青柳 富誌生【研究業績】


青柳富誌生(Toshio Aoyagi)の今までに公にした論文や国際会議のプロシーディング、日本語による解説・論文などのリストです。

MenuReferred Papers | Proceedings | 会議録 (in Japanese) | 総説、著書等 (in Japanese) | 特許 (in Japanese) | 受賞等 (in Japanese) | 学会発表等 (in Japanese) 


Referred Papers

 

  1. Bayesian estimation of phase dynamics based on partially sampled spikes generated by realistic model neurons, Kento Suzuki, Toshio Aoyagi and Katsunori Kitano, Frontiers in Computational Neuroscience, vol.11, 116 (2018). DOI:10.3389/fncom.2017.00116
  2. A dynamical systems approach for estimating phase interactions between rhythms of different frequencies from experimental data, Takayuki Onojima, Takahiro Goto, Hiroaki Mizuhara and Toshio Aoyagi  PLOS Computational Biology, 14(1), e1005928 (2018). DOI:10.1371/journal.pcbi.1005928
  3. Robust Measurements of Phase Response Curves Realized via Multicycle Weighted Spike-Triggered Averages, Takashi Imai, Kaiichiro Ota and Toshio Aoyagi, Journal of the Physical Society of Japan,Vol.86, No.2, 024009 (2017) DOI: 10.7566/JPSJ.86.024009
  4. Nonstandard transitions in the Kuramoto model: a role of asymmetry in natural frequency distributions, Yu Terada, Keigo Ito, Toshio Aoyagi and Yoshiyuki Y. Yamaguchi, Journal of Statistical Mechanics: Theory and Experiment, 013403 (2017) DOI:10.1088/1742-5468/aa53f6 (JSTAT Highlights)
  5. Dynamics of two populations of phase oscilltors with different frequency distributions, Yu Terada and Toshio Aoyagi, Physical Review E, vol.94, Issue 1, 012213(2016) DOI: 10.1103/PhysRevE.94.012213 
  6. Evaluation of the Phase-Dependent Rhythm Control of Human Walking Using Phase Response Curves,Tetsuro Funato, Yuki Yamamoto, Shinya Aoi, Takashi Imai, Toshio Aoyagi, Nozomi Tomita and Kazuo Tsuchiya, PLOS Computational Biology, 12(5), e1004950 (2016) DOI:10.1371/journal.pcbi.1 004950
  7. Improvement effect of measuring phase response curves by using multicycle data ,Takashi Imai and Toshio Aoyagi, Nonlinear Theory and Its Applications, IEICE (NOLTA) , vol.7, no.2, 58-65 (2016) DOI:10.1587/nolta.7.58
  8. Learning in neural networks based on a generalized fluctuation theorem,Takashi Hayakawa and Toshio Aoyagi, Physical Review E, vol.92,052710 (2015).
  9. Self-organization of complex networks as a dynamical system, Takaaki Aoki, Koichiro Yawata, and Toshio Aoyagi, Physical Review E, vol. 91, Issue 1, 012908 (2015).
  10. A Biologically Plausible Learning Rule for the Infomax on Recurrent Neural Networks, Hayakawa Takashi, Kaneko Takeshi and Aoyagi Toshio, Frontiers in Computational Neuroscience, vol.8, 143 (2014).
  11. A mathematical model of negative covariability of inter-columnar excitatory synaptic actions caused by presynaptic inhibition, Mitsuru Saito, Takuma Tanaka, Hajime Sato, Hiroki Toyoda, Toshio Aoyagi and Youngnam Kang, European Journal of Neuroscience, Vol.38, Issue 7, 2999–3007(2013).
  12. Scale-free structures emerging from co-evolution of a network and the distribution of a diffusive resource on it, Takaaki Aoki and Toshio Aoyagi, Physical Review Letters, vol.109, 208702 (2012). (This paper has been highlighted in Physics! See here).
  13. Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability, Takuma Tanaka, Toshio Aoyagi, Takeshi Kaneko, Neural Computation, vol. 24, no.10, 2700–2725 (2012).
  14. Self-organized network of phase oscillators coupled by activity-dependent interactions, Takaaki Aoki and Toshio Aoyagi, Physical Review E, vol.84, Issue 6, 066109 (2011).
  15. Multi-stable attractors in a network of phase oscillators with three-body interactions, Takuma Tanaka and Toshio Aoyagi, Physical Review Letters, vol.106, Issue 22, 224101 (2011).
  16. Asymmetric neighborhood functions accelerate ordering process of self-organizing maps, Kaiichiro Ota, Takaaki Aoki, Koji Kurata and Toshio Aoyagi, Physical Review E, vol.83, Issue 2, 021903(2011).
  17. Bayesian estimation of phase response curves, Ken Nakae,Yukito Iba, Yasuhiro Tsubo, Tomoki Fukai and Toshio Aoyagi, Neural Networks, Vol. 23, Issue 6, Pages 752-763 (2010),
  18. Weighted spike-triggered average of a fluctuating stimulus yielding the phase response curve, Kaiichiro Ota, Masaki Nomura, and Toshio Aoyagi, Physical Review Letters, vol.103, Issue 2, 024101(2009).
  19. Dynamics in Co-evolving Networks of Active Elements, Takuma Tanaka, Takaaki Aoki, and Toshio Aoyagi, FORMA, Vol. 24 (No. 1), 17-22, (2009).
  20. Estimation of functional connectivity that causes burst-like population activities, Masaki Nomura, Daisuke Ito, Hiroki Tamate, Kazutoshi Gohara and Toshio Aoyagi, FORMA, Vol. 24 (No. 1), 11-16, (2009).
  21. Recurrent infomax generates cell assemblies, neuronal avalanches, and simple cell-like selectivity, Takuma Tanaka, Takeshi Kaneko, and Toshio Aoyagi, Neural Computation vol. 21, no. 4, 1038–1067 (2009).
  22. Co-evolution of phases and connection strengths in a network of phase oscillators, Takaaki Aoki and Toshio Aoyagi, Physical Review Letters, vol.102, Issue 3, 034101(2009).
  23. Ordering Process of Self-Organizing Maps Improved by Asymmetric Neighborhood Function, Takaaki Aoki , Kaiichiro Ota , Koji Kurata , and Toshio Aoyagi, Cognitive Neurodynamics Vol. 3, 9-15, (2009).
  24. Optimal weighted networks of phase oscillators for synchronization,Takuma Tanaka and Toshio Aoyagi, Physical Review E, vol.78, Issue .4, 046210 (2008), (Virtual Journal of Biological Physics Research, 16 (8))
  25. Weighted scale-free networks with variable power-law exponents, Takuma Tanaka, Toshio Aoyagi, Physica D , vol. 237, no. 7, pp. 898-907 (2008).
  26. Synchrony-induced switching behavior of spike-pattern attractors created by spike-timing dependent plasticity, Takaaki Aoki and Toshio Aoyagi, Neural Computation, Vol. 19, No. 10: 2720-2738 (2007).
  27. Analysis of multi-neuronal activities by means of a kernel method, Masaki Nomura, Yoshio Sakurai and Toshio Aoyagi, Journal of Robotics and Mechatronics,vol.19,No.4 364-368 (2007).
  28. Synchrony-induced attractor transition in cortical neural networks organized by spike-timing dependent plasticity. Takaaki Aoki and Toshio Aoyagi, Journal of Robotics and Mechatronics, Vol 19, No.4, 409-415 (2007).
  29. Synchronous and asynchronous bursting states: role of intrinsic neural dynamics, Takashi Takekawa, Toshio Aoyagi, Tomoki Fukai, Journal of Computational Neuroscience vol.23, no 2:189-200 (2007).
  30. Self-Organizing maps with Asymmetric Neighborhood function, Takaaki Aoki and Toshio Aoyagi, Neural Computation, vol.19, no.8, 2525-2535 (2007).
  31. A Possible Role of Incoming Spike Synchrony in Associative Memory Model with STDP Learning rule, Takaaki Aoki and Toshio Aoyagi, Progress of Theoretical Physics Supplement, 161, 152-155 (2006).
  32. Phase analysis of inhibitory neurons involved in the thalamocortical loop, Masaki Nomura, Takuma Tanaka, Takeshi Kaneko and Toshio Aoyagi, Progress of Theoretical Physics Supplement, 161, 310-313 (2006).
  33. Synchronization properties on slow oscillatory activity in a cortex network model, Takashi Takekawa, Toshio Aoyagi and Tomoki Fukai, Progress of Theoretical Physics Supplement, 161, 356-359 (2006).
  34. Stability of Synchronous Solutions in Weakly Coupled Neuron Networks, Masaki Nomura and Toshio Aoyagi, Progress of Theoretical Physics, 113, 911-925 (2005).
  35. Possible Role of Synchronous Input Spike Trains in Controlling Function of Neural Networks, Toshio Aoyagi, Takaaki Aoki, Neurocomputing 58-60, 259-264 (2004).
  36. Gamma frequency synchronization in a local cortical network model, Masaki Nomura, Tomoki Fukai, Toshio Aoyagi,Neurocomputing 58-60, 173-178 (2004).
  37. Influences of synaptic locations on the synchronization through rhythmic bursting, Takashi Takekawa, Toshio Aoyagi, Tomoki Fukai, Network: Computation in Neural Systems, vol.15, no.1, , 1-12 (2004).
  38. Synchrony of Fast-Spiking Interneurons Interconnected by GABAergic and Electrical Synapses, Masaki, Nomura, Tomoki Fukai, Toshio Aoyagi, Neural Computation, vol.15, no.9, 2179-2198 (2003).
  39. Gamma Rhythmic Bursts: Coherence Control in Networks of Cortical Pyramidal Neurons, Toshio Aoyagi, Takashi Takekawa and Tomoki Fukai, Neural Computation vol.15, no.5, 1035-1061(2003).
  40. Two-level hierarchy with sparsely and temporally coded patterns, Masaki Nomura, Toshio Aoyagi and Masato Okada, Neural Networks, vol.16, no.7, 947-954 (2003).
  41. The role of Ca2+-dependent cationic current in generating gamma frequency rhythmic bursts: modeling study, Toshio Aoyagi, Youngnam Kang, Nobuhiko Terada, Takeshi, Kaneko and Tomoki Fukai, Neuroscience, vol.115, no.4, 1127-1138 (2002).
  42. Phase Locking States in Netwrok of Inhibitory Neuron: A Putative Role of Gap Junction, Daisuke Suzuki, Toshio Aoyagi, Journal of the Physical Society of Japan, vol.71, no.11, 2644-2648 (2002).
  43. Modeling the layer V cortical pyramidal neurons showing theta rhythmic firing in the presence of muscarine, Tomoki Fukai, Katsunori Kitano, Toshio Aoyagi and Youngnam Kang, Neurocomputing 44-46, 103-108 (2002).
  44. A possible functional organization of the corticostriatal input within the weakly-correlated striatal activity:a modeling study, Katsunori kitano, Toshio Aoyagi and Tomoki Fukai, Neuroscience Research, vol.40, no.1, 87-96 (2001).
  45. A Bursting Mechanism of Chattering Neurons Based on Ca2+-Dependent Cationic Currents, Toshio Aoyagi, Nobuhiko Terada, Youngnam Kang, Takeshi Kaneko and Tomoki Fukai, Neurocomputing, 38, 93-98 (2001).
  46. Synchronous and asynchronous activities in a network of striatal spiny projection neurons, Katsunori Kitano, Toshio Aoyagi and Tomoki Fukai, Neurocomputing, 38, 721-726 (2001).
  47. Analysis of Oscillator Neural Networks for Sparsely Coded Phase Patterns, Masaki Nomura and Toshio Aoyagi, Journal of Physics A:Mathematical and General, vol.33, no.48, 8681-8702 (2000).
  48. Oscillator neural network retrieving sparsely coded phase patterns, Toshio Aoyagi and Masaki Nomura, Physical Review Letters, vol.83, no.5, 1062-1065 (1999).
  49. Retrieval dynamics of neural networks for sparsely coded sequential patterns, Katsunori Kitano and Toshio Aoyagi, Journal of Physics A:Mathematical and General, vol.31, no.36, L613-L620 (1998).
  50. Retrieval dynamics in oscillator neural networks, Toshio Aoyagi and Katsunori Kitano, Neural Computation, vo.10, no.6, 1527-1546 (1998).
  51. Effect of random synaptic dilution on recalling dynamics in an oscillator neural network, Katsunori Kitano and Toshio Aoyagi, Physical Review E, vol.57, no.5, 5914-5919 (1998).
  52. Effect of random synaptic dilution in oscillator neural networks, Toshio Aoyagi and Katsunori Kitano, Physical Review E, vol.55, no.6,, 7424-7428 (1997).
  53. Network of Neural Oscillators for Retrieving Phase Information, Toshio Aoyagi, Physical Review Letters, vol.74, no.20, 4075-4078 (1995).
  54. A Model for Feature Linking via Collective Oscillations in the Primary Visual Cortex, Tsuyoshi Chawanya, Toshio Aoyagi, Ikuko Nishikawa, Koji Okuda and Yoshiki Kuramoto, Biological Cybernetics, vo.68, no.6, 483-490 (1993).
  55. A Network of Bursting Neurons for Temporal Association, Toshio Aoyagi, Europhysics Letters, vol.20, no.6, 565-570 (1992).
  56. Neural Network Model Carrying Phase Information,Yoshiki Kuramoto, Toshio Aoyagi, Ikuko Nishikawa, Tsuyoshi Chawanya and Koji Okuda,Progress of theoretical Physics, vol.87, no.5, 1119-1126 (1992).
  57. Frequency order and wave patterns of mutual entrainment in two-dimensional oscillator lattices,
    Toshio Aoyagi and Yoshiki Kuramoto, Physics Letters A vol.155, no6-7, 410-414 (1991).

 


Proceedings

  1. Estimating the phase response curve of human walking using WSTA method, Tetsuro Funato, Yuki Yamamoto, Shinya Aoi, Nozomi Tomita, Takashi Imai, Toshio Aoyagi, Kazuo Tsuchiya, Proceedings of SICE Annual Conference 2013, 1298-1299 (2013).
  2. Co-evolving Network Dynamics between Reaction-Diffusive Resources on Nodes and Weighted Connections, Takaaki Aoki and Toshio Aoyagi, Proc. of 2012 International Symposium on Nonlinear Theory and its Applications (NOLTA2012), 574-577 (2012).
  3. Exploration for cortical dynamics with Monte Carlo sampling of learning rules, Takashi Hayakawa, Takeshi Kaneko, Yukito Iba and Toshio Aoyagi, The Proceedings of the 21st Annual Conference of the Japanese Neural Network Society, 56-57(2011).
  4. Emergence of multiple continuous attractors in coupled neuronal oscillators by inclusion of three-body interactions, Kaiichiro Ota, Takuma Tanaka, and Toshio Aoyagi, The Proceedings of the 21st Annual Conference of the Japanese Neural Network Society, 130-131(2011).
  5. Asymptotic behavior in a co-evolving network of neurons with synaptic plasticity, Yuri Kamitani, Takaaki Aoki, Toshio Aoyagi, The Proceedings of the 21st Annual Conference of the Japanese Neural Network Society, 126-127(2011).
  6. Self-organizing network of coupled neural oscillators with synaptic plasticity, Takaaki AOKI, Yuri KAMITANI and Toshio AOYAGI, Proc. of 2011 International Symposium on Nonlinear Theory and its Applications (NOLTA2011), 350-353 (2011).
  7. Self-organized behaviors in an adaptive network of movable oscillators, Takaaki Aoki and Toshio Aoyagi, 2010 International Symposium on Nonlinear Theory and its Applications (NOLTA2010), 410-403 (2010).
  8. Asymptotic states of a recurrent network under ongoing synaptic plasticity, Takaaki Aoki, Yuri Kamitani and Toshio Aoyagi, Neuroscience Research, Vol. 68, Supplement 1, e436 (2010).
  9. Simple and complex cell-like selectivity is reproduced by sparse coding model, Takuma Tanaka, Toshio Aoyagi and Takeshi Kaneko, Neuroscience Research, Vol. 68, Supplement 1, e380 (2010).
  10. Simple Model of a Neuronal Network Reproducing Synchronous Bursts Masaki Nomura, Daisuke Ito, Kazutoshi Gohara, Toshio Aoyagi, Proceedings MEA 2010, 199-200 (2010).
  11. A Novel Method of estimating the phase response function –Weighted spike-triggered average of fluctuating stimulus–, Toshio Aoyagi and Kaiichiro Ota, Proceedings of 3rd International Symposium on Mobiligence in Awaji, 379-382 (2009).
  12. Dendritic shape and EPSP conduction of cortical nonpyramidal cells, Yoshiyuki Kubota, Fuyuki Karube, Masaki Nomura, Toshio Aoyagi, Yasuo Kawaguchi, Neuroscience Research, Volume 65, Supplement 1, S84 (2009).
  13. Estimated connections that capture population burst-like activities, Masaki Nomura, Daisuke Ito, Hiroki Tamate, Kazutoshi Gohara, Toshio Aoyagi, Neuroscience Research, Volume 65, Supplement 1, S95 (2009).
  14. Higher-order structures in natural scenes, Takuma Tanaka, Toshio Aoyagi, and Takeshi Kaneko, Neuroscience Research, Volume 65, Supplement 1, S109 (2009).
  15. Experimental measurement of phase response curve employing fluctuation in rhythmic system, Kaiichiro Ota, Masaki Nomura, and Toshio Aoyagi, Neuroscience Research, Volume 65, Supplement 1, S232 (2009).
  16. Typical behaviors in co-evolving recurrent network of oscillatory neurons, Takaaki Aoki and Toshio Aoyagi, Frontiers in Systems Neuroscience. Conference Abstract: Computational and systems neuroscience. doi: 10.3389/conf.neuro.06.2009.03.005, (2009).
  17. Immunocytochemistry in low-density culture of neurons on multielectrode arrays is effective for identification of action-potential pathway, Daisuke Ito, Hiroki Tamate, Masaki Nomura, Toshio Aoyagi and Kazutoshi Gohara, Society for Neuroscience 38th annual meeting, 797.16(CD-ROM) (2008).
  18. Estimation of neuronal functional connectivity of cultured neuronal networks, Masaki Nomura, Dausuke Ito, Hiroki Tamate, Kazutoshi Gohara and Toshio Aoyagi, Neuroscience Research, 61S, S236 (2008).
  19. Estimation of neuronal functional connectivity of rats’ hippocampus CA1 performing a conditional discrimination task, Masaki Nomura, Yoshio Sakurai and Toshio Aoyagi, Neuroscience Research, 61S, S251 (2008).
  20. A novel method of measurement for phase response curves under noisy current injection, Kaiichiro Ota, Masaki Nomura and Toshio Aoyagi, Neuroscience Research, 61S, S73 (2008).
  21. Recurrent Infomax generates cell assembly, firing sequence, neuronal avalanche, and simple cell-like selectivity, Takuma Tanaka, Takeshi Kaneko, and Toshio Aoyagi, Neuroscience Research, 61S, S195 (2008).
  22. Ordering Process of Self-Organizing Maps Improved by Asymmetric Neighborhood Function, , Takaaki Aoki , Kaiichiro Ota , Koji Kurata , and Toshio Aoyagi, ICONIP2007, LNCS, vol. 4984 pp. 426-435, 2008.
  23. Synchrony-Induced switching behavior of attractors in neural network organized by spike-timing dependent plasticity、Takaaki Aoki, Toshio Aoyagi, Proceedings of 2nd International Symposium on Mobiligence in Awaji, pp.283-286, Awaji, Japan, (2007).
  24. Dendritic dimensions of cortical nonpyramidal cells, Yoshiyuki Kubota, Fuyuki Karube, Akio Sekigawa, Masaki Nomura, Toshio Aoyagi, Atsushi Mochizuki, Yasuo Kawaguchi, Society for Neuroscience 37th annual meeting, 470.20(CD-ROM) (2007).
  25. A cooperative dynamics of network of neural oscillators between the neuronal activity and the synatptic weight, Takaaki Aoki and Toshio Aoyagi, Neuroscience Research, Volume 58, Supplement 1, S112 (2007).
  26. Presynaptic AMPA receptors on the corticostriatal terminals enhance the release probability of the synaptic vesicles, Takuma Tanaka, Fumino Fujiyama, Masaki Nomura, Toshio Aoyagi and Takeshi Kaneko, Neuroscience Research, Volume 58, Supplement 1, S211 (2007).
  27. Yoshiyuki Kubota, Fuyuki Karube, Masaki Nomura, Toshio Aoyagi, Atsushi Mochizuki and Yasuo Kawaguchi, Dendritic dimensions of cortical nonpyramidal cells, Neuroscience Research, Volume 58, Supplement 1, S73 (2007).
  28. Masaki Nomura, Yoshio Sakurai and Toshio Aoyagi, Behavioral inference based on hippocampal multi-neuronal activities of rats, Neuroscience Research, Volume 58, Supplement 1,, S160 (2007).
  29. Optimal weighted networks of phase oscillators maximizing frequency and phase orders, Toshio Aoyagi, Yoshihiro Yoshii, Yukito Iba and Tsuyoshi Chawanya, STATPHYS 23, the 23rd International Conference on Statistical Physics of the International Union for Pure and Applied Physics (IUPAP) , pp225, (2007).
  30. Kernel Analysis Of Multi-neuronal Spike Trains, Masaki Nomura, Yoshio Sakurai and Toshio Aoyagi, 2007 IEEE/ICME International Conference on Complex Medical Engineering-CME2007, 68-71 CD-ROM (2007).
  31. Synchrony-Induced transition behaviors organized under spike-timing dependent plasticity for retrieving the memorized patterns, Takaaki Aoki1, Toshio Aoyagi, Neuroscience Research, 55, S239 (2006).
  32. Synchronization properties of a reduced model with a variety of firing patterns, Takashi Takekawa, Masaki Nomura, Toshio Aoyagi, Tomoki Fukai, Neuroscience Research, 55, S180 (2006).
  33. Roles of presynaptic AMPA receptors on corticostriatal terminals in up-states of medium-sized spiny neurons Takuma Tanaka, Fumino Fujiyama, Masaki Nomura, Toshio Aoyagi, Takeshi Kaneko, Neuroscience Research, 55, S120 (2006).
  34. Synchrony-asynchrony dynamics of inhibitory neurons in the thalamocortical loop, Masaki Nomura, Toshio Aoyagi, Neuroscience Research, 52, S34 (2005).
  35. Synchronized activities during slow-wave sleep in a cortex network model, Takashi Takekawa, Toshio Aoyagi, Tomoki Fukai, Neuroscience Research, 52, S94 (2005).
  36. Effect of incoming spike synchronization on retrieving information from sequential associative memory, Takaaki Aoki, Toshio Aoyagi, Neuroscience Research, 52, S208 (2005).
  37. Masaki Nomura and Toshio Aoyagi, Stability Analysis of Synchronous and Asynchronous Behavior in Periodically Spiking Neurons, The First International Conference on Complex Medical Engineering-CME2005, Program No.OS06.4 CD-ROM (2005).
  38. Takashi Takekawa, Toshio Aoyagi and Fukai Tomoki,The effects of the synaptic location on the synchronized activity in neural networks of fast rhythmic bursting neurons, Neuroscience Research, 50, S117 (2004).
  39. Masaki Nomura, Toshio Aoyagi, Stability of Synchronous Solutions in Weakly Coupled Neuron Networks, Neuroscience Research, 50, S120 (2004).
  40. The Degree of Synchrony Among Input Spike Trains Controlling The Function of Neural Networks, Toshio Aoyagi and Takaaki Aoki, SIXTH IBRO WORLD CONGRESS OF NEUROSCIENCE, Prague, Czech Republic(2003), no.4374.
  41. GAMMA-BAND SYNCHRONY IN A LOCAL CORTICAL NETWORK MODEL Masaki Nomura, Tomoki Fukai and Toshio Aoyagi, SIXTH IBRO WORLD CONGRESS OF NEUROSCIENCE, Prague, Czech Republic(2003), no.4383.
  42. Gamma-band synchrony in a local cortical network model, M. Nomura, T. Aoyagi and T. Fukai, Neuroscience Research 46 Supplement 1, S169 (2003).
  43. Short-term synaptic depression between FRB neurons improves both transient and stationary synchronization properties in the γ band, Takashi Takekawa, Toshio Aoyagi, Tomoki Fukai, Neuroscience Research, 46, Supplement 1,S146, (2003).
  44. Synchrony of fast-spiking interneurons interconnected by GABAergic and electrical synapses, Masaki Nomura, Tomoki Fukai, Toshio Aoyagi, 2002・Proceedings of the 9th International Joint Conference on Neural Information Processing, vol. 3, 1612-1616 (2002).
  45. Synchrony in fast-spiking interneurons connected simultaneously by gabaergic and electrical synapsesTomoki Fukai, Masaki Nomura, Toshio Aoyagi, Abstracts of Society for Neuroscience, Program No.558.13 (2002).
  46. Control of switching behavior between synchrony and asynchrony in a network of cortical pyramidal neurons, Toshio Aoyagi, Takashi Takekawa, Tomoki Fukai, Abstracts of Society for Neuroscience, Program No. 753.7 (2002).
  47. Effect of various ionic currents and network structures on generation of synchronized gamma oscillaitioni, Takashi Takekawa, Toshio Aoyagi, Takeshi Kaneko, Tomoki Fukai, Neuroscience Research, 45, Supplement 1, S95 (2002).
  48. Pacemaker neuron for cortical theta rhythm: a computational model, Tomoki Fukai, K. Kitano, Toshio Aoyagi, Y. Kang, Abstracts of Society for Neuroscience 31, Program No 47.7 (2001).
  49. Dynamical properties of networks of cortical neurons exhibiting gamma rhythmic bursts, Toshio Aoyagi, Takashi Takekawa, Youngnam Kang, Tomoki Fukai, Abstracts of Society for Neuroscience, Vol.31, Program No.47.7 (2001).
  50. Regulation of Synchronization properties in networks of bursting neurons, Toshio Aoyagi, Takashi Takekawa, Tomoki Fukai, Abstract of 21st IUPAP International Conference on Statistical Physics STATPHYS21, 164 (2001).
  51. Phase-coupling analysis of synchronization between circuits, each with an excitatory and an inhibitory cell, M. Nomura and T. Aoyagi, Neuroscience Research Supplement 25, S73 (2001).
  52. A synchrony-asynchrony transitions of the gamma-frequency bursting exhibited by chattering neurons in a cortical network, Takashi Takekawa, Toshio Aoyagi, Takeshi Kaneko, Youngnam Kang, Tomoki Fukai, Neuroscience Research, 39, Supplement 1, S102 (2001).
  53. Is the striatum a competitive network or a coincidence detection network?, Katsunori Kitano,Toshio Aoyagi, Tomoki Fukai, 2000・Abstracts of Society for Neuroscience Vol.30, Program No.360.7 (2000).
  54. A bursting mechanism of chattering neurons based on a novel type of calcium-dependent cationic current, Toshio Aoyagi, Nobuhiko Terada, Youngnam Kang, Takeshi Kaneko and Tomoki Fukai, Abstracts of Society for Neuroscience Vol.30, Program No.449.4 (2000).
  55. Is the striatum a competitive network or a coincidence detector network?, Katsunori Kitano, Toshio Aoyagi and Tomoki Fukai, Neuroscience Research, Vol.38, Supplement 1, S155 (2000).
  56. The network model of the prefrontal cortex for working memory showing sustained activities with low firing rates, Tomoki Fukai, Katsunori Kitano and Toshio Aoyagi, Neuroscience Research, Vol.38, Supplement 1, S147(2000).
  57. A bursting mechanism of chatering neurons and analysis of its synchronization, Toshio Aoyagi, Nobuhiko Terada, Youngnam Kang, Takeshi Kaneko and Tomoki Fukai, Neuroscience Research, Vol.38, Supplement 1, S5(2000).
  58. Mixed state on an oscillator neural network model for sparsely coded phase patterns、Masaki Nomura, Masato Okada, Toshio Aoyagi, International Conference on Dynamical Aspects of Complex Systems from Cells to Brain, International Convention Center, Sendai, JAPAN, PS40, 35 (2000).
  59. Synchronous and asynchronous activities in the competition of the cortical network models、Katsunori Kitano, Tomoki Fukai, Toshio Aoyagi, International Conference on Dynamical Aspects of Complex Systems from Cells to Brain, International Convention Center, Sendai, JAPAN, PS45, 37 (2000).
  60. A Bursting mechanism of chattering neurons and its synchronization、Toshio Aoyagi, Nobuhiko Terada, Youngnam Kang, Takeshi Kaneko and Tomoki Fukai, International Conference on Dynamical Aspects of Complex Systems from Cells to Brain, International Convention Center, Sendai, JAPAN, PS35, 33 (2000).
  61. Temporal Association Realized by a Network of Bursting Neurons, Toshio Aoyagi, Proceedings of International Joint Conference on Neural Networks 3, 2359-2362 (1993).
  62. Neural Nets and Phase Information, Yoshiki Kuramoto, Toshio Aoyagi, IkukoNishikawa, Tsuyoshi Chawanya and Koji Okuda, Extended Abstract of 10th Symposium on Future Electron Devices・FED-110, 157-162 (1991).

 


会議録 (in Japanese)

  1. 流体計算機の記憶容量について, 中嶋浩平, 青柳富誌生, 電子情報通信学会技術研究報告, vol. 115, no. 300, 109-112 (2015).
  2. 脳波データにおける位相振動子ネットワークの推定,小野島隆之,太田絵一郎,後藤貴宏,水原啓暁,青柳富誌生, 電子情報通信学会技術研究報告, vol. 115, no. 300, CCS2015-47, pp. 11-15, (2015).
  3. 異なる自然振動数分布を持つ複数位相振動子集団のダイナミクスについて, 寺田裕, 青柳富誌生, 電子情報通信学会技術研究報告, vol. 113, no. 383, 157-161 (2014).
  4. 三体相互作用を持つ位相振動子ネットワークに生じる複数の「連続的」なアトラクタについて, 太田絵一郎, 田中琢真, 青柳富誌生, 京都大学数理解析研究所講究録, No. 1827, 62-67 (2013).
  5. 位相記述可能性の観点で見た周期性の強いカオスの特徴, 今井貴史, 末谷大道, 青柳富誌生, 第72回 形の科学シンポジウム, 形の科学会誌, vol. 26, no. 2, pp. 241-242 (2011).
  6. 振動子の最適同期をもたらすネットワークの形, 茶碗谷毅, 伊賀志朗, 伊庭幸人, 青柳富誌生, 第72回 形の科学シンポジウム, 形の科学会誌, vol. 26, no. 2, pp. 245-246 (2011).
  7. 位相振動子ネットワークの可塑性に基づいた自律的な「群れ」の形状形成, 青木高明, 青柳富誌生, 第22回自律分散システム・シンポジウム, 171-174 (2010).
  8. 結合強度が変化する位相振動子ネットワークの自己組織化, 青木高明, 青柳富誌生, 電子情報通信学会技術研究報告, vol. 109, no. 458, 103-108 (2010).
  9. 位相応答曲線を用いたカオス振動子の同期予測, 今井貴史, 末谷大道, 青柳富誌生, 電子情報通信学会技術研究報告, vol. 109, no. 269, 97-102 (2009).
  10. 非対称近傍関数の導入による自己組織化マップの学習過程の高速化,太田絵一郎,青木高明,倉田耕治,青柳富誌生,電子情報通信学会技術研究報告,vol. 109, no. 1, 13-18 (2009).
  11. リカレント情報量最大化 : 素子の特性にばらつきのある場合, 堀卓也, 田中琢真, 青柳富誌生, 電子情報通信学会技術研究報告, vol. 109, no. 1, 19-24 (2009).
  12. 結合レスラー系を用いた連想記憶モデルのカーネル法による解析、野村真樹、青柳富誌生、物性研究、Vol.87、620(2007).
  13. 文字列カーネルを応用した多次元時系列データ解析、野村真樹,櫻井芳雄, 青柳富誌生、Proceedings The Tenth Workshop on Information-Based Induction Sciences IBIS2007、 第10回情報論的学習理論ワークショップ、 pp.109-114 (2007)
  14. 神経ネットワークにおける情報表現と機能発現、青柳富誌生、システム/制御/情報、Vol.49, No.12, 482-487(2005).
  15. 非線型振動子系のダイナミクスとその機能, 青柳富誌生、精密工学会誌, 64 巻 10 号, 1435-1438、(招待論文) (1998).
  16. ニューラルネットワーク~これからの統計力学的アプローチ~京大基研研究会報告, 青柳富誌生、物性研究, 70-3, 384 (1998).

 


総説、著書等 (in Japanese)

  1. 数理科学(2015年8月号) 特集:「力学系的思考法のすすめ」- いかにして数理現象を捉えるか -,「時系列情報から縮約力学系を抽出する」 ~リズム現象を題材として~ 、青柳富誌生、サイエンス社, 53-58 (2015).
  2. 第2版 現代数理科学事典、丸善(共著)、5章 神経脳科学、5.1.1神経細胞と脳の情報表現、5.1.2神経細胞の数理モデル、青柳富誌生、300-305、および5.2.1神経細胞集団と同期、青柳富誌生、308-311 (2009).
  3. シリーズ脳科学第1巻 脳の計算論、東大出版 (共著)、3章 リズム活動と位相応答、青柳富誌生、45-92 (2009).
  4. 脳の数理モデル 生命が獲得した情報処理のしくみ, 青柳富誌生、「数理工学のすすめ」(現代数学社), 81-85 (2004).
  5. 興奮性および抑制性神経回路における同期現象、青柳富誌生、日本神経回路学会誌、Vol.6(No.2), 99-105 (2003).
  6. 脳の情報表現:ニューロン,ネットワークと数理モデルIV 13 章位相振動子モデルによる同期・非同期解析, 青柳富誌生、朝倉書店、120-127 (2002).
  7. 脳の情報表現:ニューロン,ネットワークと数理モデルIV 11 章大脳皮質の錐体細胞とガンマ周波数帯のバースト発火-FRB ニューロンのモデル- 姜英男, 青柳富誌生、深井朋樹, 朝倉書店, 146-155 (2002).
  8. 脳科学大辞典 8.6 章非対称結合と時系列, 青柳富誌生、朝倉書店, 805-808 (2000).
  9. 別冊数理科学「脳科学の前線」-数理モデルを中心として-, 振動子の神経回路(動的なニューロンのモデルへの第一歩)、青柳富誌生、サイエンス社, 133-140 (1997).

 


特許 (in Japanese)

  1. SOMニューラルネット学習制御装置、青柳富誌生・青木高明,国立大学法人京都大学, 2005年8月18日、特願2005-238031

 


受賞等 (in Japanese)

  1. 流体計算機:水面のダイナミクスを用いた実時間計算の実装, 中嶋浩平, 青柳富誌生, 日本神経回路学会 第25回全国大会(2015/9/2-2015/9/4)において大会奨励賞を受賞
  2. データの能動的獲得に基づく一般化情報量最大化学習, 早川隆, 青柳富誌生, 第17回情報論的学習理論ワークショップ(2014/11/17-2014/11/19)において学生奨励賞を受賞

 


国際および国内学会発表等 (partially in Japanese)

上記に含まれない学会発表やセミナーでの講演等のリストはこちら >> 学会・研究会等発表リスト

 

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