STDP-driven networks and the C. elegans neuronal network

被引:13
|
作者
Ren, Quansheng [2 ]
Kolwankar, Kiran M. [1 ,2 ]
Samal, Areejit [2 ,3 ,4 ]
Jost, Juergen [2 ,5 ]
机构
[1] Ramniranjan Jhunjhunwala Coll, Dept Phys, Bombay 400086, Maharashtra, India
[2] Max Planck Inst Math Sci, D-04103 Leipzig, Germany
[3] CNRS, Lab Phys Theor & Modeles Stat, F-91405 Orsay, France
[4] Univ Paris 11, UMR 8626, F-91405 Orsay, France
[5] Santa Fe Inst, Santa Fe, NM 87501 USA
关键词
Complex networks; Network evolution; Spike-timing dependent plasticity; Network motifs;
D O I
10.1016/j.physa.2010.05.018
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We study the dynamics of the structure of a formal neural network wherein the strengths of the synapses are governed by spike-timing-dependent plasticity (STOP). For properly chosen input signals, there exists a steady state with a residual network. We compare the motif profile of such a network with that of a real neural network of C. elegans and identify robust qualitative similarities. In particular, our extensive numerical simulations show that this STDP-driven resulting network is robust under variations of the model parameters. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:3900 / 3914
页数:15
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