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Morphogenesis as Bayesian inference: A variational approach to pattern formation and control in complex biological

Franz Kuchling1, Karl Friston2, Georgi Georgiev3

  • 1Department of Biology, Allen Discovery Center at Tufts University, Medford, MA, USA.

Physics of Life Reviews
|July 20, 2019
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Summary

The free energy principle offers a new framework for understanding biological development and regeneration by modeling cells as Bayesian inference agents. This approach can predict and manipulate complex pattern formation, aiding regenerative medicine and evolutionary studies.

Keywords:
Bayesian inferenceDevelopmental biologyFree energy principleMorphogenesisRegenerationTop-down modeling

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Area of Science:

  • Developmental Biology
  • Computational Neuroscience
  • Systems Biology

Background:

  • Modern molecular biology tools allow precise manipulation of cellular processes.
  • Existing physical and computational models struggle with complex, far-from-equilibrium biological systems.
  • A variational free energy principle, based on active Bayesian inference, has emerged in neuroscience and is being extended to broader biological self-organization.

Purpose of the Study:

  • To present a quantitative formalism for pattern formation based on the free energy principle.
  • To demonstrate how this principle can explain cellular decision-making in development and regeneration.
  • To show the framework's potential for understanding and intervening in processes like morphogenesis and carcinogenesis.

Main Methods:

  • Derivation of the mathematical underpinnings of Bayesian inference within the free energy principle framework.
  • Computational simulations to test the formalism's ability to reproduce experimental observations.
  • Modeling of cellular information processing and generative models.

Main Results:

  • The formalism successfully reproduces top-down manipulations of complex morphogenesis, such as altered axial polarity in simulated planarian regeneration.
  • Simulations illustrate how aberrant cellular signaling, akin to false beliefs, can initiate carcinogenesis.
  • Modifications to the inference process can induce or rescue mis-patterning without altering the cell's underlying generative model (e.g., DNA).

Conclusions:

  • The free energy principle provides a powerful, unifying framework for understanding biological self-organization, pattern formation, and cellular decision-making.
  • This approach offers novel insights into developmental evolution and potential strategies for regenerative medicine.
  • The formalism highlights the role of Bayesian inference in biological processes from embryogenesis to cancer suppression.