The Free Energy Principle (FEP) is a normative computational framework for iterative reduction of prediction error and uncertainty through perception–intervention cycles that has been presented as a potential unifying theory of all brain functions (Friston, 2006). Any theory hoping to unify the brain sciences must be able to explain the mechanisms of decision-making, an important cognitive faculty, without the addition of independent, irreducible notions. This challenge has been accepted by several proponents of the FEP (Friston, 2010; Gershman, 2019). We evaluate attempts to reduce decision-making to the FEP, using Lucas' (2005) meta-theory of the brain's contextual constraints as a guidepost. We find reductive variants of the FEP for decision-making unable to explain behavior in certain types of diagnostic, predictive, and multi-armed bandit tasks. We trace the shortcomings to the core theory's lack of an adequate notion of subjective preference or “utility”, a concept central to decision-making and grounded in the brain's biological reality. We argue that any attempts to fully reduce utility to the FEP would require unrealistic assumptions, making the principle an unlikely candidate for unifying brain science. We suggest that researchers instead attempt to identify contexts in which either informational or independent reward constraints predominate, delimiting the FEP's area of applicability. To encourage this type of research, we propose a two-factor formal framework that can subsume any FEP model and allows experimenters to compare the contributions of informational versus reward constraints to behavior.

Original languageEnglish (US)
Pages (from-to)69-79
Number of pages11
StatePublished - Jan 2024


  • Bayesian Brain Hypothesis
  • Cognitive neuroscience
  • Decision-making
  • Extended cognition
  • Free Energy Principle
  • Subjective utility

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Neuropsychology and Physiological Psychology
  • Cognitive Neuroscience


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