Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

Characterizing the variability of resting-state functional brain connectivity across subjects and/or over time has recently attracted much attention. Principal component analysis (PCA) serves as a fundamental statistical technique for such analyses. However, performing PCA on high-dimensional connec...

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Detalles Bibliográficos
Autores principales: Hirayama, Jun-ichiro, Hyvärinen, Aapo, Kiviniemi, Vesa, Kawanabe, Motoaki, Yamashita, Okito
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176286/
https://www.ncbi.nlm.nih.gov/pubmed/28002474
http://dx.doi.org/10.1371/journal.pone.0168180

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176286/
https://www.ncbi.nlm.nih.gov/pubmed/28002474
http://dx.doi.org/10.1371/journal.pone.0168180

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