Neural signatures of strategic types in a two-person bargaining game

Abstract

The management and manipulation of our own social image in the minds of others requires difficult and poorly understood computations. One computation useful in social image management is strategic deception: our ability and willingness to manipulate other people's beliefs about ourselves for gain. We used an interpersonal bargaining game to probe the capacity of players to manage their partner's beliefs about them. This probe parsed the group of subjects into three behavioral types according to their revealed level of strategic deception; these types were also distinguished by neural data measured during the game. The most deceptive subjects emitted behavioral signals that mimicked a more benign behavioral type, and their brains showed differential activation in right dorsolateral prefrontal cortex and left Brodmann area 10 at the time of this deception. In addition, strategic types showed a significant correlation between activation in the right temporoparietal junction and expected payoff that was absent in the other groups. The neurobehavioral types identified by the game raise the possibility of identifying quantitative biomarkers for the capacity to manipulate and maintain a social image in another person's mind.

Fig. 1.

Experimental task. At the beginning of each round the computer assigns a value for the widget to the buyer. The buyer “suggests a price” to the seller, who uses this information to set a final price for the object. The computer automates whether the deal occurs—if the price is less than or equal to the buyer's value, the seller receives the price, p, and the buyer receives the difference between the price and his private value, v − p. Otherwise, the deal fails and neither party receives anything. Neither party is informed of the outcome of the previous trial; payoffs are just added to a running tally of points kept by the computer.

Fig. 2.

Behavioral analysis. (A) Behavioral clustering in buyers. Incrementalists (blue) send suggestions that are highly correlated with their true value. Strategists (red) send suggestions that are negatively correlated with value. Strategists appear similar to incrementalists and thus reap the surplus from high-value trials. Conservative buyers (green) play closest to an economically rational actor and reveal no information about their value with their suggestions. Triangles indicate subjects who were classified as sophisticated “level-2” buyers according to a generative model. (B) Mean Kullback-Leibler (KL) distances of the players’ choice distribution from the uniform distribution. Incrementalists and strategists are both significantly closer to the uniform distribution than conservatives but are not significantly different from each other. (C) Histograms showing suggestion frequencies for a single incrementalist (Left) and a single strategist (Right). Note that from the perspective of the seller the two are indistinguishable.

Fig. 3.

Group differences were not explained by differences in IQ or socioeconomic status. (A) Although incrementalists had suggestively lower IQs than strategists or conservatives, this was not quite significant (P = 0.07, one-way ANOVA). However, both conservative and strategist IQs were significantly higher than average, whereas incrementalist IQs were not (11 incrementalists, 9 conservatives, and 10 strategists came back to take the IQ test); there was no significant difference between strategist and conservative IQs. (B) We also assessed socioeconomic status on 65 subjects using income, occupation, and education level and found there were no significant differences among the three groups according to one-way ANOVA. (C) Subject earnings by behavioral type: incrementalists had significantly lower final payments for the experiment (P = 0.02, one-way ANOVA); there was no significant difference in means between conservative and strategist earnings. Colored sections of the box-plots indicate the interquartile interval of the data, and whiskers show the total data extent excepting outliers, which are shown as red crosses. The black lines indicate the median data, and the notched section of the box gives a 95% confidence interval for the median.

Fig. 4.

Strategists differentially activate rDLPFC and left BA10. (A) Between-group analysis: strategist activation over the entire trial vs. other groups. Left: Left BA10. Peak voxel at (−32, 48, 20), k = 14, t = 4.72, P = 0.049 at peak voxel (corrected for familywise error over gray matter). Right: Time courses in BA10 by group. (B) Between-group analysis: incrementalist activation over the entire trial vs. other groups. Left: rDLPFC. Peak voxel at (36, 28, 36), k = 27, t = 4.62 at peak voxel, cluster-level P = 0.044 (corrected). Right: Time courses in rDLPFC by group. For both regions clusters are shown at P < 0.001, uncorrected. Cluster extents and cluster-level Ps are reported at this threshold as well. Full statistics are reported in SI Methods. For time courses, all data are normalized to trial onset, dotted black line indicates average decision time, and asterisks indicate significance of the one-way ANOVA on activation at peristimilus time at the P < 0.01 level.

Fig. 5.

Value modulates rTPJ activation only in the strategists. Between-group analysis: interaction of activation at trial onset with value, incrementalists vs. other groups. Left: rTPJ. Peak voxel at (52, −48, 20), k = 10, t = 5.41, P = 0.004 at peak voxel (corrected for familywise error over gray matter). Full statistics are reported in SI Methods. Right: Time courses in rTPJ by group.