Social ageing and higher-order interactions: social selectiveness can enhance older individuals’ capacity to transmit knowledge

In long-lived organisms, experience can accumulate with age, such that older individuals may act as repositories of ecological and social knowledge. Such knowledge is often beneficial and can spread via social transmission, leading to the expectation that ageing individuals will remain socially well-integrated. However, social ageing involves multiple processes that modulate the relationship between age and social connectivity in complex ways. We developed a generative model to explore how social ageing may drive changes in social network position and shape older individuals' capacity to transmit knowledge to others. We further employ novel hypernetwork analyses that capture higher-order interactions (i.e. involving ≥ 3 participants) to reveal potential relationships between age and sociality that conventional dyadic networks may overlook. We find that older individuals in our simulations effectively facilitate transmission across a range of scenarios, especially when transmission resembles a complex contagion or when social selectivity (i.e. prioritization of key relationships) rapidly emerges with age. These patterns result from the formation of tight-knit sets of older associates that co-occur in multiple groups, thereby reinforcing one another's capacity to transmit knowledge. Our findings suggest key avenues for future empirical work and illustrate the use of hypernetworks in advancing the study of social behaviour.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.

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Publication Details

Journal
Philosophical Transactions of the Royal Society B Biological Sciences
Published
2024-10-28
DOI
https://doi.org/10.1098/rstb.2022.0461
Citations
11
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
12.45

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article

Social ageing and higher-order interactions: social selectiveness can enhance older individuals’ capacity to transmit knowledge

Matthew J. Hasenjager, Nina H. Fefferman
11 citations
Philosophical Transactions of the Royal Society B Biological Sciences
Evolutionary Game Theory and Cooperation
12.45
article

Social ageing and higher-order interactions: social selectiveness can enhance older individuals’ capacity to transmit knowledge

Matthew J. Hasenjager, Nina H. Fefferman
article en
11 citations

Abstract

In long-lived organisms, experience can accumulate with age, such that older individuals may act as repositories of ecological and social knowledge. Such knowledge is often beneficial and can spread via social transmission, leading to the expectation that ageing individuals will remain socially well-integrated. However, social ageing involves multiple processes that modulate the relationship between age and social connectivity in complex ways. We developed a generative model to explore how social ageing may drive changes in social network position and shape older individuals' capacity to transmit knowledge to others. We further employ novel hypernetwork analyses that capture higher-order interactions (i.e. involving ≥ 3 participants) to reveal potential relationships between age and sociality that conventional dyadic networks may overlook. We find that older individuals in our simulations effectively facilitate transmission across a range of scenarios, especially when transmission resembles a complex contagion or when social selectivity (i.e. prioritization of key relationships) rapidly emerges with age. These patterns result from the formation of tight-knit sets of older associates that co-occur in multiple groups, thereby reinforcing one another's capacity to transmit knowledge. Our findings suggest key avenues for future empirical work and illustrate the use of hypernetworks in advancing the study of social behaviour.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.

Philosophical Transactions of the Royal Society B Biological SciencesVol. 379(1916)
National Institute for Mathematical and Biological Synthesis (US), University of Tennessee at Knoxville (US)
U.S. Department of Energy, Office of the Director of National Intelligence, Oak Ridge Institute for Science and Education, Intelligence Community Postdoctoral Research Fellowship Program
Reduced inequalities
Openalex Percentile: Top 1%
Evolutionary Game Theory and Cooperation
12.45
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