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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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| Pubblicato in: | J Neurosci Methods |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2015
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| Soggetti: | |
| Accesso online: | 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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