Nature Neuroscience: doi: /nn Supplementary Figure 1. Blame judgment task.

Transcription

1 Supplementary Figure Blame judgment task. Participants viewed others decisions and were asked to rate them on a scale from blameworthy to praiseworthy. Across trials we independently manipulated the amounts of profit and pain resulting from choices.

2 Supplementary Figure 2 Moral transgressions modulate relative chosen value signal in vmpfc. (a) The model-derived subjective value of the chosen option, relative to the unchosen option, was correlated positively with BOLD responses in a widespread network including vmpfc (k=57, p<0.000), mid-posterior cingulate (P FWE <0.000), precuneus (P FWE <0.000), bilateral clusters encompassing amygdala, striatum and insula (P FWE <0.000). Chosen relative to unchosen subjective value was correlated negatively with BOLD responses in mid-cingulate cortex and anterior insula (P FWE =0.0002). All results whole brain familywise error corrected at the cluster level after voxel-wise thresholding at p<0.00. Image displayed at p < 0.005, uncorrected to show extent of activation. (b) The value-sensitive region of vmpfc (circled in a) showed reduced sensitivity to the value of the harmful option in the other condition relative to the self condition (t (27)=2.5, p=0.09). *P < 0.05; n.s., nonsignificant. Error bars depict s.e.m.

3 Supplementary Figure 3 Neural representation of pain is uncorrelated with moral behavior. (a) At choice onset, left TPJ activity positively correlated with the relative amount of pain a harmful choice could inflict on others, but not self (Δs other > Δs self, mean signal extracted from independently defined ROI in TPJ, t (27) = 2.6, p = 0.05). Image displayed at p<0.005, uncorrected to show extent of activation. (b) Parameter estimates for Δs other and Δs self extracted from ROI in TPJ. At choice onset, left TPJ activity positively correlated with Δs other (t (27) = 2.27, p = 0.03), but not Δs self (t (27) = -0.30, p = 0.77); difference Δs other > Δs self, t (27) = 2.6, p = 0.05). (c) Differential response to self vs. others pain in TPJ was uncorrelated with individual differences in moral preferences (r=-0.4, 95% CI=[ ]). (d) At choice onset, ACC activity positively correlated with the relative amount of pain a harmful choice could inflict on both self and others (Δs other Δs self, mean signal extracted from independently defined ROI in ACC, t (27) = 2.56, p = 0.06). Image displayed at p<0.005, uncorrected to show extent of activation. (e) Parameter estimates for Δs other and Δs self extracted from ROI in ACC. At choice onset, ACC activity positively correlated with Δs self (t (27) = 3.35, p = 0.002) but not Δs other (t (27) = 0.77, p = 0.45). ACC tended to respond more strongly to pain for self than other (t (27) = -.9, p = 0.067). (f) Differential response to pain for self vs others in ACC was uncorrelated with individual differences in moral preferences (robust correlation, r=0.09, 95% CI=[ ]). Error bars depict s.e.m. *P < 0.05; **P < 0.0; n.s., nonsignificant; n.s.t., nonsignificant trend.

4 Supplementary Figure 4 Corticostriatal connectivity during moral decisions and value sensitivity in DS. (a) For illustrative purposes we display parameter estimates for LPFC-DS connectivity during choices to help others, harm others, and help self, extracted from the DS cluster depicted in Fig. 4a. We note that this figure is purely illustrative, and we confine our inferences solely to those arising out of a comparison between conditions (which were significant in a whole brain analysis). (b) The extent to which DS activity was sensitive to relative chosen value predicted the degree of negative connectivity between DS and LPFC during moral choices (robust correlation, r =-0.5, 95% CI [ ]). Error bars depict s.e.m.

5 Supplementary Table. Regions correlating with relative chosen value Positive correlation: Region Name Extent t-value x y z L Amygdala L Rolandic Operculum L Insula L Striatum L Cuneus R Rolandic Operculum R Insula R Striatum R MCC L MCC vmpfc R Cerebellum L Cerebellum L Middle Frontal Gyrus Negative correlation: Region Name Extent t-value x y z L Superior Medial Gyrus R ACC Extent threshold for p < 0.05 whole brain cluster level correction: k > 90 Abbreviations: MCC, mid cingulate cortex; ACC, anterior cingulate cortex

6 Supplementary Table 2. Coordinates for a priori regions of interest ROI X Y Z Reference TPJ Bzdok et al., 202 ACC Lamm et al., 200 Insula Lamm et al., 200 LPFC Hare et al., 2009, 20, 204; Rudorf & Hare 205; Maier et al. 205 DS Choi et al., 202 TPJ, temporo-parietal junction; ACC, anterior cingulate cortex; LPFC, lateral prefrontal cortex; DS, dorsal striatum 2

7 Supplementary Table 3. κself regressed onto Δsself Region Name Extent t-value x y z R Temporal Pole R Insula R Putamen R Postcentral Gyrus R Superior Temporal Gyrus Extent threshold for p < 0.05 whole brain cluster level correction: k > 70 3

8 Supplementary Table 4. Δmself > Δmother Region Name Extent t-value x y z L LPFC Extent threshold for p < 0.05 whole brain cluster level correction: k > 49 4

9 Supplementary Table 5. Moral preferences regressed onto Δmself > Δmother Region Name Extent t-value x y z L Striatum L PCC R Striatum Posterior MPFC L LPFC R Superior Temporal Gyrus Extent threshold for p < 0.05 whole brain cluster level correction: k > 53 5

10 Supplementary Table 6. Conjunction of contrasts in Supplementary Tables & 5 Region Name Extent t-value x y z L Striatum L LPFC Posterior MPFC R Striatum L Middle Frontal Gyrus L Middle Temporal Gyrus L Supramarginal Gyrus R Inferior Temporal Gyrus R Superior Temporal Gyrus Extent threshold for p < 0.05 whole brain cluster level correction: k > 53 6

11 Supplementary Table 7. Response time analysis Regressor RT-GLM t p RT-GLM2 t p Help vs x 0-4 Harm (65.68) ΔV x x 0 - (.99) (.24) Vtotal x 0-4 (4.6) (2.89) Max shocks x x 0-7 (8.3) (6.87) Other vs Self (33.89) Constant (05.43) 9.9. x (93.67) x 0-8 7

12 Supplementary Table 8. Conjunction of PPI contrasts, LPFC seed * [help other > harm other] LPFC seed * [help other > help self] Region Name Extent t-value x y z L Striatum L Thalamus Extent threshold for p < 0.05 whole brain cluster level correction: k > 53 8

13 Supplementary Table 9. Self reports of how decisions were made. Participants responses to the question How did you make decisions. Responses are sorted from highest to lowest moral preferences (kother kself). Each response was coded for content related to value computation and consideration of the pain tolerance of the receiver. 86% of participants used language indicative of value computation (e.g., worth, value, calculate ). Only 7% of participants mentioned concerns about the pain tolerance of the receiver. ID ko - ks FA FA FA5 0.2 FA FA How did you make decisions? Value? Pain? It was a trade off between shocks and money, so there were four categories. The obvious decisions were those that fell into less shocks and more money compared to more shocks and less money. The obviously trickier cases were when a higher payoff was given for more shocks (compared to less money for less shocks). For those types, my decision depended on who was being shocked. I was more willing to shock myself for more money, because I knew specifically my own tolerance and valuation of a shock as compared to being payed. For the receiver, I was inclined to shock less despite less money, as it seems analogous to harming someone for your own financial benefit. The few cases where I did choose the higher shock choice for the receiver were only if the change in shocks between the two choices were marginal yet the financial reward was significant. (If they are already going to be shocked 2 times, one more won't affect their pain levels drastically so there's no reason not to accept the higher compensation). Tried to decide monetary value per shock, if difference was high, might not have selected to shock other person. For myself, almost always chose to receive higher shocks for more money. In most cases, I was willing to receive the bigger shock for the greater amount of money, unless a reduction in the number of shocks only meant a small reduction of money (say, 5 shocks for 0 vs. 8 shocks for I would choose the lower). I also worked out the difference between the two options. So from the numbers above, the difference is 7 shocks for an extra 50p which I would deem insufficient. When deciding on shocks for the other person, I tried to minimise the number of shocks unless a small increase (approx. one or two more) meant a large increase in money (~ 5). Again, here I worked out the difference to see how much the 'extra' shocks were worth. I usually felt that the Receiver would be more sensitive to pain so I was willing to give myself higher shocks, but reluctant to give high shocks to the other. I first looked at the flat amount of money available, then i judged the difference between the amount available and the difference between the number of shocks. I would aim for the most amount of money however, if i noticed the shocks were for the receiver, i would aim for a middle ground between money and shocks. If the shocks were for myself i would be much more inclined to aim for more money. Allocated aroung per shock as to being worth it, worked out a rough gain per extra shocks for myself. For the receiver, tried to give less shocks than to myself, as I felt guilty to give them any. 9

14 FA computed money for shocks for receiver but took more shocks for myself FA3 0. rough cost per shock FA2 0.0 For tasks directed to me, I first reminded myself what a level 8 shock felt like, then considered whether the money was worth it. For shocks differing by -3 but with a larger increment in terms of money, I would normally pick the higher amount of money. But I would almost always pick 0 shocks regardless of how much money the alternative gives me. For shocks directed to the receiver, I would normally pick the lower number of shocks, but if the alternative differed by only shock but had a significantly larger amount of money, I would go for the more shocks option, thinking that the receiver wouldn't mind taking one more shock. FA Depending on the minimum number of shocks each person was to receive, how much money the extra shocks were worth. If it was 0 Id always opt for 0 shocks. FA I put myself in the shoes of the reciever and tried to see how they would feel if someone else put them through that pain for a certain amount of money. FA I tried to work out whether the level of pain was worth the money, comparing the two options. Sometimes I mathematically calculated how much each shock was in monetary value and tried to choose the best overall deal. However, I was also aiming to leave with 5 or more. FA if the money for more shocks was negligible, the lower value was chosen. Attempts were made for the Receiver to remember that (s)he would not be making any money, and therefore just the difference in shocks should be considered. Sometimes. FA I tried to quickly calculate if the tradeoff for more shocks was worth the difference in money - if there were a lot more shocks for a little bit more money, it wasn't worth it. If there were more shocks for a lot more money, than it was worth it. FA always picked best (least shock) option for receiver. For myself the decision was based on relative reward between two shock options. FA I tried to keep the number of shocks low, but earning as much as I could. FA according to how much I gained per unity shock FA I always went for the higher amount of money unless the difference in the money was small and the amount of shocks given were large FA I subtract the 2 amounts of money and compare it with the difference in the number of shocks to see if it is acceptable. The same scale is used for both myself and the receiver FA I wanted to give as few shocks as possible, but if the difference in number of shocks were low, I considered if the additional shocks would be worth the money. FA6-0.0 I tried to make objective decisions, as if I was in both sides FA I did make decisions with less schock and more money for both, me and the receiver. FA thought about how i would feel in the receivers position. Considered the gain of more money over the pain of extra shocks FA I tried to avoid the highest number of shokes if the other option was significantly lower, independently of the money. / In the 0

15 FA FA FA FA FA case where the number of shockes was similar, I made the decision deppending on the money. / I tried to do the same for decider and receiver. Determining whether the difference in money given will be worth the difference in the number of shocks, since most probably there will be shocks anyway. I tried to calculate the ratio of pain to profit and based my decisions on that. There were periods in the experiment when I had more empathy with the receiver and phases where I only considered the profit. Compared the two choices, if one was slightly more shock for an greater increase in money then I chose that one. Though only to a point if the difference in shocks was great and gain in money very little then I chose the less painful option. Mostly consistent for myself or the receiver though if it was a close decision I was slightly more likely to give the receiver more pain. Was the difference in number in shocks worth the extra value of money. ie, would getting two extra shocks be worth Pound? 30p extra a shock was about the lowest I would call it worth it During the first part of the test, I actually feel sympathetic towards the receiver, hence, I will try to compromise profit and number of shocks, and make a least shock, more profit decisions.

16 References Bzdok, D. et al. Parsing the neural correlates of moral cognition: ALE metaanalysis on morality, theory of mind, and empathy. Brain Struct. Funct. 27, (202). Choi, E. Y., Yeo, B. T. T. & Buckner, R. L. The organization of the human striatum estimated by intrinsic functional connectivity. J. Neurophysiol. 08, (202). Hare, T. A., Camerer, C. F. & Rangel, A. Self-Control in Decision-Making Involves Modulation of the vmpfc Valuation System. Science 324, (2009). Hare, T. A., Malmaud, J. & Rangel, A. Focusing Attention on the Health Aspects of Foods Changes Value Signals in vmpfc and Improves Dietary Choice. J. Neurosci. 3, (20). Hare, T. A., Hakimi, S. & Rangel, A. Activity in dlpfc and its effective connectivity to vmpfc are associated with temporal discounting. Front. Neurosci. 8, (204). Lamm, C., Decety, J. & Singer, T. Meta-analytic evidence for common and distinct neural networks associated with directly experienced pain and empathy for pain. NeuroImage 54, (20). Maier, S. U., Makwana, A. B. & Hare, T. A. Acute Stress Impairs Self-Control in Goal-Directed Choice by Altering Multiple Functional Connections within the Brain s Decision Circuits. Neuron 87, (205). Rudorf, S. & Hare, T. A. Interactions between Dorsolateral and Ventromedial Prefrontal Cortex Underlie Context-Dependent Stimulus Valuation in Goal- Directed Choice. J. Neurosci. 34, (204). 2

17 Supplementary Modeling Note Model of moral decision making The table below summarizes the comparison of behavioral fits for computational models of moral decision-making. Bayesian Information Criterion (BIC) scores are summed across subjects. The preferred model was model. All models have an inverse temperature parameter γ. Key: κ, general harm aversion; κself, harm aversion for self; κother, harm aversion for others; αmaxprofit, weight on maximum profit; αmaxpain, weight on maximum pain; βprofit_self, weight on relative profit gained from shocking oneself; βprofit_other, weight on relative profit gained from shocking others; βpain_self, weight on own relative pain; βpain_other, weight on others relative pain; ε, lapse rate. BIC differences of greater than 2 are considered significant. Model comparison summary table Model Description # parameters Model BIC γ, κself, κother γ, κ γ, κself, κother, αmaxprofit γ, κself, κother, αmaxpain γ, βprofit_self, βprofit_other, βpain_self, βpain_other 6 γ, κself, κother, ε Model (preferred model) is described in the main text. To verify that Deciders make moral decisions by separately evaluating the costs of pain for themselves and others, we fit an alternative model (model 2) with just a single harm aversion parameter, κ. ΔV = ( κ)δm κδs (model 2) To verify the assumption in model that the two profit magnitudes were weighted equally (versus placing a greater weight on the maximum relative to the minimum amount of money), we fit a model (model 3) with an additional parameter αmaxprofit that allowed for variation in the weight placed on the maximum amount of money: ΔV = ( κ)δm κδs (model 3) Δm = (α maxprofit m max m min ) To verify the assumption in model that the two shock magnitudes were weighted equally (versus placing a greater weight on the maximum relative to the minimum number of shocks), we fit a model (model 4) with an additional 3

18 parameter αmaxpain that allowed for variation in the weight placed on the maximum number of shocks: ΔV = ( κ)δm κδs (model 4) Δs = (α maxprofit s max s min ) To validate the assumption in model that the weight placed on relative profit is inversely related to the weight placed on relative pain, we fit a model (model 5) that included separate parameters for the weight placed on relative profit gained from self and others (βprofit_self, βprofit_other), and for the weight placed on relative pain for self and others (βpain_self, βpain_other): ΔV = β profit Δm β pain Δs (model 5) β profit = { β profit_self if self trial β profit_ other if other trial β pain = { β pain_self if self trial β pain_ other if other trial Parameter estimates for model 5 indicated that the weight placed on relative profit was indeed inversely correlated with the weight placed on relative pain, both for self trials (robust correlation r = -0.86, 95% CI [ ]) and other trials (robust correlation r = -0.79, 95% CI [ ]). This observation, combined with the relatively poor performance of model 5 relative to model (see table above), justifies our parameterization of harm aversion as an exchange rate (i.e., ratio) between money and pain. In earlier studies using a similar moral decision-making paradigm 5,6 we included two additional parameters in our model that are not included here. First, previous studies used a version of the task where one of the options was selected as the default at the start of the trial, and participants could switch from the default to an alternative option by pressing a key. This version permitted us to fit a loss aversion parameter that captured differences in subjective value between paying money to reduce pain and accepting money to increase pain, but this parameter was not relevant in the current study because participants made a forced choice between two alternatives rather than switching from a default to an alternative. Second, a lapse rate parameter ε captured choice noisiness resulting from factors independent of ΔV (such as inattention). In the current study, participants made highly consistent choices, resulting in the lapse rate parameter ε not improving model fits (see model 6 in table above). 4

19 Parameter estimates and fits for model β κself κother BIC Pseudo-R

20 Model of moral blame Parameter estimates for blame GLMs GLM: Individualized model GLM2: Generic model GLM3: Controlling for total money & shocks Parameter Estimate 95% CI Estimate 95% CI Estimate 95% CI Δm [ ] -0.4 [ ] [ ] Δs 0.05 [ ] 0.3 [0. 0.5] 0.05 [ ] Total money [ ] Total shocks [ ] Δm* κother -0.0 [ ] -0.0 [ ] Δm* κself [ ] [ ] Δs* κother 0.3 [ ] 0.3 [ ] Δs* κself 0.39 [ ] 0.39 [ ] Δm* κother*κself 0.43 [ ] 0.43 [ ] Δs* κother*κself [ ] [ ] constant 0.2 [ ] 0.3 [ ] 0.09 [ ] The blame model was estimated on N=49 participants who completed the moral blame task (Supplementary Fig. ) after completing the moral decision task (Fig. a). The individualized model (GLM) regressed z-scored blame judgments against choice features (Δm, Δs), individual preferences (κother, κself) and their interaction, which captured aspects of blame judgments that related to individual differences in moral preferences (F(8,97) = 6.02, p = 9.7 x 0-8 ). The generic model (GLM2) omitted the regressors pertaining to individual preference parameters, and thus captured variance in blame judgments that were common across all participants regardless of moral preferences (F(2,977) = , p =. x 0-79 ). Finally, in a third model (GLM3) we tested whether the total amounts of money and shocks on each trial exerted independent effects on blame judgments by adding regressors for the total number of money and shocks on each trial to GLM (F(0,969) = 48.76, p = 5. x 0-79 ). Neither total money, nor total shocks, impacted on blame judgments (see table above), and adding these regressors to the model did not change the effects of Δm, Δs, κother, κself and their interaction on blame judgments. In the ROI analysis reported in the main paper we tested whether LPFC signal correlated with a blame regressor built from the individualized model (GLM). We also tested whether LPFC signal correlated with a blame regressor built from the generic model (GLM2). This correlation was significant (t(27) = 5.68, p = 5 x 0-6 ). Therefore, we do not find evidence that LPFC encodes aspects of blame that are unique to a given individual, although we note that our study was not designed to dissociate generic versus individualized components of blame. Future studies could usefully investigate the neural correlates of such components by sampling individuals with sufficient variation in moral preferences such that the individualized and generic components of blame can be orthogonalized. 6