Cargando…
Robust Data Driven Model Order Estimation for Independent Component Analysis of fMRI Data with Low Contrast to Noise
Independent component analysis (ICA) has been successfully utilized for analysis of functional MRI (fMRI) data for task related as well as resting state studies. Although it holds the promise of becoming an unbiased data-driven analysis technique, a few choices have to be made prior to performing IC...
Autores principales: | Majeed, Waqas, Avison, Malcolm J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4005775/ https://www.ncbi.nlm.nih.gov/pubmed/24788636 http://dx.doi.org/10.1371/journal.pone.0094943 |
Ejemplares similares
-
A Robust Classifier to Distinguish Noise from fMRI Independent Components
por: Sochat, Vanessa, et al.
Publicado: (2014) -
On the Definition of Signal-To-Noise Ratio and Contrast-To-Noise Ratio for fMRI Data
por: Welvaert, Marijke, et al.
Publicado: (2013) -
Analysis of Residual Dependencies of Independent Components Extracted from fMRI Data
por: Vanello, N., et al.
Publicado: (2016) -
Parallel group independent component analysis for massive fMRI data sets
por: Chen, Shaojie, et al.
Publicado: (2017) -
Hand classification of fMRI ICA noise components
por: Griffanti, Ludovica, et al.
Publicado: (2017)