| Literature DB >> 32846124 |
Abigail S Greene1, Siyuan Gao2, Stephanie Noble3, Dustin Scheinost4, R Todd Constable5.
Abstract
Functional connectivity (FC) calculated from task fMRI data better reveals brain-phenotype relationships than rest-based FC, but how tasks have this effect is unknown. In over 700 individuals performing seven tasks, we use psychophysiological interaction (PPI) and predictive modeling analyses to demonstrate that task-induced changes in FC successfully predict phenotype, and these changes are not simply driven by task activation. Activation, however, is useful for prediction only if the in-scanner task is related to the predicted phenotype. To further characterize these predictive FC changes, we develop and apply an inter-subject PPI analysis. We find that moderate, but not high, task-induced consistency of the blood-oxygen-level-dependent (BOLD) signal across individuals is useful for prediction. Together, these findings demonstrate that in-scanner tasks have distributed, phenotypically relevant effects on brain functional organization, and they offer a framework to leverage both task activation and FC to reveal the neural bases of complex human traits, symptoms, and behaviors.Entities:
Keywords: Human Connectome Project; brain state; brain-phenotype relationships; fMRI; functional connectivity; individual differences; predictive modeling; tasks
Mesh:
Year: 2020 PMID: 32846124 PMCID: PMC7469925 DOI: 10.1016/j.celrep.2020.108066
Source DB: PubMed Journal: Cell Rep Impact factor: 9.423