Brain-Computer Interfaces 1

Brain-computer interfaces (BCI) are devices which measure brain activity and translate it into messages or commands, thereby opening up many investigation and application possibilities. This book provides keys for understanding and designing these multi-disciplinary interfaces, which require many fields of expertise such as neuroscience, statistics, informatics and psychology.

This first volume, Methods and Perspectives, presents all the basic knowledge underlying the working principles of BCI. It opens with the anatomical and physiological organization of the brain, followed by the brain activity involved in BCI, and following with information extraction, which involves signal processing and machine learning methods. BCI usage is then described, from the angle of human learning and human-machine interfaces.

The basic notions developed in this reference book are intended to be accessible to all readers interested in BCI, whatever their background. More advanced material is also offered, for readers who want to expand their knowledge in disciplinary fields underlying BCI.

This first volume will be followed by a second volume, entitled Technology and Applications.

Autorentext

Maureen Clerc is Senior Researcher at Inria Sophia Antipolis, France. Laurent Bougrain is Assistant Professor at the University of Lorraine, France. Fabien Lotte is Junior Researcher at Inria Bordeaux, France.

Inhalt
Foreword xiii
José DEL R. MILLAN

Introduction xv
Maureen CLERC, Laurent BOUGRAIN and Fabien LOTTE

Part 1. Anatomy and Physiology 1

Chapter 1. Anatomy of the Nervous System 3
Matthieu KANDEL and Maude TOLLET

1.1. General description of the nervous system 4

1.2. The central nervous system 5

1.2.1. The telencephalon 6

1.2.2. The diencephalon 10

1.2.3. The brain stem 12

1.3. The cerebellum 14

1.4. The spinal cord and its roots 15

1.5. The peripheral nervous system 18

1.5.1. Nerves 18

1.5.2. General organization of the PNS 19

1.5.3. The autonomic nervous system 20

1.6. Some syndromes and pathologies targeted by BrainComputer Interfaces 21

1.6.1. Motor syndromes 21

1.6.2. Some pathologies that may be treated with BCIs 22

1.7. Conclusions 23

1.8. Bibliography 24

Chapter 2. Functional Neuroimaging 25
Christian BÉNAR

2.1. Functional MRI 26

2.1.1. Basic principles of MRI 26

2.1.2. Principles of fMRI 26

2.1.3. Statistical data analysis: the linear model 27

2.1.4. Independent component analysis 29

2.1.5. Connectivity measures 30

2.2. Electrophysiology: EEG and MEG 31

2.2.1. Basic principles of signal generation 31

2.2.2. Event-related potentials and fields 31

2.2.3. Source localization 32

2.2.4. Independent component analysis 34

2.2.5. Timefrequency analysis 34

2.2.6. Connectivity 35

2.2.7. Statistical analysis 36

2.3. Simultaneous EEG-fMRI 37

2.3.1. Basic principles 37

2.3.2. Applications and data analysis 37

2.3.3. Connections between EEG and fMRI 38

2.4. Discussion and outlook for the future 38

2.5. Bibliography 40

Chapter 3. Cerebral Electrogenesis 45
Franck VIDAL

3.1. Electrical neuronal activity detected in EEG 45

3.1.1. Action and postsynaptic potentials 46

3.1.2. Resting potential, electrochemical gradient and PSPs 47

3.1.3. From PSPs to EEG 48

3.2. Dipolar and quadrupole fields 51

3.2.1. Field created by an ion current due to the opening of ion channels 51

3.2.2. Factors determining the value of the potential created by an ion current 56

3.3. The importance of geometry 57

3.3.1. Spatial summation, closed fields and open fields 57

3.3.2. Effect of synapse position on the polarity of EEG 60

3.3.3. Effect of active areas' position 61

3.4. The influence of conductive media 62

3.4.1. Influence of glial cells 62

3.4.2. Influence of skull bones 63

3.5. Conclusions 64

3.6. Bibliography 64

Chapter 4. Physiological Markers for Controlling Active and Reactive BCIs 67
François CABESTAING and Philippe DERAMBURE

4.1. Introduction 67

4.2. Markers that enable active interface control 72

4.2.1. Spatiotemporal variations in potential 72

4.2.2. Spatiotemporal wave variations 74

4.3. Markers that make it possible to control reactive interfaces 77

4.3.1. Sensory evoked potentials 77

4.3.2. Endogenous P300 potential 80

4.4. Conclusions 81

4.5. Bibliography 82

Chapter 5. Neurophysiological Markers for Passive BrainComputer Interfaces 85
Raphaëlle N. ROY and Jérémy FREY

5.1. Passive BCI and mental states 85

5.1.1. Passive BCI: definition 85

5.1.2. The notion of mental states 86

5.1.3. General categories of neurophysiological markers 87

5.2. Cognitive load 87

5.2.1. Definition 87

5.2.2. Behavioral markers 87 5.2.3. EEG markers 87</p&g...