Dynamical synapses causing self-organized criticality in neural networks

dc.creatorLevina, Anna
dc.creatorHerrmann, J. Michael
dc.creatorGeisel, Theo
dc.date2007-12-06
dc.date.accessioned2026-07-07T08:47:43Z
dc.date.available2026-07-07T08:47:43Z
dc.descriptionWe show that a network of spiking neurons exhibits robust self-organized criticality if the synaptic efficacies follow realistic dynamics. Deriving analytical expressions for the average coupling strengths and inter-spike intervals, we demonstrate that networks with dynamical synapses exhibit critical avalanche dynamics for a wide range of interaction parameters. We prove that in the thermodynamical limit the network becomes critical for all large enough coupling parameters. We thereby explain experimental observations in which cortical neurons show avalanche activity with the total intensity of firing events being distributed as a power-law.
dc.description9 pages, 4 figures
dc.identifierhttps://arxiv.org/abs/0712.1003
dc.identifierhttp://arxiv.org/abs/0712.1003
dc.identifierA. Levina, J. M. Herrmann, T. Geisel. Dynamical synapses causing self-organized criticality in neural networks, Nature Phys. 3, 857-860 (2007)
dc.identifierdoi:10.1038/nphys758
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/143697
dc.subjectStatistical Mechanics
dc.subjectDisordered Systems and Neural Networks
dc.subjectNeurons and Cognition
dc.titleDynamical synapses causing self-organized criticality in neural networks
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