Using rewards and punishments (nutrients/endorphins and shock) could be a more efficient path to anatomical control than micromanaging molecular hardware.

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• All neuronal processing and action selection minimize variational free energy, unifying perception, action, and learning.claim0.756
  Fundamental assertion: single imperative (free energy minimization) explains diverse cognitive and neural phenomena.
• Vascular system motifs are the means by which we manipulate sensations.claim0.756
  Theravada Buddhism mapping: vascular system as the physical basis of tanha-driven sensation manipulation.
• Stress-sharing populations reach anatomical targets faster than hardwired or non-sharing populations.finding0.750
  Populations with stress sharing discovered correct morphology by generation 500, vs non-sharing and hardwired (p≪0.01).
• Linear interventions across voids in activation space produce incoherent output, while following the manifold curve produces smooth control.claim0.749
  General principle derived from the Mountain Car experiment: curved manifold-following yields coherent manipulation, linear shortcuts fail.
• Morphogenesis could be trainable via reinforcement learning, enabling a new path to anatomical control in regenerative medicine.claim0.748
  Suggests training tissues as an alternative to micromanaging molecular pathways.
• The collective intelligence of tissues is sophisticated enough to be trainable via reinforcement learning for specific morphological outcomes.hypothesis0.748
  Ongoing test prediction: tissues can associate stimuli with rewards to modify anatomy.
• Bioelectric states can serve as master regulators of organogenesis, bypassing the need to manipulate downstream genetic cascades.hypothesis0.747
  Predicts that simple voltage changes can trigger complex modular morphogenetic programs, useful for regenerative medicine.
• Winner take-all architectures of decision-making are already commonplace in computational neuroscience, and the softmax function provides a smooth approximation.claim0.745
  Neural plausibility argument for softmax policy selection.