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Mel W Khaw1, Paul W Glimcher2,3, Kenway Louie4,3

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Area of Science:

  • Decision Science
  • Neuroscience
  • Behavioral Economics

Background:

  • Subjective value is a core concept in choice theories across disciplines.
  • Traditionally, subjective value is viewed as an absolute, static quantity.
  • Neurobiological studies reveal dynamic adaptation in neural value coding based on reward history.

Purpose of the Study:

  • To investigate whether behavioral valuation exhibits dynamic adaptation to temporal context.
  • To determine if human value judgments are influenced by the history of previously encountered values.
  • To explore the underlying mechanisms and unifying principles of adaptive valuation.

Main Methods:

  • Experimental design involving human subjects evaluating options.
  • Systematic manipulation of the reward history preceding value judgments.
  • Quantitative analysis of behavioral data to model valuation dynamics.

Main Results:

  • Human valuation processes dynamically adapt to the history of previously experienced values.
  • Current valuations show an inverse relationship with the average value of recently observed items.
  • The observed dynamics are accurately described by a divisive normalization model.

Conclusions:

  • Behavioral valuation is not static but dynamically adapts to temporal context.
  • Divisive normalization provides a unifying mechanism for context effects in valuation, perception, and decision-making.
  • Adaptive valuation suggests a universal principle of neural information processing across diverse fields.