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Connection-type-specific biases make uniform random network models consistent with cortical recordings
Uniform random sparse network architectures are ubiquitous in computational neuroscience, but the implicit hypothesis that they are a good representation of real neuronal networks has been met with skepticism. Here we used two experimental data sets, a study of triplet connectivity statistics and a...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Physiological Society
2014
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4200009/ https://www.ncbi.nlm.nih.gov/pubmed/24944218 http://dx.doi.org/10.1152/jn.00629.2013 |