neurons S Shinomoto, K Shima, J Tanji Neural computation 15 (12), 2823-2842, 2003 | 259 | 2003 |
Relating neuronal firing patterns to functional differentiation of cerebral cortex S Shinomoto, H Kim, T Shimokawa, N Matsuno, S Funahashi, K Shima, ... PLoS computational biology 5 (7), e1000433, 2009 | 258 | 2009 |
Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold R Kobayashi, Y Tsubo, S Shinomoto Frontiers in computational neuroscience 3, 762, 2009 | 231 | 2009 |
Four types of learning curves S Amari, N Fujita, S Shinomoto Neural Computation 4 (4), 605-618, 1992 | 214 | 1992 |
A benchmark test for a quantitative assessment of simple neuron models R Jolivet, R Kobayashi, A Rauch, R Naud, S Shinomoto, W Gerstner Journal of neuroscience methods 169 (2), 417-424, 2008 | 188 | 2008 |
The Ornstein-Uhlenbeck process does not reproduce spiking statistics of neurons in prefrontal cortex S Shinomoto, Y Sakai, S Funahashi Neural Computation 11 (4), 935-951, 1999 | 150 | 1999 |
Mutual entrainment in oscillator lattices with nonvariational type interaction H Sakaguchi, S Shinomoto, Y Kuramoto Progress of theoretical physics 79 (5), 1069-1079, 1988 | 142 | 1988 |
Phase transitions and their bifurcation analysis in a large population of active rotators with mean-field coupling H Sakaguchi, S Shinomoto, Y Kuramoto Progress of Theoretical Physics 79 (3), 600-607, 1988 | 107 | 1988 |
MST neurons code for visual motion in space independent of pursuit eye movements N Inaba, S Shinomoto, S Yamane, A Takemura, K Kawano Journal of neurophysiology 97 (5), 3473-3483, 2007 | 104 | 2007 |
A measure of local variation of inter-spike intervals S Shinomoto, K Miura, S Koyama Biosystems 79 (1-3), 67-72, 2005 | 91 | 2005 |
Temporally correlated inputs to leaky integrate-and-fire models can reproduce spiking statistics of cortical neurons Y Sakai, S Funahashi, S Shinomoto Neural Networks 12 (7-8), 1181-1190, 1999 | 91 | 1999 |
Similarity in neuronal firing regimes across mammalian species Y Mochizuki, T Onaga, H Shimazaki, T Shimokawa, Y Tsubo, R Kimura, ... Journal of Neuroscience 36 (21), 5736-5747, 2016 | 89 | 2016 |
Reconstructing neuronal circuitry from parallel spike trains R Kobayashi, S Kurita, A Kurth, K Kitano, K Mizuseki, M Diesmann, ... Nature communications 10 (1), 4468, 2019 | 86 | 2019 |
Estimating instantaneous irregularity of neuronal firing T Shimokawa, S Shinomoto Neural computation 21 (7), 1931-1951, 2009 | 85 | 2009 |
A cognitive and associative memory S Shinomoto Biological Cybernetics 57 (3), 197-206, 1987 | 82 | 1987 |
Computational neuroscience: Mathematical and statistical perspectives RE Kass, SI Amari, K Arai, EN Brown, CO Diekman, M Diesmann, ... Annual review of statistics and its application 5, 183-214, 2018 | 80 | 2018 |