General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks.

Abstract

Intrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.

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Published Version (Please cite this version)

10.1016/j.neuroimage.2019.01.068

Publication Info

Elliott, Maxwell L, Annchen R Knodt, Megan Cooke, M Justin Kim, Tracy R Melzer, Ross Keenan, David Ireland, Sandhya Ramrakha, et al. (2019). General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks. NeuroImage, 189. pp. 516–532. 10.1016/j.neuroimage.2019.01.068 Retrieved from https://hdl.handle.net/10161/21206.

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Scholars@Duke

Caspi

Avshalom Caspi

Edward M. Arnett Distinguished Professor of Psychology and Neuroscience

Caspi’s research is concerned with three questions: (1) How do childhood experiences shape aging and the course of health inequalities across the life span?  (2) How do genetic differences between people shape the way they respond to their environments? (3) How do mental health problems unfold across and shape the life course? 


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