Delay-aided stochastic multiresonances on scale-free FitzHugh－Nagumo neuronal networks

doi:10.1088/1674-1056/19/4/040508

中国物理B ›› 2010, Vol. 19 ›› Issue (4): 40508-40508.doi: 10.1088/1674-1056/19/4/040508

Delay-aided stochastic multiresonances on scale-free FitzHugh－Nagumo neuronal networks

Perc Matja{\v¹, 甘春标², 王青云³

(1)Department of Physics, Faculty of Natural Sciences and Mathematics, University of Maribor, Koro{\v ska Cesta 160, SI-{\rm 2000 Maribor, Slovenia; (2)Institute of Applied Mechanics, School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, China; (3)School of Aeronautic and Engineering Science, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;School of Statistics and Mathematics, Inner Mongolia Finance and Economics College, Huhhot 010071, China

收稿日期:2009-06-11 修回日期:2009-10-16 出版日期:2010-04-15 发布日期:2010-04-15
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos.~10672140, 10972001 and 10832006). Matja{\v z} Perc individually acknowledges the Support from the Slovenian Research Agency (Grant Nos.~Z1-9629 and Z1-2032-2547).

Delay-aided stochastic multiresonances on scale-free FitzHugh－Nagumo neuronal networks

Gan Chun-Biao(甘春标)^a), Perc Matjaž^b), and Wang Qing-Yun(王青云)^c)d)†

^a Institute of Applied Mechanics, School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, China; ^b Department of Physics, Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška Cesta 160, SI-2000 Maribor, Slovenia; ^c School of Aeronautic and Engineering Science, Beijing University of Aeronautics and Astronautics, Beijing 100191, China; ^dSchool of Statistics and Mathematics, Inner Mongolia Finance and Economics College, Huhhot 010071, China

Received:2009-06-11 Revised:2009-10-16 Online:2010-04-15 Published:2010-04-15
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos.~10672140, 10972001 and 10832006). Matja{\v z} Perc individually acknowledges the Support from the Slovenian Research Agency (Grant Nos.~Z1-9629 and Z1-2032-2547).

摘要/Abstract

摘要： The stochastic resonance in paced time-delayed scale-free FitzHugh--Nagumo (FHN) neuronal networks is investigated. We show that an intermediate intensity of additive noise is able to optimally assist the pacemaker in imposing its rhythm on the whole ensemble. Furthermore, we reveal that appropriately tuned delays can induce stochastic multiresonances, appearing at every integer multiple of the pacemaker's oscillation period. We conclude that fine-tuned delay lengths and locally acting pacemakers are vital for ensuring optimal conditions for stochastic resonance on complex neuronal networks.

Abstract: The stochastic resonance in paced time-delayed scale-free FitzHugh--Nagumo (FHN) neuronal networks is investigated. We show that an intermediate intensity of additive noise is able to optimally assist the pacemaker in imposing its rhythm on the whole ensemble. Furthermore, we reveal that appropriately tuned delays can induce stochastic multiresonances, appearing at every integer multiple of the pacemaker's oscillation period. We conclude that fine-tuned delay lengths and locally acting pacemakers are vital for ensuring optimal conditions for stochastic resonance on complex neuronal networks.

Key words: neuronal networks, delay, stochastic resonance

中图分类号: (Neural engineering)

87.85.Wc

87.85.Xd (Dynamical, regulatory, and integrative biology) 87.18.Sn (Neural networks and synaptic communication) 89.75.Hc (Networks and genealogical trees)

甘春标, Perc Matja{\v, 王青云. Delay-aided stochastic multiresonances on scale-free FitzHugh－Nagumo neuronal networks[J]. 中国物理B, 2010, 19(4): 40508-40508.

Gan Chun-Biao(甘春标), Perc Matjaž, and Wang Qing-Yun(王青云). Delay-aided stochastic multiresonances on scale-free FitzHugh－Nagumo neuronal networks[J]. Chin. Phys. B, 2010, 19(4): 40508-40508.

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Delay-aided stochastic multiresonances on scale-free FitzHugh－Nagumo neuronal networks

Delay-aided stochastic multiresonances on scale-free FitzHugh－Nagumo neuronal networks

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