Suppression of bursting synchronization in clustered scale-free (rich-club) neuronal networks

被引:47
作者
Lameu, E. L. [2 ]
Batista, C. A. S. [1 ]
Batista, A. M. [3 ]
Iarosz, K. [2 ]
Viana, R. L. [1 ]
Lopes, S. R. [1 ]
Kurths, J. [4 ,5 ,6 ]
机构
[1] Univ Fed Parana, Dept Phys, BR-80060000 Curitiba, Parana, Brazil
[2] Univ Estadual Ponta Grossa, Grad Program Phys, Ponta Grossa, Parana, Brazil
[3] Univ Estadual Ponta Grossa, Dept Math & Stat, Ponta Grossa, Parana, Brazil
[4] Humboldt Univ, Dept Phys, Berlin, Germany
[5] Inst Complex Syst & Math Biol, Aberdeen, Scotland
[6] Potsdam Inst Climate Impact Res, Potsdam, Germany
关键词
DEEP BRAIN-STIMULATION; CONNECTIONAL ORGANIZATION; DYNAMICS; OSCILLATIONS; TREMOR;
D O I
10.1063/1.4772998
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Functional brain networks are composed of cortical areas that are anatomically and functionally connected. One of the cortical networks for which more information is available in the literature is the cat cerebral cortex. Statistical analyses of the latter suggest that its structure can be described as a clustered network, in which each cluster is a scale-free network possessing highly connected hubs. Those hubs are, on their hand, connected together in a strong fashion ("rich-club" network). We have built a clustered scale-free network inspired in the cat cortex structure so as to study their dynamical properties. In this article, we focus on the synchronization of bursting activity of the cortical areas and how it can be suppressed by means of neuron deactivation through suitably applied light pulses. We show that it is possible to effectively suppress bursting synchronization by acting on a single, yet suitably chosen neuron, as long as it is highly connected, thanks to the "rich-club" structure of the network. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4772998]
引用
收藏
页数:12
相关论文
共 46 条
[1]   Statistical mechanics of complex networks [J].
Albert, R ;
Barabási, AL .
REVIEWS OF MODERN PHYSICS, 2002, 74 (01) :47-97
[2]  
[Anonymous], SPIKING NEURON MODEL
[3]   Collective Almost Synchronisation in Complex Networks [J].
Baptista, Murilo S. ;
Ren, Hai-Peng ;
Swarts, Johen C. M. ;
Carareto, Rodrigo ;
Nijmeijer, Henk ;
Grebogi, Celso .
PLOS ONE, 2012, 7 (11)
[4]  
Batista A. S., 2007, PHYS REV E, V76
[5]   Phase synchronization of bursting neurons in clustered small-world networks [J].
Batista, C. A. S. ;
Lameu, E. L. ;
Batista, A. M. ;
Lopes, S. R. ;
Pereira, T. ;
Zamora-Lopez, G. ;
Kurths, J. ;
Viana, R. L. .
PHYSICAL REVIEW E, 2012, 86 (01)
[6]   Delayed feedback control of bursting synchronization in a scale-free neuronal network [J].
Batista, C. A. S. ;
Lopes, S. R. ;
Viana, R. L. ;
Batista, A. M. .
NEURAL NETWORKS, 2010, 23 (01) :114-124
[7]   Modulation of tremor amplitude during deep brain stimulation at different frequencies [J].
Beuter, A ;
Titcombe, MS .
BRAIN AND COGNITION, 2003, 53 (02) :190-192
[8]  
Beuter Anne, 2001, Thalamus & Related Systems, V1, P203, DOI 10.1016/S1472-9288(01)00020-6
[9]  
Bower JamesM., 1998, The Book of GENESIS: Exploring Realistic Neural Models with the GEneral NEural SImulation System, V2
[10]  
Buzsaki G., 2006, RHYTHMS BRAIN, DOI DOI 10.1093/ACPROF:OSO/9780195301069.001.0001