Spontaneous scale-free structure of spike flow graphs in recurrent neural networks

DOI10.1016/j.neunet.2008.06.011zbMath1254.68221OpenAlexW2035324081WikidataQ51872157 ScholiaQ51872157MaRDI QIDQ1932124

Filip Piękniewski, Tomasz Schreiber

Publication date: 17 January 2013

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2008.06.011

zbMATH Keywords

stochastic neural networkscale-free graphwinner-take-all dynamics

Mathematics Subject Classification ID

Applications of graph theory (05C90) Learning and adaptive systems in artificial intelligence (68T05) Applications of dynamical systems (37N99)

Related Items (2)

Delay-induced synchronization transitions in modular scale-free neuronal networks with hybrid electrical and chemical synapses ⋮ Capacity of an associative memory model on random graph architectures

Cites Work

• Evolution of the social network of scientific collaborations
• Statistical mechanics of complex networks
• Emergence of Scaling in Random Networks
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