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Estimating and interpreting nonlinear receptive field of sensory neural responses with deep neural network models
Our understanding of nonlinear stimulus transformations by neural circuits is hindered by the lack of comprehensive yet interpretable computational modeling frameworks. Here, we propose a data-driven approach based on deep neural networks to directly model arbitrarily nonlinear stimulus-response map...
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| Publicado no: | eLife |
|---|---|
| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
eLife Sciences Publications, Ltd
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7347387/ https://ncbi.nlm.nih.gov/pubmed/32589140 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7554/eLife.53445 |
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