Self-organized criticality and scale-free properties in emergent functional neural networks. Shin, C. & Kim, S. Physical Review E, 74(4):045101, October, 2006.
Self-organized criticality and scale-free properties in emergent functional neural networks [link]Paper  doi  abstract   bibtex   
Recent studies on complex systems have shown that the synchronization of oscillators, including neuronal ones, is faster, stronger, and more efficient in small-world networks than in regular or random networks. We show that the functional structures in the brain can be self-organized to both small-world and scale-free networks by synaptic reorganization via spike timing dependent synaptic plasticity instead of conventional Hebbian learning rules. We show that the balance between the excitatory and the inhibitory synaptic inputs is critical in the formation of the functional structure, which is found to lie in a self-organized critical state.
@article{shin_self-organized_2006,
	title = {Self-organized criticality and scale-free properties in emergent functional neural networks},
	volume = {74},
	url = {http://link.aps.org/doi/10.1103/PhysRevE.74.045101},
	doi = {10.1103/PhysRevE.74.045101},
	abstract = {Recent studies on complex systems have shown that the synchronization of oscillators, including neuronal ones, is faster, stronger, and more efficient in small-world networks than in regular or random networks. We show that the functional structures in the brain can be self-organized to both small-world and scale-free networks by synaptic reorganization via spike timing dependent synaptic plasticity instead of conventional Hebbian learning rules. We show that the balance between the excitatory and the inhibitory synaptic inputs is critical in the formation of the functional structure, which is found to lie in a self-organized critical state.},
	number = {4},
	urldate = {2013-09-09TZ},
	journal = {Physical Review E},
	author = {Shin, Chang-Woo and Kim, Seunghwan},
	month = oct,
	year = {2006},
	pages = {045101}
}

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