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Multistability and Long-Timescale Transients Encoded by Network Structure in a Model of C. elegans Connectome Dynamics
The neural dynamics of the nematode Caenorhabditis elegans are experimentally low-dimensional and may be understood as long-timescale transitions between multiple low-dimensional attractors. Previous modeling work has found that dynamic models of the worm's full neuronal network are capable of...
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| 出版年: | Front Comput Neurosci |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Media S.A.
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5468412/ https://ncbi.nlm.nih.gov/pubmed/28659783 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fncom.2017.00053 |
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