The persuasion network is modulated by drug-use risk and predicts anti-drug message effectiveness

Richard Huskey, J Michael Mangus, Benjamin O Turner, René Weber, Richard Huskey, J Michael Mangus, Benjamin O Turner, René Weber

Abstract

While a persuasion network has been proposed, little is known about how network connections between brain regions contribute to attitude change. Two possible mechanisms have been advanced. One hypothesis predicts that attitude change results from increased connectivity between structures implicated in affective and executive processing in response to increases in argument strength. A second functional perspective suggests that highly arousing messages reduce connectivity between structures implicated in the encoding of sensory information, which disrupts message processing and thereby inhibits attitude change. However, persuasion is a multi-determined construct that results from both message features and audience characteristics. Therefore, persuasive messages should lead to specific functional connectivity patterns among a priori defined structures within the persuasion network. The present study exposed 28 subjects to anti-drug public service announcements where arousal, argument strength, and subject drug-use risk were systematically varied. Psychophysiological interaction analyses provide support for the affective-executive hypothesis but not for the encoding-disruption hypothesis. Secondary analyses show that video-level connectivity patterns among structures within the persuasion network predict audience responses in independent samples (one college-aged, one nationally representative). We propose that persuasion neuroscience research is best advanced by considering network-level effects while accounting for interactions between message features and target audience characteristics.

Keywords: elaboration likelihood model; fMRI; functional connectivity; persuasion; public service announcements.

© The Author (2017). Published by Oxford University Press.

Figures

Fig. 1.
Fig. 1.
Psychophysiological interaction results when seeding from the medial prefrontal cortex. The figure shows the AS x PHYS > Scrambled Control x PHYS contrast for (A) high-risk and (B) low-risk subjects. Results are cluster corrected for multiple comparisons with the cluster defining threshold set at Z = 2.3 and a cluster extent threshold of P  < 0.05. The red circle represents the seed ROI.
Fig. 2.
Fig. 2.
Psychophysiological interaction results when seeding from the middle frontal gyrus. The figure shows the AS x PHYS > Scrambled Control x PHYS contrast for (A) high-risk and (B) low-risk subjects. Results are cluster corrected for multiple comparisons with the cluster defining threshold set at Z = 2.3 and a cluster extent threshold of P <0.05. Note: No activations survived thresholding for high-risk subjects. The red circle represents the seed ROI.
Fig. 3.
Fig. 3.
Psychophysiological interaction results when seeding from the inferior lateral occipital cortex. The figure shows the MSV x PHYS > Scrambled Control x PHYS contrast for (A) high-risk and (B) low-risk subjects. Results are cluster corrected for multiple comparisons with the cluster defining threshold set at Z = 2.3 and a cluster extent threshold of P <0.05. The red circle represents the seed ROI.
Fig. 4.
Fig. 4.
Network-as-predictor results for high-risk subjects. A stepwise regression model was constructed where self-reported pMSV, pAS, and their interaction was entered in the first step and MFG-SPL connectivity parameter estimates (PEs) were entered in the second step. This analysis shows the unique contribution of self-report and network-connectivity PEs to overall prediction accuracy of perceived message effectiveness in two independent samples (IS1 and IS2). Results are not shown for the low-risk group as the inclusion of network-connectivity PEs did not significantly improve prediction accuracies.

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