Group-PCA for very large fMRI datasets

Increasingly-large datasets (for example, the resting-state fMRI data from the Human Connectome Project) are demanding analyses that are problematic because of the sheer scale of the aggregate data. We present two approaches for applying group-level PCA; both give a close approximation to the output...

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Detalles Bibliográficos
Autores principales: Smith, Stephen M., Hyvärinen, Aapo, Varoquaux, Gaël, Miller, Karla L., Beckmann, Christian F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2014
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4289914/
https://www.ncbi.nlm.nih.gov/pubmed/25094018
http://dx.doi.org/10.1016/j.neuroimage.2014.07.051

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4289914/
https://www.ncbi.nlm.nih.gov/pubmed/25094018
http://dx.doi.org/10.1016/j.neuroimage.2014.07.051

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