Designing EEG Experiments for Studying the Brain. Design Code and Example Datasets

282 Pages·2017·11.7 MB·English

by  Aamir Saeed Malik and Hafeez Ullah Amin (Auth.)

DESIGNING EEG
EXPERIMENTS FOR
STUDYING THE BRAIN
https://www.elsevier.com/books-and-journals/book-companion/9780128111406
Designing EEG Experiments for Studying the Brain: Design Code and Example Datasets
Aamir Saeed Malik and Hafeez Ullah Amin
Resources available:
Table of Contents:
- Chapter Abstracts
- Chapter Data
- Glossary
DESIGNING EEG
EXPERIMENTS FOR
STUDYING THE BRAIN
Design Code and Example Datasets
AAMIR SAEED MALIK
HAFEEZ ULLAH AMIN
Universiti Teknologi PETRONAS, Perak, Malaysia
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LIST OF FIGURES
Figure 1.1 EEG signal and corresponding bands 3
Figure 1.2 Example of visual stimulus in oddball task 14
Figure 1.3 Structure of oddball task in E-Prime software 15
Figure 1.4 Error message when E-Prime is not connected with 16
Net Station while Net Station package is added
Figure 1.5 Triallist of oddball experiment 17
Figure 1.6 Objects of TrialProc 17
Figure 1.7 Stimulus property setting 18
Figure 2.1 Complete experiment flow for both stress and control 39
conditions. (A) Mental stress session. (B) Control session
Figure 2.2 A model of the computer screen in the stress condition 41
Figure 3.1 BrainMaster Discovery amplifier 51
Figure 3.2 User interface of BrainMaster Discovery acquisition software 52
Figure 3.3 Data collection scheme 56
Figure 3.4 EEG data collection 57
Figure 3.5 Visual three-stimulus oddball task 57
Figure 4.1 A general scenario of epileptic seizure attack 64
Figure 4.2 Epileptic seizure categories 64
Figure 5.1 Experiment design 81
Figure 6.1 EEG recording flow diagram. (A) 3D active first group. 98
(B) 3D passive first group
Figure 7.1 PASS user interface window 111
Figure 7.2 Experiment design 112
Figure 7.3 A sample of Raven’s Advanced Progressive Matrices (RAPM) 113
problem
Figure 7.4 Sample of multiple choice question (MCQ) 114
Figure 7.5 Experimental design with session wise tasks 115
Figure 7.6 Design of E-Prime program for RAPM task 117
Figure 7.7 E-Prime recorded file in 3D recall task 118
Figure 8.1 Polygraphic Input Box (PIB) 128
Figure 8.2 Visual stimuli of oddball task (box represents the standard 130
stimulus and sphere represents the target stimulus)
Figure 9.1 3D game interface 138
Figure 9.2 Interface of 2D game 140
Figure 10.1 Flow chart of the experiment 155
Figure 10.2 A view of the stimulus as seen by the participants 156
Figure 11.1 Emotiv EPOC 16 electrodes 168
Figure 11.2 Block diagram of experiment protocol 168
Figure 12.1 Experimental design. The first row indicates the driving with 177
distraction and second row indicates the driving without
distraction
Figure 13.1 NHTSA statistics on crashes caused by driver drowsiness 182
from 2005 to 2009
ix
x List of Figures
Figure 13.2 Experimental setup 187
Figure 13.3 Experimental protocol 187
Figure 14.1 Design of experimental task 1 197
Figure 14.2 Explanation of timeline of task 1. Total time for one trial = 198
3800 ms Intertrial interval (ITI) = 2000 ms, Total time for one
level (50 trials) = 3800 × 50 + 2000 × 49 = almost 5 min,
Total time for task 1 = 5 × 3 = 15 min (exclusive of breaks
between levels)
Figure 14.3 Design of experimental task 2 199
Figure 14.4 Explanation of timeline of task 2. Total time for one trial = 199
4800 ms Intertrial interval (ITI) = 2000 ms, Total time for one
level (50 trials) = 4800 × 50 + 2000 × 49 = almost 6 min,
Total time for task 2 = 6 × 3 = 18 min (exclusive of breaks
between levels)
LIST OF TABLES
Table 1.1 Detail of EEG devices and manufacturers 20
Table 1.2 Stimulus presentation software 23
Table 2.1 Delaying response text and speed up texts to show on 41
the screen
Table 2.2 A summary of stressful feedback messages 42
Table 2.3 EEG/ERP data description 44
Table 2.4 E-Prime files of EEG stimulus experiment for stress and 44
control conditions
Table 3.1 Available clinical characteristics of SSRI responders and 55
nonresponders who participated in the study
Table 3.2 Description of EEG data files and E-Prime file 59
Table 4.1 Description of Bonn datasets 70
Table 4.2 Description of CHB-MIT dataset 71
Table 4.3 Description of European Epileptic dataset 72
Table 5.1 Sample size calculation 79
Table 5.2 EEG data description 83
Table 6.1 Description of hardware (equipment) and software 92
Table 6.2 Description of video clips in order of presentation 97
Table 6.3 SSQ Scores distribution 99
Table 6.4 EEG data description 100
Table 6.5 SSQ and feedback questionnaire data 101
Table 7.1 Detail of first session tasks 116
Table 7.2 Detail of sessions 2, 3, and 4 tasks 116
Table 7.3 E-Prime experiment design files 119
Table 7.4 EEG data description of session 1 119
Table 7.5 EEG data description of sessions 2, 3, and 4 120
Table 8.1 Data files description 131
Table 9.1 Equipment and software description 141
Table 9.2 EEG data description 145
Table 10.1 EEG and ECG data description 157
Table 11.1 Description of hardware (equipment) and software 166
Table 11.2 EEG data description 169
Table 12.1 Description of hardware and software 174
Table 12.2 Example of logical problems in the cognitive task 176
Table 12.3 EEG data files with description 178
Table 13.1 Description of hardware and software 185
Table 13.2 EEG data description 189
Table 14.1 Equipment and software 194
Table 14.2 Details of EEG data 200
xi
PREFACE
This book is intended for those who are planning brain studies using
electroencephalography (EEG) as well as those who want to explore
new clinical and behavioral applications using EEG. Prior knowledge of
brain functionality and neuromodalities is required for understanding the
material provided in this book. This book is not about EEG or about the
brain; there are already large numbers of books available on such topics.
Therefore, the reader may wish to go through the basics of brain anatomy
and physiology as well as the basics of EEG before studying this book.
Also, there are many good resources available on the Internet to study the
basics of the brain and EEG.
This book is specifically beneficial for those who want to venture into
this field by designing their own EEG experiments as well as those who
are excited about neuroscience and want to explore various applications
related to the brain. This book details experimental design for various
brain-related applications like stress, epilepsy, etc., using EEG. The main
aim of the book is to provide guidelines for designing an EEG experi-
ment. As such, the first chapter provides details on how to design an EEG
experiment as well as the various parameters that should be considered
for a successful design. Chapter emphasis is on ethical issues, sample size
computation, and data acquisition guidelines. An example of stimulus
experiment design is also provided. Various types of EEG equipment and
software are also discussed in Chapter 1, Designing an EEG Experiment.
The remaining 13 chapters provide experiment design for a num-
ber of applications including clinical as well as behavioral applications.
In addition, experiment design codes and example datasets for one sub-
ject are provided with each chapter. As each of the chapters is accompa-
nied by experiment design codes and example datasets, those interested
can quickly design their own experiments or use the current experiment
design for their own experiments. The appendices provide various forms,
including a recruitment form, feedback form, and various forms for the
subjective tests associated with the chapters. Also the chapters provide rec-
ommendations for the related hardware equipment and software for data
acquisition as well as processing and analysis.
xiii
xiv Preface
Chapter  2, Mental Stress; Chapter  3, Major Depressive Disorder;
Chapter 4, Epileptic Seizures; Chapter 5, Alcohol Addiction; Chapter 6,
Passive Polarized and Active Shutter 3D TVs; Chapter 7, 2D and 3D
Educational Contents; Chapter  8, Visual and Cognitive Fatigue dur-
ing Learning; Chapter 9, 3D Video Games; Chapter 10, Visually Induced
Motion Sickness; Chapter 11, Mobile Phone Calls; Chapter 12, Drivers’
Cognitive Distraction; Chapter  13, Drivers’ Drowsiness; Chapter  14,
Working Memory and Attention are each organized similarly. In general,
they start with the introduction of the problem being discussed in the
chapter, followed by the specific problem statement and the objectives of
the study. After that, details are provided for the hardware and software
used in that specific study. The experiment design and protocol section
includes target population, sample size computation, inclusion and exclu-
sion criteria, experiment design, and experiment procedure. Then the data
description is provided and the details of the data accompanying the chap-
ter are discussed. Finally, relevant papers and references are given.
Two chapters are provided where the experiment design for studying
stress and depression are discussed in detail, i.e., Chapter 2, Mental Stress,
on stress and Chapter 3, Major Depressive Disorder, on major depressive
disorder (MDD). The stress experiments involve designing stimulus exper-
iments for studying four levels of stress. This is done through using various
stimuli to induce the stress and then measuring the corresponding brain
signal using EEG. Chapter 3, Major Depressive Disorder, provides details
on the experiment that can be used for both diagnosis of MDD and mon-
itoring the treatment efficacy of antidepressants for MDD patients.
Chapter 4, Epileptic Seizures discusses the issue of epilepsy. Because
a large population is affected by epileptic seizures, the related researchers’
motivation is to come up with new methods that can diagnose as well as
predict the onset of epileptic seizures. Chapter 4, Epileptic Seizures, pro-
vides details on epilepsy and discusses various datasets that are available for
studying epilepsy. One of them is from MIT in the United States while the
other two datasets are from Europe. Chapter 5, Alcohol Addiction, details
an experiment for objectively recognizing alcohol use disorder (AUD)
patients. AUD subjects are classified into two categories, i.e., alcohol abuse
(AA) and alcohol dependent (AD). Both AA and AD are described dis-
tinctly according to the Diagnostic and Statistical Manual of Mental Disorders
IV (DSM-IV), as a severe form of alcohol drinking that causes distress or
harm to the drinker. In this chapter, EEG data collection for discriminating
AUD from control and for discriminating AA and AD is discussed.
Preface xv
Chapter 6, Passive Polarized and Active Shutter 3D TVs; Chapter 7, 2D
and 3D Educational Contents; Chapter 8, Visual and Cognitive Fatigue
during Learning; Chapter 9, 3D Video Games; Chapter 10, Visually Induced
Motion Sickness are related to various aspects of multimedia. Chapter 6,
Passive Polarized and Active Shutter 3D TVs, looks at the two three-dimen-
sional (3D) consumer electronics display technologies, i.e., active shuttered
and passive polarized based displays. An experiment is designed to study
which one of these technologies is superior when compared with tradi-
tional two-dimensional (2D) displays. This is done by using videos of vari-
ous 3D movies as the stimulus for the experiment. Chapter 7, 2D and 3D
Educational Contents and Chapter 8, Visual and Cognitive Fatigue during
Learning are related to learning using the various types of multimedia tools.
An experiment design is provided to compare learning with 3D tools com-
pared to traditional 2D tools. In addition, as learning is related to memory,
the design of the stimuli includes experiments for studying both short-term
and the long-term memory. Chapter 8, Visual and Cognitive Fatigue during
Learning uses the event-related potentials (ERPs) extracted from the EEG
signal to study visual and cognitive fatigue during learning. This is impor-
tant as many studies have reported that fatigue due to 3D multimedia tools
can affect the memory retention process.
Chapter 9, 3D Video Games, uses 2D and 3D games as stimuli to study
two things: the differences in brain activity for each of the gaming modes
(2D and 3D) that result in different experiences for the subject, and the
effect of violent games on subjects’ brain activity. Hence, the experiment
discussed in this chapter addresses two different questions. Chapter 10,
Visually Induced Motion Sickness is important as it provides an experi-
ment design to study visually induced motion sickness (VIMS). VIMS has
been reported in the form of nausea, headache, disorientation, and dis-
comfort after watching 3D movies and after playing 3D games. Hence, a
special movie is designed as stimulus to induce VIMS in the subjects.
Mobile phones have become a part of our daily lives and are one of
the most important technical gadgets that we carry with us all the time. A
number of studies have reported contradictory findings about the effects
of mobile phone usage on our brain. Chapter 11, Mobile Phone Calls,
provides details of an experiment that was conducted to study the effects
of mobile phones using EEG. The experiment involves four conditions,
two with the right ear and two with the left ear. One of the conditions
involves touching the ear while the other involves answering the phone
without touching the ear by keeping it at a certain distance from the ear.