Impact of Political Attack Advertisements on Cortical Intersubject Correlations in the Moral Brain

1. Political Attack Advertisements and Political Affiliation Modulate Cortical Intersubject Correlations across the Moral Brain Benjamin O. Turner, NTU Richard Huskey, CCS Lab, OSU René Weber, Media Neuroscience Lab, UCSB THE MEDIA NEUROSCIENCE LAB @MEDIANEURO • MEDIANEUROSCIENCE.ORG

2. OUTLINE 1 Neuroscience of moral processing 2 Intersubject correlation analysis 3 Present analyses & preliminary results 4 Discussion & future directions

3. Moral reasoning network • Moral Foundation Theory (MFT; Haidt, 2001) can be used to understand processing in political communication contexts (e.g., Graham et al., 2009) • Previous work has elucidated the moral reasoning network in the brain (Parkinson et al., 2011) • Other regions/networks may also represent/respond to moral information (secondary regions)

4. Intersubject correlation analysis • Method for identifying task-involved voxels based on similarity of activity timeseries across individuals (Hasson et al., 2004) • Political messages have been previously shown to influence ISCs (Schmälzle et al., 2015); previous research has also shown that synchronization between individuals’ brain activity is driven in part by moral perception (Weber et al., 2011) • Typically used in individual-agnostic way (all individuals averaged)

5. Study design • N=63 participants (21 Democrat, 22 Republican, 20 unaffiliated) • Scanned while watching 22 political attack ads (11 anti- Clinton, 11 anti-Trump; additional scans not described further here) • Block design: Ad length = 30–78s (mean = 38s) • Responses of “liked”/ “disliked” statements A. Political attack ad played for 30-78 seconds B. Between ads, subjects were asked to respond how convincing they found the ad 5 seconds +/-2 seconds jitter

6. Analytic strategy • Separately for each video and for each of 22 ROIs in moral processing network (+ others), compute all pairwise ISCs, labeled according to the partisan affiliation of each member of each pair • Compute average ISCs for each ROI for each Group: Group pairing (e.g., each Democrat–Republican pair → D:R) • Focus on question of how partisan group, ad type (anti-Trump or anti-Clinton) affect moral processing brain areas

7. Aggregated results • Averaged across ROIs, two primary effects emerge: • Anti-Trump ISCs (mean = .102) > Anti-Clinton ISCs (mean = .087) • D:X (mean = .099) & R:X (mean = .095) > U:X (mean = .089)

8. Selected ROI-specific results • Complex pattern across ROIs • E.g., R SPL shows a marginal effect of video type (p = 0.09), a main effect of affiliation (p < 0.001), and an interaction (p < 0.05)

9. Selected ROI-specific results • Complex pattern across ROIs • E.g., R SPL shows a marginal effect of video type (p = 0.09), a main effect of affiliation (p < 0.001), and an interaction (p < 0.05) • While b/l ACC shows only a main effect of affiliation (p < 0.001)

10. Selected ROI-specific results(continued) • Even regions outside of moral network show effects, e.g., visual cortex, which evinces a main effect of affiliation (p < 0.001) as well as an interaction (p < 0.05)

11. Future directions • Would like to move to a more network-based approach, cataloguing moral processing network alongside other networks • Incorporate latest approaches to accounting for non-independence in ISCs in order to generate valid statistics • In further analyses, relate moral content of ads to the relationships identified here • Integrate with other data from project (moral localizer, subsequent partisan behavior)

12. Contributors René Richard Ben Michael Ori Chelsea Freddy Jacob Special Thanks To: Scott Grafton, Michael B. Miller, Joseph N. Cappella Funding: Annenberg Foundation, McCune Foundation, UCSB Brain Imaging Center, UCSB Academic Senate

13. Thank You! THE MEDIA NEUROSCIENCE LAB @MEDIANEURO • MEDIANEUROSCIENCE.ORG