Counterfactual choice and learning in a neural network centered on human lateral frontopolar cortex
Erie D Boorman1, Timothy E Behrens, Matthew F Rushworth
1Department of Experimental Psychology, University of Oxford, Oxford, UK. eboorman@hss.caltech.edu
Plos Biology
|July 9, 2011
Summary
This study reveals a new brain system that tracks potential outcomes of unchosen options, crucial for decision-making and learning. This system informs future choices and learning from hypothetical feedback.
Area of Science:
- Neuroscience
- Cognitive Science
- Decision Science
Background:
- Real-world decision-making necessitates tracking chosen and unchosen (counterfactual) options and their outcomes.
- While neural systems for tracking chosen options are known, the existence of systems for counterfactual information remains unclear.
Purpose of the Study:
- To investigate the neural coding of counterfactual choices and prediction errors in the human brain.
- To identify brain regions involved in tracking the value of unchosen alternatives.
Main Methods:
- Utilized a three-alternative decision-making task.
- Employed a Bayesian reinforcement-learning algorithm.
- Conducted functional magnetic resonance imaging (fMRI) in human participants.
Main Results:
- Lateral frontal polar cortex (lFPC), dorsomedial frontal cortex (DMFC), and posteromedial cortex (PMC) encode reward evidence for the best future counterfactual choice.
- This network processes counterfactual prediction errors, distinct from regret theory.
- Individual differences in neural activity correlate with behavioral strategies in future choices and learning from hypothetical feedback.
Conclusions:
- Identified a novel neural system for tracking counterfactual choice options and outcomes.
- Provides neural and behavioral evidence for a system supporting complex decision-making and learning.
- This system is critical for evaluating unchosen alternatives and adapting future behavior.
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