1. The Effect of Energy Drinks on Spatial Attention and EEG Data
David Lahm​1,2​
, Tasnia Tabassum​1,2
1​
Department of Biomedical Engineering, University of Wisconsin­Madison
2​
Institute of Biomedical and Neural Engineering, Reykjavik University
Abstract:​ ​ The purpose of this research is to examine the effects of energy drink consumption
upon spatial attention and the subsequent EEG data. In the experimental procedure, the subject
is asked to complete a series of SART tests, a spatial attention test with a response
suppression element. While wearing a 32 channel EEG cap, the subject completes one series
of tests before consuming an energy drink, and one series after. The resulting EEG data
confirms existing literature, showing that caffeine increases beta wave frequency in the brain.
Furthermore, the data shows that energy drink consumption produces greater levels of electrical
activity in the subject, following an incorrect answer, suggesting increased stress levels.
Key words: ​Electroencephalography, EEG, SART test, spatial attention, beta wave, caffeine
1. Introduction
In today’s high stress university environment, students spend an average of 19 hours a
week studying and more during exam weeks (National Survey of Student Engagement), and
consistently fall short of the recommended minimum of 8 hours of sleep per day (Buboltz, Brown
et al). This lifestyle can lead to fewer hours of sleep or rest, and as a result, many students are
resorting to energy drinks such as Red Bull, Monster, Rockstar and Starbucks Doubleshot
Energy for improved memory, increased alertness and elevated mood (Alford et al. 2001).
While energy drinks, as well as other sources of caffeine and stimulants, can have a perceived
positive impact, they also have negative side effects such as increased blood pressure,
tachycardia, muscle twitching, anxiety and insomnia (Alsunni 2015). These effects have
prompted governmental organizations such as the Food and Drug Administration (FDA) to
regulate the caffeine content by setting a limit on the amount of caffeine in a single serving. The
FDA recommended daily intake of caffeine for healthy adults is around 400 milligrams, which is
equivalent to 4 cups of coffee, 10 cans of cola or just two energy drinks. This means that one
energy drink can provide half or more of the recommended daily caffeine intake, all in a
concentrated single serving. As a result, just one of these concentrated servings can have a
negative effect on one’s physical well being as well as their neurophysiological health. The
consumption of energy drinks can increase the frequency of beta waves which are responsible
for logical thinking and conscious thought. An increased frequency of beta waves can lead to
anxiety and stress. The purpose of this study is to analyze the effects of energy drink
consumption on EEG data, specifically to prove whether the caffeine will increase the amplitude
of the electrical activity in the brain.

2. 2. Background
2.1 Energy Drinks
Common components of energy beverages include caffeine, taurine, and glucose, and
their physiological effects have been commonly studied. Caffeine is a stimulant, and has been
shown to have physiological effects including increased heart rate and decreased reaction time
(Dixit et al. 2012). Caffeine has beneficial effects on control, memory, and reaction time (Giles et
al. 2012). While taurine is not a stimulant, this amino acid has been found to possibly increase
exercise performance (Whirley et al. 2008). Taurine has many functions within the body, but the
amounts in these beverages is not enough to negatively or positively affect these functions
(Higgins et al. 2010). In energy beverages, taurine has increased the reaction time for choices
while decreasing reaction times for activities involving working memory (Giles et al. 2012).
Glucose indirectly stimulates the body by producing insulin. Glucose has been found to increase
reaction time by itself, but increase working memory in conjunction with caffeine, and increase
attention in conjugation with taurine (Giles et al. 2012).
2.2 Electroencephalography (EEG)
Electroencephalography (EEG) is a non invasive, electrophysiological means of
monitoring and recording electrical activity within the brain. Generally, electrodes are placed on
scalp with means of adhesion such as an electrode cap or tape. These electrodes are then filled
with a conductive saline gel that allows for transmission of the electrical signal from the scalp
surface to the electrode. The main use for EEG today is the diagnosis of epilepsy, which results
in abnormalities in the EEG recording.
2.3 Human Brain Anatomy and Diagram
The human brain on average weighs approximately 1.5 kilograms, making up 2% of a
human’s body weight, and consists of four primary sections. These primary sections are the
cerebellum, cerebrum, limbic system and brain stem. The cerebrum is the largest section of the
brain, responsible for brain function such as thought and action. The cerebrum is divided into
four different lobes, the frontal, parietal, occipital and temporal lobes, that are each associated
with different functions. The frontal lobe is associated with reasoning and planning, making this
lobe the center of thought in the brain. The parietal lobe controls movement, recognition and
orientation, also known as the motor cortex. The temporal lobe is associated with recognition of
auditory stimuli, speech and memory, and the occipital lobe with visual processing.

3.
Figure 1: Diagram showing sections of the brain and their associated functions
2.4 Sustained Attention to Response Task (SART)
A simple and consistent method of testing a subject’s spatial attention and response time
is needed in this study. The answer to this is the Sustained Attention to Response Task (SART)
which can be made on Eevoke. Eevoke is a media presentation software that uses a
combination of visual images and words and auditory stimuli for the purpose of testing and
monitoring subject responses. Eevoke is developed and sold by ANT Neuro, the same company
that designed Advanced Source Analysis, the primary software used for data processing.
3. Experimental Protocol
3.1 Fatigue Testing
The first step in the experimental procedure was to conduct a series of fatigue tests with
the goal of producing a baseline test comparison as well as showing the effects of fatigue
resulting from the multiple repetitions of the SART test. The subject completed three individual
SART tests, with a duration of four minutes and twenty seconds each, in a row with a thirty
second gap in between each test to allow for data completion and test setup. Then the subject
had a five minute break, in which they drank a glass of water to simulate the consumption of an
energy drink, albeit without the effects of an energy drink. After this break, the subject then
completed three more SART tests in the same order and intervals as the first three tests. Three
different subjects completed the fatigue tests and their data was averaged to produce the final

4. data. An EEG electrode cap was not used in this test for the purpose of simplicity, keeping in
mind that the purpose of this preliminary test was to observe and record the effects of fatigue on
SART test results.
3.2 Live Study Testing
Once the results of the fatigue tests had been recorded and averaged, the live study
tests with the energy drink replacing a glass of water were conducted on a later date. As a
measure to guarantee experimental integrity, the test subjects were asked to refrain from
consuming any source of caffeine at least twelve hours before the testing, as the half life of
caffeine is around six hours (Grant, Tang et. al. 1983). The twelve hours gives us a factor of
safety of two for the experimental results. A 32 channel EEG cap built by ANT Neuro was
placed on the subjects head and OneStep Cleargel was injected into the individual channels to
allow for a conductive channel for the EEG signals. The cap was then plugged into the ANT
Neuro amplifier set up and impedance activated to check the conductivity of the newly gelled
channels. Keep in mind that it may take some time for the gel in the channels to settle, meaning
that initially the impedance levels will be higher than usual. Once the EEG cap set up was
completed, the subject followed the same procedure as the fatigue testing in regards to the
SART tests, but when it came time for the five minute break, the subject drank an 8oz can of
standard, regular flavor Red Bull. After the Red Bull break, the subject then completed another
three SART tests in the same order and intervals. Once the series of SART tests had been
completed, the ANT Neuro Xensor software was used to record the locations of the electrodes
on the subjects head. The purpose of doing so is to be able to compare electrode location to the
voltage map and understand which electrodes are picking up the most electrical activity. Once
the electrode locations were recorded, the saved file was exported to the computer hard drive
for storage.
3.3 Advanced Source Analysis (ASA) Data Processing.
When it came time to process the data, Advanced Source Analysis (ASA) by ANT Neuro
was used. Another common software used for EEG data processing is EEGLab on MatLab
which is more efficient at filtering the data. However, it was decided to use ASA due to its
superior 3D head model images, making it easier to analyze the final results. Start the analysis
by opening the CNT file containing the raw EEG data using ASA. Once the data was open in
ASA, a generic head model was imported. The file containing the electrode placement was then
imported and overlaid onto the head model. The data set was then filtered in order to eliminate
artifacts such as eye blinks by setting the low and high frequencies on the filter feature at .3 and
30Hz respectively. After filtering, the triggers were conditioned to follow a set of criteria in order
to be labeled under their respective conditions. The data around each condition was averaged
to produce 3D voltage and frequency maps of each condition. In this case, since there were
three conditions, three 3D head models appeared after converting from the averaged data to 3D
view. At this point, the processed EEG data was ready for a visual analysis.

5. 4. Results
4.1 Beta Wave Activity
In the study titled ​Acute dose­effect relationships of caffeine and mental performance,
EEG, cardiovascular and subjective parameters by Hasenfratz, Battig et al 1983, the
researchers investigated the effects of caffeine on mental performance and EEG signals, similar
to this study. The researchers came to the conclusion that increased caffeine doses increased
the alpha and beta frequency waves, meaning that caffeine is more beneficial at lower doses.
This literature was used as a testing parameter in the present study to prove the efficiency and
accuracy of the experimental design. Figures two and three show the electrical frequencies in
the subject before and after consuming one can of Red Bull.
Figure 2: EEG frequencies before consuming one can of Red Bull
Figure 3: EEG frequencies after consuming one can of Red Bull
It can be noted that the beta frequency map, located on the far right, has a greater level
of activity in the form of red shading in Figure 3 than Figure 2.
4.2 Observing and Identifying Numbers on the Screen
The average human reaction time to a visual stimulus is between .2 and .3 seconds, with
a delayed physical response after. In the SART testing, it took the uncaffeinated subjects
around .225 seconds to identify the number on the screen. This can be confirmed by visually

6. inspecting the visual cortex of the subject on the 3D voltage map, using the ASA software.
Figure 4 shows an ASA 3D map of a subject registering a visual stimulus at around 210
milliseconds.
Figure 4: This figure shows electrical activity in the visual cortex of the subject at around 210
ms, indicating that the visual stimulus (number appearing on screen) has registered with the
subject.
As was stated in the experimental protocol section of this report, the subject was asked
to complete a series of SART tests by clicking the trigger button in response to a number
between 1­9 appearing on the screen, other than the number 3. For the purpose of this
experiment, the 3D head models are labelled as “1+64” for when the subject clicked the button
in response to 1,2 and 4­9. The head model labelled “3+64” represents an incorrect answer,
when the subject clicked the button in response to the number three on screen.
The purpose of this study is to explore the effects of an energy drink on EEG data
recordings by comparing the EEG recordings of the subject before and after consuming an
energy drink. The hypothesis, that the consumption of an energy drink will increase the
amplitude of the EEG voltage, was strengthened by the visual stimulus recognition data results.
Figures 5 and 6 show side by side images of the voltage maps before and after energy drink
consumption, in which the amplitude is greater after the consumption of an energy drink.

7. Figure 5: Visual cortex activity of a correct answer before (left) and after (right) the consumption
of an energy drink.
Figure 6: Visual cortex activity of an incorrect answer before (left) and after (right) the
consumption of an energy drink.
4.3 Response to a Correct or Incorrect Answer
One observation subjects made was that while they were completing the SART tests,
incorrectly pressing the button when number three appeared on screen triggered a negative
response and increased levels of stress, especially after consuming a can of energy drink.
Figure 7 shows a side by side comparison of the 3D voltage maps after a correct answer and an
incorrect answer, before consuming an energy drink. Figure 8 shows voltage maps after
consuming an energy drink.

8. Figure 7: Correct (left) and incorrect (right) answer responses before consuming energy drink
Figure 8: Correct (left) and incorrect (right) answer responses after consuming energy drink
An important observation to be made regarding these figures is the greater amplitude in
the incorrect answer voltage map after consuming an energy drink than before. This
strengthens the hypothesis of an increase in amplitude produced by consuming an energy drink.
This also correlates with the observations made by the subjects, as this increase in amplitude
represents an increase in electrical activity that can be associated with increased levels of
stress and negative response to an incorrect answer.
5. Discussion
The aim of this study was to observe the effects of the consumption of an energy drink
(Red Bull) on fatigue during a SART test through the analysis of brain wave patterns. The
hypothesis maintained that the beta wave activity would increase after the consumption of
caffeine by way of an energy drink.
Caffeine has been found to increase beta wave activity. As a main component of Red
Bull is caffeine, we found our preliminary testing sufficient to confirm the prior findings with
regards to an increase in beta waves. Caffeine is also known to decrease reaction time. This
was observed in our experimental subjects as the reaction time decreased by about 0.1 to 0.15
seconds.
There is confidence in the experimental methods used, but the sample size was small.
Our sample size was only 3, and if this study were to be repeated in the future, we would aim for
a greater number of experimental subjects, at least a sample size of 5. Across the three
subjects, there were similar results in the decrease in reaction time and increase in beta waves.
We are confident in the results obtained as experimental subjects were asked to refrain from the

9. consumption of caffeine for at least 12 hours before. Because the procedure was completed
within the hour on a single day, differences in external factors were accounted that could have
affected the results, such as fatigue and consumption of other food and drink.
We were able to accept our hypothesis. The results were comparable to the results of other
studies in terms of the effects of the ingredients commonly found in energy drinks in terms of
beta brain wave activity.
6. Future Work
In the future, it would be best to create a more formalized version of this study. In the
course of the experimental procedure, we realized that it would have been best to complete the
normal SART test and post energy drink SART test on separate days, or at least with a greater
time interval in between, so that the subject does not experience any fatigue that will affect the
results. Along with this, we should ensure that the subject has not become accustomed to the
SART tests to the point of gaining proficiency. Another important change to be made to the
experiment is the number of subjects. Three subjects is not a sufficient number to produce
experimentally sound results, so any future experiments should include much more than three
subjects.
Acknowledgements: ​We would like to thank Kyle Edmunds and Paolo Gargiulo for their
technical and experimental advice along the way. Along with this, we would like to thank
Berglind Fredriksdottir for volunteering as an experimental subject.
Conflict of Interest: ​The authors declare no potential conflicts of interest with respect to the
research, authorship, and/or publication of this article.
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