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Identification of a stochastic neural firing rhythm lying in period-adding bifurcation and resembling chaos

Gu Hua-Guang Xi Lei Jia Bing

Identification of a stochastic neural firing rhythm lying in period-adding bifurcation and resembling chaos

Gu Hua-Guang, Xi Lei, Jia Bing
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  • To identify non-periodic neural rhythm to be chaos or stochasticity has been an important scientific thesis. A kind of non-periodic spontaneous firing pattern, whose behavior is transition between period-k burst in a string and period-k+1 burst in a string (k=1,2), lying between period-k bursting pattern and period-k+1 bursting pattern, is found in the experimental neural pacemaker. The deterministic structures of the firing are identified by nonlinear prediction and first return map of the interspike intervals (ISIs) series. The co-existence of the period-k bursting and period-k+1 bursting is manifested in the deterministic theoretical neuronal model, Chay model. Non-periodic firing patterns similar to the experimental observation are simulated in the co-existing parameter region, implying that the firing pattern is transition between two kinds of bursts induced by noise. A binary series can be acquired by transforming two kinds of bursts to symbols 0 and 1, respectively. The stochastic dynamics within the transitions between two kinds of bursts are detected by probability analysis on the binary series. It not only shows that the rhythm is stochastic firing with deterministic structures instead of chaos, but also provides the typical examples and effective methods to intensively identify the chaotic and stochastic firing patterns in a real nervous system.
      Corresponding author: , guhuaguang@263.net
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 11072135, 10772101, 10432010, 30300107) and the Fundamental Scientific Research Foundation for the Central Universities of China (Grant No. GK200902025).
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    Hayashi H, Ishzuka S, Hirakawa K 1983 Phys. Lett. A 98 474

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    Li L, Gu H G, Yang M H, Liu Z Q, Ren W 2004 Int. J. Bifur. Chaos 14 1813

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    Wang D, Mo J, Zhao X Y, Gu H G, Qu S X, Ren W 2010 Chin. Phys. Lett. 27 070503

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    Gu H G, Zhu Z, Jia B 2011 Acta Phys. Sin. 60 100505 (in Chinese) [古华光, 朱洲, 贾冰 2011 物理学报 60 100505]

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    Yang M H, Liu Z Q, Li L, Xu Y L, Liu H J, Gu H G, Ren W 2009 Int. J. Bifur. Chaos 19 453

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    Ren W, Hu S J, Zhang B J, Xu J X, Gong Y F 1997 Int. J. Bifur. Chaos. 7 1867

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    Gu H G, Yang M H, Li L, Liu Z Q, Ren W 2004 Dynam. Contin. Dis. B 11 19

    [13]

    Zhao X Y, Song S L, Wei C L, Gu H G, Ren W 2010 Acta Biophys. Sin. 26 61 (in Chinese) [赵小燕, 宋绍丽, 魏春玲, 古华光, 任维 2010 生物物理学报 26 61]

    [14]

    Xie Y, Xu J X, Kang Y M, Hu S J, Duan Y B 2003 Acta Phys. Sin. 52 1112 (in Chinese) [谢勇, 徐健学, 康艳梅, 胡三觉, 段玉斌 2003 物理学报 52 1112]

    [15]

    Fan Y S, Holden A V 1993 Chaos Solitons Fract. 3 439

    [16]

    Chay T R 1985 Physica D 16 233

    [17]

    Wu S G, He D R 2000 Chin. Phys. Lett. 76 398

    [18]

    Wu S G, He D R 2001 Commun. Theor. Phys. 35 272

    [19]

    Schiff S J, Jerger K, Duong D H 1994 Nature 370 615

    [20]

    Thomas E, William J R, Zbigniew J K, James E S, Karl E G, Niels B 1994 Physiol. Rev. 74 1

    [21]

    Lovejoy L P, Shepard P D, Canavier C C 2001 Neuroscience 104 829

    [22]

    Kanno T, Miyano T, Tokudac I, Galvanovskisd J, Wakui M 2007 Physica D 226 107

    [23]

    Hu S J, Yang H J, Jian Z, Long K P, Duan Y B, Wan Y H, Xing J L, Xu H, Ju G 2000 Neuroscience 101 689

    [24]

    So P 1998 Biophys J. 74 2776

    [25]

    Jian Z, Xing J L, Yang G S, Hu S J 2004 Neurosignals 13 150

    [26]

    Wan Y H, Jian Z, Hu S J 2000 Neuroreport 11 3295

    [27]

    Longtin A, Bulsara A, Moss F 1991 Phys. Rev. Lett. 67 656

    [28]

    Braun H A, Wissing H, Schäfer K, Hirsch M C 1994 Nature 367 270

    [29]

    Xing J L, Hu S J, Xu H, Han S, Wan Y H 2001 Neuroreport 12 1311

    [30]

    Gu H G, Ren W, Lu Q S, Wu S G, Yang M H, Chen W J 2001 Phys. Lett. A 285 63

    [31]

    Gong P L, Xu J X, Hu S J, Long K P 2002 Int. J. Bifur. Chaos 12 319

    [32]

    Gu H G, Jia B, Lu Q S 2011 Cogn. Neurodyn. 5 87

    [33]

    Gu H G, Zhang H M, Wei C L, Yang M H, Liu Z Q, Ren W 2011 Int. J. Mod. Phys. B 25 3977

    [34]

    Jia B, Gu H G, Li Y Y 2011 Chin. Phys. Lett. 28 090507

    [35]

    Huber M T, Krige J C, Braun H A, Pei X, Neiman A, Moss F 2000 Neurocomputing 32---33 823

    [36]

    Gu H G, Yang M H, Li L, Liu Z Q, Ren W 2003 Phys. Lett. A 319 89

    [37]

    Gu H G, Yang M H, Li L, Liu Z Q, Ren W 2003 Int. J. Mod. Phys. B 17 4195

    [38]

    Mannella R, Palleschi V 1989 Phys. Rev. A 40 3381

    [39]

    Theiler J, Eubank S, Longtin A, Galdrinkian B 1992 Physica D 58 77

    [40]

    Sauer T 1994 Phys. Rev. Lett. 72 3811

  • [1]

    May R M 1976 Nature 261 459

    [2]

    Gammaitoni L, Hänggi P, Jung P, Marchesoni F 1998 Rev. Mod. Phys. 70 22

    [3]

    Hayashi H, Ishzuka S, Ohta M, Hirakawa K 1982 Phys. Lett. A 88 435

    [4]

    Hayashi H, Ishzuka S, Hirakawa K 1983 Phys. Lett. A 98 474

    [5]

    Aihara K, Matsumoto G, Ikegaya Y 1984 J. Theor. Biol. 109 249

    [6]

    Hayashi H, Ishzuka S 1992 J. Theor. Biol. 156 269

    [7]

    Li L, Gu H G, Yang M H, Liu Z Q, Ren W 2004 Int. J. Bifur. Chaos 14 1813

    [8]

    Wang D, Mo J, Zhao X Y, Gu H G, Qu S X, Ren W 2010 Chin. Phys. Lett. 27 070503

    [9]

    Gu H G, Zhu Z, Jia B 2011 Acta Phys. Sin. 60 100505 (in Chinese) [古华光, 朱洲, 贾冰 2011 物理学报 60 100505]

    [10]

    Yang M H, Liu Z Q, Li L, Xu Y L, Liu H J, Gu H G, Ren W 2009 Int. J. Bifur. Chaos 19 453

    [11]

    Ren W, Hu S J, Zhang B J, Xu J X, Gong Y F 1997 Int. J. Bifur. Chaos. 7 1867

    [12]

    Gu H G, Yang M H, Li L, Liu Z Q, Ren W 2004 Dynam. Contin. Dis. B 11 19

    [13]

    Zhao X Y, Song S L, Wei C L, Gu H G, Ren W 2010 Acta Biophys. Sin. 26 61 (in Chinese) [赵小燕, 宋绍丽, 魏春玲, 古华光, 任维 2010 生物物理学报 26 61]

    [14]

    Xie Y, Xu J X, Kang Y M, Hu S J, Duan Y B 2003 Acta Phys. Sin. 52 1112 (in Chinese) [谢勇, 徐健学, 康艳梅, 胡三觉, 段玉斌 2003 物理学报 52 1112]

    [15]

    Fan Y S, Holden A V 1993 Chaos Solitons Fract. 3 439

    [16]

    Chay T R 1985 Physica D 16 233

    [17]

    Wu S G, He D R 2000 Chin. Phys. Lett. 76 398

    [18]

    Wu S G, He D R 2001 Commun. Theor. Phys. 35 272

    [19]

    Schiff S J, Jerger K, Duong D H 1994 Nature 370 615

    [20]

    Thomas E, William J R, Zbigniew J K, James E S, Karl E G, Niels B 1994 Physiol. Rev. 74 1

    [21]

    Lovejoy L P, Shepard P D, Canavier C C 2001 Neuroscience 104 829

    [22]

    Kanno T, Miyano T, Tokudac I, Galvanovskisd J, Wakui M 2007 Physica D 226 107

    [23]

    Hu S J, Yang H J, Jian Z, Long K P, Duan Y B, Wan Y H, Xing J L, Xu H, Ju G 2000 Neuroscience 101 689

    [24]

    So P 1998 Biophys J. 74 2776

    [25]

    Jian Z, Xing J L, Yang G S, Hu S J 2004 Neurosignals 13 150

    [26]

    Wan Y H, Jian Z, Hu S J 2000 Neuroreport 11 3295

    [27]

    Longtin A, Bulsara A, Moss F 1991 Phys. Rev. Lett. 67 656

    [28]

    Braun H A, Wissing H, Schäfer K, Hirsch M C 1994 Nature 367 270

    [29]

    Xing J L, Hu S J, Xu H, Han S, Wan Y H 2001 Neuroreport 12 1311

    [30]

    Gu H G, Ren W, Lu Q S, Wu S G, Yang M H, Chen W J 2001 Phys. Lett. A 285 63

    [31]

    Gong P L, Xu J X, Hu S J, Long K P 2002 Int. J. Bifur. Chaos 12 319

    [32]

    Gu H G, Jia B, Lu Q S 2011 Cogn. Neurodyn. 5 87

    [33]

    Gu H G, Zhang H M, Wei C L, Yang M H, Liu Z Q, Ren W 2011 Int. J. Mod. Phys. B 25 3977

    [34]

    Jia B, Gu H G, Li Y Y 2011 Chin. Phys. Lett. 28 090507

    [35]

    Huber M T, Krige J C, Braun H A, Pei X, Neiman A, Moss F 2000 Neurocomputing 32---33 823

    [36]

    Gu H G, Yang M H, Li L, Liu Z Q, Ren W 2003 Phys. Lett. A 319 89

    [37]

    Gu H G, Yang M H, Li L, Liu Z Q, Ren W 2003 Int. J. Mod. Phys. B 17 4195

    [38]

    Mannella R, Palleschi V 1989 Phys. Rev. A 40 3381

    [39]

    Theiler J, Eubank S, Longtin A, Galdrinkian B 1992 Physica D 58 77

    [40]

    Sauer T 1994 Phys. Rev. Lett. 72 3811

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  • Received Date:  23 August 2011
  • Accepted Date:  28 April 2012
  • Published Online:  20 April 2012

Identification of a stochastic neural firing rhythm lying in period-adding bifurcation and resembling chaos

    Corresponding author: guhuaguang@263.net
  • 1. College of Physics and Information Technology, Shaanxi Normal University, Xi'an 710062, China;
  • 2. College of Life Sciences, Shaanxi Normal University, Xi’an 710062, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant Nos. 11072135, 10772101, 10432010, 30300107) and the Fundamental Scientific Research Foundation for the Central Universities of China (Grant No. GK200902025).

Abstract: To identify non-periodic neural rhythm to be chaos or stochasticity has been an important scientific thesis. A kind of non-periodic spontaneous firing pattern, whose behavior is transition between period-k burst in a string and period-k+1 burst in a string (k=1,2), lying between period-k bursting pattern and period-k+1 bursting pattern, is found in the experimental neural pacemaker. The deterministic structures of the firing are identified by nonlinear prediction and first return map of the interspike intervals (ISIs) series. The co-existence of the period-k bursting and period-k+1 bursting is manifested in the deterministic theoretical neuronal model, Chay model. Non-periodic firing patterns similar to the experimental observation are simulated in the co-existing parameter region, implying that the firing pattern is transition between two kinds of bursts induced by noise. A binary series can be acquired by transforming two kinds of bursts to symbols 0 and 1, respectively. The stochastic dynamics within the transitions between two kinds of bursts are detected by probability analysis on the binary series. It not only shows that the rhythm is stochastic firing with deterministic structures instead of chaos, but also provides the typical examples and effective methods to intensively identify the chaotic and stochastic firing patterns in a real nervous system.

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