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How single neuron properties shape chaotic dynamics and signal transmission in random neural networks
While most models of randomly connected neural networks assume single-neuron models with simple dynamics, neurons in the brain exhibit complex intrinsic dynamics over multiple timescales. We analyze how the dynamical properties of single neurons and recurrent connections interact to shape the effect...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586367/ https://www.ncbi.nlm.nih.gov/pubmed/31181063 http://dx.doi.org/10.1371/journal.pcbi.1007122 |