Neural Activity Reveals Preferences without Choices

被引：66

作者：

Smith, Alec ^{[1
]}

Bernheim, B. Douglas ^{[2
,3
]}

Camerer, Colin F. ^{[1
]}

Rangel, Antonio ^{[1
]}

机构：

[1] CALTECH, Pasadena, CA 91125 USA

[2] Stanford Univ, Dept Econ, Stanford, CA 94305 USA

[3] NBER, Cambridge, MA 02138 USA

来源：

AMERICAN ECONOMIC JOURNAL-MICROECONOMICS | 2014年 / 6卷 / 02期

关键词：

ORBITOFRONTAL CORTEX; LOGISTIC-REGRESSION; SUBJECTIVE VALUE; GOAL VALUES; VALUATION; FMRI; PREDICTION; MODELS; CLASSIFICATION; REGULARIZATION;

D O I：

10.1257/mic.6.2.1

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We investigate the feasibility of inferring the choices people would make (if given the opportunity) based on their neural responses to the pertinent prospects when they are not engaged in actual decision making. The ability to make such inferences is of potential value when choice data are unavailable, or limited in ways that render standard methods of estimating choice mappings problematic. We formulate prediction models relating choices to "nonchoice" neural responses, and use them to predict out-of-sample choices for new items and for new groups of individuals. The predictions are sufficiently accurate to establish the feasibility of our approach.

引用

页码：1 / 36

页数：36