Unknown

Dataset Information

0

Spreading inequality: neural computations underlying paying-it-forward reciprocity.


ABSTRACT: People tend to pay the generosity they receive from a person forward to someone else even if they have no chance to reciprocate directly. This phenomenon, known as paying-it-forward (PIF) reciprocity, crucially contributes to the maintenance of a cooperative human society by passing kindness among strangers and has been widely studied in evolutionary biology. To further examine its neural implementation and underlying computations, we used functional magnetic resonance imaging together with computational modeling. In a modified PIF paradigm, participants first received a monetary split (i.e. greedy, equal or generous) from either a human partner or a computer. They then chose between two options involving additional amounts of money to be allocated between themselves and an uninvolved person. Behaviorally, people forward the previously received greed/generosity towards a third person. The social impact of previous treatments is integrated into computational signals in the ventromedial prefrontal cortex and the right temporoparietal junction during subsequent decision making. Our findings provide insights to understand the proximal origin of PIF reciprocity.

SUBMITTER: Hu Y 

PROVIDER: S-EPMC6022566 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

altmetric image

Publications

Spreading inequality: neural computations underlying paying-it-forward reciprocity.

Hu Yang Y   He Lisheng L   Zhang Lei L   Wölk Thorben T   Dreher Jean-Claude JC   Weber Bernd B  

Social cognitive and affective neuroscience 20180601 6


People tend to pay the generosity they receive from a person forward to someone else even if they have no chance to reciprocate directly. This phenomenon, known as paying-it-forward (PIF) reciprocity, crucially contributes to the maintenance of a cooperative human society by passing kindness among strangers and has been widely studied in evolutionary biology. To further examine its neural implementation and underlying computations, we used functional magnetic resonance imaging together with comp  ...[more]

Similar Datasets

| S-EPMC3964069 | biostudies-literature
| S-EPMC6872737 | biostudies-literature
| S-EPMC5662289 | biostudies-literature
| S-EPMC2761331 | biostudies-literature
| S-EPMC3968946 | biostudies-literature
| S-EPMC5158095 | biostudies-literature
| S-EPMC10133909 | biostudies-literature
| S-EPMC10801870 | biostudies-literature
| S-EPMC4222636 | biostudies-literature
| S-EPMC3240652 | biostudies-literature