Dynamical Criticality in the Collective Activity of a Population of Retinal Neurons

Recent experimental results based on multielectrode and imaging techniques have reinvigorated the idea that large neural networks operate near a critical point, between order and disorder. However, evidence for criticality has relied on the definition of arbitrary order parameters, or on models that...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Physical review letters Ročník 114; číslo 7; s. 078105
Hlavní autoři: Mora, Thierry, Deny, Stéphane, Marre, Olivier
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States American Physical Society 20.02.2015
Témata:
Animals
Critical point
Disorders
Life Sciences
Models, Neurological
Networks
Neural networks
Neurons
Order parameters
Rats
Retina
Retinal Ganglion Cells
Retinal Ganglion Cells - chemistry
Retinal Ganglion Cells - physiology
Statistics
Thermodynamics
ISSN:0031-9007, 1079-7114
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Recent experimental results based on multielectrode and imaging techniques have reinvigorated the idea that large neural networks operate near a critical point, between order and disorder. However, evidence for criticality has relied on the definition of arbitrary order parameters, or on models that do not address the dynamical nature of network activity. Here we introduce a novel approach to assess criticality that overcomes these limitations, while encompassing and generalizing previous criteria. We find a simple model to describe the global activity of large populations of ganglion cells in the rat retina, and show that their statistics are poised near a critical point. Taking into account the temporal dynamics of the activity greatly enhances the evidence for criticality, revealing it where previous methods would not. The approach is general and could be used in other biological networks.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0031-9007
1079-7114
DOI:10.1103/PhysRevLett.114.078105