Ю. Г. Древс, А. С. Мигалев

Данный обзор посвящен исследованию, моделированию и применению синаптической пластичности, зависящей от момента времени импульса. Рассматриваются работы по экспериментальному исследованию данного типа пластичности на мозге животных, теоретическому исследованию его функций и свойств, а также современные методы моделирования и его применение для решения технических задач

1. Никколс Д., Мартин Р., Валлас Б., Пол Ф. От нейрона к мозгу / Пер. С англ. П. М. Балабана, А. В. Галкина, Р. А. Гиниатуллина, Р. Н. Хазипова, Л. С. Хируга. М.: Едиториал УРСС. 2003. 672 с.
2. Purves D., Augustine G.J., Fitzpatrick D., Hall W.C. Anthony-Samuel Lamantia (Editor), McNamara J. O., Williams S. M.  Neuroscience // Sinauer Associates. June 2004. 773 pp.
3. Скребицкий В.Г. Синаптическая пластичность как проблема в нейрофизиологии // ВЕСТНИК РФФИ. Декабрь 2004. № 4(38).
4. Bi G-Q., Poo M.M. Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type // J. Neurosci. 1998 Dec. 15; 18(24) Р. 10464-72.
5. Abbott L.F., Gerstner W. Homeostasis and learning through spike-timing dependent plasticity // In D. Hansel, C. Chow, B. Gutkin, and C. Meunier,  editors, Methods and Models in Neurophysics, 2004.
6. Dan Y., Poo M.M. Spike timing-dependent plasticity: from synapse to perception // Physiol Rev. 2006 Jul. V. 86. № 3. Р. 1033-48
7. Song S., Miller K.D., Abbott L.F. Competitive Hebbian learning through spike-timing-dependent synaptic plasticity // Nat Neurosci. 2000. V. 3. № 9. Р. 919-26.
8. Froemke R.C., Dan Y. Spike-timing-dependent synaptic modification induced by natural spike trains // Nature. 2002 Mar. V. 28; 416(6879). P. 433-8.
9. Nelson S.B., Sjöström P.J., Turrigiano G.G. Rate and timing in cortical synaptic plasticity // Philos Trans R Soc Lond B Biol Sci. 2002 Dec. V. 29; 357(1428). P. 1851-7.
10. Kampa B.M., Letzkus J.J., Stuart G.J.  Requirement of dendritic calcium spikes for induction of spike-timing-dependent synaptic plasticity // J. Physiol. 2006 Jul. V. 1;574(Pt. 1). P. 283-90. Epub. 2006 May 4.
11. Kampa B.M., Stuart G.J. Calcium spikes in basal dendrites of layer 5 pyramidal neurons during action potential bursts // J. Neurosci. 2006 Jul. V. 12; 26(28). P. 7424-32.
12. Kobayashi K, Poo M.M. Spike train timing-dependent associative modification of hippocampal CA3 recurrent synapses by mossy fibers // Neuron. 2004 Feb. V. 5; 41(3). P. 445-54.
13. Froemke R.C., Tsay I.A., Raad M., Long J.D., Dan Y. Contribution of individual spikes in burst-induced long-term synaptic modification // J. Neurophysiol. 2006 Marh. V.95(3). P. 1620-9. Epub 2005 Nov. 30.
14. Wang H.X., Gerkin R.C., Nauen D.W., Bi G-Q. Coactivation and timing-dependent integration of synaptic potentiation and depression // Nat. Neurosci. 2005 Feb. V. 8(2). P. 187-93. Epub 2005 Jan 16.
15. Haas J.S., Nowotny T., Abarbanel H.D. Spike-timing-dependent plasticity of inhibitory synapses in the entorhinal cortex // J. Neurophysiol. 2006 Dec. V. 96(6). P. 3305-13. Epub 2006 Aug 23.
16. Tzounopoulos T., Rubio M.E., Keen J.E., Trussell L.O. Coactivation of pre- and postsynaptic signaling mechanisms determines cell-specific spike-timing-dependent plasticity // Neuron. 2007 Apr. V. 19; 54(2). P. 291-301.
17. Rumsey C.C., Abbott L.F. Synaptic democracy in active dendrites // J. Neurophysiol. 2006 Nov. V. 96(5). P. 2307-18. Epub 2006 Jul 12.
18. Letzkus J.J., Kampa B.M., Stuart G.J. Learning rules for spike timing-dependent plasticity depend on dendritic synapse location // J. Neurosci. 2006 Oct. V. 11; 26(41). P. 10420-9.
19. Lu J.T., Li C.Y., Zhao J.P., Poo M.M. Zhang XH.  Spike-timing-dependent plasticity of neocortical excitatory synapses on inhibitory interneurons depends on target cell type // J. Neurosci. 2007 Sep. V. 5; 27(36). P. 9711-20.
20. Izhikevich E.M., Gally J.A., Edelman G.M. Spike-timing dynamics of neuronal groups // Cereb Cortex. 2004 Aug. V. 14(8). P. 933-44. Epub 2004 May 13.
21. Masquelier T., Guyonneau R., Thorpe S.J. Spike timing dependent plasticity finds the start of repeating patterns in continuous spike trains // Cereb Cortex. 2004 Aug. V. 14(8). P. 933-44. Epub 2004 May 13.
22. Young J.M., Waleszczyk W.J., Wang C., Calford M.B., Dreher B., Obermayer K. Cortical reorganization consistent with spike timing-but not correlation-dependent plasticity // Nat. Neurosci. 2007 Jul. V. 10(7). P. 887-95. Epub 2007 May 27.
23. Nowotny T., Zhigulin V.P., Selverston A.I., Abarbanel H.D., Rabinovich M.I. Enhancement of synchronization in a hybrid neural circuit by spike-timing dependent plasticity // J. Neurosci. 2003 Oct. 29;23(30). P. 9776-85.
24. Masuda N., Kori H. Formation of feedforward networks and frequency synchrony by spike-timing-dependent plasticity // J. Comput Neurosci. 2007 Jun.; V. 22(3). P. 327-45. Epub 2007 March 28.
25. Hopfield J.J., Brody C.D. Learning rules and network repair in spike-timing-based computation networks // Proc. Natl Acad. Sci. USA. 2004 Jan. V. 6;101(1). P. 337-42. Epub 2003 Dec. 23.
26. Toyoizumi T., Pfister J-P., Aihara K., Gerstner W. Spike-timing dependent plasticity and mutual information maximization for a spiking neuron model // Advances in Neural Information Processing Systems 17, 2005, p. 1409-1416 MIT Press, 2005.
27. Gerstner W., Kistler W.M. Spiking Neuron Models: Single Neurons, Populations, Plasticity // Cambridge University Press; 1 edition (August 15, 2002), 400 pp.  
28. Bohte S.M., Mozer M.C. Reducing spike train variability:a computational theory of spike-timing dependent plastisity // Proceedings of advances in neural information processing (NIPS)17 Vancouver, Canada, 2004
29. Pfister J.P., Toyoizumi T., Barber D., Gerstner W. Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning // Neural Comput. 2006 Jun. V. 18(6). P. 1318-48.
30. Carr C.E., Konishi M. A circuit for detection of interaural time differences in the brain stem of the barn owl // J. Neurosci. 1990 Oct; V. 10(10). P. 3227-46.
31. Fetz E.E., Baker M.A. Operantly conditioned patterns on precentral unit activity and correlated responses in adjacent cells and contralateral muscles // J. Neurophysiol. 1973 March. V. 36(2). P. 179-204.
32. Fetz E.E. Volitional control of neural activity: implications for brain-computer interfaces // J. Physiol. 2007 March. V. 15; 579(Pt 3). V. 571-9. Epub 2007 Jan 18.
33. Chapin J.K., Moxon K.A., Markowitz R.S., Nicolelis M.A.  Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex // Nat. Neurosci. 1999 Jul. V. 2(7). P. 664-70.
34. Carmena J.M., Lebedev M.A., Crist R.E., O'Doherty J.E., Santucci D.M., Dimitrov D.F., Patil P.G., Henriquez C.S., Nicolelis M.A. Learning to control a brain-machine interface for reaching and grasping by primates // PLoS Biol. 2003 Nov. V. 1(2). P. E42. Epub 2003 Oct. 13.
35. Taylor D.M., Tillery S.I., Schwartz A.B. Direct cortical control of 3D neuroprosthetic devices // Science. 2002 Jun. V.  7; 296(5574). P. 1829-32.
36. Velliste M., Perel S., Spalding M.C., Whitford A.S., Schwartz A.B. Cortical control of a prosthetic arm for self-feeding // Nature. 2008 Jun. V. 19; 453(7198). P. 1098-101. Epub 2008 May 28.
37. Legenstein R., Pecevski D., Maass W. Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity // Proceedings of advances in neural information processing (NIPS) 2007, 3-8 Dec 2007, Vancouver, Canada.
38. Izhikevich E.M. Solving the distal reward problem through linkage of STDP and dopamine signaling // Cereb Cortex. 2007 Oct. V. 17(10). P. 2443-52. Epub 2007 Jan. 13.
39. Legenstein R., Pecevski D., Maass W. Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity // Proceedings of advances in neural information processing 2007 (NIPS 2007). December 5, 2007
40. Schultz W. Predictive reward signal of dopamine neurons // J. Neurophysiol. 1998 Jul. V. 80(1). P. 1-27.
41. Bartlett P.L., Baxter J. Estimation and approximation bounds for gradient-based reinforcement learning // Proceedings of the Thirteenth Annual Conference on Computational Learning Theory. 2000. P. 133-141.
42. Baxter J., Bartlett H.L. Infinite-horizon policy-gradient estimation // Journal of Artificial Intelligence Research. 2001. 15. P. 319-350.
43. Florian R.V. Reinforcement learning through modulation of spike-timing-dependent synaptic plasticity // Neural Computation. 2007. 19(6). P. 1468-1502.
44. Cai Y., Gavornik J.P., Cooper L.N., Yeung L.C., Shouval H.Z. Effect of stochastic synaptic and dendritic dynamics on synaptic plasticity in visual cortex and hippocampus // J. Neurophysiol. 2007 Jan.; V. 97(1). P. 375-86. Epub 2006. Oct. 11.
45. Pfister J.P., Gerstner W. Triplets of spikes in a model of spike timing-dependent plasticity // J. Neurosci. 2006 Sep. V. 20; 26(38). P. 9673-82.
46. Liu X., Wang Y., Zhou C. A new formula of synaptic plasticity based on STDP and its implications // International Conference on Neural Networks and Brain, 2005 (ICNN&B '05).
47. Standage D., Trappenberg T. The trouble width weight-dependent STDP // Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, USA, August 12-17, 2007.
48. Dockendorf K.P., DeMarse T.B. Amplitude and spike timing dependent plasticity // Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, USA, August 12-17, 2007.
49. Schemmel J., Meier K., Mueller E. A new VLSI model of neural microcircuits including spike time dependent plasticity // Proceedings of International Joint Conference on Neural Networks, Budapest, Hungary, 25-29 July, 2004.
50. Mehrtash N., Jung D., Hellmich H.H., Schoenauer T., Lu V.T., Klar H. Synaptic plasticity in spiking neural networks (SP2INN): a system approach //  IEEE Transactions on  Neural Networks. Sept. 2003. V. 14, Is. 5. P. 980-992.
51. Schaefer M., Schoenauer T., Wolff C.,  Hartmann G., Klar H., Ruckert U. Simulation of spiking neural networks - architectures and implementations // Elsevier,  Neurocomputing. October 2002. V. 48, № 1. Р. 647-679(33).
52. Grassmann C., Schoenauer T., Wolff C. PCNN neurocomputers - event driven and parallel architectures //  European Symposium on Artificial Neural Networks (ESANN'2002). Belgium, 24-26 April 2002. Р. 331-336.
53. Indiveri, G., Chicca, E., Douglas, R. A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity // Transactions on Neural Networks, IEEE. Volume 17, Issue 1, Jan. 2006 Page(s): 211 - 221.
54. Vogelstein R.J. Mallik U., Vogelstein J.T., Cauwenberghs G. Dynamically reconfigurable silicon array of spiking neurons with conductance-based synapses // IEEE Transactions on Neural Networks. Jan. 2007. V. 18. Is. 1. Р. 253-265.
55. Renaud S., Tomas J., Bornat Y., Daouzli A., Saighi S.  Neuromimetic ICs with analog cores: an alternative for simulating spiking neural networks // IEEE International Symposium on  Circuits and Systems (ISCAS 2007), New Orleans, LA,  2007. 27-30 May 2007.
56. Arena P., Fortuna L., Frasca M., Patane L., Sala C. Integrating high-level sensor features via STDP for bio-inspired navigation // IEEE International Symposium on Circuits and Systems, 2007. ISCAS 2007. New Orleans, LA. May 2007. Р. 609-612.
57. Nielsen, J., Lund, H.H. Spiking neural building block robot with Hebbian learning // International Conference on Intelligent Robots and Systems, 2003. (IROS 2003). Oct. 2003. V. 2. Р. 1363-1369.
58. Mokhtar M., Halliday D.M., Tyrrel A. M. Autonomus navigational controller inspired by the hyppocampus // Proceedings of international joint conference on neural networks , Oriando, Florida, USA, August 12-17, 2007.
59. Tovar G.M., Fukuda E.S., Asai T., Hirose T., Amemiya Y. Neuromorphic CMOS circuits implementing a novel neural segmentation model based on symmetric STDP learning // International Joint Conference on Neural Networks, 2007. (IJCNN 2007). Orlando, Florida. Aug. 2007. Р. 897-901.
60. Koickal T.J. Hamilton A., Tan S.L., Covington J.A., Gardner J.W., Pearce T.C. Analog VLSI Circuit Implementation of an Adaptive Neuromorphic Olfaction Chip //  IEEE Transactions on  Circuits and Systems I: Regular Papers, [ IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications]. Jan. 2007. V. 54. Is. 1. Р. 60-73.
61. Cameron, K. Murray, A. Collins, S. Spike timing dependent adaptation for mismatch compensation // International Symposium on Circuits and Systms, 2006. (ISCAS 2006). 21-24 May 2006. Рage(s): 4. Р. 1223-226.
62. Cameron K., Boonsobhak V., Murray A., Renshaw D. Spike timing dependent plasticity (STDP) can ameliorate process variations in neuromorphic VLSI // IEEE Transactions on Neural Networks. Nov. 2005. V. 16. Is. 6. Р. 1626-1637.
63. Yang Z., Murray A., Worgotter F., Cameron K., Boonsobhak V. A neuromorphic depth-from-motion vision model with STDP adaptation // IEEE Transactions on Neural Networks. March 2006. V. 17. Is. 2. P. 482-495.
64. Gupta A., Long L.N. Character recognition using spiking neural networks // International Joint Conference on Neural Networks, 2007(IJCNN 2007) Orlando, FL,. Aug. 2007. Р. 53-58.
65. Saeki K., Hayashi Y., Sekine Y. Extraction of Phase Information Buried in Fluctuation of a Pulse-type Hardware Neuron Model Using STDP //  International Joint Conference on Neural Networks, 2006. (IJCNN apos;06) Vancouver, BC. Volume, Issue, 0-0 0 Page(s):1505-1510.
66. Bofill-i-Petit A., Murray A.F. Synchrony detection and amplification by silicon neurons with STDP synapses // IEEE Transactions on neural networks. 2004. V. 15. № 5.
67. Maass W., Bishop C.M. Pulsed neural networks // The MIT Press (March 1, 2001) 407 pp.