BOOK
Practical Guide To Brain Data Analysis, A
Vieito Joao Paulo | Da Rocha Armando Freitas | Thomaz Carlos
(2016)
Additional Information
Book Details
Abstract
This book was developed to help students and researchers in the fields of economics, finance, law and other social science areas to understand and apply neuroscience. With the use of neuroscience technologies, it is now possible to understand how people make decisions in practice, using friendly and ecological experimental setups. The first half of the book studies the decision-making process and explains how the brain is organized. It presents the brain as a distributed processing system, shows how to record brain activities, and how to combine neurosciences and statistical tools to design experiments. In the last chapters, experiments on stock market decision, dilemma judgment, vote decision and understanding of media propaganda are described and discussed.
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| Contents | xiii | ||
| Preface | v | ||
| About the Authors | ix | ||
| Chapter 1 Introduction | 1 | ||
| 1.1 Economy and Finances | 1 | ||
| 1.2 Social Sciences | 4 | ||
| 1.2.1 Moral | 6 | ||
| 1.2.2 Law | 9 | ||
| 1.2.2.1 Neurodynamics of a social decision-making | 10 | ||
| 1.2.2.2 Future | 11 | ||
| References | 12 | ||
| Chapter 2 Decision-making Process | 17 | ||
| 2.1 Reasoning Process | 18 | ||
| 2.2 Financial and Economics Decision-making | 21 | ||
| References | 25 | ||
| Chapter 3 How the Brain is Organized | 27 | ||
| 3.1 The Neuron | 27 | ||
| 3.2 The Brain | 29 | ||
| 3.3 The Basic Structure of the Cortex: The Cortical Column | 30 | ||
| 3.4 The Distributed Character of Cortical Processing | 30 | ||
| 3.5 The Properties of Distributed Intelligent Processing Systems | 34 | ||
| 3.6 Neural Networks | 36 | ||
| References | 38 | ||
| Chapter 4 The Brain as a Distributed Processing System | 39 | ||
| 4.1 Segmenting Cortex into Brodmann Areas | 40 | ||
| 4.2 Value, Benefit and Risk Assessment | 40 | ||
| 4.3 Working Memory | 42 | ||
| 4.4 Attention Control | 42 | ||
| 4.5 Memory Access | 44 | ||
| 4.6 Arithmetic Calculation | 44 | ||
| 4.7 Language Production and Comprehension | 46 | ||
| 4.8 Acting | 46 | ||
| 4.9 Assessing Other Actions | 48 | ||
| 4.10 Reasoning as a Cooperative Action between Specialized Circuits | 49 | ||
| References | 50 | ||
| Chapter 5 How to Map the Brain | 55 | ||
| 5.1 Positron Emission Tomography and Single-Photon Emission Computed Tomography | 55 | ||
| 5.2 Using Functional Magnet Resonance Image | 56 | ||
| 5.3 Using EEG | 60 | ||
| 5.3.1 Event-related activity | 63 | ||
| 5.3.2 Low resolution tomography (LORETA) analysis | 64 | ||
| 5.4 Statistical Techniques to Analyze EEG Data | 64 | ||
| 5.4.1 Quantifying the amount of information provided by each electrode | 64 | ||
| 5.4.2 Factor analysis | 65 | ||
| 5.4.3 Linear discriminant analysis | 66 | ||
| 5.4.4 Multiple regression analysis | 67 | ||
| 5.5 Comparing fMRI and EEG | 69 | ||
| References | 70 | ||
| Chapter 6 How to Make an Experiment with EEG | 73 | ||
| 6.1 Type of Experiment | 73 | ||
| 6.2 Designing Software to Make a Decision-making Simulation | 74 | ||
| 6.3 Using EEG | 74 | ||
| 6.4 Analysis of the EEG Data Quality | 77 | ||
| 6.5 Tools used for EEG Analysis | 77 | ||
| 6.5.1 EEG average and grand average | 79 | ||
| 6.5.2 Using LORETA | 82 | ||
| 6.5.2.1 Identifying amplitude sources | 82 | ||
| 6.5.2.2 Identifying band frequency sources | 85 | ||
| 6.5.3 Multivariate analysis | 87 | ||
| References | 88 | ||
| Chapter 7 Financial Decision-making | 91 | ||
| 7.1 Designing Trading as an Ecological Game | 91 | ||
| 7.2 The Experimental Setting | 94 | ||
| 7.3 Population | 94 | ||
| 7.4 EEG Components Identified in Grand Average | 95 | ||
| 7.5 Activated Cortical Areas | 96 | ||
| 7.6 EEG Band Frequencies | 98 | ||
| 7.7 Source Sequence | 100 | ||
| 7.8 LORETA Sources and Grand Average | 101 | ||
| 7.9 h(ei) and Factor Analysis | 104 | ||
| 7.10 Logistic Regression and Linear Discriminant Analysis | 106 | ||
| 7.11 Associating LORETA Sources to FA and LDA Mappings | 107 | ||
| 7.12 Multilinear Regression Analysis | 110 | ||
| 7.13 Final Comments | 112 | ||
| References | 113 | ||
| Chapter 8 Moral Dilemma Judgment | 115 | ||
| 8.1 Experimental Design | 116 | ||
| 8.2 The Experimental Setting | 118 | ||
| 8.3 EEG Components Identified in Grand Average | 118 | ||
| 8.4 Activated Cortical Areas | 120 | ||
| 8.5 EEG Band Frequencies | 123 | ||
| 8.6 Cortical Activation | 124 | ||
| 8.7 ILS Sequence | 125 | ||
| 8.8 Low Resolution Tomography (LORETA) Sources and Grand Average | 127 | ||
| 8.9 h(ei) and Factor Analysis | 129 | ||
| 8.10 Multilinear Regression Analysis | 133 | ||
| 8.11 Final Comments | 135 | ||
| References | 137 | ||
| Chapter 9 Thinking about Firearm Control | 139 | ||
| 9.1 Experimental Design | 139 | ||
| 9.2 Brain Activity Associated with Vote Decision | 142 | ||
| 9.2.1 Averaged EEG | 142 | ||
| 9.2.2 Activated cortical areas | 143 | ||
| 9.2.3 ILS sequence | 145 | ||
| 9.2.4 LORETA sources and grand average | 146 | ||
| 9.2.5 h(ei) and factor analysis | 149 | ||
| 9.2.6 Multilinear regression analysis | 151 | ||
| 9.3 Brain Activity and Media Propaganda | 152 | ||
| 9.3.1 Averaged EEG | 153 | ||
| 9.3.2 Activated cortical areas | 154 | ||
| 9.3.3 LORETA sources and grand average | 155 | ||
| 9.3.4 h(ei) and FA | 158 | ||
| References | 162 | ||
| Chapter 10 Multivariate Brain Signal Analysis | 163 | ||
| 10.1 Vectors and Matrices | 164 | ||
| 10.2 Eigenvectors and Eigenvalues | 165 | ||
| 10.3 Entropy and Information | 166 | ||
| 10.4 EEG Summarization | 168 | ||
| 10.5 Principal Component Analysis | 170 | ||
| 10.6 Factor Analysis | 173 | ||
| 10.7 Linear Discriminant Analysis | 175 | ||
| References | 178 | ||
| Chapter 11 Concluding Remarks | 181 | ||
| Index | 185 |