A Hierarchical Bayesian Mixture Model Approach for Analysis of Resting-State Functional Brain Connectivity: An Alternative to Thresholding

This article proposes a Bayesian hierarchical mixture model to analyze functional brain connectivity where mixture components represent “positively connected” and “non-connected” brain regions. Such an approach provides a data-informed separation of reliable and spurious connections in contrast to a...

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Detalles Bibliográficos
Autores principales: Gorbach, Tetiana, Lundquist, Anders, de Luna, Xavier, Nyberg, Lars, Salami, Alireza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc., publishers 2020
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310299/
https://www.ncbi.nlm.nih.gov/pubmed/32308015
http://dx.doi.org/10.1089/brain.2020.0740

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310299/
https://www.ncbi.nlm.nih.gov/pubmed/32308015
http://dx.doi.org/10.1089/brain.2020.0740

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