ORCiD, ResearcherID

  1. C. L. Buckley, S. Tajima, T. Yanagawa, K. Takakura, Y. Nagasaka, N. Fujii, and T. Toyoizumi, arXiv:1602.08881.
    "Brain state control by closed-loop environmental feedback"
  2. L. Kusmierz, T. Isomura, and T. Toyoizumi, Current Opinion in Neurobiology 46, 170-177 (2017). PDF
    "Learning with three factors: modulating Hebbian plasticity with errors"
  3. S. Tajima, T. Mita, D. Bakkum, H. Takahashi, and T. Toyoizumi, Proc. Natl. Acad. Sci. USA 114, 9517-9522 (2017). PDF
    "Locally embedded presages of global network bursts"
  4. 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). PDF
    "Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions"
  5. V. Jacob, A. Mitani, T. Toyoizumi, and K. Fox, Journal of Neurophysiology 117, 4-17 (2017). PDF
    "Whisker row deprivation affects the flow of sensory information through rat barrel cortex"
  6. H. Huang and T. Toyoizumi, Physical Review E 94, 062310 (2016). PDF
    "Unsupervised feature learning from finite data by message passing: discontinuous versus continuous phase transition"
  7. M. Lankarany, J. Heiss, I. Lampl, and T. Toyoizumi, Frontiers in Computational Neuroscience 10:110 (2016). PDF Supplementary Material
    "Simultaneous Bayesian estimation of excitatory and inhibitory synaptic conductances by exploiting multiple recorded trials"
  8. T. Isomura and T. Toyoizumi, Scientific Reports 6, 28073 (2016). PDF Supplementary information
    "A local learning rule for independent component analysis"
  9. H. Huang and T. Toyoizumi, Physical Review E 93, 062416 (2016). PDF
    "Clustering of neural code words revealed by a first-order phase transition"
  10. 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"
  11. S. Tajima, T. Yanagawa, N. Fujii, and T. Toyoizumi, PLOS Computational Biology 11, e1004537 (2015). PDF
    "Untangling brain-wide dynamics in consciousness by cross-embedding"
  12. H. Huang and T. Toyoizumi, Physical Review E 91, 050101 (2015). PDF
    "Advanced mean field theory of the restricted Boltzmann machine"
  13. H. Shimazaki, K. Sadeghi, T. Ishikawa, Y. Ikegaya, and T. Toyoizumi, Scientific Reports 5, 9821 (2015). PDF Supplementary information
    "Simultaneous silence organizes structured higher-order interactions in neural populations."
  14. T. Toyoizumi and H. Huang, Physical Review E 91, 032802 (2015). PDF
    "Structure of attractors in randomly connected networks"
  15. T. Toyoizumi, M. Kaneko, M. P. Stryker, and K. D. Miller, Neuron 84, 497-510 (2014). PDF
    "Modeling the dynamic interaction of Hebbian and homeostatic plasticity"
  16. S. Tajima and T. Toyoizumi, Seitai-no-Kagaku 65, 478-479 (2014). PDF
    "Understandig large-scale dynamical systems by the embedding theorem" (in Japanese)
  17. T. Toyoizumi, H. Miyamoto, Y. Yazaki-Sugiyama, N. Atapour, T. K. Hensch, and K. D. Miller, Neuron 80, 51-63 (2013). PDF  Supplemental information
    "A theory of the transition to critical period plasticity: inhibition selectively suppresses spontaneous activity"
  18. M. Lankarany, W. P. Zhu, M. N. S. Swamy, T. Toyoizumi, Frontiers in Computational Neuroscience 7:109 (2013). PDF
    "Inferring trial-to-trial excitatory and inhibitory synaptic inputs from membrane potential using Gaussian Mixture Kalman Filtering"
  19. S. Amari, H. Ando, T. Toyoizumi, and N. Masuda, Physical Review E 87, 022814 (2013). PDF
    "State concentration exponent as a measure of quickness in Kauffman-type networks"
  20. T. Toyoizumi, Neural Computation 24, 2678-2699 (2012). PDF   Color figures
    "Nearly extensive sequential memory lifetime achieved by coupled nonlinear neurons"
  21. T. Toyoizumi and L. F. Abbott, Physical Review E 84, 051908 (2011). PDF
    "Beyond the edge of chaos: Amplification and temporal integration by recurrent networks in the chaotic regime"
  22. J. Gjorgjieva, T. Toyoizumi and S. J. Eglen, PLoS Computational Biology 5, e1000618 (2009). PDF
    "Burst-time-dependent plasticity robustly guides ON/OFF segregation in the lateral geniculate nucleus"
  23. T. Toyoizumi and K. D. Miller, Journal of Neuroscience 29, 6514-6525 (2009). PDF  Supplemental materials
    "Equalization of ocular dominance columns induced by an activity-dependent learning rule and the maturation of inhibition"
  24. T. Toyoizumi, K. Rahnama Rad and L. Paninski, Neural Computation 21, 1203-1243 (2009). PDF  Color figures
    "Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness"
  25. Y. Sato, T. Toyoizumi and K. Aihara, Neural Computation 19, 3335-3355 (2007). PDF
    "Bayesian inference explains perception of unity and ventriloquism aftereffect: identification of common sources of audiovisual stimuli."
  26. D. Sussillo, T. Toyoizumi and W. Maass, Journal of Neurophysiology 97, 4079-4095 (2007). PDF  Supplementary material
    "Self-tuning of neural circuits through short-term synaptic plasticity"
  27. T. Toyoizumi, J.-P. Pfister, K. Aihara and W. Gerstner, Neural Computation 19, 639-671 (2007). PDF
    "Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution"
  28. T. Toyoizumi, K. Aihara and S. Amari, Physical Review Letters 97, 098102 (2006). PDF
    "Fisher Information for Spike-Based Population Decoding"
  29. T. Toyoizumi and K. Aihara, Journal of the Society of Instrument and Control Engineers 45, 741-747 (2006). PDF
    "A Synaptic Plasticity Rule Derived Based on the Information Maximization Principle and Firing Rate Control" (A review in Japanese)
  30. J.-P. Pfister, T. Toyoizumi, D. Barber and W. Gerstner, Neural Computation 18, 1318-1348 (2006). PDF
    "Optimal Spike-Timing Dependent Plasticity for Precise Action Potential Firing"
  31. T. Toyoizumi and K. Aihara, International Journal of Bifurcation and Chaos 16, 129-136 (2006). PDF
    "Generalization of the mean-field method for power-law distributions"
  32. T. Toyoizumi, J.-P. Pfister, K. Aihara and W. Gerstner, Proc. Natl. Acad. Sci. USA 102, 5239-5244 (2005). PDF  Supporting text
    "Generalized Bienenstock-Cooper-Munro rule for spiking neurons that maximizes information transmission"
  33. 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"
  34. 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)
  35. T. Sasamoto, T. Toyoizumi and H. Nishimori, Journal of Physics A 34, 9555-9567 (2001). PDF
    "Statistical mechanics of an NP-complete problem: Subset sum"