ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2022
Collective minds: social network topology shapes collective cognition.
Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
15 citing papers in PubMed.
- Condorcet and Beyond: An Empirical Comparison of Voting Rules.Cognitive science · 2026Article
- Group cognitive space of online rumors in public health emergencies: a theoretical and empirical study.Frontiers in public health · 2026Article
- The effect of habitat health and environmental change on cultural diversity and richness in animals.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- GTAT: empowering graph neural networks with cross attention.Scientific reports · 2025Article
- Human-inspired strategies for controlling swarm systems.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- The Relative Contributions of Traits and Contexts on Social Network Learning.Open mind : discoveries in cognitive science · 2025Article
- Update on "Emotion and autobiographical memory": 14 years of advances in understanding functions, constructions, and consequences.Physics of life reviews · 2024Review
- Oxytocin homogenizes horse group organization.iScience · 2024Article
- Collective events and individual affect shape autobiographical memory.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- A rubric for human-like agents and NeuroAI.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Promoting the Integration of Elderly Healthcare and Elderly Nursing: Evidence from the Chinese Government.International journal of environmental research and public health · 2022Article
- Social learning in swarm robotics.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- The emergence of collective knowledge and cumulative culture in animals, humans and machines.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- The origins of human cumulative culture: from the foraging niche to collective intelligence.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- Paradox of diversity in the collective brain.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
Corrections and comments
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Authors and funding
1 author.
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Abstract
Human cognition is not solitary, it is shaped by collective learning and memory. Unlike swarms or herds, human social networks have diverse topologies, serving diverse modes of collective cognition and behaviour. Here, we review research that combines network structure with psychological and neural experiments and modelling to understand how the topology of social networks shapes collective cognition. First, we review graph-theoretical approaches to behavioural experiments on collective memory, belief propagation and problem solving. These results show that different topologies of communication networks synchronize or integrate knowledge differently, serving diverse collective goals. Second, we discuss neuroimaging studies showing that human brains encode the topology of one's larger social network and show similar neural patterns to neural patterns of our friends and community ties (e.g. when watching movies). Third, we discuss cognitive similarities between learning social and non-social topologies, e.g. in spatial and associative learning, as well as common brain regions involved in processing social and non-social topologies. Finally, we discuss recent machine learning approaches to collective communication and cooperation in multi-agent artificial networks. Combining network science with cognitive, neural and computational approaches empowers investigating how social structures shape collective cognition, which can in turn help design goal-directed social network topologies. This article is part of a discussion meeting issue 'The emergence of collective knowledge and cumulative culture in animals, humans and machines'.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.