Bayesian computational markers of relapse in methamphetamine dependence

Methamphetamine use disorder is associated with a high likelihood of relapse. Identifying robust predictors of relapse that have explanatory power is critical to develop secondary prevention based on a mechanistic understanding of relapse. Computational approaches have the potential to identify such...

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Detalles Bibliográficos
Autores principales: Harlé, Katia M., Yu, Angela J., Paulus, Martin P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444286/
https://www.ncbi.nlm.nih.gov/pubmed/30928810
http://dx.doi.org/10.1016/j.nicl.2019.101794

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444286/
https://www.ncbi.nlm.nih.gov/pubmed/30928810
http://dx.doi.org/10.1016/j.nicl.2019.101794

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