The Variational Principles of Cognition

  • Karl Friston
Part of the Nonlinear Systems and Complexity book series (NSCH, volume 20)


This chapter provides a theoretical perspective on a dynamics, from the perspective of the free-energy principle. This variational principle offers a natural explanation for neuronal activity that is formulated in terms of dynamical systems and attracting sets. We will see that the free-energy principle emerges when we consider the ensemble dynamics of any pattern forming, self-organizing system. When we look closely what this principle implies for the behavior of systems like the brain, one finds a fairly simple explanation for active inference and the Bayesian brain hypothesis. Within the Bayesian brain framework, the ensuing dynamics can be separated, in a principled way, into those serving perceptual inference, learning and behavior. Dynamics here are central; not only to an understanding the nature of self-organizing systems but also to explain the adaptive nature of neuronal dynamics and plasticity in terms of optimization. The special focus of this chapter is on the pre-eminent role of heteroclinic cycles in providing deep and dynamic (generative) models of the sensorium; particularly, the sensations that we generate ourselves through movement. In what follows, we will briefly rehearse the basic theory and illustrate its implications using simulations of action (handwriting)—and its observation.


Free energy Entropy Neural activity Bayesian brain Dynamics 



I am indebted to Mikhail Rabinovich for his guidance and insights into winnerless competition and its formulation in terms of generalized Lotka–Volterra systems that underly the work presented in this chapter. The Wellcome Trust funded this work.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.The Wellcome Trust Centre for NeuroimagingUniversity College LondonLondonUK

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