Percolation in living neural networks
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 critical exponent β 0.65 is independent of the balance between excitatory and inhibitory neurons and indicates that the degree distribution is gaussian rather than scale free
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