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The free-energy principle: a unified brain theory?
Karl Friston
Abstract | A free-energy principle has been proposed recently that accounts for action, perception and learning. This Review looks at some key brain theories in the biological (for example, neural Darwinism) and physical (for example, information theory and optimal control theory) sciences from the free-energy perspective. Crucially, one key theme runs through each of these theories optimization. Furthermore, if we look closely at what is optimized, the same quantity keeps emerging, namely value (expected reward, expected utility) or its complement, surprise (prediction error, expected cost). This is the quantity that is optimized under the free-energy principle, which suggests that several global brain theories might be unified within a free-energy framework.
Free energy
An information theory measure that bounds or limits (by being greater than) the surprise on sampling some data, given a generative model.
Homeostasis
The process whereby an open or closed system regulates its internal environment to maintain its states within bounds.
Entropy
The average surprise of outcomes sampled from a probability distribution or density. A density with low entropy means that, on average, the outcome is relatively predictable. Entropy is therefore a measure of uncertainty.
Despite the wealth of empirical data in neuroscience, there are relatively few global theories about how the brain works. A recently proposed free-energy principle for adaptive systems tries to provide a unified account of action, perception and learning. Although this principle has been portrayed as a unified brain theory1, its capacity to unify different perspectives on brain function has yet to be established. This Review attempts to place some key theories within the free-energy framework, in the hope of identifying common themes. I first review the free-energy principle and then deconstruct several global brain theories to show how they all speak to the same underlying idea.
The free-energy principle
The free-energy principle (BOX 1) says that any self-
organizing system that is at equilibrium with its environment must minimize its free energy2. The principle is essentially a mathematical formulation of how adaptive systems (that is, biological agents, like animals or brains) resist a natural tendency to disorder36. What follows is a non-mathematical treatment of the motivation and implications of the principle. We will see that although the motivation...