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

By Aamir Saeed Malik and Hafeez Ullah Amin

Designing EEG Experiments for Studying the Brain: Design Code and Example Datasets details the design of various brain experiments using electroencephalogram (EEG). Providing guidelines for designing an EEG experiment, it is primarily for researchers who want to venture into this field by designing their own experiments as well as those who are excited about neuroscience and want to explore various applications related to the brain. The first chapter describes how to design an EEG experiment and details the various parameters that should be considered for success, while remaining chapters provide experiment design for a number of neurological applications, both clinical and behavioral. As each chapter is accompanied with experiment design codes and example datasets, those interested can quickly design their own experiments or use the current design for their own purposes. Helpful appendices provide various forms for one’s experiment including recruitment forms, feedback forms, ethics forms, and recommendations for related hardware equipment and software for data acquisition, processing, and analysis.

• Written to assist neuroscientists in experiment designs using EEG
• Presents a step-by-step approach to designing both clinical and behavioral EEG experiments
• Includes experiment design codes and example datasets
• Provides inclusion and exclusion criteria to help correctly identify experiment subjects and the minimum number of samples
• Includes appendices that provide recruitment forms, ethics forms, and various subjective tests associated with each of the chapters

• Language: English
• Publisher: Academic Press
• Release date: May 25, 2017
• ISBN: 9780128111413

Aamir Saeed Malik

Dr. Malik has a B.S. in Electrical Engineering from University of Engineering and Technology, Lahore, Pakistan, M.S in Nuclear Engineering from Quaid-i-Azam University, Islamabad, Pakistan, another M.S in Information & Communication and Ph.D in Information & Mechatronics from Gwangju Institute of Science & Technology, Gwangju, Korea. He has more than 15 years of research experience and has worked for IBM, Hamdard University, Government of Pakistan, Yeungnam University and Hanyang University in Korea. He is currently working as Associate Professor at Universiti Teknologi PETRONAS in Malaysia. He is fellow of IET and senior member of IEEE. He is board member of Asia Pacific Neurofeedback Association (APNA) and member of Malaysia Society of Neuroscience (MSN). His research interests include neuro-signal & neuro-image processing and neuroscience big data analytics. He is author of 3 books and a number of international journal and conference papers with more than 1000 citations and cumulative impact factor of more than 180. He has a number of patents, copyrights and awards.

Book preview

Designing EEG Experiments for Studying the Brain

Design Code and Example Datasets

Aamir Saeed Malik

Hafeez Ullah Amin

Universiti Teknologi PETRONAS, Perak, Malaysia

Table of Contents

Cover image

Title page

Copyright

List of Figures

List of Tables

Preface

Chapter 1. Designing an EEG Experiment

Abstract

1.1 Introduction

1.2 Fundamental of EEG Waves

1.3 Importance of Experiment Design

1.4 EEG Experimentation: Ethical Issues and Guidelines

1.5 Sample Size Computation

1.6 Example of Experiment Design

1.7 EEG Equipment and Software

1.8 Guidelines for EEG Data Acquisition

1.9 Summary

References

Chapter 2. Mental Stress

Abstract

2.1 Introduction

2.2 Importance of Mental Stress Evaluation

2.3 Problem Statement

2.4 Software and Hardware

2.5 Experimental Design and Protocol

2.6 Detail of Ethics Approval

2.7 Data Description

2.8 Relevant Papers

Acknowledgments

References

Chapter 3. Major Depressive Disorder

Abstract

3.1 Introduction

3.2 Importance of Studying MDD

3.3 Problem Statement

3.4 Software/Hardware

3.5 Experiment Design and Protocol

3.6 Experimental Tasks and Procedure

3.7 Data Description

3.8 Relevant Papers

Acknowledgments

References

Chapter 4. Epileptic Seizures

Abstract

4.1 Introduction

4.2 Importance of Studying Epilepsy

4.3 Problem Statement

4.4 Details of Public EEG Databases

4.5 Dataset Availability

Acknowledgments

References

Chapter 5. Alcohol Addiction

Abstract

5.1 Introduction

5.2 Importance of Studying Drug Addiction

5.3 Problem Formulation

5.4 Research Design

5.5 Experiment Procedure

5.6 Software/Hardware Details

5.7 Data Description

5.8 Relevant Papers

Acknowledgments

References

Chapter 6. Passive Polarized and Active Shutter 3D TVs

Abstract

6.1 Introduction

6.2 Importance of Studying 3D Display Technologies

6.3 Problem Statement

6.4 Software and Hardware Tools

6.5 Experimental Design and Protocol

6.6 Data Description

6.7 Relevant Papers

Acknowledgments

References

Chapter 7. 2D and 3D Educational Contents

Abstract

7.1 Introduction

7.2 Importance of Studying 3D-Based Multimedia Educational Tools

7.3 Problem Statement

7.4 Software and Hardware

7.5 Experimental Design and Protocol

7.6 Data Description

7.7 Relevant Papers

Acknowledgments

References

Chapter 8. Visual and Cognitive Fatigue During Learning

Abstract

8.1 Introduction

8.2 Importance and Significance of Visual and Mental Fatigue during Learning

8.3 Problem Statement

8.4 Software and Hardware

8.5 Experiment Design and Protocol

8.6 Data Description

8.7 Relevant Papers

Acknowledgments

References

Chapter 9. 3D Video Games

Abstract

9.1 Introduction

9.2 Importance of Studying 3D Violence Game

9.3 Problem Statement

9.4 Description of 2D- and 3D-Based Video Games

9.5 Software and Hardware Tools

9.6 Experimental Design and Protocol

9.7 Experimental Data Accompanying This Chapter

9.8 Relevant Papers

Acknowledgments

References

Chapter 10. Visually Induced Motion Sickness

Abstract

10.1 Introduction

10.2 Importance of Studying VIMS for 3D Displays

10.3 Problem Statement and Objectives

10.4 Visually Induced Motion Sickness

10.5 Software and Hardware

10.6 Experimental Design and Protocol

10.7 Experiment Data Accompanying this Book

10.8 Relevant Papers

Acknowledgments

References

Chapter 11. Mobile Phone Calls

Abstract

11.1 Introduction

11.2 Previous Studies

11.3 Importance of Studying the Effects of Mobile Phone Calls

11.4 Problem Description

11.5 Software and Hardware

11.6 Experiment Design and Protocol

11.7 Data Description

Acknowledgments

References

Chapter 12. Drivers’ Cognitive Distraction

Abstract

12.1 Introduction

12.2 Importance of Studying Driver Distraction

12.3 Software and Hardware

12.4 Experiment Design and Protocol

12.5 EEG Data Description

12.6 Relevant Papers

Acknowledgments

References

Chapter 13. Drivers’ Drowsiness

Abstract

13.1 Introduction

13.2 Importance of Studying Drivers’ Drowsiness

13.3 Problem Statement

13.4 Software and Hardware

13.5 Experiment Design and Protocol

13.6 Data Description

13.7 Relevant Papers

Acknowledgments

References

Chapter 14. Working Memory and Attention

Abstract

14.1 Introduction

14.2 Importance of Studying Working Memory Assessment

14.3 Problem Statement

14.4 Software and Hardware

14.5 ExperimentAL Design and Protocol

14.6 Data Description

14.7 Relevant Papers

Acknowledgments

References

Appendices

Appendix 2A Subject Recruitment Pro Forma Sheet

Appendix 2B Feedback questionnaire

Appendix 2C Subject Information and Consent Form

Appendix 2D Perceived Stress Scale (PSS) Questionnaire

Appendix 3A Hospital Anxiety and Depression Scale (HADS)

Appendix 3B Beck Depression Inventory-II (BDI-II)

Interpreting the Beck Depression Inventory

Appendix 5A The Alcohol Use Disorders Identification Test

Appendix 5B Mini International Neuropsychiatric Interview (MINI)

Appendix 5C Alcohol Withdrawal Assessment Scoring Guidelines (CIWA-Ar)

Appendix 6A Demographic Data

Appendix 6B Simulator Sickness Questionnaire (SSQ) And Feedback Form

Appendix 7A Screening Questionnaire

Appendix 7B Feedback Questionnaire

Appendix 9A Questionnaire

Appendix 10A Eye Examination Form

Appendix 10B Motion Sickness Susceptibility Questionnaire

Appendix 11A Questionnaire Form

Appendix 13A Sample Size Calculation

Appendix 13B Drowsiness Questionnaire

Appendix 14 Subject Research Information

Introduction

Purpose of the Study

Qualification to Participate

Study Procedures

Risks

Reporting Health Experiences

Participation in the Study

Questions

Confidential

Signatures

Introduction

Purpose of the Study

Qualification to Participate

Study Procedure

Risks

Reporting Health Experiences

Participation in the Study

Possible Benefits

Questions

Confidentiality

Signatures

Introduction

Purpose of the Study

Qualification to Participate

Study Procedures

Risks

Reporting Health Experiences

Participation in the Study

Possible Benefits

Questions

Confidentiality

Signatures

Introduction

Purpose of the Study

Qualification to Participate

Study Procedures

Risks

Reporting Health Experiences

Participation in the Study

Possible Benefits

Questions

Confidentiality

Signatures

Introduction

Purpose of the Study

Qualification to Participate

Study Procedures

Risks

Reporting Health Experiences

Participation in the study

Questions

Confidentiality

Signatures

References

Glossary

Index

Copyright

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Notices

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List of Figures

List of Tables

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 experiment. 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 number of applications including clinical as well as behavioral applications. In addition, experiment design codes and example datasets for one subject are provided with each chapter. As each of the chapters is accompanied 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 recommendations for the related hardware equipment and software for data acquisition as well as processing and analysis.

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 during 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 exclusion criteria, experiment design, and experiment procedure. Then the data description is provided and the details of the data accompanying the chapter 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 experiments 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 monitoring 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, provides 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 distinctly 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.

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-dimensional (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 traditional two-dimensional (2D) displays. This is done by using videos of various 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 compared 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 important 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 experiment design to study visually induced motion sickness (VIMS). VIMS has been reported in the form of nausea, headache, disorientation, and discomfort 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.

Chapter 12, Drivers’ Cognitive Distraction, and Chapter 13, Drivers’ Drowsiness, deal with another important aspect of our lives: driving. Almost everyone is exposed to driving in one way or another. We are either driving ourselves or traveling in a vehicle driven by others. It has been reported in many transport safety-related reports that the majority of accidents are due to the driver. Hence, in these two chapters, an experiment design is provided for studying two important parameters related to driving, i.e., driver cognitive distraction and driver drowsiness. The stimulus for studying cognitive distraction involves asking the subject to answer analytical and logical questions while driving. For driver drowsiness, the subject drives on a long road with monotonous environment for a long time, and EEG signals are recorded while the subject drives.

Finally, Chapter 14, Working Memory and Attention, is related to working memory and attention. There are three processes related to memory, i.e., memory formation, memory retention, and retrieval. The experiment in the chapter specifically addresses the memory formation and maintenance stages. Attention, distraction, and interruption are used in the stimuli to study the memory stages.

After the design of experiments and collection of data, the next stage is the preprocessing, processing, and analysis of the EEG data. We plan to publish another book that will explain the process of analysis of EEG data for the various brain-related applications mentioned in this book. In the meantime, the readers can access the papers listed in the Relevant Papers section in each of the chapters. These papers provide the details of various analysis techniques for particular applications. In the upcoming book, a step-by-step guide will be presented to analyze the data, and complete details of the analysis techniques with MATLAB code will be provided.

Chapter 1

Designing an EEG Experiment

Abstract

This chapter describes the basics of electroencephalography (EEG) research and experiment design. At the beginning the fundamental EEG waves are briefly described. EEG experiments and related factors that can highly influence the experimental results, such as clear definition of study objectives, ethical issues, and proper sample size calculation are discussed. In addition, an example of experiment design is explained in detail. The well-known EEG data acquisition systems and stimulus presentation software are listed. Finally, general guidelines for EEG data collection are provided including general data acquisition setup, proper experiment design, preparation of participant, and EEG system check-up.

Keywords

EEG research; experiment design; ethical issues; ethical approval; sample size calculation; guidelines for EEG data acquisition

Contents

1.1 Introduction 2

1.2 Fundamental of EEG Waves 2

1.2.1 Delta Waves (Up to 4 Hz) 2

1.2.2 Theta Waves (4–8 Hz) 3

1.2.3 Alpha Waves (8–13 Hz) 3

1.2.4 Beta Waves (13–25 Hz) 4

1.2.5 Gamma Waves (above 25 Hz) 4

1.3 Importance of Experiment Design 4

1.4 EEG Experimentation: Ethical Issues and Guidelines 6

1.4.1 Ethical Issues 6

1.4.2 Ethics Approval Guidelines 7

1.5 Sample Size Computation 9

1.5.1 Objective and Hypothesis of the Study 9

1.5.2 Target Population 9

1.5.3 Statistical Attributes of Sample Size 10

1.5.4 Types and Numbers of Dependent and Independent Variables 11

1.5.5 Groups, Conditions, and Statistical Tests 11

1.5.6 Available Software 12

1.6 Example of Experiment Design 13

1.6.1 Objective 13

1.6.2 Instructions to Participant 14

1.6.3 Stimulus and Time 14

1.6.4 Trials, Blocks, and Conditions 15

1.6.5 Participants’ Response and Feedback 17

1.6.6 Events Synchronization with EEG 19

1.6.7 End of Task 19

1.7 EEG Equipment and Software 19

1.7.1 EEG Equipment and Data Acquisition Software 19

1.7.2 Presentation Software 22

1.8 Guidelines for EEG Data Acquisition 25

1.8.1 General Data Acquisition Setup 25

1.8.2 Experiment Design 28

1.8.3 Preparation of Participant 28

1.8.4 EEG System Check-Up 29

1.9 Summary 29

References 29

1.1 Introduction

Electroencephalography (EEG) is a reliable and widely used measurement tool for studying brain functions, abnormalities, and neurophysiological dynamics due to its low cost, noninvasiveness, portability, and high temporal resolution in the millisecond range.¹ In the field of neural signal processing, EEG is commonly used as a noninvasive brain imaging technique for diagnosis of brain disorders and normal EEG for understanding of brain functions in research studies. It enables the researchers and clinicians to study brain functions such as memory, vision, intelligence, motor imagery, emotion, perception, and recognition, as well as detect abnormalities such as epilepsy, stroke, dementia, sleep disorders, depression, and trauma. EEG signals reflect the electrical neuronal activity of the brain, which contains useful information about the brain state. This chapter will discuss the fundamentals of EEG, EEG experiments, ethical approval guidelines, sample size computation, experiment design, EEG equipment and presentation software, and EEG data acquisition.

1.2 Fundamental of EEG Waves

Since the beginnings of EEG, the study of different brain oscillations and their relationship with different brain functions has attracted the attention of researchers. Hans Berger discovered the presence of alpha and beta waves in EEG. The brain oscillations are categorized in frequency bands and related with different brain states or functions. In this section, a brief description of EEG frequency bands is provided. A typical example of EEG waves can be seen in Fig. 1.1.

Figure 1.1 EEG signal and corresponding bands.

1.2.1 Delta Waves (Up to 4 Hz)

EEG delta waves are high-amplitude brain waves and are associated with deep sleep stages. The delta waves are also associated with different brain functions other than deep sleep, e.g., high frontal delta waves in awake subjects are associated with cortical plasticity. Delta bands are reported as prominent brain waves in cognitive processing especially in event-related studies.² EEG low-frequency components, especially delta bands, are the primary contributor to the P300 peak of event-related potentials (ERPs). P300 is a widely studied and well-known indicator of cognitive processing.

1.2.2 Theta Waves (4–8 Hz)

Theta waves are observed in the drowsy state and more common in children than adults. In the awake adult, without doing any attention/cognitive activity, high theta activity is considered abnormal and associated with different brain disorders, e.g., high frontal theta is linked with nonresponse to antidepressant treatment in depression patients. However, high theta activity plays a significant role in attentional processing and working memory, see for review.³ Changes in theta activity are also reported in brain disorders such