Toward Brain-Computer Interfacing

© 2007 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means(including photocopying, recording, or information storage and retrieval) without permission in writing from thepublisher. This book was set in LaTex by the authors and was printed and bound in the United States of America Library of Congress Cataloging-in-Publication Data Towards Brain-Computer Interfacing / edited by Guido Dornhege, Jose del R. Millan, Thilo Hinterberger, Dennis McFarland, Klaus-Robert Muller. p.; cm. (Neural information processing series) “A Bradford book.” Includes bibliographical references and index. ISBN 978-0-262-04244

[1]  E. John,et al.  Evoked-Potential Correlates of Stimulus Uncertainty , 1965, Science.

[2]  E. Donchin,et al.  On quantifying surprise: the variation of event-related potentials with subjective probability. , 1977, Psychophysiology.

[3]  M. Posner,et al.  Orienting of Attention* , 1980, The Quarterly journal of experimental psychology.

[4]  W. M. Carey,et al.  Digital spectral analysis: with applications , 1986 .

[5]  David J. Krus,et al.  Demonstration of properties of a suppressor variable , 1986 .

[6]  Emanuel Donchin,et al.  Definition, Identification, and Reliability of Measurement of the P300 Component of the Event-Related Brain Potential , 1987 .

[7]  Samuel D. Stearns,et al.  Signal processing algorithms , 1988 .

[8]  E. Donchin,et al.  Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. , 1988, Electroencephalography and clinical neurophysiology.

[9]  J. Polich.  Habituation of P300 from auditory stimuli , 1989, Psychobiology.

[10]  D J McFarland,et al.  An EEG-based brain-computer interface for cursor control. , 1991, Electroencephalography and clinical neurophysiology.

[11]  Dennis J. McFarland,et al.  An EEG-based method for graded cursor control , 1993, Psychobiology.

[12]  Gert Pfurtscheller,et al.  Brain-computer interface: a new communication device for handicapped persons , 1993 .

[13]  J. Wolpaw,et al.  Multichannel EEG-based brain-computer communication. , 1994, Electroencephalography and clinical neurophysiology.

[14]  Dennis J. McFarland,et al.  Design and operation of an EEG-based brain-computer interface with digital signal processing technology , 1997 .

[15]  G. Pfurtscheller,et al.  EEG-Based Communication: Evaluation of Alternative Signal Prediction Methods - EEG-basierte Kommunikation: Evaluierung alternativer Methoden zur Signalprädiktion , 1997, Biomedizinische Technik. Biomedical engineering.

[16]  E. Bullmore,et al.  Society for Neuroscience Abstracts , 1997 .

[17]  J R Wolpaw,et al.  Spatial filter selection for EEG-based communication. , 1997, Electroencephalography and clinical neurophysiology.

[18]  J. Cohen,et al.  On the number of trials needed for P300. , 1997, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[19]  N. Birbaumer,et al.  Self-regulation of slow cortical potentials in completely paralyzed human patients , 1998, Neuroscience Letters.

[20]  G Pfurtscheller,et al.  Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[21]  F. L. D. Silva,et al.  Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.

[22]  R. Knight,et al.  Neural origins of the P300. , 2000, Critical reviews in neurobiology.

[23]  Margot J. Taylor,et al.  Guidelines for using human event-related potentials to study cognition: recording standards and publication criteria. , 2000, Psychophysiology.

[24]  H. Flor,et al.  The thought translation device (TTD) for completely paralyzed patients. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[25]  E Donchin,et al.  Brain-computer interface technology: a review of the first international meeting. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[26]  E Donchin,et al.  The mental prosthesis: assessing the speed of a P300-based brain-computer interface. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[27]  Helge J. Ritter,et al.  Improving Transfer Rates in Brain Computer Interfacing: A Case Study , 2002, NIPS.

[28]  G. Pfurtscheller,et al.  Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.

[29]  N. Birbaumer,et al.  The thought-translation device (TTD): neurobehavioral mechanisms and clinical outcome , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[30]  K.-R. Muller,et al.  Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[31]  K.-R. Muller,et al.  Linear and nonlinear methods for brain-computer interfaces , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[32]  D. McFarland,et al.  Spectral dynamics of electroencephalographic activity during auditory information processing , 2003, Hearing Research.

[33]  J. Wolpaw,et al.  EMG contamination of EEG: spectral and topographical characteristics , 2003, Clinical Neurophysiology.

[34]  W. A. Sarnacki,et al.  Brain–computer interface (BCI) operation: optimizing information transfer rates , 2003, Biological Psychology.

[35]  C.W. Anderson,et al.  Comparison of linear, nonlinear, and feature selection methods for EEG signal classification , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[36]  Koby Crammer,et al.  A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities , 2004, NIPS.

[37]  Christa Neuper,et al.  An asynchronously controlled EEG-based virtual keyboard: improvement of the spelling rate , 2004, IEEE Transactions on Biomedical Engineering.

[38]  Helge J. Ritter,et al.  BCI competition 2003-data set IIb: support vector machines for the P300 speller paradigm , 2004, IEEE Transactions on Biomedical Engineering.

[39]  N. Birbaumer,et al.  BCI2000: a general-purpose brain-computer interface (BCI) system , 2004, IEEE Transactions on Biomedical Engineering.

[40]  Jonathan R Wolpaw,et al.  Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[41]  Colin Fyfe,et al.  A canonical correlation neural network for multicollinearity and functional data , 2004, Neural Networks.

[42]  D. Mackinnon,et al.  Equivalence of the Mediation, Confounding and Suppression Effect , 2000, Prevention Science.

[43]  G. Pfurtscheller,et al.  Conversion of EEG activity into cursor movement by a brain-computer interface (BCI) , 2004, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[44]  D.J. McFarland,et al.  Sensorimotor rhythm-based brain-computer interface (BCI): feature selection by regression improves performance , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[45]  Nilli Lavie,et al.  Look here but ignore what you see: effects of distractors at fixation. , 2005, Journal of experimental psychology. Human perception and performance.

[46]  Dennis J. McFarland,et al.  Brain-computer interface (BCI) operation: signal and noise during early training sessions , 2005, Clinical Neurophysiology.

[47]  Wolfgang Skrandies,et al.  Brain mapping of visual evoked activity--topographical and functional components. , 2005, Acta neurologica Taiwanica.

[48]  J. Wolpaw,et al.  Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface , 2005, Neurology.

[49]  Lynn Friedman,et al.  Graphical Views of Suppression and Multicollinearity in Multiple Linear Regression , 2005 .

[50]  E. Donchin,et al.  A P300-based brain–computer interface: Initial tests by ALS patients , 2006, Clinical Neurophysiology.

[51]  D.J. McFarland,et al.  The wadsworth BCI research and development program: at home with BCI , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[52]  J. Wolpaw,et al.  A P300 event-related potential brain–computer interface (BCI): The effects of matrix size and inter stimulus interval on performance , 2006, Biological Psychology.

[53]  Klaus-Robert Müller,et al.  The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States , 2006, J. Univers. Comput. Sci..

[54]  F. Piccione,et al.  P300-based brain computer interface: Reliability and performance in healthy and paralysed participants , 2006, Clinical Neurophysiology.

[55]  K.-R. Muller,et al.  BCI meeting 2005-workshop on BCI signal processing: feature extraction and translation , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[56]  Dean J Krusienski,et al.  Brain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms. , 2006, Progress in brain research.

[57]  José del R. Millán,et al.  Probabilistically Modeling and Decoding Neural Population Activity in Motor Cortex , 2007 .

[58]  José del R. Millán,et al.  Advances in Cognitive Neural Prosthesis: Recognition of Neural Data with an Information-Theoretic Objective , 2007 .

[59]  Klaus-Robert Müller,et al.  The Berlin Brain-Computer Interface , 2008, WCCI.