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Title: Percolation in Living Neural Networks
Author: Breskin, Ilan
Soriano i Fradera, Jordi
Moses, Elisha
Tlusty, Tsvi
Keywords: Física de partícules
Particle physics
Issue Date: 30-Oct-2006
Publisher: American Physical Society
Abstract: We study living neural networks by measuring the neurons' response to a global electrical stimulation. Neural connectivity is lowered by reducing the synaptic strength, chemically blocking neurotransmitter receptors. We use a graph-theoretic approach to show that the connectivity undergoes a percolation transition. This occurs as the giant component disintegrates, characterized by a power law with an exponent β ≃ 0.65 . β is independent of the balance between excitatory and inhibitory neurons and indicates that the degree distribution is Gaussian rather than scale free.
Note: Reproducció del document publicat a:
It is part of: Physical Review Letters, 2006, vol. 97, num. 18, p. 188102
Related resource:
ISSN: 0031-9007
Appears in Collections:Articles publicats en revistes (Física de la Matèria Condensada)

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