ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019
Statistical physics of liquid brains.
Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Transcriptional Profiling of Planarian Regeneration Habituating to Physiological Stressor Reveals Individual and Collective Dynamics.bioRxiv : the preprint server for biology · 2026Article
- Exploring the computing power of microbes that shapes the environment.Current opinion in microbiology · 2026Review
- Foraging ants as liquid brains: Movement heterogeneity shapes collective efficiency.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Metareview: a survey of active matter reviews.The European physical journal. E, Soft matter · 2025Review
- Fundamental constraints to the logic of living systems.Interface focus · 2024Review
- Spatiotemporal organization of ant foraging from a complex systems perspective.Scientific reports · 2024Article
- Collective intelligence: A unifying concept for integrating biology across scales and substrates.Communications biology · 2024Review
- Self-complexification through integral feedback in eusocial paper wasps of various levels of sociality.Heliyon · 2023Article
- Evolution of Brains and Computers: The Roads Not Taken.Entropy (Basel, Switzerland) · 2022Article
- Embodiment in distributed information processing: "Solid" plants versus "liquid" ant colonies.Quantitative plant biology · 2022Review
- Fate of Duplicated Neural Structures.Entropy (Basel, Switzerland) · 2020Review
- Liquid brains, solid brains.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019Article
- The Neglected Pieces of Designing Collective Decision-Making Processes.Frontiers in robotics and AI · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liquid neural networks (or 'liquid brains') are a widespread class of cognitive living networks characterized by a common feature: the agents (ants or immune cells, for example) move in space. Thus, no fixed, long-term agent-agent connections are maintained, in contrast with standard neural systems. How is this class of systems capable of displaying cognitive abilities, from learning to decision-making? In this paper, the collective dynamics, memory and learning properties of liquid brains is explored under the perspective of statistical physics. Using a comparative approach, we review the generic properties of three large classes of systems, namely: standard neural networks (solid brains), ant colonies and the immune system. It is shown that, despite their intrinsic physical differences, these systems share key properties with standard neural systems in terms of formal descriptions, but strongly depart in other ways. On one hand, the attractors found in liquid brains are not always based on connection weights but instead on population abundances. However, some liquid systems use fluctuations in ways similar to those found in cortical networks, suggesting a relevant role for criticality as a way of rapidly reacting to external signals. This article is part of the theme issue 'Liquid brains, solid brains: How distributed cognitive architectures process information'.
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