Reward-based decision making under social interaction

Damon Tomlin

MURI Kick-Off meeting

September 13, 2007

The decision task

A B

The underlying structure . . .

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A more interesting case . . .

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Adding social interaction . . .

• Feedback

– None

– Choice history

– Individual rewards

Adding social interaction

• Feedback

• Different games

• NEO data

Conditions in the experiment: “Alone”

Conditions in the experiment: “Rewards”

Conditions in the experiment: “Choices”

Logistics

• Group size

• Subject payment

• Behavioral cohort

• Imaging cohort

Game elements

• Crossing points

• Optimal reward

• Short term vs. long term gains

Games within the experiment"Simple" Rising Optimum

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How frequently do subjects find the optimum?

Once found, do they stay?

Games within the experiment"Simple" Rising Optimum

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Are subjects naturally biased toward A or B?

Games within the experiment“Complex" Rising Optimum

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Can subjects find a more subtle strategy?

How do social partners affect adherence to it?

Individual behavior

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Individual behavior

QuickTime™ and aCinepak decompressor

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Games within the experimentConverging Gaussians

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How much exploration occurs in a simple task?

Individual behavior

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Games within the experimentDiverging Gaussians

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How does social information produce herd behavior?

Individual behavior

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Summary

• Binary choice decision paradigm

• Social conditions:– Alone– Reward Information– Choice Information

• Games examining:– Exploratory behavior– Herd behavior– Strategy maintenance