Image processing and analysis

EPI data were analysed using SPM8 (www.fil.ion.ucl.ac.uk/spm). The first five volumes were discarded, and the data were realigned to the sixth volume, unwarped using a fieldmap, normalized to the Montreal Neurological Institute template resampling to a voxel size of 2x2x2 mm, and smoothed with an 8 mm full width at half-maximum Gaussian filter. Data were high-pass filtered at 128 s to remove low-frequency drifts, and the statistical model included an AR(1) autoregressive function to account for autocorrelations.

An event-related analysis was conducted to compare neural responses associated with moral transgression (harm-to-other) and morally neutral (harm-to-self) scenarios. Onsets of interest were time-locked to the appraisal phase of the trial and to the guilt-rating phase of the trial, for both harm-to-self and harm-to-other scenarios, with durations of 6 s for the appraisal phase and variable duration (0-4 s) for the guilt-rating phase. Regressors of interest were created by convolution of these onsets with a canonical hemodynamic response function. Other regressors modelled in the analysis included: goal presentation (pooled across all scenarios); null trials; and errors. The six realignment parameters were modelled as parameters of no interest in both analyses. For one participant, an extra regressor was included to model 3 corrupted images resulting from excessive motion.

132 These images were removed and the adjacent images interpolated in order to prevent

distortion of the between-subjects mask. First-level contrast images were calculated by applying appropriate linear contrasts to the parameter estimates of regressors of interest and entered into second-level analyses. Second-level analyses were conducted by performing one-sample t-tests on each of these contrasts using the summary-statistics approach to random-effects analysis. Whole-brain analyses were conducted using a threshold of p < 0.05, FWE corrected at the voxel level, after applying an inclusive grey matter mask (segmented from the group average anatomical scan). To identify regions that were commonly active during the moral appraisal and guilt reflection, a mask was created at a liberal threshold of p < .001, uncorrected, for the two contrasts of interest (appraisal of harm to other>appraisal of harm to self (AHO > AHS), and reflection on guilt for harm to other>reflection on guilt for harm to self (RHO > RHS). We then ran each contrast using an inclusive mask derived from running the other contrast with a cluster-forming threshold of p<.001 (uncorrected), cluster size 20 voxels), using a threshold of p<0.05 corrected for multiple comparisons at the cluster-level within the mask.

To identify associations between individual differences in psychopathic traits and individual differences in hemodynamic response during moral and guilt processing, we used the Marsbar toolbox (Brett et al., 2009) to create regions of interest (ROIs) and

extracted average contrast estimates across these ROIs based on significant peaks identified from the above whole-brain analyses (ROIs defined as 8 mm spheres with peaks of

significant clusters as centre coordinates). Note that these correlation analyses are

orthogonal to the contrast used to define the ROI. To ensure that our results were due to our personality constructs of interest (distinct dimensions of psychopathy), we ran multiple

133 regression analyses including trait anxiety and intelligence as covariates to control for these variables. Subsequently, to examine the influence of the unique variance of each SRP dimension on criterion variables, the other SRP dimension was entered as a third control variable. Adjustment using the Benjamini and Hochberg False Discovery Rate procedure (FDR; Benjamini and Hochberg, 1995) was used to control the probability of making a Type-I error across multiple regions.

To further clarify the associations found between the magnitude of mOFC response during guilt reflection and psychopathy lifestyle and antisocial personality traits, we carried out a psychophysiological interaction (PPI) analysis, which can elucidate whether

functional integration occurs between regions, as well as how this integration changes as a function of different psychological contexts (Friston et al., 1997). The PPI analysis consists of a design matrix with three regressors: the psychological variable, which represents the experimental task (here, the contrast RHO>RHS); the physiological variable, which represents the neural response in the seed region (here, the mOFC); and a third variable representing the interaction between the first and the second variables. The coordinates of the seed region corresponded to the peak activation within the mOFC cluster detected in RHO>RHS contrast. For each individual, the principal eigenvariate across the fMRI time- series was extracted from a sphere of 8 mm radius centred on the peak height coordinates (physiological variable). This was multiplied by the RHO>RHS contrast (psychological variable) to create a third variable representing the interaction between the time-series and the psychological variable (PPI variable). Following estimation, subject-specific contrast images were then entered into two random-effects analyses using one-sample t-tests: the first using the physiological variable to estimate the direction of the coupling of the mOFC

134 seed region with other regions; and the second using the PPI variable to identify which regions had increased coupling with the mOFC during guilt reflection (RHO relative to RHS). Whole-brain analyses were conducted with a cluster-forming threshold of p<.001 (uncorrected) and cluster size of 20 voxels after applying an inclusive grey matter mask. Regions surviving FWE cluster level correction (p<.05) across the whole brain were considered statistically significant. To examine whether the increased coupling identified during RHO was associated with individual differences in psychopathic traits, we extracted PPI estimates using the Marsbar toolbox (Brett et al., 2002) as described above for the categorical fMRI analysis.

5.4. Results

Demographic and personality statistics are presented on Table 5.1.

Table 5.1. Participants’ demographic and personality statistics

Minimum Maximum Mean S.D.

Age 20 40 26.31 5.51 WASI matrices 41 68 56.83 6.12 STAI Trait 22 58 39.79 9.49 SRP Total 31 80 55.24 14.09 SRP Affective-Interpersonal 14 39 27.38 7.75 SRP Lifestyle-Antisocial 15 46 26.72 7.85

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