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噪声广泛存在于生物神经系统中,对系统功能具有重要作用.采用神经元二维映射模型构建一个复杂神经网络,由多个小世界子网络构成,研究了Gaussian白噪声诱导的随机共振现象.研究发现,只有合适的噪声强度才能使神经网络对输入刺激信号的频率响应达到峰值.另外,网络结构对系统随机共振特性有重要影响.在固定的耦合强度下,存在一个最优的局部小世界子网络结构,使得整个系统的频率响应最佳.
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关键词:
- 神经元二维映射模型 /
- Gaussian白噪声 /
- 随机共振 /
- 小世界网络
Noise exists widely in biological neural systems, and plays an important role in system functions. A complex neural network, which contains several small-world subnetworks, is constructed based on a two-dimensional neural map. The phenomenon of stochastic resonance induced by Gaussian white noise is studied. It is found that only with an appropriate noise, can the frequency response of the network to input signal reach a peak value. Moreover, network structure has an important influence on the stochastic resonance of the neural system. With a fixed coupling strength, there exists an optimal local small-world topology, which can offer the best frequency response of the network.-
Keywords:
- two-dimensional neural map /
- Gaussian white noise /
- stochastic resonance /
- small-world network
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-
[1] Gammaitoni L, Hanggi P, Jung P, Marchesoni F 1998 Rev. Mod. Phys. 70 233
[2] Wang B H, Lu Q S, Lu S J 2009 Acta Phys. Sin. 58 7458 (in Chinese) [王宝华, 陆启韶, 吕淑娟 2009 58
[3] [4] Benzi R, Sutera A, Vulpiani A 1981 J. Phys. A 14 453
[5] [6] [7] Zhang X Y, Xu W, Zhou B C 2011 Acta Phys. Sin. 60 060514 (in Chinese) [张晓燕, 徐伟, 周丙常 2011 60 060514]
[8] Schwarzkopf D S, Silvanto J, Rees G 2011 J. Neurosci. 31 3143
[9] [10] White J A, Rubinstein J T, Kay A R 2000 Trends Neurosci. 23 131
[11] [12] [13] Song Y, Zhao T J, Liu J W, Wang X Q, Zhan Y 2006 Acta Phys. Sin. 55 4020 (in Chinese) [宋扬, 赵同军, 刘金伟, 王向群, 展永 2006 55 4020]
[14] [15] Wang M S, Huang W X, Cui Z F 2010 Acta Phys. Sin. 59 4485 (in Chinese) [汪茂胜, 黄万霞, 崔执凤 2010 59 4485]
[16] [17] Kosko B, Mitaim S 2003 Neural Networks 16 755
[18] Levin J E, Miller J P 1996 Nature 380 165
[19] [20] Kanamaru T, Okabe Y 2000 Phys. Rev. E 62 2629
[21] [22] Mato G 1998 Phys. Rev. E 58 876
[23] [24] [25] Lee S G, Kim S 1999 Phys. Rev. E 60 826
[26] Hasefawa H 2002 Phys. Rev. E 66 021902
[27] [28] Patel A, Kosko B 2005 Neural Networks 18 467
[29] [30] [31] Stocks N G, Mannella R 2001 Phys. Rev. E 64 30902
[32] [33] Zhang G J, Xu J X 2005 Acta Phys. Sin. 54 557 (in Chinese) [张广军, 徐建学 2005 54 557]
[34] [35] Shimokawa T, Pakdaman K, Sato S 1999 Phys. Rev. E 59 3427
[36] Kang Y M, Xu J X, Xie Y 2005 Chaos, Solitons and Fractals 25 165
[37] [38] [39] Wang M S 2009 Acta Phys. Sin. 58 6833 (in Chinese) [汪茂胜 2009 58 6833]
[40] [41] Perc M 2007 Phys. Rev. E 76 066203
[42] [43] Zhou X R, Luo X S, Jiang P Q, Yuan W J 2007 Acta Phys. Sin. 56 5679 (in Chinese) [周小荣, 罗晓曙, 蒋品群, 袁五届 2007 56 5679]
[44] Ozer M, Perc M, Uzuntarla M 2009 Phys. Lett. A 373 964
[45] [46] [47] Bullmore E, Sporns O 2009 Nature 10 186
[48] [49] Zamora-Lopez G, Zhou C, Kurths J 2010 Front Neuroinformatics 41
[50] Rulkov N F 2001 Phys. Rev. Lett. 86 183
[51] [52] Rulkov N F 2002 Phys. Rev. E 65 041922
[53] [54] Watts D J, Strogatz S H 1998 Nature 393 440
[55] [56] [57] Pikovsky A, Zaikin A 2002 Phys. Rev. Lett. 88 050601
[58] [59] Barlow H B, Levick W R, Yoon M 1971 Vision Res. 11 87
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