Fig 1.
Task structure for C2 phase and interaction effect.
A, sequence of task for the 2 conditions. B, payoff matrices for both conditions. Participants should ideally classify the image objectively (as they did in the initial classification phase) without using the bet to inform their decision. C, psychometric functions showing the percentage of scene in the image versus probability of responding scene averaged over all participants. D, participant’s choices displayed a motivational bias. The bet x group interaction shows that participants in the cooperation group tended to align with the bet (higher probability of answering scene when the bet was scene), while the competition group tended to disagree with the bet (higher probability of responding with scene when the bet was face). E, response patterns for the two experimental conditions. Self-deception is defined differently based upon experimental group.
Fig 2.
A, the 2-level HGF with parallel processing streams for social and non-social stimuli. The choice data is fed into the model, which is inverted to obtain parameter estimations for an individual. The perceptual model includes the both the social and non-social information, which is then used to compute the combined belief, b. This combined belief is the input to the response model. More details are given in the methods. B, increasing ωs causes the prediction about the accuracy of the bet () to become closer to an extreme (1 or 0). This tilts the combined belief towards this prediction. C, increasing ωns causes the recency bias to have less of an effect on the prediction about the image categorization (
) while perceived tendency (second level belief) dominates the prediction. The effect is stronger when the recent image is very ambiguous.
Fig 3.
Self-deceptive responses occurred more with ambiguous images and are different between paranoia groups.
A, the high paranoia group self-deceived more on slightly less ambiguous images than the low paranoia group. B, the high paranoia group had elevated raw self-deception scores (percentage of self-deceptive responses). C, mean confidence on those self-deceptive trials was elevated in high paranoia participants. D, the confidence-weighted self-deception, which controls for individual variation in baseline-confidence, is higher in the high paranoia group. E, confidence-weighted self-deception is also elevated in the cooperation group relative to the competition group. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001.
Fig 4.
Estimated parameters show differences based on paranoia group and experimental group.
A, the cooperation group has an elevated prior for the social information (μ02,s) compared to the competition group. B, the variance of the perceived tendency of image categorization (ωns) is increased in high paranoia group as well as C, the variance of the perceived tendency of bet accuracy (ωs). *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001. D, ωns (variance of xs,ns) is correlated with confidence weighted self-deception. The correlation is statistically stronger in the high paranoia group. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001.
Fig 5.
A, Difference between the relative perceived choice reliability (rank of ωns) and relative objective classification performance (rank of C1 accuracy) is correlated with confidence-weighted self-deception. A higher ωns represents a lower perceived choice reliability (analogously, a higher perceived choice unreliability), so individuals scoring high on this rank difference have high perceived unreliability and low ability. This relationship is significantly stronger in the high paranoia group compared to the low paranoia group. B, High paranoia is responsible for elevated ωns independent of anxiety. The high paranoia high anxiety group showed similar values of ωns to the high paranoia low anxiety group, while the low paranoia high anxiety group had a significantly decreased ωns.