Three‐way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data

• Published in: Human brain mapping Vol. 43; no. 4; pp. 1280 - 1294
• Main Authors: Qi, Shile, Silva, Rogers F., Zhang, Daoqiang, Plis, Sergey M., Miller, Robyn, Vergara, Victor M., Jiang, Rongtao, Zhi, Dongmei, Sui, Jing, Calhoun, Vince D.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.03.2022
• Subjects: 4D fMRI; Adult; Brain; Brain - diagnostic imaging; Brain - physiology; Brain mapping; Brain research; Cerebellum; Cognitive ability; Decomposition; Female; Functional magnetic resonance imaging; Functional Neuroimaging - methods; group ICA; Humans; Image Processing, Computer-Assisted - methods; Independent component analysis; independent component analysis (ICA); Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Medical imaging; Mental disorders; Methods; Middle Aged; Nerve Net - diagnostic imaging; Nerve Net - physiology; Neural networks; Neuroimaging; Noise levels; Optimization; parallel ICA; Resonance; Schizophrenia; Schizophrenia - diagnostic imaging; Schizophrenia - physiopathology; Simulation; Spatial Analysis; Spatio-Temporal Analysis; Structure-function relationships; Temporal variations; three‐way multimodal fusion; unify; Visual discrimination; parallel ICA; three-way multimodal fusion; group ICA; independent component analysis (ICA); 4D fMRI; unify

Advances in imaging acquisition techniques allow multiple imaging modalities to be collected from the same subject. Each individual modality offers limited yet unique views of the functional, structural, or dynamic temporal features of the brain. Multimodal fusion provides effective ways to leverage...