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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Detalles Bibliográficos
Autores principales: Keshishian, Menoua, Akbari, Hassan, Khalighinejad, Bahar, Herrero, Jose L, Mehta, Ashesh D, Mesgarani, Nima
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2020
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347387/
https://www.ncbi.nlm.nih.gov/pubmed/32589140
http://dx.doi.org/10.7554/eLife.53445

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347387/
https://www.ncbi.nlm.nih.gov/pubmed/32589140
http://dx.doi.org/10.7554/eLife.53445

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