Related Experiment Video
Updated: Jul 9, 2026
13:04
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
Nonlinear neurobiological probability weighting functions for aversive outcomes
Gregory S Berns1, C Monica Capra, Jonathan Chappelow
1Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA. gberns@emory.edu
Neuroimage
|December 7, 2007
Summary
People often misjudge probabilities, overweighting unlikely events and underweighting likely ones. This study reveals brain activity patterns linked to this nonlinear probability weighting during decision-making.
Area of Science:
- Neuroscience
- Decision Science
- Behavioral Economics
Background:
- Standard economic models assume objective probability assessment, but human behavior deviates.
- Individuals often exhibit nonlinear probability weighting, overestimating low probabilities and underestimating high ones.
- A biological basis for this cognitive bias remains largely unexplored.
Purpose of the Study:
- To investigate the neural mechanisms underlying nonlinear probability weighting.
- To identify brain regions involved in processing probabilistic information during decision-making.
- To determine if neural responses to probability predict subsequent choices.
Main Methods:
- Functional magnetic resonance imaging (fMRI) was used to monitor brain activity.
- Participants were presented with lotteries involving potential electric shocks, varying in shock probability and intensity.
- Neural activity during the prospect phase was analyzed for correlations with probability weighting.
Main Results:
- A network including anterior cingulate, visual, parietal, and temporal cortices showed activity tracking probability.
- Responses in these regions were consistent with nonlinear probability weighting.
- Neural activity predicted 79% of subsequent lottery choices, outperforming behavioral predictions near the indifference point.
Conclusions:
- Neural responses in specific brain regions reflect nonlinear probability weighting.
- These brain-based probability assessments significantly predict individual decision-making.
- The findings provide a biological account for deviations from objective probability treatment in economic behavior.
Related Concept Videos
00:57Weighted Mean
While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
01:09Decision Making: P-value Method
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can have a...