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The role of neural architecture and the speed of signal propagation in the process of synchronization of bursting neurons

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  • Gosak, Marko
  • Markovič, Rene
  • Marhl, Marko

Abstract

Synchronized neuronal activity has been observed at all levels of human and any other nervous systems and was suggested as particularly relevant in information processing and coding. In the present paper we investigate the synchronization of bursting neuronal activity. Motivated by the fact that in neural systems the interplay between the network structure and the dynamics taking place on it is closely interrelated, we develop a spatial network representation of neural architecture in which we can tune the network organization between a scale-free network with dominating long-range connections and a homogeneous network with mostly adjacent neurons connected. Our results reveal that the most synchronized response is obtained for the intermediate regime where long- as well as short-range connections constitute the neural architecture. Moreover, the optimal response is additionally enhanced when the speed of signal propagation is optimized.

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  • Gosak, Marko & Markovič, Rene & Marhl, Marko, 2012. "The role of neural architecture and the speed of signal propagation in the process of synchronization of bursting neurons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2764-2770.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:8:p:2764-2770
    DOI: 10.1016/j.physa.2011.12.027
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    References listed on IDEAS

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    1. Hao, Yinghang & Gong, Yubing & Wang, Li & Ma, Xiaoguang & Yang, Chuanlu, 2011. "Single or multiple synchronization transitions in scale-free neuronal networks with electrical or chemical coupling," Chaos, Solitons & Fractals, Elsevier, vol. 44(4), pages 260-268.
    2. Jorge J. Palop & Jeannie Chin & Lennart Mucke, 2006. "A network dysfunction perspective on neurodegenerative diseases," Nature, Nature, vol. 443(7113), pages 768-773, October.
    3. M. R. Mehta & A. K. Lee & M. A. Wilson, 2002. "Role of experience and oscillations in transforming a rate code into a temporal code," Nature, Nature, vol. 417(6890), pages 741-746, June.
    4. Batista, C.A.S. & Batista, A.M. & de Pontes, J.C.A. & Lopes, S.R. & Viana, R.L., 2009. "Bursting synchronization in scale-free networks," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2220-2225.
    5. Agnes, E.J. & Erichsen, R. & Brunnet, L.G., 2010. "Synchronization regimes in a map-based model neural network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 651-658.
    6. Li, Tao & Fei, Shu-min & Zhang, Kan-jian, 2008. "Synchronization control of recurrent neural networks with distributed delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 982-996.
    7. de Pontes, J.C.A. & Viana, R.L. & Lopes, S.R. & Batista, C.A.S. & Batista, A.M., 2008. "Bursting synchronization in non-locally coupled maps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4417-4428.
    8. Wang, Kai & Teng, Zhidong & Jiang, Haijun, 2008. "Adaptive synchronization of neural networks with time-varying delay and distributed delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 631-642.
    9. Sun, Yongzheng & Zhao, Donghua & Ruan, Jiong, 2010. "Consensus in noisy environments with switching topology and time-varying delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4149-4161.
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    Cited by:

    1. Markovič, Rene & Gosak, Marko & Marhl, Marko, 2014. "Broad-scale small-world network topology induces optimal synchronization of flexible oscillators," Chaos, Solitons & Fractals, Elsevier, vol. 69(C), pages 14-21.
    2. Liu, Chen & Wang, Jiang & Yu, Haitao & Deng, Bin & Wei, Xile & Sun, Jianbing & Chen, Yingyuan, 2013. "The effects of time delay on the synchronization transitions in a modular neuronal network with hybrid synapses," Chaos, Solitons & Fractals, Elsevier, vol. 47(C), pages 54-65.
    3. Gong, Yubing & Wang, Li & Xu, Bo, 2012. "Delay-induced diversity of firing behavior and ordered chaotic firing in adaptive neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 45(4), pages 548-553.

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