The price of your soul: neural evidence for the non-utilitarian representation of sacred values

نویسندگان

  • Gregory S. Berns
  • Emily Bell
  • C. Monica Capra
  • Michael J. Prietula
  • Sara Moore
  • Brittany Anderson
  • Jeremy Ginges
  • Scott Atran
چکیده

Sacred values, such as those associated with religious or ethnic identity, underlie many important individual and group decisions in life, and individuals typically resist attempts to trade off their sacred values in exchange for material benefits. Deontological theory suggests that sacred values are processed based on rights and wrongs irrespective of outcomes, while utilitarian theory suggests that they are processed based on costs and benefits of potential outcomes, but which mode of processing an individual naturally uses is unknown. The study of decisions over sacred values is difficult because outcomes cannot typically be realized in a laboratory, and hence little is known about the neural representation and processing of sacred values. We used an experimental paradigm that used integrity as a proxy for sacredness and which paid real money to induce individuals to sell their personal values. Using functional magnetic resonance imaging (fMRI), we found that values that people refused to sell (sacred values) were associated with increased activity in the left temporoparietal junction and ventrolateral prefrontal cortex, regions previously associated with semantic rule retrieval. This suggests that sacred values affect behaviour through the retrieval and processing of deontic rules and not through a utilitarian evaluation of costs and benefits.

برای دانلود 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

A New Iterative Neural Based Method to Spot Price Forecasting

Electricity price predictions have become a major discussion on competitive market under deregulated power system. But, the exclusive characteristics of electricity price such as non-linearity, non-stationary and time-varying volatility structure present several challenges for this task. In this paper, a new forecast strategy based on the iterative neural network is proposed for Day-ahead price...

متن کامل

Short-term Prediction of Tehran Stock Exchange Price Index (TEPIX): Using Artificial Neural Network (ANN)

The main objective of this study is to find out whether an Artificial Neural Network (ANN) will be useful to predict stock market price, which is highly non-linear and uncertain. Specifically, this study will focus on forecasting TSE Price Index (TEPIX) as the most significant index of Iran Stock Market. Many data have been used as inputs to the network. These data are observations of 2000 day...

متن کامل

Forecasting Stock Market Using Wavelet Transforms and Neural Networks and ARIMA (Case study of price index of Tehran Stock Exchange)

The goal of this research is to predict total stock market index of Tehran Stock Exchange, using the compound method of ARIMA and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. First, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

متن کامل

Application of an Improved Neural Network Using Cuckoo Search Algorithm in Short-Term Electricity Price Forecasting under Competitive Power Markets

Accurate and effective electricity price forecasting is critical to market participants in order to make an appropriate risk management in competitive electricity markets. Market participants rely on price forecasts to decide on their bidding strategies, allocate assets and plan facility investments. However, due to its time variant behavior and non-linear and non-stationary nature, electricity...

متن کامل

Neuron Mathematical Model Representation of Neural Tensor Network for RDF Knowledge Base Completion

In this paper, a state-of-the-art neuron mathematical model of neural tensor network (NTN) is proposed to RDF knowledge base completion problem. One of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. For this reason, a new representation of this network is suggested that solves this difficulty. In the representation, th...

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

برای دانلود 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

عنوان ژورنال:

دوره 367  شماره 

صفحات  -

تاریخ انتشار 2012