Bougrain Laurent - Brain Computer Interfaces

1. 4 Physiological Markers for Controlling Active and Reactive BCIs
2. 9 Statistical Learning for BCIs
3. 10 Adaptive Methods in Machine Learning

1. Introduction
2. 1 Anatomy of the Nervous System
3. 2 Functional Neuroimaging
4. 3 Cerebral Electrogenesis
5. 4 Physiological Markers for Controlling Active and Reactive BCIs
6. 5 Neurophysiological Markers for Passive BrainComputer Interfaces
7. 6 Electroencephalography Data Preprocessing
8. 7 EEG Feature Extraction
9. 8 Analysis of Extracellular Recordings
10. 9 Statistical Learning for BCIs
11. 10 Adaptive Methods in Machine Learning
12. 11 Human Learning for BrainComputer Interfaces
13. 12 BrainComputer Interfaces for HumanComputer Interaction
14. 13 Brain Training with Neurofeedback

Series Editor

Maureen Clerc

Edited by

First published 2016 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

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John Wiley & Sons, Inc.
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ISTE Ltd 2016

The rights of Maureen Clerc, Laurent Bougrain and Fabien Lotte to be identified as the author of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2016942416

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISBN 978-1-84821-826-0

A BrainComputer Interface (BCI) records brain signals, translates them into commands that operate a variety of devices, and provides feedback to the user about how intentions are transformed into actions. These three essential components, forming a closed-loop system, define the core components of a BCI. Their natural target population has traditionally been people with motor disabilities that have lost control of their body but have preserved cognitive functions, and BCIs have been intended to act as alternative assistive devices for them. However, in recent years the scope of a BCI has widened to include restoration or rehabilitation of motor and even cognitive functions for patients after some kind of central nervous system injury, brain state monitoring for healthy subjects, and new tools for studying human brain functions.

An anecdotal, even fringe, field of research at the confines with science fiction when it appeared, BCIs have grown over the last 40 years from early prototypes in a handful of locations to more than 3,000 research labs and nearly 150 companies working in BCI-related areas nowadays. The complexity of todays BCI systems, which are moving beyond constrained laboratory conditions, calls for truly multidisciplinary efforts spanning clinical research to computer science and humancomputer interfaces, from neuroscience to biomedical and neuroengineering, from rehabilitation to robotics and virtual reality, and from human psychology to material and electrical engineering.

This wide range of fields that contribute to BCI makes it difficult, if not impossible, to have a unified view covering all the facets of this fascinating scientific and translational enterprise. Thus, a certain bias is always present and openly acknowledged in our research. This book is no exception. It is edited by signal processing and machine learning specialists. Yet, aiming to become a reference for the French speaking research community, it gathers a collective body of expertise from all the fields involved in BCI research and practice. We consider this a challenge that the editors have successfully tackled, as the book covers state-of-the-art research and results in a way that all other communities can relate to. Furthermore, the curious layperson I hope you are if you want to live long with a healthy brain! can also profit from a significant number of chapters that do not require any specific background.

The book is organized into seven parts, distributed in two volumes. In the first volume (Foundations and Methods) , readers walk along the path covering the main principles of BCI, with all its subtle meanders which they may decide to jump over or to explore in more details. This is a volume that we may well need to read in several iterations as we go into detail into the field and its different components. deals with human learning, and the interplay between the human and the machine.

BrainComputer Interfaces by Clerc, Bougrain and Lotte is the first BCI book for and by the French-speaking community. Here, it is also translated in English as it has important lessons for all BCI researchers and practitioners worldwide. I am certain that this book will appeal to each of them as it has done to me. Enjoy it.

Jos DEL R. MILLN

Geneva

Switzerland

May 2016

A BrainComputer interface (BCI) is a system that translates a users brain activity into messages or commands for an interactive application. BCIs represent a relatively recent technology that is experiencing a rapid growth. The objective of this introductory chapter is to briefly present an overview of the history of BCIs, the technology behind them, the terms and classifications used to describe them and their possible applications. The books content is presented, and a reading guide is provided so that you, the reader, can easily find and use whatever you are searching for in this book.

The idea of being able to control a device through mere thought is not new. In the scientific world, this idea was proposed by Jacques Vidal in 1973 in an article entitled Toward Direct BrainComputer Communications [VID 73]. In this article, the Belgian scientist, who had studied in Paris and taught at the University of California, Los Angeles, describes the hardware architecture and the processing he sought to implement in order to produce a BCI through electroencephalographic signals. In 1971, Eberhard Fetz had already shown that it was possible to teach a monkey to voluntarily control motor cortex brain activity by providing visual information according to discharge rate [FET 71]. These two references show that since that time, BCIs could be implemented in the form of invasive or non-invasive brain activity measurements, that is, measurements of brain activity at the neural or scalp levels. For a more comprehensive history of BCIs, the reader may refer to the following articles: [LEB 06, VAA 09].

Although BCIs have been present in the field of research for over 40 years, they have only recently come to the medias attention, often described in catchy headlines such as writing through thought is possible or a man controls a robot arm by thinking. Beyond announcements motivated by journalists love for novelty or by scientists and developers hopes of attracting the attention of the public and of potential funding sources, what are the real possibilities for BCIs within and outside research labs?