A behavioral and neural evaluation of prospective decision-making under risk.

نویسندگان

  • Mkael Symmonds
  • Peter Bossaerts
  • Raymond J Dolan
چکیده

Making the best choice when faced with a chain of decisions requires a person to judge both anticipated outcomes and future actions. Although economic decision-making models account for both risk and reward in single-choice contexts, there is a dearth of similar knowledge about sequential choice. Classical utility-based models assume that decision-makers select and follow an optimal predetermined strategy, regardless of the particular order in which options are presented. An alternative model involves continuously reevaluating decision utilities, without prescribing a specific future set of choices. Here, using behavioral and functional magnetic resonance imaging (fMRI) data, we studied human subjects in a sequential choice task and use these data to compare alternative decision models of valuation and strategy selection. We provide evidence that subjects adopt a model of reevaluating decision utilities, in which available strategies are continuously updated and combined in assessing action values. We validate this model by using simultaneously acquired fMRI data to show that sequential choice evokes a pattern of neural response consistent with a tracking of anticipated distribution of future reward, as expected in such a model. Thus, brain activity evoked at each decision point reflects the expected mean, variance, and skewness of possible payoffs, consistent with the idea that sequential choice evokes a prospective evaluation of both available strategies and possible outcomes.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Entrepreneurship policy and innovative indicators of industrial companies: Evaluation by MCDM and ANN Methods

The present paper presented a methodology for prioritizing the innovative and entrepreneurial indicators using Multi Criteria Decision Making (MCDM) and Artificial Neural Networks (ANNs), taking into account three individual, organizational and cultural dimensions simultaneously in decision making procedure. This methodology has two main advantages: first, the speed of operation in the accounti...

متن کامل

Assessment of Prospective Memory, Risky Decision-Making, Collaborative Decision-Making among Individuals with Morning and Evening Circadian Typology

Introduction: Biological aspects of personality have an influence on people psychological dimensions. The present study was aimed to compare prospective memory, risky decision-making, collaborative decision-making between individuals with morning and evening circadian typology. Methods: For this purpose, a study with quantitative methodology approach and a descriptive design was conceived. T...

متن کامل

A conjugate gradient based method for Decision Neural Network training

Decision Neural Network is a new approach for solving multi-objective decision-making problems based on artificial neural networks. Using inaccurate evaluation data, network training has improved and the number of educational data sets has decreased. The available training method is based on the gradient decent method (BP). One of its limitations is related to its convergence speed. Therefore,...

متن کامل

The Comparison of Credit Risk between Artificial Neural Network and Logistic Regression Models in Tose-Taavon Bank in Guilan

One of the most important issues always facing banks and financial institutes is the issue of credit risk or the possibility of failure in the fulfillment of obligations by applicants who are receiving credit facilities. The considerable number of banks’ delayed loan payments all around the world shows the importance of this issue and the necessary consideration of this topic. Accordingly...

متن کامل

A novel risk-based analysis for the production system under epistemic uncertainty

Risk analysis of production system, while the actual and appropriate data is not available, will cause wrong system parameters prediction and wrong decision making. In uncertainty condition, there are no appropriate measures for decision making. In epistemic uncertainty, we are confronted by the lack of data. Therefore, in calculating the system risk, we encounter vagueness that we have to use ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • The Journal of neuroscience : the official journal of the Society for Neuroscience

دوره 30 43  شماره 

صفحات  -

تاریخ انتشار 2010