Brain–Computer Interfaces 1
Foundations and Methods
Publication Date: July 2016 Hardback 330 pp.
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
Part 1. Anatomy and Physiology.
1. Anatomy of the Nervous System, Matthieu Kandel and Maude Tollet.
2. Functional Neuroimaging, Christian Bénar.
3. Cerebral Electrogenesis, Franck Vidal.
4. Physiological Markers for Controlling Active and Reactive BCIs, François Cabestaing and Philippe Derambure.
5. Neurophysiological Markers for Passive Brain–Computer Interfaces, Raphaëlle N. Roy and Jérémy Frey.
Part 2. Signal Processing and Machine Learning.
6. Electroencephalography Data Preprocessing, Maureen Clerc.
7. EEG Feature Extraction, Fabien Lotte and Marco Congedo.
8. Analysis of Extracellular Recordings, Christophe Pouzat.
9. Statistical Learning for BCIs, Rémi Flamary, Alain Rakotomamonjy and Michèle Sebag.
Part 3. Human Learning and Human–Machine Interaction.
10. Adaptive Methods in Machine Learning, Maureen Clerc, Emmanuel Daucé and Jérémie Mattout.
11. Human Learning for Brain–Computer Interfaces, Camille Jeunet, Fabien Lotte and Bernard N’Kaoua.
12. Brain–Computer Interfaces for Human–Computer Interaction, Andéol Evain, Nicolas Roussel, Géry Casiez, Fernando Argelaguet-Sanz and Anatole Lécuyer.
13. Brain Training with Neurofeedback, Lorraine Perronnet, Anatole Lécuyer, Fabien Lotte, Maureen Clerc and Christian Barillot.
About the Authors
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.