Cargando…
Insight and inference for DVARS
Estimates of functional connectivity using resting state functional Magnetic Resonance Imaging (rs-fMRI) are acutely sensitive to artifacts and large scale nuisance variation. As a result much effort is dedicated to preprocessing rs-fMRI data and using diagnostic measures to identify bad scans. One...
Autores principales: | Afyouni, Soroosh, Nichols, Thomas E. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academic Press
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5915574/ https://www.ncbi.nlm.nih.gov/pubmed/29307608 http://dx.doi.org/10.1016/j.neuroimage.2017.12.098 |
Ejemplares similares
-
Grain growth prediction based on data assimilation by implementing 4DVar on multi-phase-field model
por: Ito, Shin-ichi, et al.
Publicado: (2017) -
Effective degrees of freedom of the Pearson's correlation coefficient under autocorrelation
por: Afyouni, Soroosh, et al.
Publicado: (2019) -
Directed functional connectivity using dynamic graphical models
por: Schwab, Simon, et al.
Publicado: (2018) -
Confound modelling in UK Biobank brain imaging☆
por: Alfaro-Almagro, Fidel, et al.
Publicado: (2021) -
Functional Connectivity Alterations of the Temporal Lobe and Hippocampus in Semantic Dementia and Alzheimer’s Disease
por: Schwab, Simon, et al.
Publicado: (2020)