Shigeru Shinomoto

Shinsuke Koyama, Takahiro Omi, Robert E. Kass, Shigeru Shinomoto: Information Transmission Using Non-Poisson Regular Firing. Neural Computation 25(4): 854-876 (2013)

Hideaki Kim, Barry J. Richmond, Shigeru Shinomoto: Neurons as ideal change-point detectors. Journal of Computational Neuroscience 32(1): 137-146 (2012)

Ryota Kobayashi, Shigeru Shinomoto, Petr Lánský: Estimation of Time-Dependent Input from Neuronal Membrane Potential. Neural Computation 23(12): 3070-3093 (2011)

Takahiro Omi, Shigeru Shinomoto: Optimizing Time Histograms for Non-Poissonian Spike Trains. Neural Computation 23(12): 3125-3144 (2011)

Ryota Kobayashi, Yasuhiro Tsubo, Petr Lánský, Shigeru Shinomoto: Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron. NIPS 2011: 217-225

Hideaki Shimazaki, Shigeru Shinomoto: Kernel bandwidth optimization in spike rate estimation. Journal of Computational Neuroscience 29(1-2): 171-182 (2010)

Takeaki Shimokawa, Shinsuke Koyama, Shigeru Shinomoto: A characterization of the time-rescaled gamma process as a model for spike trains. Journal of Computational Neuroscience 29(1-2): 183-191 (2010)

Shigeru Shinomoto: Fitting a stochastic spiking model to neuronal current injection data. Neural Networks 23(6): 764-769 (2010)

Takeaki Shimokawa, Shigeru Shinomoto: Estimating Instantaneous Irregularity of Neuronal Firing. Neural Computation 21(7): 1931-1951 (2009)

Shigeru Shinomoto, Hideaki Kim, Takeaki Shimokawa, Nanae Matsuno, Shintaro Funahashi, Keisetsu Shima, Ichiro Fujita, Hiroshi Tamura, Taijiro Doi, Kenji Kawano, Naoko Inaba, Kikuro Fukushima, Sergei Kurkin, Kiyoshi Kurata, Masato Taira, Ken-Ichiro Tsutsui, Hidehiko Komatsu, Tadashi Ogawa, Kowa Koida, Jun Tanji, Keisuke Toyama: Relating Neuronal Firing Patterns to Functional Differentiation of Cerebral Cortex. PLoS Computational Biology 5(7) (2009)

Shinsuke Koyama, Shigeru Shinomoto: Inference of intrinsic spiking irregularity based on the Kullback-Leibler information. Biosystems 89(1-3): 69-73 (2007)

Hideaki Shimazaki, Shigeru Shinomoto: A Method for Selecting the Bin Size of a Time Histogram. Neural Computation 19(6): 1503-1527 (2007)

Ryota Kobayashi, Shigeru Shinomoto: Predicting spike times from subthreshold dynamics of a neuron. NIPS 2006: 721-728

Hideaki Shimazaki, Shigeru Shinomoto: A recipe for optimizing a time-histogram. NIPS 2006: 1289-1296

Yasuhiro Tsubo, Takeshi Kaneko, Shigeru Shinomoto: Predicting spike timings of current-injected neurons. Neural Networks 17(2): 165-173 (2004)

Shigeru Shinomoto, Keisetsu Shima, Jun Tanji: Differences in Spiking Patterns Among Cortical Neurons. Neural Computation 15(12): 2823-2842 (2003)

Shigeru Shinomoto, Keisetsu Shima, Jun Tanji: New classification scheme of cortical sites with the neuronal spiking characteristics. Neural Networks 15(10): 1165-1169 (2002)

Shigeru Shinomoto, Yutaka Sakai, Shintaro Funahashi: The Ornstein-Uhlenbeck Process Does Not Reproduce Spiking Statistics of Neurons in Prefrontal Cortex. Neural Computation 11(4): 935-951 (1999)

Yutaka Sakai, Shintaro Funahashi, Shigeru Shinomoto: Temporally correlated inputs to leaky integrate-and-fire models can reproduce spiking statistics of cortical neurons. Neural Networks 12(7-8): 1181-1190 (1999)

Shigeru Shinomoto, Yutaka Sakai: Inter-spike Interval Statistics of Cortical Neurons. IWANN (1) 1999: 171-179

Yoshiyuki Kabashima, Shigeru Shinomoto: Acceleration of Learning in Binary Choice Problems. COLT 1993: 446-452

Shun-ichi Amari, Naotake Fujita, Shigeru Shinomoto: Four Types of Learning Curves. Neural Computation 4(4): 605-618 (1992)

Yoshiyuki Kabashima, Shigeru Shinomoto: Learning Curves for Error Minimum and Maximum Likelihood Algorithms. Neural Computation 4(5): 712-719 (1992)