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leiden_hybrid_concepts
label: haiku
community:leiden_hybrid_concepts-run4-c3-c6Bioelectric computation and morphological intelligence
Systems across kingdoms (neurons, plants, salamanders, xenobots) use bioelectric signaling to solve morphogenesis and behavior, independent of genetic specification.
10 members. Each node is clickable.
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The papers/notes whose extracted claims & findings make up this cluster.
- Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organisms5 members
- Multiple ways to implement and infer sentience3 members
- Active Inference: A Process Theory1 member
- Emergence and Causality in Complex Systems: A Survey on Causal Emergence and Related Quantitative Studies1 member
Bridges (6)
Other communities that share members with this one — cross-cutting threads or papers that sit at the seam between two themes.
Findings (6)
- Plants display goal-directed, anticipatory, flexible, and adaptive behaviors including kin discrimination, cooperation, mimicry, and risk evaluationEmpirical evidence from plant neurobiology showing behavioral patterns historically attributed to animal sentience.
- Ant colony task assignment: interactions between foragers show higher noise than nurses/cleaners; CE stabilizes overall colony cohesion.Swain et al. (2022) EI-based study of ant colonies.
- Plants Display Action-Potential-Like Depolarizations Along Vascular Networks
- Plants synthesize and signal with common neurotransmitters including glutamate and display action-potential-like depolarizations.
- Salamander limb regeneration exhibits precise morphological target-seekingSalamander limbs regenerate missing parts precisely and stop when target morphology is reached, demonstrating goal-directed morphogenesis.
- Salamanders regenerate limbs, jaws, eyes, tails, and ovaries.From McCusker & Gardiner (2011), example of robust regenerative capacity.
Claims (4)
- All neuronal processing and action selection minimize variational free energy, unifying perception, action, and learning.Fundamental assertion: single imperative (free energy minimization) explains diverse cognitive and neural phenomena.
- Evolution learns to generalize beyond default morphologies, producing problem-solving machines.Argues that evolutionary learning goes beyond specific adaptations.
- Physiological software dynamics, not genetic hardware, determine organism phenotype.Authors' central interpretive assertion: genome specifies cell-level components but outcome is product of dynamics not easily predicted from genetic sequence.
- Xenobots’ anatomical and behavioral goals are emergent, rather than directly selected over aeons.Argues that goal states arise without direct evolutionary sculpting.