Cargando…
Dynamic connectivity detection: an algorithm for determining functional connectivity change points in fMRI data
Recently there has been an increased interest in using fMRI data to study the dynamic nature of brain connectivity. In this setting, the activity in a set of regions of interest (ROIs) is often modeled using a multivariate Gaussian distribution, with a mean vector and covariance matrix that are allo...
Autores principales: | Xu, Yuting, Lindquist, Martin A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4560110/ https://www.ncbi.nlm.nih.gov/pubmed/26388711 http://dx.doi.org/10.3389/fnins.2015.00285 |
Ejemplares similares
-
Detecting functional connectivity change points for single-subject fMRI data
por: Cribben, Ivor, et al.
Publicado: (2013) -
A pooling-LiNGAM algorithm for effective connectivity analysis of fMRI data
por: Xu, Lele, et al.
Publicado: (2014) -
Arousal Contributions to Resting-State fMRI Connectivity and Dynamics
por: Gu, Yameng, et al.
Publicado: (2019) -
Network Connectivity in Epilepsy: Resting State fMRI and EEG–fMRI Contributions
por: Centeno, Maria, et al.
Publicado: (2014) -
Variational Bayesian causal connectivity analysis for fMRI
por: Luessi, Martin, et al.
Publicado: (2014)