Cargando…
Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models
Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distri...
Autores principales: | Rostami, Vahid, Porta Mana, PierGianLuca, Grün, Sonja, Helias, Moritz |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5645158/ https://www.ncbi.nlm.nih.gov/pubmed/28968396 http://dx.doi.org/10.1371/journal.pcbi.1005762 |
Ejemplares similares
-
Perfect Detection of Spikes in the Linear Sub-threshold Dynamics of Point Neurons
por: Krishnan, Jeyashree, et al.
Publicado: (2018) -
Ergodic theory, entropy
por: Smorodinsky, Meir
Publicado: (1971) -
Entropy and Ergodicity of Boole-Type Transformations
por: Blackmore, Denis, et al.
Publicado: (2021) -
Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models
por: Stein, Richard R., et al.
Publicado: (2015) -
A pairwise maximum entropy model accurately describes resting-state human brain networks
por: Watanabe, Takamitsu, et al.
Publicado: (2013)