Collective intelligence: A unifying concept for integrating biology across scales and substrates

Communications Biology, Год журнала: 2024, Номер 7(1)

Опубликована: Март 28, 2024

Abstract A defining feature of biology is the use a multiscale architecture, ranging from molecular networks to cells, tissues, organs, whole bodies, and swarms. Crucially however, not only nested structurally, but also functionally: each level able solve problems in distinct problem spaces, such as physiological, morphological, behavioral state space. Percolating adaptive functionality one competent subunits higher functional organization requires collective dynamics: multiple components must work together achieve specific outcomes. Here we overview number biological examples at different scales which highlight ability cellular material make decisions that implement cooperation toward homeodynamic endpoints, intelligence by solving cell, tissue, whole-organism levels. We explore hypothesis province groups animals, an important symmetry exists between science swarms competencies cells other systems scales. then briefly outline implications this approach, possible impact tools field diverse for regenerative medicine synthetic bioengineering.

Язык: Английский

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Future medicine: from molecular pathways to the collective intelligence of the body

Trends in Molecular Medicine, Год журнала: 2023, Номер 29(9), С. 687 - 710

Опубликована: Июль 20, 2023

The remarkable anatomical homeostasis exhibited by complex living organisms suggests that they are inherently reprogrammable information-processing systems offer numerous interfaces to their physiological and problem-solving capacities. We briefly review data suggesting the multiscale competency of forms affords a new path for biomedicine exploits innate collective intelligence tissues organs. concept tissue-level allostatic goal-directedness is already bearing fruit in clinical practice. sketch roadmap towards 'somatic psychiatry' using advances bioelectricity behavioral neuroscience design methods induce self-repair structure function. Relaxing assumption cellular control mechanisms static, exploiting powerful concepts from cybernetics, science, developmental biology may spark definitive solutions current biomedical challenges.

Язык: Английский

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Principled Limitations on Self-Representation for Generic Physical Systems

Entropy, Год журнала: 2024, Номер 26(3), С. 194 - 194

Опубликована: Фев. 24, 2024

The ideas of self-observation and self-representation, the concomitant idea self-control, pervade both cognitive life sciences, arising in domains as diverse immunology robotics. Here, we ask a very general way whether, to what extent, these make sense. Using generic model physical interactions, prove theorem several corollaries that severely restrict applicable notions self-observation, self-control. We show, particular, adding observational, representational, or control capabilities meta-level component system cannot, even principle, lead complete representation whole. conclude self-representation can at best be heuristic, self models general, empirically tested by systems implement them.

Язык: Английский

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Aging as a loss of morphostatic information: A developmental bioelectricity perspective

Ageing Research Reviews, Год журнала: 2024, Номер 97, С. 102310 - 102310

Опубликована: Апрель 17, 2024

Язык: Английский

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Stress sharing as cognitive glue for collective intelligences: A computational model of stress as a coordinator for morphogenesis

Biochemical and Biophysical Research Communications, Год журнала: 2024, Номер 731, С. 150396 - 150396

Опубликована: Июль 14, 2024

Individual cells have numerous competencies in physiological and metabolic spaces. However, multicellular collectives can reliably navigate anatomical morphospace towards much larger, reliable endpoints. Understanding the robustness control properties of this process is critical for evolutionary developmental biology, bioengineering, regenerative medicine. One mechanism that has been proposed enabling individual to coordinate toward specific morphological outcomes sharing stress (where a parameter reflects current amount error context homeostatic loop). Here, we construct analyze multiscale agent-based model morphogenesis which quantitatively examine impact on ability reach target morphology. We found improves morphogenetic efficiency collectives; populations with reached targets faster. Moreover, influenced future fate distant multi-cellular collective, enhancing cells' movement their radius influence, consistent hypothesis works increase cohesiveness collectives. During development, goal states could not be inferred from observation states, revealing limitations knowledge goals by an extern observer outside system itself. Taken together, our analyses support important role natural engineered systems seek robust large-scale behaviors emerge activity competent components.

Язык: Английский

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Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales

Entropy, Год журнала: 2024, Номер 26(7), С. 532 - 532

Опубликована: Июнь 21, 2024

In recent years, the scientific community has increasingly recognized complex multi-scale competency architecture (MCA) of biology, comprising nested layers active homeostatic agents, each forming self-orchestrated substrate for layer above, and, in turn, relying on structural and functional plasticity layer(s) below. The question how natural selection could give rise to this MCA been focus intense research. Here, we instead investigate effects such decision-making competencies agential components process evolution itself, using silico neuroevolution experiments simulated, minimal developmental biology. We specifically model morphogenesis with neural cellular automata (NCAs) utilize an evolutionary algorithm optimize corresponding parameters objective collectively self-assembling a two-dimensional spatial target pattern (reliable morphogenesis). Furthermore, systematically vary accuracy which uni-cellular agents NCA can regulate their cell states (simulating stochastic processes noise during development). This allows us continuously scale agents' levels from direct encoding scheme (no competency) (with perfect reliability decision executions). demonstrate that proceeds much more rapidly when evolving compared directly. Moreover, evolved MCAs generalize well toward system parameter changes even modified functions process. Thus, adaptive problem-solving parts our NCA-based strongly affect process, suggesting significant implications near-ubiquitous seen living matter.

Язык: Английский

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AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks

eLife, Год журнала: 2025, Номер 13

Опубликована: Янв. 13, 2025

Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, controlling the complex behavior of chemical genetic networks. The emerging field diverse intelligence investigates problem-solving capacities unconventional agents. However, few quantitative tools exist for exploring competencies non-conventional systems. Here, we view gene regulatory networks (GRNs) as agents navigating a problem space develop automated to map robust goal states GRNs can reach despite perturbations. Our contributions include: (1) Adapting curiosity-driven exploration algorithms from AI discover range reachable GRNs, (2) Proposing empirical tests inspired by behaviorist approaches assess their navigation competencies. data shows that models inferred biological wide spectrum steady states, exhibiting various physiological network dynamics without requiring structural changes properties or connectivity. We also explore applicability these ‘behavioral catalogs’ comparing evolved across networks, designing drug interventions biomedical contexts bioengineering. These emphasis behavior-shaping open new paths efficiently For interactive version this paper, please visit https://developmentalsystems.org/curious-exploration-of-grn-competencies .

Язык: Английский

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The Genomic Code: the genome instantiates a generative model of the organism

Trends in Genetics, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

How does the genome encode form of organism? What is nature this genomic code? Inspired by recent work in machine learning and neuroscience, we propose that encodes a generative model organism. In scheme, analogy with variational autoencoders (VAEs), comprises connectionist network, embodying compressed space 'latent variables', weights get encoded algorithm evolution decoded through processes development. The accounts for complex, distributed genetic architecture most traits emergent robustness evolvability developmental processes, while also offering conception lends itself to formalization.

Язык: Английский

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How Physical Information Underlies Causation and the Emergence of Systems at all Biological Levels

Acta Biotheoretica, Год журнала: 2025, Номер 73(2)

Опубликована: Март 25, 2025

To bring clarity, the term 'information' is resolved into three distinct meanings: physical pattern, statistical relations and knowledge about things. In parallel, kinds of 'causation' are resolved: action force constrained by pattern (efficient cause), cybernetic (formal cause) inference. Cybernetic causation an expression fundamental (necessary) logical relations, inference phenomenological, but information proposed as what actually happens in world. Examples latter given to illustrate underlying material dynamics a range biological systems from appearance 'synergistic information' among multiple variables (mainly neuroscience); positional multicellular development; organisational structure ecological communities, especially incorporating niche construction theory. A rigorous treatment multi-level provided well explanation causal power non-physical structure, interaction networks. The focus on particular echoing insights Howard Pattee, provides more physically grounded view emergence, downward concept 'closure efficient causation', all now prevalent approach biology.

Язык: Английский

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Basal Xenobot transcriptomics reveals changes and novel control modality in cells freed from organismal influence

Communications Biology, Год журнала: 2025, Номер 8(1)

Опубликована: Апрель 22, 2025

Abstract Would transcriptomes change if cell collectives acquired a novel morphogenetic and behavioral phenotype in the absence of genomic editing, transgenes, heterologous materials, or drugs? We investigate effects morphology nascent emergent life history on gene expression basal (no engineering, no sculpting) form Xenobots —autonomously motile constructs derived from Xenopus embryo ectodermal explants. To differences between cells context an with those that have been freed instructive signals lived experiences, we compare these age-matched embryos. Basal show significantly larger inter-individual variability than embryos, suggesting increased exploration transcriptional space. identify at least 537 (non-epidermal) transcripts uniquely upregulated Xenobots. Phylostratigraphy shows majority transcriptomic shifts towards evolutionarily ancient transcripts. Pathway analyses indicate categories motility machinery, multicellularity, stress immune response, metabolism, thanatotranscriptome, sensory perception sound mechanical stimuli. experimentally confirm respond to acoustic stimuli via changes behavior. Together, data may implications for evolution, biomedicine, synthetic morphoengineering.

Язык: Английский

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