Cargando…
Construction of functional brain connectivity networks from fMRI data with driving and modulatory inputs: an extended conditional Granger causality approach
We propose a numerical-based approach extending the conditional MVAR Granger causality (MVGC) analysis for the construction of directed connectivity networks in the presence of both exogenous/stimuli and modulatory inputs. The performance of the proposed scheme is validated using both synthetic stoc...
Autores principales: | Almpanis, Evangelos, Siettos, Constantinos |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AIMS Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7321769/ https://www.ncbi.nlm.nih.gov/pubmed/32607412 http://dx.doi.org/10.3934/Neuroscience.2020005 |
Ejemplares similares
-
Construction of embedded fMRI resting-state functional connectivity networks using manifold learning
por: Gallos, Ioannis K., et al.
Publicado: (2020) -
Increasing fMRI Sampling Rate Improves Granger Causality Estimates
por: Lin, Fa-Hsuan, et al.
Publicado: (2014) -
Is Granger Causality a Viable Technique for Analyzing fMRI Data?
por: Wen, Xiaotong, et al.
Publicado: (2013) -
Granger causality analysis reveals distinct spatio-temporal connectivity patterns in motor and perceptual visuo-spatial working memory
por: Protopapa, Foteini, et al.
Publicado: (2014) -
Correction: Increasing fMRI Sampling Rate Improves Granger Causality Estimates
Publicado: (2014)