Neural Random Utility: Relating Cardinal Neural Observables to Stochastic Choice Behavior

被引:15
作者
Webb, Ryan [1 ,2 ]
Levy, Ifat [3 ,4 ]
Lazzaro, Stephanie C. [5 ]
Rutledge, Robb B. [6 ]
Glimcher, Paul W. [7 ]
机构
[1] Univ Toronto, Rotman Sch Management, 105 St George St, Toronto, ON M5S 3E6, Canada
[2] Univ Toronto, Dept Econ, Toronto, ON, Canada
[3] Yale Sch Med, Dept Comparat Med, New Haven, CT USA
[4] Yale Sch Med, Dept Neurosci, New Haven, CT USA
[5] UCL, Inst Cognit Neurosci, London, England
[6] UCL, Wellcome Trust Ctr Neuroimaging, London, England
[7] NYU, Langone Sch Med, Dept Neurosci & Physiol, New York, NY 10003 USA
关键词
stochastic choice; valuation; choice prediction; measurement error; EXPECTED UTILITY; VALUATION SYSTEM; BRAIN; ERROR; FMRI; REPRESENTATION; PREFERENCES; RESPONSES; SIGNALS; MODEL;
D O I
10.1037/npe0000101
中图分类号
F [经济];
学科分类号
02 ;
摘要
We assess whether a cardinal model can he used to relate neural observables to stochastic choice behavior. We develop a general empirical framework for relating any neural observable to choice prediction and propose a means of benchmarking their predictive power. In a previous study, measurements of neural activity were made while subjects considered consumer goods. Here, we find that neural activity predicts choice behavior with the degree of stochasticity in choice related to the cardinality of the measurement. However, we also find that current methods have a significant degree of measurement error which severely limits their inferential and predictive performance.
引用
收藏
页码:45 / 72
页数:28
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