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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...
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| Veröffentlicht in: | PLoS One |
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| Hauptverfasser: | , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Public Library of Science
2016
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5176286/ https://ncbi.nlm.nih.gov/pubmed/28002474 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0168180 |
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