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Classifying dynamic transitions in high dimensional neural mass models: A random forest approach
Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understand how dynamics change when parameters are varied....
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| Publicado en: | PLoS Comput Biol |
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| Autores principales: | , , |
| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Public Library of Science
2018
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| Materias: | |
| Acceso en línea: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5851637/ https://ncbi.nlm.nih.gov/pubmed/29499044 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1006009 |
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