Time-Evolving Dynamics in Brain Networks Forecast Responses to Health Messaging
Social and Behavioral Sciences
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 forty-five adult smokers using functional magnetic resonance imaging while they viewed antismoking images. Participants reported their smoking behavior and intentions to quit smoking before the scan and one 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 frontoparietal networks also demonstrated larger increases in their intentions to quit smoking one month later. We further examined dynamics of the 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.