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Toshiaki Omori - Publications

Affiliations: 
Univ. of Tokyo, Bunkyō-ku, Tōkyō-to, Japan 
Area:
Theoretical Neuroscience
Website:
http://mns.k.u-tokyo.ac.jp/~omori/index-E.html
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33 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2022 Inoue H, Hukushima K, Omori T. Estimating Distributions of Parameters in Nonlinear State Space Models with Replica Exchange Particle Marginal Metropolis-Hastings Method. Entropy (Basel, Switzerland). 24. PMID 35052141 DOI: 10.3390/e24010115  0.548
2018 Otsuka S, Omori T. Estimation of neuronal dynamics based on sparse modeling. Neural Networks : the Official Journal of the International Neural Network Society. 109: 137-146. PMID 30453159 DOI: 10.1016/j.neunet.2018.10.006  0.352
2017 Omori T, Sekiguchi T, Okada M. Belief Propagation for Probabilistic Slow Feature Analysis Journal of the Physical Society of Japan. 86: 84802. DOI: 10.7566/Jpsj.86.084802  0.428
2014 Omori T. Relation between Non-uniform Electrical Properties and Signal Transfer in Hippocampal Pyramidal Neurons The Brain & Neural Networks. 21: 115-121. DOI: 10.3902/jnns.21.115  0.32
2014 Yotsukura S, Omori T, Nagata K, Okada M. Sparse Estimation of Spike-Triggered Average Ipsj Online Transactions. 7: 52-58. DOI: 10.2197/IPSJTRANS.7.52  0.451
2012 Ota K, Omori T, Miyakawa H, Okada M, Aonishi T. Higher-order spike triggered analysis of neural oscillators. Plos One. 7: e50232. PMID 23226249 DOI: 10.1371/Journal.Pone.0050232  0.508
2012 Kitazono J, Omori T, Aonishi T, Okada M. Estimating membrane resistance over dendrite using Markov random field Ipsj Online Transactions. 5: 186-191. DOI: 10.2197/ipsjtrans.5.186  0.445
2011 Ota K, Omori T, Watanabe S, Miyakawa H, Okada M, Aonishi T. Measurement of infinitesimal phase response curves from noisy real neurons. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 84: 041902. PMID 22181170 DOI: 10.1103/Physreve.84.041902  0.522
2011 Iida M, Omori T, Aonishi T, Okada M. Nonlinear effect on phase response curve of neuron model Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7064: 240-250. DOI: 10.1007/978-3-642-24965-5_26  0.42
2010 Omori T, Aonishi T, Okada M. Switch of encoding characteristics in single neurons by subthreshold and suprathreshold stimuli. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 81: 021901. PMID 20365589 DOI: 10.1103/PhysRevE.81.021901  0.5
2010 Monai H, Omori T, Okada M, Inoue M, Miyakawa H, Aonishi T. An analytic solution of the cable equation predicts frequency preference of a passive shunt-end cylindrical cable in response to extracellular oscillating electric fields. Biophysical Journal. 98: 524-33. PMID 20159148 DOI: 10.1016/J.Bpj.2009.10.041  0.475
2010 Ota K, Omori T, Watanabe S, Miyakawa H, Okada M, Aonishi T. Identification of neural feature space from spike triggered covariance expressed as a function of PRC Bmc Neuroscience. 11. DOI: 10.1186/1471-2202-11-S1-P14  0.521
2010 Tsunoda T, Omori T, Miyakawa H, Okada M, Aonishi T. Estimation of intracellular calcium ion concentration by nonlinear state space modeling and expectation-maximization algorithm for parameter estimation Journal of the Physical Society of Japan. 79. DOI: 10.1143/JPSJ.79.124801  0.456
2010 Aonishi T, Tsunoda T, Omori T, Okada M, Miyakawa H, Ota K. Bayesian method and dynamic clamp technique to measure neural phase-response curves Neuroscience Research. 68: e46. DOI: 10.1016/J.Neures.2010.07.448  0.44
2010 Tsunoda T, Omori T, Miyakawa H, Okada M, Aonishi T. Quantitative estimation of Ca2+ concentrations with simple state space model of calcium imaging signals Neuroscience Research. 68: e107. DOI: 10.1016/j.neures.2010.07.234  0.448
2010 Omori T, Aonishi T, Okada M. Estimation of non-uniform membrane properties over the dendrite: A statistical approach using data assimilation method Neuroscience Research. 68: e111. DOI: 10.1016/j.neures.2010.07.2058  0.454
2010 Ota K, Omori T, Watanabe S, Miyakawa H, Okada M, Aonishi T. Derivation of the neural feature space for oscillating neurons from spike triggered covariance Neuroscience Research. 68: e435. DOI: 10.1016/J.Neures.2010.07.1929  0.485
2009 Omori T, Aonishi T, Miyakawa H, Inoue M, Okada M. Steep decrease in the specific membrane resistance in the apical dendrites of hippocampal CA1 pyramidal neurons. Neuroscience Research. 64: 83-95. PMID 19428686 DOI: 10.1016/j.neures.2009.01.012  0.462
2009 Ota K, Omori T, Aonishi T. MAP estimation algorithm for phase response curves based on analysis of the observation process. Journal of Computational Neuroscience. 26: 185-202. PMID 18751879 DOI: 10.1007/S10827-008-0104-8  0.337
2009 Monai H, Omori T, Okada M, Inoue M, Miyakawa H, Aonishi T. An analytical solution of the cable equation predicts the frequency preference of a passive non-uniform cylindrical cable in response to extracellular oscillating electrical fields Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P38  0.433
2009 Ota K, Omori T, Watanabe S, Miyakawa H, Okada M, Aonishi T. Is the Langevin phase equation an efficient model for stochastic limit cycle oscillators in real neurons? Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P236  0.469
2009 Kitazono J, Omori T, Okada M. Neural network model with discrete and continuous information representation Journal of the Physical Society of Japan. 78. DOI: 10.1143/JPSJ.78.114801  0.425
2009 Ota K, Tsunoda T, Omori T, Watanabe S, Miyakawa H, Okada M, Aonishi T. Is the Langevin phase equation an efficient model for oscillating neurons? Journal of Physics: Conference Series. 197. DOI: 10.1088/1742-6596/197/1/012016  0.414
2009 Monai H, Omori T, Okada M, Inoue M, Miyakawa H, Aonishi T. An analytical solution of the cable equation predicts frequency preference of a cylindrical cable in response to extracellular electrical fields Neuroscience Research. 65: S136. DOI: 10.1016/J.Neures.2009.09.668  0.426
2009 Tsunoda T, Omori T, Miyakawa H, Okada M, Aonishi T. Estimation of intracellular calcium ion concentration and Ca influx by nonlinear state space modeling Neuroscience Research. 65: S84. DOI: 10.1016/j.neures.2009.09.330  0.447
2009 Aoyama S, Omori T, Aonishi T, Inoue M, Miyakawa H. Morphology dependence of the membrane potential response of a branched neuron for extracellular electric field: a modeling study Neuroscience Research. 65: S74. DOI: 10.1016/j.neures.2009.09.262  0.347
2008 Cousseau F, Mimura K, Omori T, Okada M. Statistical mechanics of lossy compression for nonmonotonic multilayer perceptrons. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 78: 021124. PMID 18850803 DOI: 10.1103/PhysRevE.78.021124  0.403
2007 Ota K, Aonishi T, Watanabe S, Miyakawa H, Omori T, Okada M. Perturbation response measurements in hippocampal CA1 pyramidal neuron based on Bayesian statistics Neuroscience Research. 58: S185. DOI: 10.1016/J.Neures.2007.06.810  0.496
2007 Omori T, Aonishi T, Okada M. Non-uniformity of membrane property improves dendritic signal transfer in hippocampal CA1 pyramidal neuron Neuroscience Research. 58: S40. DOI: 10.1016/j.neures.2007.06.235  0.483
2006 Omori T, Aonishi T, Miyakawa H, Inoue M, Okada M. Estimated distribution of specific membrane resistance in hippocampal CA1 pyramidal neuron. Brain Research. 1125: 199-208. PMID 17113056 DOI: 10.1016/j.brainres.2006.09.095  0.473
2004 Omori T, Horiguchi T. Dynamical Neural Network Model of Hippocampus with Excitatory and Inhibitory Neurons Journal of the Physical Society of Japan. 73: 749-755. DOI: 10.1143/JPSJ.73.749  0.34
2004 Omori T, Horiguchi T. Dynamical State Transition by Neuromodulation Due to Acetylcholine in Neural Network Model for Oscillatory Phenomena in Thalamus Journal of the Physical Society of Japan. 73: 3489-3494. DOI: 10.1143/JPSJ.73.3489  0.323
2004 Omori T, Horiguchi T. Dynamical properties of neural network model for working memory with Hodgkin–Huxley neurons Physica a: Statistical Mechanics and Its Applications. 334: 600-614. DOI: 10.1016/J.PHYSA.2003.11.022  0.35
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