Dataset Information

Let's get it together: Infants generate visual predictions based on collaborative goals.

ABSTRACT: Infants engage in social interactions that include multiple partners from very early in development. A growing body of research shows that infants visually predict the outcomes of an individual's intentional actions, such as a person reaching towards an object (e.g., Krogh-Jespersen & Woodward, 2014), and even show sophistication in their predictions regarding failed actions (e.g., Brandone, Horwitz, Aslin, & Wellman, 2014). Less is known about infants' understanding of actions involving more than one individual (e.g., collaborative actions), which require representing each partners' actions in light of the shared goal. Using eye-tracking, Study 1 examined whether 14-month-old infants visually predict the actions of an individual based on her previously shared goal. Infants viewed videos of two women engaged in either a collaborative or noncollaborative interaction. At test, only one woman was present and infants' visual predictions regarding her future actions were measured. Fourteen-month-olds anticipated an individual's future actions based on her past collaborative behavior. Study 2 revealed that 11-month-old infants only visually predict higher-order shared goals after engaging in a collaborative intervention. Together, our results indicate that by the second year after birth, infants perceive others' collaborative actions as structured by shared goals and that active engagement in collaboration strengthens this understanding in young infants.

SUBMITTER: Krogh-Jespersen S

PROVIDER: S-EPMC7299182 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:For socially monogamous species, breeder bond dissolution has important consequences for population dynamics, but the extent to which extrinsic or intrinsic population factors causes pair dissolution remain poorly understood, especially among carnivores. Using an extensive life-history data set, a survival analysis and competing risks framework, we examined the fate of 153 different wolf (Canis lupus) pairs in the recolonizing Scandinavian wolf population, during 14 winters of snow tracking and DNA monitoring. Wolf pair dissolution was generally linked to a mortality event and was strongly affected by extrinsic (i.e. anthropogenic) causes. No divorce was observed, and among the pair dissolution where causes have been identified, death of one or both wolves was always involved. Median time from pair formation to pair dissolution was three consecutive winters (i.e. approximately 2 years). Pair dissolution was mostly human-related, primarily caused by legal control actions (36·7%), verified poaching (9·2%) and traffic-related causes (2·1%). Intrinsic factors, such as disease and age, accounted for only 7·7% of pair dissolutions. The remaining 44·3% of dissolution events were from unknown causes, but we argue that a large portion could be explained by an additional source of human-caused mortality, cryptic poaching. Extrinsic population factors, such as variables describing the geographical location of the pair, had a stronger effect on risk of pair dissolution compared to anthropogenic landscape characteristics. Population intrinsic factors, such as the inbreeding coefficient of the male pair member, had a negative effect on pair bond duration. The mechanism behind this result remains unknown, but might be explained by lower survival of inbred males or more complex inbreeding effects mediated by behaviour. Our study provides quantitative estimates of breeder bond duration in a social carnivore and highlights the effect of extrinsic (i.e. anthropogenic) and intrinsic factors (i.e. inbreeding) involved in wolf pair bond duration. Unlike the effects of intrinsic and extrinsic factors that are commonly reported on individual survival or population growth, here we provide quantitative estimates of their potential effect on the social unit of the population, the wolf pair.

Dataset Information

Let's get it together: Infants generate visual predictions based on collaborative goals.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure