Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition With Spatial Sparsity Constraint

Tucker decomposition can provide an intuitive summary to understand brain function by decomposing multi-subject fMRI data into a core tensor and multiple factor matrices, and was mostly used to extract functional connectivity patterns across time/subjects using orthogonality constraints. However, th...

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Detalles Bibliográficos
Autores principales: Han, Yue, Lin, Qiu-Hua, Kuang, Li-Dan, Gong, Xiao-Feng, Cong, Fengyu, Wang, Yu-Ping, Calhoun, Vince D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9012952/
https://www.ncbi.nlm.nih.gov/pubmed/34694992
http://dx.doi.org/10.1109/TMI.2021.3122226

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9012952/
https://www.ncbi.nlm.nih.gov/pubmed/34694992
http://dx.doi.org/10.1109/TMI.2021.3122226

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