paper:doi-10-1146-annurev-bioeng-071114-040647Endogenous Bioelectric Signaling Networks: Exploiting Voltage Gradients for Control of Growth and Form
Original abstract (expand)
Living systems exhibit remarkable abilities to self-assemble, regenerate, and remodel complex shapes. How cellular networks construct and repair specific anatomical outcomes is an open question at the heart of the next-generation science of bioengineering. Developmental bioelectricity is an exciting emerging discipline that exploits endogenous bioelectric signaling among many cell types to regulate pattern formation. We provide a brief overview of this field, review recent data in which bioelectricity is used to control patterning in a range of model systems, and describe the molecular tools being used to probe the role of bioelectrics in the dynamic control of complex anatomy. We suggest that quantitative strategies recently developed to infer semantic content and information processing from ionic activity in the brain might provide important clues to cracking the bioelectric code. Gaining control of the mechanisms by which large-scale shape is regulated in vivo will drive transformative advances in bioengineering, regenerative medicine, and synthetic morphology, and could be used to therapeutically address birth defects, traumatic injury, and cancer.
Related work— refs + corpus + external arXiv
Cited / in-corpus / arXiv badges show which signals surfaced each row. Multi-source rows weighted higher.
- AI-driven control of bioelectric signalling for real-time topological reorganization of cellsGon\c{c}alo Hora de Carvalho2025≈ 80%
- Bioelectrical Interfaces Beyond Cellular Excitability: Cancer, Aging, and Gene Expression ReprogrammingMatthew Burgess, Catarina Franco Jones, Titouan Luciani, Marzia Iarossi, Manuel Schr\"oter, Nako Nakatsuka, Mustafa B. A. Djamgoz, Gil Gon\c{c}alves, Paola Sanju\'an-Alberte, Paula M. Mendes, Frankie J. Rawson, Malavika Nair, Michael Levin, Rosalia Moreddu Paolo Cadinu2025≈ 76%
- The computational boundary of a 'self': developmental bioelectricity drives multicellularity and scale-free cognitionin corpus2019≈ 74%
- Developmental Bioelectricity: the cognitive glue enabling evolutionary scaling from physiology to mindin corpus2023≈ 74%
- Engineering morphogenesis of cell clusters with differentiable programmingFrancesco Mottes, Ariana-Dalia Vlad, Michael P. Brenner, Alma dal Co Ramya Deshpande2025≈ 73%
- Modeling Bioelectric State Transitions in Glial Cells: An ASAL-Inspired Computational Approach to Glioblastoma InitiationWiktoria Agata Pawlak2025≈ 73%
- Optical control of waves in a cardiac excitable mediumAlekxandra Klimas, Christina M. Ambrosi, Emilia Entcheva, and Gil Bub Rebecca A.B. Burton2015≈ 72%
- ≈ 71%
- Microelectronic Morphogenesis: Progress towards Artificial OrganismsDaniil Karnaushenko, Minshen Zhu and Oliver G. Schmidt John S. McCaskill2024≈ 71%
- The scaling of goals via homeostasis: an evolutionary simulation, experiment and analysisJohanna Bischof, Jennifer V. LaPalme, and Michael Levin Leo Pio-Lopez2022≈ 71%
- Bio-Inspired Artificial Neural Networks based on Predictive CodingCharlotte Frenkel, Justin Dauwels Davide Casnici2025≈ 71%
- Plant Bioelectric Early Warning Systems: A Five-Year Investigation into Human-Plant Electromagnetic CommunicationPeter A. Gloor2025≈ 71%
- ≈ 71%
- Collective intelligence: A unifying concept for integrating biology across scales and substratesin corpus2024≈ 70%
- Self-Evidencing Through Hierarchical Gradient Decomposition: A Dissipative System That Maintains Non-Equilibrium Steady-State by Minimizing Variational Free EnergyMichael James McCulloch2025≈ 70%
- Brief Architectural Survey of Biopotential Recording Front-Ends since the 1970sMinkyu Je Taeju Lee2023≈ 70%
- Simulating Tissue Morphogenesis and SignalingSimon Tanaka, Patrick Fried, Philipp Germann and Denis Menshykau Dagmar Iber2013≈ 70%
- ≈ 70%
- Emergent thresholds in genetic regulatory networks: Protein patterning in Drosophila morphogenesisDaniele Muraro Rui Dil\~ao2009≈ 70%
- Control flow in active inference systemsFilippo Fabrocini, Karl Friston, James F. Glazebrook, Hananel Hazan, Michael Levin, and Antonino Marciano Chris Fields2023≈ 70%
- Learning without neurons in physical systemsin corpus2022≈ 70%
- Darwin's agential materials: evolutionary implications of multiscale competency in developmental biologyin corpus2023≈ 69%
- The biogenic approach to cognitionin corpus2005≈ 69%
- Endless forms most beautiful 2.0: teleonomy and the bioengineering of chimaeric and synthetic organismsin corpus2023≈ 69%
- ≈ 68%
- ≈ 68%
- ≈ 68%
- ≈ 68%
- Active Inference: A Process Theoryin corpus2017≈ 68%
- ≈ 67%
Similar preprints — Semantic Scholar
Cited by (5)
- Developmental Bioelectricity: the cognitive glue enabling evolutionary scaling from physiology to mind
Developmental bioelectricity—the network of ion channels, gap junctions, and neurotransmitter-mediated Vmem (membrane potential) dynamics operating across all body cells, not just neurons—functions as
- Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology
Cellular collectives operating between the genotype and anatomical phenotype constitute an agential substrate that fundamentally reshapes the evolutionary search process—this is the central claim of L
- Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds
TAME—Technological Approach to Mind Everywhere—formalizes a non-binary, empirically grounded framework for recognizing, comparing, and manipulating cognition across radically diverse substrates, from
- The computational boundary of a 'self': developmental bioelectricity drives multicellularity and scale-free cognition
Scale-Free Cognition, the framework introduced here, proposes that any coherent Self is demarcated by a 'cognitive light cone'—a spatio-temporal boundary of events a system can measure, model, and att
- AI: a Bridge toward Diverse Intelligence and Humanity’s Future
Current AI debates are importantly incomplete because they fixate on large language models while ignoring the broader space of impending minds — including cyborgs, hybrots, genetically augmented human