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Comparison of IVA and GIG-ICA in Brain Functional Network Estimation Using fMRI Data
Spatial group independent component analysis (GICA) methods decompose multiple-subject functional magnetic resonance imaging (fMRI) data into a linear mixture of spatially independent components (ICs), some of which are subsequently characterized as brain functional networks. Group information guide...
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| 出版年: | Front Neurosci |
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| 主要な著者: | , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Frontiers Media S.A.
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5437155/ https://ncbi.nlm.nih.gov/pubmed/28579940 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2017.00267 |
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