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A range-normalization model of context-dependent choice: a new model and evidence.
Alireza Soltani1, Benedetto De Martino, Colin Camerer
1Howard Hughes Medical Institute and Department of Neurobiology, Stanford University School of Medicine, Stanford, California, United States of America. asoltani@stanford.edu
Plos Computational Biology
|July 26, 2012
Summary
Choice behavior is influenced by irrelevant options, known as decoys. A new neuronal model explains this context-dependent preference as a natural brain mechanism called range normalization, crucial for distinguishing stimuli within neural limits.
Area of Science:
- Neuroscience
- Decision Science
- Cognitive Psychology
Background:
- Utility theories assume choices are unaffected by irrelevant options (decoys).
- Behavioral data show preferences depend on decoys and context.
- Neural mechanisms for context-dependent preference remain unclear.
Purpose of the Study:
- Investigate neural mechanisms of context-dependent choice.
- Measure within-subject decoy effects.
- Develop a neuronal model for decoy effects.
Main Methods:
- Designed a novel experiment to measure within-subject decoy effects.
- Collected behavioral data on choice preferences with and without decoys.
- Constructed a neuronal model based on range normalization.
Main Results:
- Confirmed within-subject decoy effects similar to previous studies.
- Found decoy effects correlate and increase with decoy-option distance.
- The proposed range normalization model explains observed decoy effects.
- Model predictions contrast with previous context-dependent choice models.
Conclusions:
- Context-dependent choice behavior, including decoy effects, may arise from neural biophysical limits.
- Range normalization is a plausible mechanism for representing stimuli within bounded neural activity.
- The model offers a computationally efficient explanation for decoy effects, independent of choice set size.
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