A Multi-scale View of the Emergent Complexity of Life: A Free-Energy Proposal

  • Casper HespEmail author
  • Maxwell Ramstead
  • Axel Constant
  • Paul Badcock
  • Michael Kirchhoff
  • Karl Friston
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


We review some of the main implications of the free-energy principle (FEP) for the study of the self-organization of living systems – and how the FEP can help us to understand (and model) biotic self-organization across the many temporal and spatial scales over which life exists. In order to maintain its integrity as a bounded system, any biological system – from single cells to complex organisms and societies – has to limit the disorder or dispersion (i.e., the long-run entropy) of its constituent states. We review how this can be achieved by living systems that minimize their variational free energy. Variational free energy is an information-theoretic construct, originally introduced into theoretical neuroscience and biology to explain perception, action, and learning. It has since been extended to explain the evolution, development, form, and function of entire organisms, providing a principled model of biotic self-organization and autopoiesis. It has provided insights into biological systems across spatiotemporal scales, ranging from microscales (e.g., sub- and multicellular dynamics), to intermediate scales (e.g., groups of interacting animals and culture), through to macroscale phenomena (the evolution of entire species). A crucial corollary of the FEP is that an organism just is (i.e., embodies or entails) an implicit model of its environment. As such, organisms come to embody causal relationships of their ecological niche, which, in turn, is influenced by their resulting behaviors. Crucially, free-energy minimization can be shown to be equivalent to the maximization of Bayesian model evidence. This allows us to cast evolution (i.e., natural selection) in terms of Bayesian model selection, providing a robust theoretical account of how organisms come to match or accommodate the spatiotemporal complexity of their surrounding niche. In line with the theme of this volume, namely, biological complexity and self-organization, this chapter will examine a variational approach to self-organization across multiple dynamical scales.


Free-energy principle Active inference Self-organization Markov blanket Niche construction Variational neuroethology 


  1. Adams, R. A., Bauer, M., Pinotsis, D., & Friston, K. J. (2016). Dynamic causal modelling of eye movements during pursuit: Confirming precision-encoding in V1 using MEG. NeuroImage, 132, 175–189.CrossRefGoogle Scholar
  2. Ao, P. (2008). Emerging of Stochastic Dynamical Equalities and Steady State Thermodynamics. Commun. Theor. Phys. (Beijing, China), 49, 1073–1090.Google Scholar
  3. Arnal, L. H., Wyart, V., & Giraud, A.-L. (2011). Transitions in neural oscillations reflect prediction errors generated in audiovisual speech. Nature Neuroscience, 14(6), 797–801.CrossRefGoogle Scholar
  4. Badcock, P. B. (2012). Evolutionary systems theory: A unifying meta-theory of psychological science. Review of General Psychology: Journal of Division 1, of the American Psychological Association, 16(1), 10–23.CrossRefGoogle Scholar
  5. Badcock, P. B., Davey, C. G., Whittle, S., Allen, N. B., & Friston, K. J. (2017). The Depressed Brain: An Evolutionary Systems Theory. Trends in Cognitive Sciences, 21(3), 182–194.CrossRefGoogle Scholar
  6. Badcock, P. B., Ploeger, A., & Allen, N. B. (2016). After phrenology: Time for a paradigm shift in cognitive science. The Behavioral and Brain Sciences, 39, e121.CrossRefGoogle Scholar
  7. Barandiaran, X., & Moreno, A. (2008). Adaptivity: From Metabolism to Behavior. Adaptive Behavior, 16(5), 325–344.CrossRefGoogle Scholar
  8. Bastos, A. M., Usrey, W. M., Adams, R. A., Mangun, G. R., Fries, P., & Friston, K. J. (2012, November 21). Canonical Microcircuits for Predictive Coding. Neuron.Google Scholar
  9. Berger, P. L. & T. Luckmann. (1966). The Social Construction of Reality: A Treatise in the Sociology of Knowledge. Garden City, NY: Anchor Books.Google Scholar
  10. Branco, T., Clark, B. A., & Häusser, M. (2010). Dendritic discrimination of temporal input sequences in cortical neurons. Science, 329(5999), 1671–1675.ADSCrossRefGoogle Scholar
  11. Bruineberg, J. (2018). Anticipating affordances: Intentionality in self-organizing brain-body-environment systems (Doctoral dissertation). Retrieved from UvA-DARE.Google Scholar
  12. Bruineberg, J., & Rietveld, E. (2014). Self-organization, free energy minimization, and optimal grip on a field of affordances. Frontiers in Human Neuroscience, 8, 599.CrossRefGoogle Scholar
  13. Campbell, J. O. (2016). Universal Darwinism As a Process of Bayesian Inference. Frontiers in Systems Neuroscience, 10, 49.CrossRefGoogle Scholar
  14. Chemero, A. (2009). Radical embodied cognition. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
  15. Clark, A. (2015). Surfing uncertainty: prediction, action, and the embodied mind. New York, N.Y.: Oxford University Press.Google Scholar
  16. Colombo, M. (2014). Explaining social norm compliance. A plea for neural representations. Phenomenol. Cogn. Sci. 13, 217–238.CrossRefGoogle Scholar
  17. Constant, A., Bervoets, J., Hens, K., & Van de Cruys, S. (2018a). Precise Worlds for Certain Minds: An Ecological Perspective on the Relational Self in Autism. Topoi. An International Review of Philosophy, 1–13.Google Scholar
  18. Constant, A., Ramstead, M. J. D., Veissière, S. P. L., Campbell, J. O., & Friston, K. J. (2018b). A variational approach to niche construction. Journal of the Royal Society, Interface, 15(141).Google Scholar
  19. Cook, R., Bird, G., Catmur, C., Press, C., & Heyes, C. (2014). Mirror neurons: From origin to function. Behavioral and Brain Sciences, 37(2), 177–192.CrossRefGoogle Scholar
  20. Dawkins, R. (1976). The Selfish Gene, New York: Oxford University Press.Google Scholar
  21. Edelman, G. M. (1987). The Theory of Neuronal Group Selection. New York: Basic Books.Google Scholar
  22. Engel, A. K., Friston, K. J., & Kragic, D. (2016). The Pragmatic Turn: Toward Action-Oriented Views in Cognitive Science. MIT Press.Google Scholar
  23. Fragaszy, D. M. (2011). Community Resources for Learning: How Capuchin Monkeys Construct Technical Traditions. Biological Theory, 6(3), 231–240. CrossRefGoogle Scholar
  24. Fragaszy, D. M., Eshchar, Y., Visalberghi, E., Resende, B., Laity, K., & Izar, P. (2017). Synchronized practice helps bearded capuchin monkeys learn to extend attention while learning a tradition. Proceedings of the National Academy of Sciences, 114(30), 7798–7805.CrossRefGoogle Scholar
  25. Friston, K. J. (2010). The free-energy principle: a unified brain theory? Nature Reviews. Neuroscience, 11(2), 127–138.CrossRefGoogle Scholar
  26. Friston, K., Levin, M., Sengupta, B., & Pezzulo, G. (2015). Knowing one’s place: A free-energy approach to pattern regulation. Journal of the Royal Society Interface, 12(105), 20141383.CrossRefGoogle Scholar
  27. Friston, K. J. (2013). Life as we know it. Journal of the Royal Society, Interface / the Royal Society, 10(86), 20130475.CrossRefGoogle Scholar
  28. Friston, K., & Ao, P. (2012). Free-energy, value and attractors. Computational and mathematical methods in medicine, 937860.zbMATHGoogle Scholar
  29. Friston, K. J., Daunizeau, J., & Kiebel, S. J. (2009). Reinforcement learning or active inference? PloS One, 4(7), e6421.ADSCrossRefGoogle Scholar
  30. Friston, K. J., & Frith, C. D. (2015). Active inference, communication and hermeneutics. Cortex; a Journal Devoted to the Study of the Nervous System and Behavior, 68, 129–43.CrossRefGoogle Scholar
  31. Friston, K., Mattout, J., & Kilner, J. (2011). Action understanding and active inference. Biological Cybernetics, 104(1–2), 137–160.MathSciNetzbMATHCrossRefGoogle Scholar
  32. Friston, K., Thornton, C., & Clark, A. (2012). Free-energy minimization and the dark-room problem. Frontiers in Psychology, 3, 130.Google Scholar
  33. Gibson, J. J. (1979). The ecological approach to visual perception: classic edition. Psychology Press.Google Scholar
  34. Godfrey-Smith, P. (1996). Complexity and the Function of Mind in Nature. Cambridge University Press.Google Scholar
  35. Gulledge, A. T., Kampa, B. M., & Stuart, G. J. (2005). Synaptic integration in dendritic trees. Journal of Neurobiology, 64(1), 75–90.CrossRefGoogle Scholar
  36. Hamilton, W. D. (1964). The genetical evolution of social behaviour. I. Journal of Theoretical Biology, 7(1), 1–16.MathSciNetCrossRefGoogle Scholar
  37. Hickok, G. (2010). The role of mirror neurons in speech perception and action word semantics. Language and Cognitive Processes, 25:6, 749–776.CrossRefGoogle Scholar
  38. Hickok, G. (2013). Predictive coding? Yes, but from what source? The Behavioral and Brain Sciences, 36(4), 358.CrossRefGoogle Scholar
  39. Hohwy, J. (2013). The predictive mind. Oxford: Oxford University Press.CrossRefGoogle Scholar
  40. Hohwy, J. (2016), The Self-Evidencing Brain. Noûs, 50: 259–285.CrossRefGoogle Scholar
  41. Huygens, C. (1673). Horologium oscillatorium. France: Parisiis.Google Scholar
  42. Kiebel, S. J., Daunizeau, J., & Friston, K. J. (2008). A hierarchy of time-scales and the brain. PLoS Computational Biology, 4(11), e1000209.ADSCrossRefGoogle Scholar
  43. Kiebel, S. J., & Friston, K. J. (2011). Free energy and dendritic self-organization. Frontiers in Systems Neuroscience, 5, 80.CrossRefGoogle Scholar
  44. Kilner, J. M., Friston, K. J., & Frith, C. D. (2007). Predictive coding: an account of the mirror neuron system. Cognitive Processing, 8(3), 159–166.CrossRefGoogle Scholar
  45. Kirchhoff, M. (2017a). Predictive brains and embodied, enactive cognition: an introduction to the special issue. Synthese, 1–12.Google Scholar
  46. Kirchhoff, M., Parr, T., Palacios, E., Friston, K., & Kiverstein, J. (2018). The Markov blankets of life: autonomy, active inference and the free energy principle. Journal of the Royal Society, Interface / the Royal Society, 15(138).
  47. Kirchhoff, M.D. (2017b). Predictive processing, perceiving and imagining: Is to perceive to imagine, or something close to it? Philosophical Studies, 1–17, doi:
  48. Kirchhoff, M.D. (2015). Species of realization and the Free Energy Principle. The Australasian Journal of Philosophy, 93(4), 706–723.CrossRefGoogle Scholar
  49. Lendvai, B., Stern, E. A., Chen, B., and Svoboda, K. (2000). Experience-dependent plasticity of dendritic spines in the developing rat barrel cortex in vivo. Nature 404, 876–881.ADSCrossRefGoogle Scholar
  50. Manneville, P. (1995). Dissipative Structures and Weak Turbulence. Springer Lecture Notes in Physics, 457, 257–272.ADSMathSciNetzbMATHCrossRefGoogle Scholar
  51. Maynard Smith, J. (1964). Group selection and kin selection. Nature, 201(4924), 1145–1147.CrossRefGoogle Scholar
  52. McKinley, J. (2015). Critical Argument and Writer Identity: Social Constructivism as a Theoretical Framework for EFL Academic Writing. Critical Inquiry in Language Studies, 12(3), 184–207.CrossRefGoogle Scholar
  53. Mirza, M. B., Adams, R. A., Mathys, C. D., & Friston, K. J. (2016). Scene Construction, Visual Foraging, and Active Inference. Frontiers in Computational Neuroscience, 10, 56.CrossRefGoogle Scholar
  54. Naiman, R. J., Johnston, C. A., & Kelley, J. C. (1988). Alteration of North American Streams by Beaver: The structure and dynamics of streams are changing as beaver recolonize their historic habitat. Bioscience, 38(11), 753–762.CrossRefGoogle Scholar
  55. Noë, A. (2004). Action in Perception. MIT Press.Google Scholar
  56. Odling-Smee, F. J., & Laland, K. N. (2000). Niche Construction and Gene-Culture Coevolution: An Evolutionary Basis for the Human. In T. N. S. Tonneau F. (Ed.), Perspectives in Ethology (Vol. Sciences Perspecties in Ethology, 13). Boston, MA: Springer.Google Scholar
  57. Odling-Smee, J., Erwin, D. H., Palkovacs, E. P., Feldman, M. W., & Laland, K. N. (2013). Niche construction theory: a practical guide for ecologists. The Quarterly Review of Biology, 88(1), 4–28.CrossRefGoogle Scholar
  58. Odling-Smee, J., Laland, K. N., & Feldman, M. W. (2003). Niche Construction: The Neglected Process in Evolution. Princeton University Press.Google Scholar
  59. Palacios, E. R., Razi, A., Parr, T., Kirchhoff, M., & Friston, K. (2017, November 30). Biological Self-organisation and Markov blankets. bioRxiv. bioRxiv.Google Scholar
  60. Orgel, L. E., & Crick, F. H. C. (1980). Selfish DNA: the ultimate parasite. Nature, 284(5757), 604–607.ADSCrossRefGoogle Scholar
  61. Parr, T., & Friston, K. J. (2018). Active inference and the anatomy of oculomotion. Neuropsychologia, 111, 334–343.CrossRefGoogle Scholar
  62. Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Mateo, CA: Morgan Kaufmann.zbMATHGoogle Scholar
  63. Ramstead, M. J. D., Badcock, P. B., & Friston, K. J. (2017). Answering Schrödinger’s question: A free-energy formulation. Physics of Life Reviews.
  64. Ramstead, M. J. D., Badcock, P. B., & Friston, K. J. (2018). Variational neuroethology: Answering further questions: Reply to comments on “Answering Schrödinger’s question: A free-energy formulation.” Physics of Life Reviews, 24, 59–66.Google Scholar
  65. Ramstead, M. J. D., Veissière, S. P. L., & Kirmayer, L. J. (2016). Cultural affordances: scaffolding local worlds through shared intentionality and regimes of attention. Frontiers in Psychology, 7, 1090.CrossRefGoogle Scholar
  66. Seifert, U. (2012). Stochastic thermodynamics, fluctuation theorems and molecular machines. Rep Prog Phys, 75(12), 126001. doi: ADSCrossRefGoogle Scholar
  67. Sengupta, B., Stemmler, M. B., & Friston, K. J. (2013). Information and Efficiency in the Nervous System – A Synthesis. PLoS Computational Biology, 9(7).Google Scholar
  68. Sengupta, B., Tozzi, A., Cooray, G. K., Douglas, P. K., & Friston, K. J. (2016). Towards a Neuronal Gauge Theory. PLoS Biology, 14(3), e1002400.CrossRefGoogle Scholar
  69. Sgrò, C. M., Lowe, A. J. and Hoffmann, A. A. (2011), Building evolutionary resilience for conserving biodiversity under climate change. Evolutionary Applications, 4: 326–337.CrossRefGoogle Scholar
  70. Stotz, K. (2017). Why developmental niche construction is not selective niche construction: and why it matters. Interface Focus, 7(5), 20160157.CrossRefGoogle Scholar
  71. Sun, Y., Gomez, F., #252, & Schmidhuber, R. (2011). Planning to be surprised: optimal Bayesian exploration in dynamic environments. Paper presented at the Proceedings of the 4th international conference on Artificial general intelligence, Mountain View, CA.Google Scholar
  72. Thompson, E. (2007). Mind in life: biology, phenomenology, and the sciences of mind. Cambridge, MA: Harvard University Press.Google Scholar
  73. Torben-Nielsen, B., & Stiefel, K. M. (2009). Systematic mapping between dendritic function and structure. Network, 20(2), 69–105.CrossRefGoogle Scholar
  74. van Dijk, L., Withagen, R., & Bongers, R. M. (2015). Information without content: A Gibsonian reply to enactivists’ worries. Cognition, 134, 210–214.CrossRefGoogle Scholar
  75. Varela, F. G., Maturana, H. R., & Uribe, R. (1974). Autopoiesis: the organization of living systems, its characterization and a model. Currents in Modern Biology, 5(4), 187–96.Google Scholar
  76. Varela, F. J., Thompson, E., & Rosch, E. (2017). The Embodied Mind: Cognitive Science and Human Experience. MIT Press.Google Scholar
  77. Weiss, L., Brandl, P., & Frynta, D. (2015). Fear reactions to snakes in naïve mouse lemurs and pig-tailed macaques. Primates, 56(3), 279–284.CrossRefGoogle Scholar
  78. Yi, S., Wierstra, D., Schaul, T., & Schmidhuber, J. (2009). Stochastic search using the natural gradient. In Proceedings of the 26th Annual International Conference on Machine Learning – ICML ‘09 (pp. 1–8). New York, New York, USA: ACM Press.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Casper Hesp
    • 1
    Email author
  • Maxwell Ramstead
    • 2
  • Axel Constant
    • 1
  • Paul Badcock
    • 3
  • Michael Kirchhoff
    • 4
  • Karl Friston
    • 5
  1. 1.Amsterdam Centre for Brain and CognitionUniversity of AmsterdamAmsterdamNetherlands
  2. 2.Department of PhilosophyMcGill UniversityMontrealCanada
  3. 3.Melbourne School of Psychological SciencesThe University of MelbourneMelbourneAustralia
  4. 4.Department of PhilosophyUniversity of WollongongWollongongAustralia
  5. 5.Wellcome Centre for NeuroimagingUniversity College LondonLondonUK

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