A pooling-LiNGAM algorithm for effective connectivity analysis of fMRI data

The Independent Component Analysis (ICA)—linear non-Gaussian acyclic model (LiNGAM), an algorithm that can be used to estimate the causal relationship among non-Gaussian distributed data, has the potential value to detect the effective connectivity of human brain areas. Under the assumptions that (a...

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Detalles Bibliográficos
Autores principales: Xu, Lele, Fan, Tingting, Wu, Xia, Chen, KeWei, Guo, Xiaojuan, Zhang, Jiacai, Yao, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4186480/
https://www.ncbi.nlm.nih.gov/pubmed/25339895
http://dx.doi.org/10.3389/fncom.2014.00125

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4186480/
https://www.ncbi.nlm.nih.gov/pubmed/25339895
http://dx.doi.org/10.3389/fncom.2014.00125

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