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A Neuronal Model of Human Choice Rome ESA June 30, 2007 Authors:John Dickhaut, Ovidiu Longu, Baohua Xin and Aldo Rustichini.

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Presentation on theme: "A Neuronal Model of Human Choice Rome ESA June 30, 2007 Authors:John Dickhaut, Ovidiu Longu, Baohua Xin and Aldo Rustichini."— Presentation transcript:

1 A Neuronal Model of Human Choice Rome ESA June 30, 2007 Authors:John Dickhaut, Ovidiu Longu, Baohua Xin and Aldo Rustichini

2 Overview Develop and test a unified account of the processes underlying behavior in the classical choice task. Consistent account of error, reaction time and activation in classical choice task in risky and ambiguous choice tasks. Subject evaluates information in task, maps stimuli onto ordered line segment in horizontal intraparietal sulcus (stochastically) and chooses in a paired choice task. Evidence is stochastically accumulating until a barrier (or threshold is reached.)

3 Task Description {15, 17, 20, 23, 25, 27,30} Certainty Values Choices Available Display Choice After Choice Blocks 1 and 3 Block 2 Ambiguous Risky Display Choice Spin After Choice Display Choice Risky Displayed Spin After Choice

4 Theory Choice Stimulus Choice Stimulus projected continuously to retina, through optic Chasm to occipital lobe and ultimately to intraparietal sulcus. Each member of choice pair is projected stochastically and the 50/50 gamble is generated with more noise than the 27 certainty. 27>50/50 is preferred more often than 50/50 >27. Barrier(red dashed line) is reached first for 27>50 (Subject chooses 27). For the ambiguous choice the distribution on the real line segment is much more diffuse. Given this diffuseness the barrier (red dashed line) is set lower than for the risky case. The implication is that the barrier can be reached sooner (faster reaction time and less activation) in the ambiguous vs. 27 than the risky vs 27. In the comparison of the 50/50 gamble to the 30 certainty equivalent the quality of the information does(same barrier). Thirty is further removed from 50/50 than 27 meaning that 30 > 50/50 is much more likely to occur than 27 > 50/50. Predictions: 1)Fewer errors in comparing 50/50 vs. 30 than 50/50 vs. 27. Reaction time will be faster and there will be less activation for the 50/50 vs. 30 comparison.

5 Behavioral Results Given more dollars are preferred to less there will be a cutoff policy where above the cutoff the certainty amount is chosen and below the cutoff the uncertain gamble is chosen. Checks for cutoffs Checks for errors in choice relative to the estimated cutoff.

6 Imaging Slide 1 Display Choice After-Choice vs. Display contrasts ROA Display After-Choice % bold change Seconds from event

7 Imaging Slide-Tests of Theory’s Predictions Relative activation in risky versus ambiguous for same subtraction Regression coefficients of bold on distance from cutoff, current $ amount, ambiguity/risk, and total choices to date. Distance Current Amb/Risk # Choices Estimated Coefficients Estimated Coefficients Estimated Coefficients Estimated Coefficients Left IPSRight IPS MFGOFC


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