Ryota Kobayashi
Ryota Kobayashi
Bestätigte E-Mail-Adresse bei k.u-tokyo.ac.jp - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold
R Kobayashi, Y Tsubo, S Shinomoto
Frontiers in computational neuroscience 3, 9, 2009
1892009
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
1552008
TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics
R Kobayashi, R Lambiotte
ICWSM' 2016, 191-200, 2016
1232016
Estimation of time-dependent input from neuronal membrane potential
R Kobayashi, S Shinomoto, P Lansky
Neural computation 23 (12), 3070-3093, 2011
382011
Reconstructing neuronal circuitry from parallel spike trains
R Kobayashi, S Kurita, A Kurth, K Kitano, K Mizuseki, M Diesmann, ...
Nature communications 10 (1), 1-13, 2019
322019
Impact of network topology on inference of synaptic connectivity from multi-neuronal spike data simulated by a large-scale cortical network model.
R Kobayashi, K Kitano
Journal of computational neuroscience, 2013
272013
State space method for predicting the spike times of a neuron
R Kobayashi, S Shinomoto
Physical Review E 75 (1), 011925, 2007
262007
Optimal decoding and information transmission in Hodgkin–Huxley neurons under metabolic cost constraints
L Kostal, R Kobayashi
Biosystems 136, 3-10, 2015
192015
Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron
R Kobayashi, Y Tsubo, P Lansky, S Shinomoto
Advances in Neural Information Processing Systems 24, 217-225, 2011
162011
Impact of slow K+ currents on spike generation can be described by an adaptive threshold model
R Kobayashi, K Kitano
Journal of computational neuroscience 40 (3), 347-362, 2016
142016
Input-output relationship in social communications characterized by spike train analysis
T Aoki, T Takaguchi, R Kobayashi, R Lambiotte
Physical Review E 94 (4), 042313, 2016
132016
Predicting the success of online petitions leveraging multidimensional time-series
J Proskurnia, P Grabowicz, R Kobayashi, C Castillo, P Cudré-Mauroux, ...
Proceedings of the 26th International Conference on World Wide Web, 755-764, 2017
122017
Estimation of excitatory and inhibitory synaptic conductance variations in motoneurons during locomotor-like rhythmic activity
R Kobayashi, H Nishimaru, H Nishijo
Neuroscience 335, 72-81, 2016
82016
Estimation of the synaptic input firing rates and characterization of the stimulation effects in an auditory neuron
R Kobayashi, J He, P Lansky
Frontiers in computational neuroscience 9, 59, 2015
62015
Population coding is essential for rapid information processing in the moth antennal lobe
R Kobayashi, S Namiki, R Kanzaki, K Kitano, I Nishikawa, P Lansky
Brain research 1536, 88-96, 2013
62013
Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth
M Levakova, L Kostal, C Monsempès, P Lucas, R Kobayashi
Journal of the Royal Society Interface 16 (157), 20190246, 2019
52019
Fluctuation scaling in neural spike trains
S Koyama, R Kobayashi
Mathematical Biosciences & Engineering 13 (3), 537, 2016
52016
The influence of firing mechanisms on gain modulation
R Kobayashi
Journal of Statistical Mechanics: Theory and Experiment 2009 (01), P01017, 2009
42009
Predicting spike times from subthreshold dynamics of a neuron
R Kobayashi, S Shinomoto
Advances in Neural Information Processing Systems, 721-728, 2007
32007
Analyzing temporal patterns of topic diversity using graph clustering
T Hashimoto, DL Shepard, T Kuboyama, K Shin, R Kobayashi, T Uno
The Journal of Supercomputing 77 (5), 4375-4388, 2021
22021
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20