Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference

Jordan W. Suchow, David D. Bourgin, Thomas L. Griffiths

Research output: Contribution to journalReview article

7 Scopus citations

Abstract

Evolutionary theory describes the dynamics of population change in settings affected by reproduction, selection, mutation, and drift. In the context of human cognition, evolutionary theory is most often invoked to explain the origins of capacities such as language, metacognition, and spatial reasoning, framing them as functional adaptations to an ancestral environment. However, evolutionary theory is useful for understanding the mind in a second way: as a mathematical framework for describing evolving populations of thoughts, ideas, and memories within a single mind. In fact, deep correspondences exist between the mathematics of evolution and of learning, with perhaps the deepest being an equivalence between certain evolutionary dynamics and Bayesian inference. This equivalence permits reinterpretation of evolutionary processes as algorithms for Bayesian inference and has relevance for understanding diverse cognitive capacities, including memory and creativity.

Original languageEnglish (US)
Pages (from-to)522-530
Number of pages9
JournalTrends in Cognitive Sciences
Volume21
Issue number7
DOIs
StatePublished - Jul 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

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

Keywords

  • Bayesian inference
  • cognitive processes
  • creativity
  • evolution
  • learning
  • memory

Fingerprint Dive into the research topics of 'Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference'. Together they form a unique fingerprint.

  • Cite this