An efficient analytical reduction of detailed nonlinear neuron models

Detailed conductance-based nonlinear neuron models consisting of thousands of synapses are key for understanding of the computational properties of single neurons and large neuronal networks, and for interpreting experimental results. Simulations of these models are computationally expensive, consid...

Descripción completa

Detalles Bibliográficos
Autores principales: Amsalem, Oren, Eyal, Guy, Rogozinski, Noa, Gevaert, Michael, Kumbhar, Pramod, Schürmann, Felix, Segev, Idan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6962154/
https://www.ncbi.nlm.nih.gov/pubmed/31941884
http://dx.doi.org/10.1038/s41467-019-13932-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6962154/
https://www.ncbi.nlm.nih.gov/pubmed/31941884
http://dx.doi.org/10.1038/s41467-019-13932-6

Ejemplares similares