CAPTURING SUBJECT VARIABILITY IN FMRI DATA : A GRAPH-THEORETICAL ANALYSIS OF GICA VS. IVA

BACKGROUND: Recent studies using simulated functional magnetic resonance imaging (fMRI) data show that independent vector analysis (IVA) is a superior solution for capturing spatial subject variability when compared with the widely used group independent component analysis (GICA). Retaining such var...

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Bibliografiset tiedot
Julkaisussa:J Neurosci Methods
Päätekijät: Laney, Jonathan, Westlake, Kelly, Ma, Sai, Woytowicz, Elizabeth, Calhoun, Vince D., Adalı, Tülay
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: 2015
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Article
Linkit:https://ncbi.nlm.nih.gov/pmc/articles/PMC4961734/
https://ncbi.nlm.nih.gov/pubmed/25797843
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jneumeth.2015.03.019
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