Continuous Attractor Neural Networks: Candidate of a Canonical Model for Neural Information Representation

Owing to its many computationally desirable properties, the model of continuous attractor neural networks (CANNs) has been successfully applied to describe the encoding of simple continuous features in neural systems, such as orientation, moving direction, head direction, and spatial location of obj...

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Detalles Bibliográficos
Autores principales: Wu, Si, Wong, K Y Michael, Fung, C C Alan, Mi, Yuanyuan, Zhang, Wenhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000Research 2016
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4752021/
https://www.ncbi.nlm.nih.gov/pubmed/26937278
http://dx.doi.org/10.12688/f1000research.7387.1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4752021/
https://www.ncbi.nlm.nih.gov/pubmed/26937278
http://dx.doi.org/10.12688/f1000research.7387.1

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