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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...
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| Main Authors: | , , , , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
American Physiological Society
2014
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4200009/ https://ncbi.nlm.nih.gov/pubmed/24944218 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1152/jn.00629.2013 |
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