Durant et al. 2017 Long-term stochastic editing of regenerative anatomy via bioelectric gradients (Biophys J)

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• The randomization of bioelectric state and downstream morphogen gradients is interpreted with respect to anterior-posterior organ identity by collectives, not by individual cells.claim0.822
  Argues that stochastic outcomes in regeneration are still collective decisions, not cellular chaos.
• Bioelectric networks scale cell computation into anatomical homeostasis and are a mechanism for evolving larger Selves.claim0.776
  Developmental bioelectricity is proposed as a tractable entry point to understand the informational architecture of collective intelligence in morphogenesis.
• Vertebrate face patterning via bioelectric gradientsfinding0.776
• Developmental bioelectricity scales cell-level feedback into anatomical homeostasis.hypothesis0.776
• Bioelectric pattern memories store target morphology for anatomical homeostasis.claim0.772
  Planarian head number can be permanently altered by re-writing bioelectric prepatterns.
• Manipulating bioelectric states can reprogram target morphology without changing genetics.hypothesis0.771
  Demonstrated by inducing two-headed planaria via ion channel drugs; predicts cancer normalization.
• Morphogenetic tissues can be trained via reinforcement learning for specific anatomical outcomes, bypassing the complexity of genomic editing.claim0.770
  Proposes a biomedical strategy of controlling growth by exploiting the learning capacity of cellular collectives.
• If intercellular signaling (not genes) is the cognitive medium of morphogenesis, then bioelectric signals can be read, interpreted, and rewritten to predictively control growth and form without genetic changes.hypothesis0.768
  Predictive hypothesis validated in planarians and other species; enables therapeutic manipulation of morphogenetic targets.