Discovering hidden brain network responses to naturalistic stimuli via tensor component analysis of multi-subject fMRI data

• Published in: NeuroImage (Orlando, Fla.) Vol. 255; p. 119193
• Main Authors: Hu, Guoqiang, Li, Huanjie, Zhao, Wei, Hao, Yuxing, Bai, Zonglei, Nickerson, Lisa D., Cong, Fengyu
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.07.2022; Elsevier Limited; Elsevier
• Subjects: Algorithms; Brain; Brain - diagnostic imaging; Brain - physiology; Brain mapping; Brain Mapping - methods; Data analysis; Decomposition; fMRI; Functional magnetic resonance imaging; Humans; Inter-subject correlation; Magnetic Resonance Imaging - methods; Methods; Motion Pictures; Naturalistic stimuli; Reproducibility; Reproducibility of Results; Spatial distribution; Tensor components analysis; fMRI; Inter-subject correlation; Tensor components analysis; Naturalistic stimuli

The study of brain network interactions during naturalistic stimuli facilitates a deeper understanding of human brain function. To estimate large-scale brain networks evoked with naturalistic stimuli, a tensor component analysis (TCA) based framework was used to characterize shared spatio-temporal p...