| Year |
Citation |
Score |
| 2024 |
Terada Y, Toyoizumi T. Chaotic neural dynamics facilitate probabilistic computations through sampling. Proceedings of the National Academy of Sciences of the United States of America. 121: e2312992121. PMID 38648479 DOI: 10.1073/pnas.2312992121 |
0.751 |
|
| 2021 |
Shimizu G, Yoshida K, Kasai H, Toyoizumi T. Computational roles of intrinsic synaptic dynamics. Current Opinion in Neurobiology. 70: 34-42. PMID 34303124 DOI: 10.1016/j.conb.2021.06.002 |
0.327 |
|
| 2020 |
Kuśmierz Ł, Ogawa S, Toyoizumi T. Edge of Chaos and Avalanches in Neural Networks with Heavy-Tailed Synaptic Weight Distribution. Physical Review Letters. 125: 028101. PMID 32701351 DOI: 10.1103/Physrevlett.125.028101 |
0.367 |
|
| 2019 |
Humble J, Hiratsuka K, Kasai H, Toyoizumi T. Intrinsic Spine Dynamics Are Critical for Recurrent Network Learning in Models With and Without Autism Spectrum Disorder. Frontiers in Computational Neuroscience. 13: 38. PMID 31263407 DOI: 10.3389/Fncom.2019.00038 |
0.359 |
|
| 2018 |
Buckley CL, Toyoizumi T. A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback. Plos Computational Biology. 14: e1005926. PMID 29342146 DOI: 10.1371/Journal.Pcbi.1005926 |
0.318 |
|
| 2017 |
Kuśmierz Ł, Isomura T, Toyoizumi T. Learning with three factors: modulating Hebbian plasticity with errors. Current Opinion in Neurobiology. 46: 170-177. PMID 28918313 DOI: 10.1016/J.Conb.2017.08.020 |
0.309 |
|
| 2017 |
Tajima S, Mita T, Bakkum DJ, Takahashi H, Toyoizumi T. Locally embedded presages of global network bursts. Proceedings of the National Academy of Sciences of the United States of America. PMID 28827362 DOI: 10.1073/Pnas.1705981114 |
0.731 |
|
| 2017 |
Keck T, Toyoizumi T, Chen L, Doiron B, Feldman DE, Fox K, Gerstner W, Haydon PG, Hübener M, Lee HK, Lisman JE, Rose T, Sengpiel F, Stellwagen D, Stryker MP, et al. Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 372. PMID 28093552 DOI: 10.1098/Rstb.2016.0158 |
0.721 |
|
| 2017 |
Newton AJH, Seidenstein AH, McDougal RA, Pérez-Cervera A, Huguet G, M-Seara T, Haimerl C, Angulo-Garcia D, Torcini A, Cossart R, Malvache A, Skiker K, Maouene M, Ragognetti G, Lorusso L, ... ... Toyoizumi T, et al. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Bmc Neuroscience. 18. DOI: 10.1186/S12868-017-0372-1 |
0.694 |
|
| 2016 |
Lankarany M, Heiss JE, Lampl I, Toyoizumi T. Simultaneous Bayesian Estimation of Excitatory and Inhibitory Synaptic Conductances by Exploiting Multiple Recorded Trials. Frontiers in Computational Neuroscience. 10: 110. PMID 27867353 DOI: 10.3389/Fncom.2016.00110 |
0.3 |
|
| 2016 |
Sharpee TO, Destexhe A, Kawato M, Sekulić V, Skinner FK, Wójcik DK, Chintaluri C, Cserpán D, Somogyvári Z, Kim JK, Kilpatrick ZP, Bennett MR, Josić K, Elices I, Arroyo D, ... ... Toyoizumi T, et al. 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54. PMID 27534393 DOI: 10.1186/S12868-016-0283-6 |
0.568 |
|
| 2015 |
Tajima S, Yanagawa T, Fujii N, Toyoizumi T. Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. Plos Computational Biology. 11: e1004537. PMID 26584045 DOI: 10.1371/Journal.Pcbi.1004537 |
0.72 |
|
| 2015 |
Toyoizumi T, Huang H. Structure of attractors in randomly connected networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 91: 032802. PMID 25871152 DOI: 10.1103/Physreve.91.032802 |
0.31 |
|
| 2014 |
Toyoizumi T, Kaneko M, Stryker MP, Miller KD. Modeling the dynamic interaction of Hebbian and homeostatic plasticity. Neuron. 84: 497-510. PMID 25374364 DOI: 10.1016/J.Neuron.2014.09.036 |
0.646 |
|
| 2014 |
Toyoizumi T, Kaneko M, Stryker MP, Miller KD. 1SEP-06 Modeling the dynamical interaction of Hebbian and homeostatic plasticity(1SEP Cooperativity in shaping the nerve cell function,Symposium,The 52nd Annual Meeting of the Biophysical Society of Japan(BSJ2014)) Seibutsu Butsuri. 54: S124. DOI: 10.2142/Biophys.54.S124_6 |
0.623 |
|
| 2013 |
Toyoizumi T, Miyamoto H, Yazaki-Sugiyama Y, Atapour N, Hensch TK, Miller KD. A theory of the transition to critical period plasticity: inhibition selectively suppresses spontaneous activity. Neuron. 80: 51-63. PMID 24094102 DOI: 10.1016/J.Neuron.2013.07.022 |
0.471 |
|
| 2013 |
Lankarany M, Zhu WP, Swamy MN, Toyoizumi T. Inferring trial-to-trial excitatory and inhibitory synaptic inputs from membrane potential using Gaussian mixture Kalman filtering. Frontiers in Computational Neuroscience. 7: 109. PMID 24027523 DOI: 10.3389/Fncom.2013.00109 |
0.304 |
|
| 2013 |
Amari S, Ando H, Toyoizumi T, Masuda N. State concentration exponent as a measure of quickness in Kauffman-type networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 87: 022814. PMID 23496575 DOI: 10.1103/Physreve.87.022814 |
0.476 |
|
| 2013 |
Buckley CL, Toyoizumi T. The role of environmental feedback in a brain state switch from passive to active sensing Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P395 |
0.359 |
|
| 2013 |
Lankarany M, Zhu W, Swamy M, Toyoizumi T. Trial-to-trial tracking of excitatory and inhibitory synaptic conductance using Gaussian-mixture Kalman filtering Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-O2 |
0.324 |
|
| 2012 |
Toyoizumi T. Nearly extensive sequential memory lifetime achieved by coupled nonlinear neurons. Neural Computation. 24: 2678-99. PMID 22594828 DOI: 10.1162/Neco_A_00324 |
0.302 |
|
| 2011 |
Toyoizumi T, Abbott LF. Beyond the edge of chaos: amplification and temporal integration by recurrent networks in the chaotic regime. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 84: 051908. PMID 22181445 DOI: 10.1103/PhysRevE.84.051908 |
0.639 |
|
| 2011 |
Gilson M, Fukai T, Toyoizumi T. Interplay between dendritic non-linearities and STDP Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P338 |
0.4 |
|
| 2011 |
Toyoizumi T, Miyamoto H, Yazaki-Sugiyama Y, Hensch TK, Miller KD. Suppression of spontaneous activity by GABA circuit maturation is sufficient for developmental transitions in visual cortical plasticity Neuroscience Research. 71: e146. DOI: 10.1016/J.Neures.2011.07.631 |
0.444 |
|
| 2009 |
Gjorgjieva J, Toyoizumi T, Eglen SJ. Burst-time-dependent plasticity robustly guides ON/OFF segregation in the lateral geniculate nucleus. Plos Computational Biology. 5: e1000618. PMID 20041207 DOI: 10.1371/Journal.Pcbi.1000618 |
0.328 |
|
| 2009 |
Toyoizumi T, Rad KR, Paninski L. Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness. Neural Computation. 21: 1203-43. PMID 19718814 DOI: 10.1162/Neco.2008.04-08-757 |
0.355 |
|
| 2009 |
Toyoizumi T, Miller KD. Equalization of ocular dominance columns induced by an activity-dependent learning rule and the maturation of inhibition. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 29: 6514-25. PMID 19458222 DOI: 10.1523/Jneurosci.0492-08.2009 |
0.462 |
|
| 2007 |
Sussillo D, Toyoizumi T, Maass W. Self-tuning of neural circuits through short-term synaptic plasticity. Journal of Neurophysiology. 97: 4079-95. PMID 17409166 DOI: 10.1152/Jn.01357.2006 |
0.729 |
|
| 2007 |
Toyoizumi T, Pfister JP, Aihara K, Gerstner W. Optimality model of unsupervised spike-timing-dependent plasticity: synaptic memory and weight distribution. Neural Computation. 19: 639-71. PMID 17298228 DOI: 10.1162/Neco.2007.19.3.639 |
0.733 |
|
| 2006 |
Toyoizumi T, Aihara K, Amari S. Fisher information for spike-based population decoding. Physical Review Letters. 97: 098102. PMID 17026405 DOI: 10.1103/Physrevlett.97.098102 |
0.504 |
|
| 2006 |
Pfister JP, Toyoizumi T, Barber D, Gerstner W. Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning. Neural Computation. 18: 1318-48. PMID 16764506 DOI: 10.1162/Neco.2006.18.6.1318 |
0.721 |
|
| 2005 |
Toyoizumi T, Pfister JP, Aihara K, Gerstner W. Generalized Bienenstock-Cooper-Munro rule for spiking neurons that maximizes information transmission. Proceedings of the National Academy of Sciences of the United States of America. 102: 5239-44. PMID 15795376 DOI: 10.1073/Pnas.0500495102 |
0.73 |
|
| 2005 |
Toyoizumi T, Pfister JP, Aihara K, Gerstner W. Spike-timing dependent plasticity and mutual information maximization for a spiking neuron model Advances in Neural Information Processing Systems. |
0.702 |
|
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