Author
Kyoto UniversityORCID 0000-0002-5745-7736Unclaimed ORCID profile · follow to get notified of new preprints
5 papers
Recent·Most cited
Shigeru Shinomoto, Yasuhiro Tsubo
The paper examines the relationship between monosynaptic and functional connectivity in neural circuits using spike train data and simulated calcium imaging, finding they provide complementary insights into neural computation.
bioRxiv · May 5, 2025 · PreprintNeuroscience
Yasuhiro Tsubo, Shigeru Shinomoto
The paper identifies non-differentiable fluctuations in neural activity that cause cusp-like features in cross-correlograms, proposing a new analysis method to address this issue.
PNAS Nexus · Jun 28, 2024Peer-reviewedNeuroscience
Daisuke Endo, Ryota Kobayashi, Ramón Bartolo, Bruno B. Averbeck, Yasuko Sugase-Miyamoto, Kazuko Hayashi, Kenji Kawano, Barry J. Richmond, Shigeru Shinomoto
The paper introduces a convolutional neural network to estimate synaptic connectivity from spike trains without requiring parameter tuning, and applies it to construct neuronal circuit diagrams in monkey cortical areas.
Scientific Reports · Jun 8, 2021Peer-reviewedNeuroscience
Huu Hoang, Masa-aki Sato, Shigeru Shinomoto, Shinichiro Tsutsumi, Miki Hashizume, Tomoe Ishikawa, Masanobu Kano, Yuji Ikegaya, Kazuo Kitamura, Mitsuo Kawato, Keisuke Toyama
This paper introduces HA_time, a hyperacuity algorithm for precise spike timing estimation from calcium imaging, achieving up to 20-fold improvement in spike time precision.
Scientific Reports · Oct 20, 2020Peer-reviewedNeuroscience
Ryota Kobayashi, Shuhei Kurita, Anno Christopher Kurth, Katsunori Kitano, Kenji Mizuseki, Markus Diesmann, Barry J. Richmond, Shigeru Shinomoto
This paper develops a method to reconstruct neuronal circuitry from spike trains using a generalized linear model, validated on rat hippocampal data.
Nature Communications · Oct 2, 2019Peer-reviewedNeuroscience