Related Experiment Video
Updated: Aug 19, 2025
13:04
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
12.2K
Goals, usefulness and abstraction in value-based choice.
Benedetto De Martino1, Aurelio Cortese1
1Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK; Computational Neuroscience Laboratories, ATR Institute International, 619-0288 Kyoto, Japan.
Trends in Cognitive Sciences
|November 29, 2022
Summary
Value in decision-making shifts with changing goals. This study explores how the brain computes usefulness by creating flexible abstractions, integrating artificial intelligence and cognitive neuroscience.
Area of Science:
- Cognitive Neuroscience
- Neuroeconomics
- Artificial Intelligence
Background:
- Decision-making research often equates value with reward, focusing on hedonic aspects.
- The functional, concept-like nature of value computation has been overlooked.
- Real-life scenarios demonstrate the need for flexible value reassessment.
Purpose of the Study:
- To outline computational and biological principles of adaptive value computation.
- To explain how the brain creates abstractions for flexible goal adaptation.
- To compare algorithmic architectures from AI and cognitive neuroscience.
Main Methods:
- Reviewing computational and biological principles of value.
- Presenting algorithmic architectures from AI and cognitive neuroscience.
- Comparing these with psychological theories.
Main Results:
- The brain computes usefulness through abstractions that adapt to changing goals.
- Different algorithmic architectures can model this adaptive value computation.
- Parallels are drawn between AI, neuroscience, and psychological theories.
Conclusions:
- Value computation is not solely reward-based but involves flexible, goal-dependent abstractions.
- Understanding these principles can bridge artificial intelligence and cognitive neuroscience.
- Adaptive value computation is crucial for navigating dynamic environments.
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