Topography and behavioral relevance of the global signal in the human brain

• Published in: Scientific reports Vol. 9; no. 1; pp. 14286 - 10
• Main Authors: Li, Jingwei, Bolt, Taylor, Bzdok, Danilo, Nomi, Jason S., Yeo, B. T. Thomas, Spreng, R. Nathan, Uddin, Lucina Q.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 03-10-2019; Nature Publishing Group; Nature Portfolio
• Subjects: 59; 59/36; 631/378/2607; 631/378/2649; Adult; Applications; Brain - physiology; Brain Mapping; Cognition; Cognitive Sciences; Correlation analysis; Functional magnetic resonance imaging; Humanities and Social Sciences; Humans; Image processing; Life Sciences; Magnetic Resonance Imaging; Medical imaging; multidisciplinary; Nerve Net - physiology; Neuroimaging; Neurons and Cognition; Phenotypes; Principal Component Analysis; Principal components analysis; Rest; Science; Science (multidisciplinary); Statistics; Topography; Young Adult
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-019-50750-8

The global signal in resting-state functional MRI data is considered to be dominated by physiological noise and artifacts, yet a growing literature suggests that it also carries information about widespread neural activity. The biological relevance of the global signal remains poorly understood. Applying principal component analysis to a large neuroimaging dataset, we found that individual variation in global signal topography recapitulates well-established patterns of large-scale functional brain networks. Using canonical correlation analysis, we delineated relationships between individual differences in global signal topography and a battery of phenotypes. The first canonical variate of the global signal, resembling the frontoparietal control network, was significantly related to an axis of positive and negative life outcomes and psychological function. These results suggest that the global signal contains a rich source of information related to trait-level cognition and behavior. This work has significant implications for the contentious debate over artifact removal practices in neuroimaging.