Simple Lie Detector Test

Abstract

Have you ever watched a great sports player and imitated his or her moves over and over again? Or have you ever felt really bad when someone got hurt or things just weren't going his or her way? If so, you might be surprised to learn that you have been practicing skills closely tied to lying! In this science fair project, you'll discover how your brain gets a workout when it moves from truth-telling to lying, and how you can detect the shift. That's no lie!

Summary

Areas of Science

Human Biology & Health

Difficulty

Method

Scientific Method

Time Required

Average (6-10 days)

Prerequisites

None

Material Availability

None

Cost

Very Low (under $20)

Safety

No issues

Credits

Kristin Strong, Science Buddies Alumni

Laura Ohl, PhD, Science Buddies Alumni

This project was inspired by the experiments of Debora Capper and her son, Conrad. The project was further improved with input from educators Laurel Matsuda and Kelly Barrick.

Science Buddies is committed to creating content authored by scientists and educators. Learn more about our process and how we use AI.

Image Credit: Laura Ohl, Ph.D. / Science Buddies

Image of fMRI images with test true or false.

Objective

To see if you can detect when someone is lying or telling the truth because of the brain's impact on the body when a person lies.

Introduction

Although lying is discouraged in many cultures, lying is a fundamental social skill that most humans begin to develop around age three. The development of lying is directly tied to the Theory of Mind. When you begin to understand that what you know about the world might be different than what another person knows, then you begin to have the capacity to lie. Lying is tied to empathy, which is the ability to "walk in another person's shoes," the ability to see things from another person's perspective.

People with certain brain-development problems, such as autism spectrum disorders, have great difficulty lying, and some people with autism never lie. Some neuroscientists (scientists who study the nervous system) believe that a problem with special brain nerve cells, called mirror neurons may be partly at fault. Mirror neurons are active whenever a person observes or tries to imitate another person's actions. Imitation is an important step toward empathy and viewing the world from another person's perspective. People with autism have difficulty with this skill.

Neuroscientists are also involved in helping the military, law enforcement, and security personnel detect lying in people suspected of having committed a crime. Standard lie-detection techniques include the use of a polygraph, a machine that measures the body's response to the stress caused by telling a lie. The polygraph continuously monitors heart rate, blood pressure, and sweating and watches for any increases in these that could signal that the person has just lied.

The problem with polygraphs, though, is that there can be false positives, which are false increases in heart rate, blood pressure, and/or sweating because of anxiety about the test or other unrelated issues. There can also be false negatives, where the person being investigated is telling a lie, but he or she either does not feel guilt about it, or has learned how to stop the body's responses to lies. This has led to an interest in developing alternative methods of detecting lies. The most promising machine is currently the functional magnetic resonance imaging, or fMRI scanner.

The fMRI differs from a standard MRI in that the standard MRI shows the brain's anatomy at high resolution (in great detail), whereas the fMRI shows how the brain is functioning and interacting, in lesser resolution, as the brain performs a specific task. fMRI maps blood flow to different regions of the brain in real-time. So, for example, if you were shown a photograph of a family member, the fMRI would tell the neuroscientists which parts of your brain were active when you looked at the image of your family member, such as the vision center, the emotional center, and the facial recognition center. With a standard MRI, your brain will look the same anatomically, regardless of what task you are doing—listening to music, looking a photograph, or telling a lie.

With fMRI, neuroscientists have discovered that your brain works harder when it is telling a lie, than when it is telling a truth! More and different parts of the brain are active during lying, as compared to truth-telling. While just four parts are active during truth-telling, seven parts are active during lying. In this science fair project, you'll take advantage of this difference in brain states to form a simple lie detector test. You'll give a person a physical task to do and have him or her tell a truth, and then tell a lie. You'll see if the person is better able to do the task when his or her brain is less active (telling a truth), or more active (telling a lie). So go call all your friends and family, and see if you can detect a harder-working brain!

Terms and Concepts

• Social skill
• Theory of Mind
• Empathy
• Autism spectrum disorder
• Neuroscientist
• Mirror neuron
• Polygraph
• Stress
• False positive
• False negative
• Functional magnetic resonance imaging (fMRI)
• MRI
• Real-time
• Brain state
• Blinded study
• Informed consent
• Resistance

Questions

• What does Theory of Mind mean?
• What does a polygraph do? Are they always accurate? Why or why not?
• What is the difference between fMRI and MRI? Why is low resolution better for detecting lies?
• How do the brains of people who are lying and those who are telling the truth differ when they are observed with fMRI?

Questions

• What is a lie?
• What are lie detectors used for, and are they accurate?
• What is a false positive and a false negative?
• What does an fMRI show you?
• How can you tell with an fMRI when someone is lying?
• How can different brain states be used to create a lie detector?
• What parts of the brain are important for telling lies?

Materials and Equipment

• Volunteers (at least 10 total, age 7+)
• Lab notebook
• Paper
• Stool or stair (if needed)

This project follows the Scientific Method. Review the steps before you begin.

Prepare Your Volunteers

In this experiment, you will test if you can detect when someone is lying or telling the truth. You are able to do this based on previous knowledge that the brain impacts the body when someone lies. In physical tests like this, it is important not to know when a participant is telling the truth or lying. This is also known as being blinded or not knowing or predicting the results. Why is this so important for physical and psychological tests? Because our brains love to predict what will happen, which can often influence or introduce bias into our interpretation of the results. Therefore, to be the best and most ethical scientist and to do the best test of whether this lie detector test works, you will want to remain blinded or lack knowledge of whether the participant is telling the truth or lying throughout the study. You will only look at the results provided by all the participants after all of the testing is done to perform a properly blinded study. 

1. Before starting the experiment, inform the participant of the study requirements. Inform the volunteer that you will have them say a few phrases and that the goal is to keep their arm up. This is called receiving informed consent.
2. Then, ask the volunteer to write down 6 sentences, 3 true and 3 false. Ask them to write them randomly in the data table, similar to table 1 below.
   1. CAUTION: Do not watch the volunteer write them down, as this will unblind you from the experiment. A blinded experiment is one done to prevent you from seeing any results, which could introduce bias into your interpretation of the results. 

Image Credit: Kristin Strong, Science Buddies / Science Buddies
Figure 1. This photograph shows how to conduct a simple lie-detector test

Test Your Volunteers

1. Instruct the volunteer to stand a few feet away from you and face towards you.
   1. Note: If there is a height difference, use a chair so that your arms are similar to your volunteers' height. 
2. Ask the volunteer to extend their arm straight out in front of you with their palm facing down. Then, extend your arm and place your hand, palm down, over the volunteer's hand and wrist, as shown in Figure 1.
3. Perform a baseline reading by asking the volunteer to hold out their arm and remain silent. This will be their initial baseline score, which should feel like there is no resistance. Feel the resistance and add a score (0) to your data table.
4. Score if there is any resistance using the scale below:
   1. 0 = no/weak resistance
   2. 1 = medium resistance
   3. 2 = strong resistance
5. Ask the volunteer to read the first statement aloud and observe their arm resistance. 
6. Add the resistance score to the data table. 
7. Ask the volunteers to read their remaining 2-6 statements, assessing and adding their respective resistance scores to the data table, similar to Table 1.
8. When you are done rating the resistance for each of the 6 statements, ask the volunteer to write down whether the statement was true or false in the data table.
   1. Note: This will unblind you from the results for this participant, and is okay to do so at this point since the testing and interpretation of the scores is already done. 
9. Average the resistance score associated with all of the true answers and all of the false answers.
   1. For example, if a volunteer's answer was true three times and the resistance score for each was 0, 1, and 0, the total resistance score for all of that volunteer's true answers would be 0+1+0 = 1. You would then divide the total resistance by the number of statements to get the average resistance of the true statements, for example, 1/3 or 0.33. 
10. Repeat the experiment for an additional 9 volunteers, creating a new data table for each volunteer.

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Statements ("I love ___" OR "I like to ___")	Resistance score (0-2)	Volunteer's answers (True/False) after testing
Average resistance of true statements score: _______       Average resistance of false statements score: _______

Table 1. Example data table for 1 volunteer's resistance scores and associated true/false statements revealed after testing. 

Combine and Analyze Your Data

1. Compile the average resistance scores for the true and false statements for each of the 10 volunteers in a data table, like Table 2. 
2. Calculate the total average for each column by adding up all of the scores and dividing by the number of volunteers.
   1. For example: If the average resistance of true statement scores are 0, 0.33, 0.33, 0, 1, 0.66, 0.66, 1, 0, 1, add them up, which equals 5, then divide by 10 to get 5/10 = 1/2 = 0.5. 
3. Add the average resistance statement scores to the data table. 

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Volunteer number	Average resistance of true statements score	Average resistance of false statements score
1
2
3
4
5
6
7
8
9
10
Total Average

Table 2. Example of a summary data table for all 10 volunteers' average resistance scores for true/false statements. 

Conclusions

1. How much variability was there between participants? To quantitatively determine this, you can calculate the standard deviation of all of the true answer scores compared to the false answer scores. 
2. How effective was the arm test at detecting true statements compared to false statements? If not, why do you think that is? If the lie detector test works well and is an accurate test, the average score for false statements should be higher than the average score for true statements. For example, if the test is very accurate for all participants, the average resistance of true statements should be between 0 and 1, while the average resistance of false statement scores should be between 1 and 2.
3. Were some volunteers better at hiding false statements as true than others? Were there any outliers or participants who fell outside the expected resistance range scores?
4. Do you think arm resistance, or keeping your arm up, is the most reliable measure of detecting truth from lies? Are there other physical variables that could impact arm resistance, such as muscle strength, medical conditions, or muscle fatigue?  

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