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Control of criticality and computation in spiking neuromorphic networks with plasticity

The critical state is assumed to be optimal for any computation in recurrent neural networks, because criticality maximizes a number of abstract computational properties. We challenge this assumption by evaluating the performance of a spiking recurrent neural network on a set of tasks of varying com...

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Pubblicato in:Nat Commun
Autori principali: Cramer, Benjamin, Stöckel, David, Kreft, Markus, Wibral, Michael, Schemmel, Johannes, Meier, Karlheinz, Priesemann, Viola
Natura: Artigo
Lingua:Inglês
Pubblicazione: Nature Publishing Group UK 2020
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Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7275091/
https://ncbi.nlm.nih.gov/pubmed/32503982
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-020-16548-3
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