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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...
Autores principales: | Hirayama, Jun-ichiro, Hyvärinen, Aapo, Kiviniemi, Vesa, Kawanabe, Motoaki, Yamashita, Okito |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
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 |
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