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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
F1000Research
2016
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| Materias: | |
| 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 |