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A unifying computational framework for stability and flexibility of arousal

Arousal and consciousness flexibly adjust to salient cues, but remain stable despite noise and disturbance. Diverse, highly interconnected neural networks govern the underlying transitions of behavioral state; these networks are robust but very complex. Frameworks from systems engineering provide po...

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Bibliografische gegevens
Hoofdauteurs: Kosse, Christin, Burdakov, Denis
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: Frontiers Media S.A. 2014
Onderwerpen:
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC4202806/
https://ncbi.nlm.nih.gov/pubmed/25368557
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnsys.2014.00192
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