Cargando…
Robust brain network identification from multi-subject asynchronous fMRI data
We describe a novel method for robust identification of common brain networks and their corresponding temporal dynamics across subjects from asynchronous functional MRI (fMRI) using tensor decomposition. We first temporally align asynchronous fMRI data using the orthogonal BrainSync transform, allow...
Autores principales: | Li, Jian, Wisnowski, Jessica L., Joshi, Anand A., Leahy, Richard M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7983296/ https://www.ncbi.nlm.nih.gov/pubmed/33301936 http://dx.doi.org/10.1016/j.neuroimage.2020.117615 |
Ejemplares similares
-
Are you thinking what I’m thinking? Synchronization of resting fMRI time-series across subjects
por: Joshi, Anand A., et al.
Publicado: (2018) -
Identification of overlapping and interacting networks reveals intrinsic spatiotemporal organization of the human brain
por: Li, Jian, et al.
Publicado: (2023) -
Temporal Non-Local Means Filtering Reveals Real-Time Whole-Brain Cortical Interactions in Resting fMRI
por: Bhushan, Chitresh, et al.
Publicado: (2016) -
Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study
por: Yu, Qingbao, et al.
Publicado: (2016) -
Robust brain parcellation using sparse representation on resting-state fMRI
por: Zhang, Yu, et al.
Publicado: (2014)