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Symmetries Constrain Dynamics in a Family of Balanced Neural Networks
We examine a family of random firing-rate neural networks in which we enforce the neurobiological constraint of Dale’s Law—each neuron makes either excitatory or inhibitory connections onto its post-synaptic targets. We find that this constrained system may be described as a perturbation from a syst...
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| 出版年: | J Math Neurosci |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer Berlin Heidelberg
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5635020/ https://ncbi.nlm.nih.gov/pubmed/29019105 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13408-017-0052-6 |
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