ORCiD, ResearcherID

  1. R. Legaspi and T. Toyoizumi, bioRxiv 433888
    “A Bayesian psychophysics model of sense of agency”
  2. T. Isomura and T. Toyoizumi, arXiv:1808.00668
    “On the achievability of blind source separation for high-dimensional nonlinear source mixtures”
  3. T. Isomura and T. Toyoizumi, Scientific Reports 9:7127 (2019). DOI:10.1038/s41598-019-43423-z  PDF
    “Multi-context blind source separation by error-gated Hebbian rule”
  4. R. Legaspi, Z. He and T. Toyoizumi, Current Opinion in Behavioral Sciences 29:84-90 (2019). DOI:10.1016/j.cobeha.2019.04.004   PDF
    "Synthetic Agency: Sense of Agency in Artificial Intelligence"
  5. E. Munro Krull, S. Sakata and T. Toyoizumi, Frontiers in Neuroscience 13:316 (2019). DOI:10.3389/fnins.2019.00316  PDF
    "Theta oscillations alternate with high amplitude neocortical population within synchronized states"
  6. H. Okazaki, A. Hayashi-Takagi, A. Nagaoka, M. Negishi, H. Ucar, S. Yagishita, K. Ishii, T. Toyoizumi, K. Fox, and H. Kasai, Neuroscience Letters 671, 99-102 (2018). DOI:10.1016/j.neulet.2018.02.006  PDF
    “Calcineurin knockout mice show a selective loss of small spines”
  7. C. L. Buckley and T. Toyoizumi, PLOS Computational Biology 14, e1005926 (2018). DOI:10.1371/journal.pcbi.1005926  PDF  Supporting information
    "A theory of how active behavior stabilizes neural activity: neural gain modulation by closed-loop environmental feedback"
  8. T. Isomura and T. Toyoizumi, Scientific Reports 8:1835 (2018). DOI:10.1038/s41598-018-20082-0  PDF  Supplementary information
    "Error-Gated Hebbian Rule: A Local Learning Rule for Principal and Independent Component Analysis"
  9. T. Danjo, T. Toyoizumi, and S. Fujisawa, Science 359, 213-218 (2018). DOI:10.1126/science.aao3898  PDF
    "Spatial representations of self and other in the hippocampus"
  10. Ł. Kuśmierz and T. Toyoizumi, Physical Review Letters 119, 250601 (2017). DOI:10.1103/PhysRevLett.119.250601  PDF
    "Emergence of Lévy walks from second-order stochastic optimization"
  11. Ł. Kuśmierz, T. Isomura, and T. Toyoizumi, Current Opinion in Neurobiology 46, 170-177 (2017). DOI:10.1016/j.conb.2017.08.020  PDF
    "Learning with three factors: modulating Hebbian plasticity with errors"
  12. S. Tajima, T. Mita, D. Bakkum, H. Takahashi, and T. Toyoizumi, Proc. Natl. Acad. Sci. USA 114, 9517-9522 (2017). DOI:10.1073/pnas.1705981114  PDF
    "Locally embedded presages of global network bursts"
  13. T. Keck, T. Toyoizumi, L. Chen, B. Doiron, D. E. Feldman, K. Fox, W. Gerstner, P. G. Haydon, M. Hubener, H.-K. Lee, J. E. Lisman, T. Rose, F. Sengpiel, D. Stellwagen, M. P. Stryker, G. G. Turrigiano, M. C. van Rossum, Philosophical Transaction of the Royal Society B 372, 1715 (2017). DOI:10.1098/rstb.2016.0158  PDF
    "Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions"
  14. V. Jacob, A. Mitani, T. Toyoizumi, and K. Fox, Journal of Neurophysiology 117, 4-17 (2017). DOI:10.1152/jn.00289.2016  PDF
    "Whisker row deprivation affects the flow of sensory information through rat barrel cortex"
  15. H. Huang and T. Toyoizumi, Physical Review E 94, 062310 (2016). DOI:10.1103/PhysRevE.94.062310  PDF
    "Unsupervised feature learning from finite data by message passing: discontinuous versus continuous phase transition"
  16. M. Lankarany, J. Heiss, I. Lampl, and T. Toyoizumi, Frontiers in Computational Neuroscience 10:110 (2016). DOI:10.3389/fncom.2016.00110  PDF  Supplementary material
    "Simultaneous Bayesian estimation of excitatory and inhibitory synaptic conductances by exploiting multiple recorded trials"
  17. T. Isomura and T. Toyoizumi, Scientific Reports 6:28073 (2016). DOI:10.1038/srep28073  PDF  Supplementary information
    "A local learning rule for independent component analysis"
  18. H. Huang and T. Toyoizumi, Physical Review E 93, 062416 (2016). DOI:10.1103/PhysRevE.93.062416  PDF
    "Clustering of neural code words revealed by a first-order phase transition"
  19. S. Dasguputa, I. Nishikawa, K. Aihara, and T. Toyoizumi, NIPS Workshop on Modeling and Inference for Dynamics on Complex Interaction Networks (2015). PDF
    "Efficient signal processing in random networks that generate variability"
  20. S. Tajima, T. Yanagawa, N. Fujii, and T. Toyoizumi, PLOS Computational Biology 11, e1004537 (2015). DOI:10.1371/journal.pcbi.1004537  PDF
    "Untangling brain-wide dynamics in consciousness by cross-embedding"
  21. H. Huang and T. Toyoizumi, Physical Review E 91, 050101 (2015). DOI:10.1103/PhysRevE.91.050101  PDF
    "Advanced mean field theory of the restricted Boltzmann machine"
  22. H. Shimazaki, K. Sadeghi, T. Ishikawa, Y. Ikegaya, and T. Toyoizumi, Scientific Reports 5:9821 (2015). DOI:10.1038/srep09821  PDF  Supplementary information
    "Simultaneous silence organizes structured higher-order interactions in neural populations."
  23. T. Toyoizumi and H. Huang, Physical Review E 91, 032802 (2015). DOI:10.1103/PhysRevE.91.032802  PDF
    "Structure of attractors in randomly connected networks"
  24. T. Toyoizumi, M. Kaneko, M. P. Stryker, and K. D. Miller, Neuron 84, 497-510 (2014). DOI:10.1016/j.neuron.2014.09.036  PDF
    "Modeling the dynamic interaction of Hebbian and homeostatic plasticity"
  25. S. Tajima and T. Toyoizumi, Seitai-no-Kagaku 65, 478-479 (2014). DOI:10.11477/mf.2425200048  PDF
    "Understandig large-scale dynamical systems by the embedding theorem" (in Japanese)
  26. T. Toyoizumi, H. Miyamoto, Y. Yazaki-Sugiyama, N. Atapour, T. K. Hensch, and K. D. Miller, Neuron 80, 51-63 (2013). DOI:10.1016/j.neuron.2013.07.022  PDF  Supplemental information
    "A theory of the transition to critical period plasticity: inhibition selectively suppresses spontaneous activity"
  27. M. Lankarany, W. P. Zhu, M. N. S. Swamy, T. Toyoizumi, Frontiers in Computational Neuroscience 7:109 (2013). DOI:10.3389/fncom.2013.00109  PDF
    "Inferring trial-to-trial excitatory and inhibitory synaptic inputs from membrane potential using Gaussian Mixture Kalman Filtering"
  28. S. Amari, H. Ando, T. Toyoizumi, and N. Masuda, Physical Review E 87, 022814 (2013). DOI:10.1103/PhysRevE.87.022814  PDF
    "State concentration exponent as a measure of quickness in Kauffman-type networks"
  29. T. Toyoizumi, Neural Computation 24, 2678-2699 (2012). DOI:10.1162/NECO_a_00324  PDF   Color figures
    "Nearly extensive sequential memory lifetime achieved by coupled nonlinear neurons"
  30. T. Toyoizumi and L. F. Abbott, Physical Review E 84, 051908 (2011). DOI:10.1103/PhysRevE.84.051908  PDF
    "Beyond the edge of chaos: Amplification and temporal integration by recurrent networks in the chaotic regime"
  31. J. Gjorgjieva, T. Toyoizumi and S. J. Eglen, PLoS Computational Biology 5, e1000618 (2009). DOI:10.1371/journal.pcbi.1000618  PDF
    "Burst-time-dependent plasticity robustly guides ON/OFF segregation in the lateral geniculate nucleus"
  32. T. Toyoizumi and K. D. Miller, Journal of Neuroscience 29, 6514-6525 (2009). DOI:10.1523/JNEUROSCI.0492-08.2009  PDF  Supplemental materials
    "Equalization of ocular dominance columns induced by an activity-dependent learning rule and the maturation of inhibition"
  33. T. Toyoizumi, K. Rahnama Rad and L. Paninski, Neural Computation 21, 1203-1243 (2009). DOI:10.1162/neco.2008.04-08-757  PDF  Color figures
    "Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness"
  34. Y. Sato, T. Toyoizumi and K. Aihara, Neural Computation 19, 3335-3355 (2007). DOI:10.1162/neco.2007.19.12.3335  PDF
    "Bayesian inference explains perception of unity and ventriloquism aftereffect: identification of common sources of audiovisual stimuli."
  35. D. Sussillo, T. Toyoizumi and W. Maass, Journal of Neurophysiology 97, 4079-4095 (2007). DOI:10.1152/jn.01357.2006  PDF  Supplementary material
    "Self-tuning of neural circuits through short-term synaptic plasticity"
  36. T. Toyoizumi, J.-P. Pfister, K. Aihara and W. Gerstner, Neural Computation 19, 639-671 (2007). DOI:10.1162/neco.2007.19.3.639  PDF
    "Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution"
  37. T. Toyoizumi, K. Aihara and S. Amari, Physical Review Letters 97, 098102 (2006). DOI:10.1103/PhysRevLett.97.098102  PDF
    "Fisher Information for Spike-Based Population Decoding"
  38. T. Toyoizumi and K. Aihara, Journal of the Society of Instrument and Control Engineers 45, 741-747 (2006). DOI:10.11499/sicejl1962.45.74  PDF
    "A Synaptic Plasticity Rule Derived Based on the Information Maximization Principle and Firing Rate Control" (A review in Japanese)
  39. J.-P. Pfister, T. Toyoizumi, D. Barber and W. Gerstner, Neural Computation 18, 1318-1348 (2006). DOI:10.1162/neco.2006.18.6.1318  PDF
    "Optimal Spike-Timing Dependent Plasticity for Precise Action Potential Firing"
  40. T. Toyoizumi and K. Aihara, International Journal of Bifurcation and Chaos 16, 129-136 (2006). DOI:10.1142/S0218127406014630  PDF
    "Generalization of the mean-field method for power-law distributions"
  41. T. Toyoizumi, J.-P. Pfister, K. Aihara and W. Gerstner, Proc. Natl. Acad. Sci. USA 102, 5239-5244 (2005). DOI:10.1073/pnas.0500495102  PDF  Supporting text
    "Generalized Bienenstock-Cooper-Munro rule for spiking neurons that maximizes information transmission"
  42. T. Toyoizumi, J.-P. Pfister, K. Aihara and W. Gerstner, Advances in Neural Information Processing Systems 17, 1409-1416 (2005). PDF
    "Spike-timing dependent Plasticity and mutual information maximization for a spiking neuron model"
  43. T. Toyoizumi and K. Aihara, Transactions of the Institute of Electronics 86-D2, 959-965 (2003). PDF
    "Mean-field and Variational Methods for alpha-families" (in Japanese)
  44. T. Sasamoto, T. Toyoizumi and H. Nishimori, Journal of Physics A 34, 9555-9567 (2001). DOI:10.1088/0305-4470/34/44/314  PDF
    "Statistical mechanics of an NP-complete problem: Subset sum"