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Self-contribution to the income (individual achievement) was an important factor which needs to be taken into individual’s fairness considerations. This study aimed at elucidating the modulation of self-contribution to the income, on recipient’s responses to unfairness in the Ultimatum Game. Eighteen participants were scanned while they were playing an adapted version of the Ultimatum Game as responders. Before splitting money, the proposer and the participant (responder) played the ball-guessing game. The responder’s contribution to the income was manipulated by both the participant’s and the proposer’s accuracy in the ball-guessing game. It turned out that the participants more often rejected unfair offers and gave lower fairness ratings when they played a more important part in the earnings. At the neural level, anterior insula, anterior cingulate cortex, dorsolateral prefrontal cortex and temporoparietal junction showed greater activities to unfairness when self-contribution increased, whereas ventral striatum and medial orbitofrontal gyrus showed higher activations to fair (vs unfair) offers in the other-contributed condition relative to the other two. Besides, the activations of right dorsolateral prefrontal cortex during unfair offers showed positive correlation with rejection rates in the self-contributed condition. These findings shed light on the significance of self-contribution in fairness-related social decision-making processes. [ABSTRACT FROM AUTHOR]

Human empathy is not merely a resonance with others’ physical condition, but is modulated by social factors. Using functional magnetic resonance imaging, the present study demonstrated an increased brain empathic response to others in pain when they received no rather than a large reward, with increments of the ACC, aMCC, insula and postcentral gyrus in the pain matrix and temporoparietal junction. Thus, pain target’s financial situation modulated brain empathic responses in the pain matrix based on an understanding of the situation pain target faces. [ABSTRACT FROM AUTHOR]

We propose two efficient numerical methods of evaluating the luminosity distance in the spatially flat Lambda cold dark matter universe. The first method is based on the Carlson symmetric form of elliptic integrals, which is highly accurate and can replace numerical quadratures. The second method, using a modified version of Hermite interpolation, is less accurate but involves only basic numerical operations and can be easily implemented. We compare our methods with other numerical approximation schemes and explore their respective features and limitations. Possible extensions of these methods to other cosmological models are also discussed. [ABSTRACT FROM AUTHOR]