Quarterly (Winter, Spring, Summer, Fall)
330 pp. per issue
8 1/2 x 11
E-ISSN
2472-1751

Network Neuroscience

Olaf Sporns, Editor
2019, Vol. 3, No. 1, Pages 138-156
(doi: 10.1162/netn_a_00058)
© 2018 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license
Time-evolving dynamics in brain networks forecast responses to health messaging
Article PDF (1.15 MB)
Abstract
Neuroimaging measures have been used to forecast complex behaviors, including how individuals change decisions about their health in response to persuasive communications, but have rarely incorporated metrics of brain network dynamics. How do functional dynamics within and between brain networks relate to the processes of persuasion and behavior change? To address this question, we scanned 45 adult smokers by using functional magnetic resonance imaging while they viewed anti-smoking images. Participants reported their smoking behavior and intentions to quit smoking before the scan and 1 month later. We focused on regions within four atlas-defined networks and examined whether they formed consistent network communities during this task (measured as allegiance). Smokers who showed reduced allegiance among regions within the default mode and fronto-parietal networks also demonstrated larger increases in their intentions to quit smoking 1 month later. We further examined dynamics of the ventromedial prefrontal cortex (vmPFC), as activation in this region has been frequently related to behavior change. The degree to which vmPFC changed its community assignment over time (measured as flexibility) was positively associated with smoking reduction. These data highlight the value in considering brain network dynamics for understanding message effectiveness and social processes more broadly.How do functional dynamics within and between brain networks relate to the processes of persuasion and behavior change? In this report, we assess brain network dynamics by using fMRI while smokers view antismoking messages, and relate these metrics to smoking behavior and intentions to quit smoking 1 month following the scan. Smokers who showed reduced allegiance (less consistent network communities) among regions within the default mode and fronto-parietal networks also demonstrated larger increases in their intentions to quit smoking. Furthermore, the degree to which the ventromedial prefrontal cortex flexibly changed its community assignment over time was positively associated with later smoking reduction. These data show that metrics of functional network dynamics can provide new information about individual differences in responsiveness to anti-smoking messaging.