Identifying and removing widespread signal deflections from fMRI data: Rethinking the global signal regression problem
One of the most controversial procedures in the analysis of resting-state functional magnetic resonance imaging (rsfMRI) data is global signal regression (GSR): the removal, via linear regression, of the mean signal averaged over the entire brain. On one hand, the global mean signal contains varianc...
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| Autori principali: | , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier
2020-05-01
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| Serie: | NeuroImage |
| Soggetti: | |
| Accesso online: | http://www.sciencedirect.com/science/article/pii/S1053811920301014 |
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