Cargando…
Interpretation of correlated neural variability from models of feed-forward and recurrent circuits
Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A nu...
Autores principales: | Pernice, Volker, da Silveira, Rava Azeredo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5833435/ https://www.ncbi.nlm.nih.gov/pubmed/29408930 http://dx.doi.org/10.1371/journal.pcbi.1005979 |
Ejemplares similares
-
High-Fidelity Coding with Correlated Neurons
por: da Silveira, Rava Azeredo, et al.
Publicado: (2014) -
Improved Estimation and Interpretation of Correlations in Neural Circuits
por: Yatsenko, Dimitri, et al.
Publicado: (2015) -
Biases and Variability from Costly Bayesian Inference
por: Prat-Carrabin, Arthur, et al.
Publicado: (2021) -
Noise correlations in the human brain and their impact on pattern classification
por: Bejjanki, Vikranth R., et al.
Publicado: (2017) -
Application of feed forward and recurrent neural networks in simulation of left ventricular mechanics
por: Dabiri, Yaghoub, et al.
Publicado: (2020)