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Uncovering the computational mechanisms underlying many-alternative choice
Armin W Thomas1,2,3,4, Felix Molter2,3,5, Ian Krajbich6
1Technische Universität Berlin, Berlin, Germany.
Elife
|April 6, 2021
Summary
Human decision-making with many choices is best explained by models where gaze actively influences perceived value. A gaze-driven satisficing model closely fits choices and response times.
Area of Science:
- Cognitive Psychology
- Decision Science
- Neuroscience
Background:
- Decision-making research often separates small and large choice sets.
- Small choice sets favor gaze-driven evidence accumulation models.
- Large choice sets suggest optimal choice, satisficing, or hybrid models.
Purpose of the Study:
- To bridge the gap between small and large choice set decision models.
- To compare different decision models in a many-alternative setting.
- To investigate the role of gaze in value-based choice.
Main Methods:
- Developed and compared various decision models.
- Conducted a value-based choice experiment with 9, 16, 25, and 36 alternatives.
- Analyzed choices and response times in relation to gaze allocation.
Main Results:
- Models incorporating gaze's effect on subjective value best explained human choices.
- Gaze-driven probabilistic satisficing models showed slightly better fits for choices and response times.
- A gaze-driven evidence accumulation and comparison model provided the most comprehensive account of the data.
Conclusions:
- Gaze plays an active role in how individuals evaluate options in large choice sets.
- Gaze-driven satisficing and evidence accumulation models offer valuable insights into complex decision-making.
- Future research should integrate gaze dynamics into decision models for a holistic understanding.
Keywords:
attentioncomputational biologydecision makingevidence accumulationeye trackinghumanmany-alternative choiceneurosciencesatisficingsystems biologyMore Related Videos
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