Shigeru Shinomoto
Shigeru Shinomoto
ATR Institute International
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Cited by
Cited by
A method for selecting the bin size of a time histogram
H Shimazaki, S Shinomoto
Neural computation 19 (6), 1503-1527, 2007
Kernel bandwidth optimization in spike rate estimation
H Shimazaki, S Shinomoto
Journal of computational neuroscience 29, 171-182, 2010
Phase transitions in active rotator systems
S Shinomoto, Y Kuramoto
Progress of Theoretical Physics 75 (5), 1105-1110, 1986
Local and grobal self-entrainments in oscillator lattices
H Sakaguchi, S Shinomoto, Y Kuramoto
Progress of Theoretical Physics 77 (5), 1005-1010, 1987
Differences in spiking patterns among cortical neurons
S Shinomoto, K Shima, J Tanji
Neural computation 15 (12), 2823-2842, 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
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
Four types of learning curves
S Amari, N Fujita, S Shinomoto
Neural Computation 4 (4), 605-618, 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
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
Mutual entrainment in oscillator lattices with nonvariational type interaction
H Sakaguchi, S Shinomoto, Y Kuramoto
Progress of theoretical physics 79 (5), 1069-1079, 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
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
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
A measure of local variation of inter-spike intervals
S Shinomoto, K Miura, S Koyama
Biosystems 79 (1-3), 67-72, 2005
Estimating instantaneous irregularity of neuronal firing
T Shimokawa, S Shinomoto
Neural computation 21 (7), 1931-1951, 2009
A cognitive and associative memory
S Shinomoto
Biological Cybernetics 57 (3), 197-206, 1987
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
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
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
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