Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6238
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Title: Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure
Authors: Li, X
Small, M
Issue Date: Jun-2012
Source: Chaos, June 2012, v. 22, 023104, p. 1-10
Abstract: Neuronal avalanche is a spontaneous neuronal activity which obeys a power-law distribution of population event sizes with an exponent of –3/2. It has been observed in the superficial layers of cortex both invivo and invitro. In this paper, we analyze the information transmission of a novel self-organized neural network with active-neuron-dominant structure. Neuronal avalanches can be observed in this network with appropriate input intensity. We find that the process of network learning via spike-timing dependent plasticity dramatically increases the complexity of network structure, which is finally self-organized to be active-neuron-dominant connectivity. Both the entropy of activity patterns and the complexity of their resulting post-synaptic inputs are maximized when the network dynamics are propagated as neuronal avalanches. This emergent topology is beneficial for information transmission with high efficiency and also could be responsible for the large information capacity of this network compared with alternative archetypal networks with different neural connectivity.
Keywords: Biological techniques
Biology computing
Brain entropy
Neural nets
Neurophysiology
Publisher: American Institute of Physics
Journal: Chaos 
ISSN: 1054-1500
EISSN: 1089-7682
DOI: 10.1063/1.3701946
Rights: © 2012 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in X. Li & M. Small, Chaos: an interdisciplinary journal of nonlinear science 22, 023104 (2012) and may be found at http://link.aip.org/link/?cha/22/023104
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