Related Experiment Video
Updated: Jan 14, 2026
13:04
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Published on: September 19, 2012
12.4K
Modeling value integration during decision making under uncertainty with the Florida and Georgia gambling task
Shensheng Wang1, Robert C Wilson2, Natalie C Ebner3,4
1Department of Psychology, University of Central Florida, Orlando, FL, USA.
Scientific Reports
|October 22, 2025
Summary
Cognitive biases impact decisions under uncertainty. A new gambling task revealed people underweight outliers and favor recent outcomes, but showed no loss aversion.
Area of Science:
- Cognitive Psychology
- Decision Science
- Behavioral Economics
Background:
- Human decision-making under uncertainty is influenced by cognitive biases.
- Understanding how biases affect value integration in choices is crucial.
Purpose of the Study:
- To investigate the influence of cognitive biases on decision-making value integration.
- To introduce and validate the Florida-And-Georgia (FLAG) gambling task.
Main Methods:
- Developed the novel Florida-And-Georgia (FLAG) gambling task.
- Participants chose between variable outcomes and a sure-thing offer.
- Modeled value integration influenced by learning (primacy-recency) and Prospect Theory factors (outliers, loss aversion).
Main Results:
- Individuals underweight outliers for both gains and losses.
- Decision-making was biased by recent outcomes (recency effect).
- No evidence of loss aversion was found in the study population.
Conclusions:
- The FLAG task balances experimental control with ecological validity for studying decision-making.
- Findings provide insights into cognitive processes like outlier sensitivity and recency bias.
- The FLAG task has potential societal and clinical applications for understanding decision biases.
More Related Videos
Related Concept Videos
01:09Decision Making: P-value Method
6.8K
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...
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...
6.8K
01:14Decision Making: Traditional Method
5.1K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
5.1K
01:20Decision Making
884
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Automatic decision-making is fast, intuitive, and relies on gut feelings...
884
01:27Growth Models with Integration: Problem Solving
9
In population modeling, integration provides a systematic way to determine accumulated quantities from known rates of change. One such application arises in ecology, where the total weight of a fish population in a body of water is referred to as its biomass. When the rate of growth of this biomass is known as a function of time, calculus can be used to determine the total biomass at a future date.Growth Rate and Biomass FunctionLet the growth rate of the fish population be represented by a...
9
01:29Mathematical Modeling: Problem Solving
252
Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
252
01:30Application of Integration: Problem Solving
35
The process of breathing involves the periodic intake and expulsion of air, known as the respiratory cycle, which typically lasts about five seconds. Modeling the volume of air inhaled into the lungs as a function of time provides insight into both the dynamics and efficiency of pulmonary ventilation. This volume is determined by integrating the airflow rate over time, which captures the cumulative effect of air entering the lungs.Sinusoidal Model of AirflowAirflow during respiration is not...
35