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Neural network models of the tactile system develop first-order units with spatially complex receptive fields
First-order tactile neurons have spatially complex receptive fields. Here we use machine-learning tools to show that such complexity arises for a wide range of training sets and network architectures. Moreover, we demonstrate that this complexity benefits network performance, especially on more diff...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6002100/ https://www.ncbi.nlm.nih.gov/pubmed/29902277 http://dx.doi.org/10.1371/journal.pone.0199196 |