ReviewIntegrative biology : quantitative biosciences from nano to macro2015
Re-membering the body: applications of computational neuroscience to the top-down control of regeneration of limbs and other complex organs.
Review in Integrative biology : quantitative biosciences from nano to macro, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
71 citing papers in PubMed, 176 citations in OpenAlex.
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- Aging as a Loss of Goal-Directedness: An Evolutionary Simulation and Analysis Unifying Regeneration with Anatomical Rejuvenation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
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- Bioelectricity is a universal multifaced signaling cue in living organisms.Molecular biology of the cell · 2025Review
- AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks.eLife · 2025Article
- Life, its origin, and its distribution: a perspective from the Conway-Kochen Theorem and the Free Energy Principle.Communicative & integrative biology · 2025Review
- Stress sharing as cognitive glue for collective intelligences: A computational model of stress as a coordinator for morphogenesis.Biochemical and biophysical research communications · 2024Article
- Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales.Entropy (Basel, Switzerland) · 2024Article
- Self-Improvising Memory: A Perspective on Memories as Agential, Dynamically Reinterpreting Cognitive Glue.Entropy (Basel, Switzerland) · 2024Article
- Collective intelligence: A unifying concept for integrating biology across scales and substrates.Communications biology · 2024Review
- Embryos assist morphogenesis of others through calcium and ATP signaling mechanisms in collective teratogen resistance.Nature communications · 2024Article
- Motile Living Biobots Self-Construct from Adult Human Somatic Progenitor Seed Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain.iScience · 2023Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
A major goal of regenerative medicine and bioengineering is the regeneration of complex organs, such as limbs, and the capability to create artificial constructs (so-called biobots) with defined morphologies and robust self-repair capabilities. Developmental biology presents remarkable examples of systems that self-assemble and regenerate complex structures toward their correct shape despite significant perturbations. A fundamental challenge is to translate progress in molecular genetics into control of large-scale organismal anatomy, and the field is still searching for an appropriate theoretical paradigm for facilitating control of pattern homeostasis. However, computational neuroscience provides many examples in which cell networks - brains - store memories (e.g., of geometric configurations, rules, and patterns) and coordinate their activity towards proximal and distant goals. In this Perspective, we propose that programming large-scale morphogenesis requires exploiting the information processing by which cellular structures work toward specific shapes. In non-neural cells, as in the brain, bioelectric signaling implements information processing, decision-making, and memory in regulating pattern and its remodeling. Thus, approaches used in computational neuroscience to understand goal-seeking neural systems offer a toolbox of techniques to model and control regenerative pattern formation. Here, we review recent data on developmental bioelectricity as a regulator of patterning, and propose that target morphology could be encoded within tissues as a kind of memory, using the same molecular mechanisms and algorithms so successfully exploited by the brain. We highlight the next steps of an unconventional research program, which may allow top-down control of growth and form for numerous applications in regenerative medicine and synthetic bioengineering.
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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.