BCI Papers

New papers

• Brain–Computer Interface Design for Asynchronous Control Applications: Improvements to the LF-ASD Asynchronous Brain Switch
  Jaimie F. Borisoff, Steve G. Mason, Ali Bashashati, and Gary E. Birch,
  IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 51, NO. 6, JUNE 2004 pp.985-992
  http://ieeexplore.ieee.org/iel5/10/28897/01300793.pdf
    

• ACNS (2006). Guidelines for standard electrode position nomenclature. American Clinical
  Neurophysiology Society. http://www.acns.org/pdfs/ACFDD46.pdf.
  Birbaumer, N. (2006). Brain-computer-interface research: Coming of age. Clinical Neurophysiology, 117:479–83.
    

• Birbaumer, N., Kubler, A., Ghanayim, N., Hinterberger, T., Perelmouter, J., Kaiser, J.,
  Iversen, I., Kotchoubey, B., Neumann, N., and Flor, H. (2000).
  The thought translation device (ttd) for completely paralyzed patients. IEEE Trans Rehabil Eng, 8(2):190–3.
  1063-6528 (Print) Journal Article.
    

• Neural Networks for Pattern Recognition
  Bishop, C.M. (1995).
  Oxford University Press.
    

• The berlin brain-computer interface: Eeg-based communication without subject training.
  Blankertz, B., Dornhege, G., Krauledat, M., Müller, K.-R., Kunzmann, V., Losch, F., and Curio, G. (2006).
  IEEE Transactions on neural system and rehabilitation engineering, 14(2):147–52.
    

• Brown, L. M., Brewster, S. A., and Purchase, H. C. (2005). A first investigation into the
  effectiveness of tactons. Proceedings of the First Joint Eurohaptics Conference and
  Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
  (WHC’05), pages 167–76.
   

• Burde, W. and Blankertz, B. (2006). Is the locus of control of reinforcement a predictor
  of brain-computer interface performance. Proceedings of the 3rd international braincomputer
  inferface workshop and training course 2006, pages 76–7.
   

• Cabeza, R. and Nyberg, L. (2000). Imaging cognition ii: An empirical review of 275 pet
  and fmri studies. Cognitive Neuroscience, 12(1):1–47.
  
  Cincotti, F., Bianci, L., Birch, G., Guger, C., Mellinger, J., Scherer, R., Schmidt, R. N.,
  Suárez, O. Y., and Schalk, G. (2006). Bci meeting 2005—workshop on technology:
  63 Hardware and software. IEEE Transactions on neural system and rehabilitation engineering,
  14(2):128–31.
  
  Curran, E. and Stokes, M. (2003). Learning to control brain activity: A review of the
  production and control of eeg components for driving brain-computer interface (bci)
  systems. Brain and Cognition, 51:326–36.
  
  David, O., Kiebel, S. J., Harrison, L. M., Mattout, J., Kilner, J. M., and Friston, K. J.
  (2006). Dynamic causal modeling of evoked responses in eeg and meg. Neuroimage,
  30:1255–72.
  
  Decety, J. (1996). The neurophysiological basis of motor imagery. Behavioural Brain
  Reseach, 77:45–52.
  
  Egner, T. and Gruzelier, J. (2004). Eeg biofeedback of low beta band components:
  frequency-specific effects on variables of attention and event-related brain potentials.
  Clinical Neurophysiology, 115:131–9.
  
  Farwell, L. and Donchin, E. (1988). Talking off the top of your head: toward a mental
  prosthesis utilizing event-related brain potentials. Electroencephalography and clinical
  Neurophysiology, 70:510–23.
  
  Gazzaniga, M. S., Ivry, R. B., and Mangun, G. R. (2002). Cognitive Neuroscience. W.W.
  Norton & Company.
  Glaser, R. and Bassok, M. (1989). Learning theory and the study of instruction. Annual
  reviews of psychology, 40:631–66.
  
  Reversible jump markov chain monte carlo computation and bayesian model determination
  Green, P. J. (1995).
  Biometrika, 82(4):711–32.
  
  Guger, C., Edlinger, G., Harkam, W., Niedermayer, I., and Pfurtscheller, G. (2003). How
  many people are able to operate an eeg-based brain-computer interface (bci)? IEEE
  Trans Neural Syst Rehabil Eng, 11(2):145–7. 1534-4320 Clinical Trial Journal Article
  Validation Studies.
  
  Hikosaka, O., Nakamura, K., Sakai, K., and Nakahara, H. (2002). Central mechanisms of
  motor skill learning. Current opinion in neurobiology, 12:217–22.
  
  Hinterberger, T., Neumann, N., Pham, M., Kübler, A., Grether, A., Hofmayer, N., Wilhelm,
  B., Flor, H., and Birbaumer, N. (2004). A multimodal brain-based feedback and
  communication system. Experimental Brain Research, 154:521–26.
  64
  
  Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand, J. A., Saleh, M., Caplan,
  A. H., Branner, A., Chen, D., Penn, R. D., and Donoghue, J. P. (2006). Neuronal
  ensemble control of prosthetic devices by a human with tetraplegia. Nature Articles,
  442(13):164–71.
  
  Hämäläinen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J., and Lounasmaa, O. V. (1993).
  Magnetoencephalography—theory, instrumentation, and applications to noninvasive
  studies of the working human brain. Reviews of Modern Physics, 65(2):413–97.
  
  Jacko, J., Emery, V. K., Edwards, P. J., Ashok,M., Barnard, L., Kongnakorn, T.,Moloney,
  K. P., and Sainfort, F. (2004). The effects of multimodal feedback on older adults’ task
  performance given varying levels of computer experience. Behaviour & Information
  Technology, 23(4):247–64.
  
  Jeannerod, M. and Frak, V. (1999). Mental imaging of motor activity in humans. Current
  Opinion in Neurobiology, 9(6):735–39.
  
  Jylänki, P., Menendez, R., Cincotti, F., Kauhanen, L., and Vehtari, A. (2006). A bayesian
  approach to select linearly separable spectral feature combinations. Proceedings of the
  "Challenging Brain Computer Interfaces: Neural Engineering Meets Clinical Needs
  in Neurorehabilitation" - MAIA Workshop, November 9-10, Fondazione Santa Lucia,
  Rome, Italy, page 18.
    

• Kaminski, M., Ding, M., Truccolo, W., and Bressler, S. (2001). Evaluating causal relations
  in neural systems: granger causality, directed transfer function and statistical
  assessment of significance. Biological cybernetics, 85:145–57.
    

• Kauhanen, L., Palomäki, T., Jylänki, P., Aloise, F., Nuttin,M., and Millan Jdel, R. (2006).
  Haptic feedback compared with visual feedback for bci. Proceedings of the 3rd international
  brain-computer interface workshop and training course 2006, pages 66–7.
    

• Kubler, A., Kotchoubey, B., Kaiser, J., Wolpaw, J. R., and Birbaumer, N. (2001). Braincomputer
  communication: unlocking the locked in. Psychol Bull, 127(3):358–75.
  0033-2909 (Print) Journal Article Review.
    

• Kübler, A., Mushahwar, V., Hochberg, L., and Donoghue, J. (2006). Bci meeting 2005—
  workshop on clinical issues and applications. IEEE Transactions on neural system and
  rehabilitation engineering, 14(2):131–4.
    

• Lemm, S., Blankertz, B., Curio, G., and Muller, K. R. (2005). Spatio-spectral filters for
  improving the classification of single trial eeg.
  IEEE Trans Biomed Eng, 52(9):1541–8, 0018-9294 (Print) Clinical Trial Journal Article.
   

• Motor imagery
  Lotze, M. and Halsband, U. (2006).
  Journal of Physiology - Paris, 99:386–95.
    

• Evaluation the performance of self-paced braincomputer interface technology, revision 1.0 (draft)
  Mason, S., Kronegg, J., Huggins, J., Fatourechi, M., and Schlögl, A. (2006).
  http://www.bciinfo.tugraz.at/Research_Info/documents/articles/self_paced_tech_report-2006-05-19.pdf.
   

• Real-time control of a video game with a direct brain-computer interface.
  Mason, S. G., Bohringer, R., Borisoff, J. F., and Birch, G. E. (2004).
  Journal of Clinical Neurophysiology, 21(6):404–8.
    

• McCullagh, P. and Nelder, J. A. (1989). Generalized Linear Models, volume 37 of Monographs on Statistics and Applied Probability. Chapman & Hall, second edition.
    

• McFarland, D. J., Anderson, C. W., Müller, K.-R., Schlögl, A., and Krusienski, D. J. (2006)
  Bci meeting 2005—workshop on bci signal processing: Feature extraction and translation.
  IEEE Transactions on neural system and rehabilitation engineering, 14(2):135–8.
    

• McFarland, D. J., McCane, L. M., and Wolpaw, J. R. (1998). Eeg-based communication
  and control: short-term role of feedback. IEEE transactions on rehabilitation engineering,
  6(1):7–11.
    

• Asynchronous bci and local neural classifiers: an overview of the adaptive brain interface project
  Millan Jdel, R. and Mourino, J. (2003).
  IEEE Trans Neural Syst Rehabil Eng, 11(2):159–61. 1534-4320
    

• Noninvasive brainactuated control of a mobile robot by human eeg.
  Millan Jdel, R., Renkens, F., Mourino, J., and Gerstner, W. (2004).
  IEEE Trans Biomed Eng, 51(6):1026–33. 0018-9294
    

• Designing optimal spatial filters for single-trial eeg classification in a movement task.
  Müller-Gerking, J., Pfurtscheller, G., and Flyvbjerg, H. (1999).
  Clinical Neurophysiology, 110:787–98.
    

• Bayesian Learning for Neural Networks.
  Neal, R. M. (1996).
  Springer.
    

• Slice sampling.
  Neal, R. M. (2003).
  The Annals of Statistics, 31(3):705–67.
    

• Neuper, C., Scherer, R., Reiner, M., and Pfurscheller, G. (2005).
  Imagery of motor actions: Differential effects of kinesthetic and visual-motor mode of imagery in singletrial eeg.
  Cognitive Brain Research, 25:668–77.
    

• Niedermeyer, E. and Lopes da Silva, F. H. (1999). Electroencephalography: Basic Principles,
  Clinical Applications, and Related Fields. LippincottWilliams & Wilkins, (fourth edition).
    

• Shared autonomy for wheel chair control: attempts to assess the user’s autonomy.
  Nuttin,M., Demeester, E., Vanhooydonck, D., and Van Brussel, H. (2001).
  Autonome Mobile Systeme, 17:127–33.
    

• Hidden markov models for online classification of single trial eeg data.
  Obermaier, B., Guger, C., Neuper, C., and Pfurtscheller, G. (2001).
  Pattern Recognition Letters, 22(12):1299–309.
    

• Dynamic models for nonstationary signal segmentation.
  Penny, W. D. and Roberts, S. J. (1999).
  Computers and biomedical research, 32(6):483–502.
    

• Event-related synchronization (ers): an electrophysiological correlate of cortical areas at rest.
  Pfurtscheller, G. (1992).
  Electroencephalography and Clinical Neurophysiology, 83(1):62–9.
    

• Pfurtscheller, G., Guger, C., Muller, G., Krausz, G., and Neuper, C. (2000). Brain oscillations
  control hand orthosis in a tetraplegic. Neurosci Lett, 292(3):211–4. 0304-3940
    

• Eeg-based asynchronous bci controls functional electrical stimulation in a tetraplegic patient.
  Pfurtscheller, G., Müller-Putz, G. R., Pfurtscheller, J., and Rupp, R. (2005).
  Applied Signal Processing, 2005(19):3152–55.
    

• Motor imagery and direct brain-computer communication.
  Pfurtscheller, G. and Neuper, C. (2001).
  Proceedings of the IEEE, 89(7):1123–33.
    

• Graz-bci: state of the art and clinical applications.
  Pfurtscheller, G., Neuper, C., Muller, G. R., Obermaier, B., Krausz, G., Schlogl, A., Scherer, R., Graimann, B., Keinrath, C., Skliris, D., Wortz, M., Supp, G., and Schrank, C. (2003).
  IEEE Trans Neural Syst Rehabil Eng, 11(2):177–80. 1534-4320
   

• An auditory brain-computer interface based on the self-regulation of slow cortical potentials.
  Pham, M., Hinterberger, T., Neumann, N., Kübler, A., Hofmayer, N., Grether, A., Wilhelm, B., Vatine, J., and Birbaumer, N. (2005).
  Neurorehabilitation and Neural Repair, 19(3):206–18.
   

• Gaussian Processes for Machine Learning.
  Rasmussen, C. E. and Williams, C. K. I. (2006).
  MIT Press.
   

• Real-time brain-computer interfacing: a preliminary study using bayesian learning.
  Roberts, S. and Penny, W. (2000).
  Medical & Biological Engineering and Computing, 38:56–61.
   

• Supporting presence in collaborative environments by haptic force feedback.
  Sallnäs, E.-L., Rassmus-Gröhn, K., and Sjöström, C. (2000).
  ACM transactions on computerhuman interaction, 7(4):461–76.
   

• Plasticity and primary motor cortex.
  Sanes, J. and Donoghue, J. (2002).
  Annual Reviews of Neuroscience, 23:393–415.
   

• Santhanam, G., Ryu, S. I., Yu, B. M., Afshar, A., and Shenoy, K. V. (2006). A highperformance
  brain-computer interface. Nature Letters, 442(13):195–8.
   

• Bci2000: a general-purpose brain-computer interface (bci) system.
  Schalk, G., McFarland, D. J., Hinterberger, T., Birbaumer, N., and Wolpaw, J. R. (2004).
  IEEE Trans Biomed Eng, 51(6):1034–43. 0018-9294
    

• Measuring information transfer.
  Schreiber, T. (2000).
  Physical review letters, 85(2):461–64.
   

• Stinear, C.M., Byblow,W. D., Steyvers,M., Levin, O., and Swinnen, S. P. (2006). Kinesthetic,
  but not visual, motor imagery modulates corticomotor excitability. Experimental
  Brain Research, 168:157–64.
    

• Sykacek, P., Roberts, S. J., and Stokes, M. (2004). Adaptive bci based on variational
  bayesian kalman filtering: an empirical evaluation. IEEE Trans Biomed Eng,
  51(5):719–27. 0018-9294 (Print) Evaluation Studies Journal Article Validation Studies.
  Townsend, G., Graimann, B., and Pfurtscheller, G. (2006). A comparison of common
  spatial patterns with complex band power features in a four-class bci experiment. IEEE
  Transactions on Biomedical Engineering, 53(4):642–51.
  Vaughan, T. M. (2006). Home use of a brain-computer interface (bci): Initial studies.
  Personal communication at the 3rd International BCI Workshop and Training Course
  2006, Graz, Austria.
  
  Real-time detection of brain events in eeg.
  Vidal, J. (1977).
  Proceedings of the IEEE, 65(5):633–41.
  
  Toward direct brain-computer communication.
  Vidal, J. J. (1973).
  Annual Review of Biophysics and Bioengineering, 2:157–80.
  
  Near infrared spectroscopy (nirs): a new tool to study hemodynamic changes during activation of brain function in human adults.
  Villringer, A., Planck, J., Hock, C., Schleinkofer, L., and Dirnagl, U. (1993).
  Neuroscience letters, 14(154):101–4.
  
  A practical VEP-based brain-computer interface.
  Wang, Y., Wang, R., Gao, X., Hong, B., and Gao, S. (2006).
  IEEE Transactions on neural system and rehabilitation engineering, 14(2):234–9.
   

• Motor processes in mental rotation.
  Wexler, M., Kosslyn, S., and Berthoz, A. (1998).
  Cognition, 68:77–94.
   

• A neuropsychological theory of motor skill learning.
  Willingham, D. (1998).
  Psychological review, 105(3):558–84.
   

• DASHER—an efficient writing system for braincomputer interfaces?
  Wills, S. A. and MacKay, D. J. (2006).
  IEEE Transactions on neural system and rehabilitation engineering, 14(2):244–6.
  http://ieeexplore.ieee.org/iel5/7333/34432/01642779.pdf?tp=&isnumber=34432&arnumber=1642779
   

• Brain-computer interfaces for communication and control.
  Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., and Vaughan, T. M. (2002).
  Clin Neurophysiol, 113(6):767–91. 1388-2457
   

• Bci meeting 2005—workshop on signals and recording methods.
  Wolpaw, J. R., Loeb, G. E., Allison, B. Z., Donchin, E., Nascimento, O. F.,
  Heetderks, W. J., Nijboer, F., Shain,W. G., and Turner, J. N. (2006).
  IEEE Transactions on neural system and rehabilitation engineering, 14(2):138–41.
   

• Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans.
  Wolpaw, J. R. and McFarland, D. J. (2004).
  Proc Natl Acad Sci USA, 101(51):17849–54. 0027-8424
   

• SINGLE-TRIAL EEG CLASSIFICATION FOR BRAIN-COMPUTER INTERFACE USING WAVELET DECOMPOSITION
   Anysia Yong and Neil Hurley
   

• Comparison of Linear and Nonlinear Methods for EEG Signal Classification.
  Garrett, D., Peterson, D.A., Anderson, C.W., Thaut, M.H. (2003)
  IEEE Transactions on Neural Systems and Rehabilitative Engineering, vol. 11, no. 2, pp. 141--144.
   

• Linear and Non-linear Methods in Brain-Computer Interfaces
  Muller, K.-R., Anderson, C., and Birch, G. (2003)
  IEEE Transactions on Neural Systems and Rehabilitative Engineering, vol. 11, no. 2, pp. 162--165.
  http://www.cs.cmu.edu/~tanja/BCI/LinAndNonlin2003.pdf
   

• EEG Subspace Representations and Feature Selection for Brain-Computer Interfaces
  Anderson, C.W., and Kirby, M. (2003)
  http://www.cs.colostate.edu/eeg/publications/cvpr03.ps
  Proceedings of the 1st IEEE Workshop on Computer Vision and Pattern Recognition for
  Human Computer Interaction (CVPRHCI), June 17, 2003, Madison, Wisconsin.
   

• A Data Analysis Competition to Evaluate Machine Learning Algorithms for Use in Brain-Computer Interfaces
  Paul Sajda, Adam Gerson, Klaus-Robert Müller, Benjamin Blankertz, and Lucas Parra
  http://newton.bme.columbia.edu/publications/sajdaTNSRE03.pdf 
   

• Multidimensional EMG-Based Assessment of Walking Dynamics 
  Ben H. Jansen, Senior Member, IEEE, Vonda H. Miller, Demetrios C. Mavrofrides, and Caroline W. Stegink Jansen 
  IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING , VOL. 11, NO. 3, SEPTEMBER 2003 p294
  http://www.udel.edu/PT/rudolph/Jansen2003.pdf 
   
• A Simulation Study of Reflex Instability in Spasticity: Origins of Clonus 
  Joseph M. Hidler and W. Zev Rymer
  IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, VOL. 7, NO. 3, SEPTEMBER 1999 p327 
  http://engineering.cua.edu/biomedical/faculty/hidler/Clonus.pdf  
   
• Human Hand Modeling, Analysis and Animation in the Context of HCI
  Ying Wu, Thomas S. Huang
  In Proc. IEEE Int'l Conf. on Image Processing (ICIP'99), Japan, Oct., 1999 . [PS, PDF] 
   
• An improvement of a time-frequency approach for an EEG-based brain-computer interface
  Nobuyuki Yamawaki, C Wilke, ZM Liu and B He
  Int. J of Bioelectromagnetism, accepted for publication, 2005.
   
• Enhancement of performance of an EEG-based brain-computer interface by means of a time-frequency approach
  Nobuyuki Yamawaki, Wilke C, Liu ZM and He B
  Proceedings of the 2 nd International IEEE EMBS Conference on Neural Engineering (CD-ROM), March, 2005
   

• Extracting Features for a Brain-Computer Interface by Self-Organising Fuzzy Neural Network-based Time Series Prediction 
  Damien Coyle, Girijesh Prasad and Thomas M. McGinnity
  Proceedings of the 26th Annual International Conference of the IEEE EMBS San Francisco, CA, USA • September 1-5, 2004 
  http://www.gtec.at/biosignal/MovementImagination/BCI_EMB04_Colye.pdf 
   

• Conversion of EEG Activity Into Cursor Movement by a Brain–Computer Interface (BCI)
  Georg E. Fabiani, Dennis J. McFarland, Jonathan R. Wolpaw, and Gert Pfurtscheller
  IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING,
  VOL. 12, NO. 3, SEPTEMBER 2004 pages.331
  http://www.rpi.edu/~bennek/class/mmld/papers/BCIIEEETRAN.pdf  
   

• Semester Project Design of a brain-actuated device for human-computer interaction
  Abel Villca Roque
  Swiss Federal Institute of Technology
  http://bci.epfl.ch/publications/villca_bcireport.pdf
   

• Brain-computer interface using fMRI: spatial navigation by thoughts  
  Seung-Schik Yoo, Ty Fairneny, Nan-Kuei Chen, Seh-Eun Choo, Lawrence P. Panych, HyunWook Park, Soo-Young Lee and Ferenc A. Jolesz
  http://www.brain.hr/Mind&Brain4/ADDITIONAL_SELECTED_ARTICLES/GOEBEL_pdfs/BCIFMRIP.PDF  
    

• Principles of a Brain-Computer Interface (BCI) Based on Real-Time Functional Magnetic Resonance Imaging (fMRI)
  Nikolaus Weiskopf, Klaus Mathiak, Simon W. Bock, Frank Scharnowski, Ralf Veit, Wolfgang Grodd, Rainer Goebel, and Niels Birbaumer 
  IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 51, NO. 6, JUNE 2004 p. 966
  http://njc.berkeley.edu/Papers/Weiskopf_BCI.pdf  
   

•  
  http://www.dpmi.tu-graz.ac.at/~schloegl/matlab/eeg/gdf4/TR_GDF.pdf  
   

•  
  http://njc.berkeley.edu/Papers/Weiskopf_BCI.pdf  
    

• Computer Game Control through Relaxation-Induced EEG Changes  
  Lucas Tschuor (Prof: Touradj Ebrahimi) 4.2.2002
  Signal Processing Institute
  http://bci.epfl.ch/publications/rapport_lucastschuor.pdf  
     

• Toward Direct Brain-Computer Musical Interfaces
  Eduardo Miranda and Andrew Brouse
  2005 International Conference on New Interfaces for Musical Expression - 
  http://cmr.soc.plymouth.ac.uk/publications/NIME05-BrouseMiranda.pdf  
   

• Publications of the BCI-Lab 
  http://www.dpmi.tu-graz.ac.at/publications.htm
   

• Graz-BCI: State of the Art and Clinical Applications Interesting paper
  http://newton.bme.columbia.edu/liinc_pubs.htm  
    

• “Virtual Keyboard” Controlled by Spontaneous EEG Activity 
  B. Obermaier, G. R. Müller and G. Pfurtscheller,  
  IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING , VOL. 11, NO. 4, DECEMBER 2003 http://www.cs.umass.edu/~bernier/IEEE%20Neur%20Sys%20Rehab%20Eng%202003%2011(4)%20PFURT.pdf  
   

• Linear Classification of Low-Resolution EEG Patterns Produced by Imagined Hand Movements 
  F. Babiloni, F. Cincotti, L. Lazzarini, J. Millán, J. Mouriño, M. Varsta, J. Heikkonen, L. Bianchi, and M. G. Marciani 
  IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, VOL. 8, NO. 2, JUNE 200
  http://www.ocf.berkeley.edu/~anandk/neuro/reading%20imagined%20hand%20movements%20with%20EEG.pdf  
   

• Behavioral & Brain Sciences Index of Target Articles 1993 — year-end-2000 
  http://bbsonline.cup.cam.ac.uk/Preprints/OldArchive/ 
   
• Papers on BCI and misc.
  http://www.idiap.ch/index.php?content=PublicationsList&IncFile=PageType&UrlTemplateType=13&#Journals 
   

• GOOD Journals 
  http://www.idiap.ch/index.php?content=PublicationsList&IncFile=PageType&UrlTemplateType=13&#Journals 
   

• Improving speed and accuracy of brain-computer interfaces using readiness potential features.
  Matthias Krauledat, Guido Dornhege, Benjamin Blankertz, Florian Losch, Gabriel Curio, and Klaus-Robert Mueller.
  Proceedings of the 26th Annual International Conference IEEE EMBS on Biomedicine, San Francisco, 2004
   

• Scale degree profiles from audio investigated with machine learning techniques
  Hendrik Purwins, Benjamin Blankertz, Guido Dornhege, and Klaus Obermayer
  Audio Engeneering Society 116th Convention, Berlin, 2004
   

Papers

• On the Possibility of Developing a Brain-Computer Interface (BCI)
  Torsten Felzer (Technical University of Darmstadt, Germany)
  Technical Report (finished in 2001)
  http://www.st.informatik.tu-darmstadt.de:8080/felzer/eeg.pdf 
   
  On the Need for On-Line Learning in Brain-Computer Interfaces (2004)
  J. del R. Milla¡n
  in "Proceedings of the International Joint Conference on Neural Networks", 2004. 
   
• HMM and IOHMM Modeling of EEG Rhythms for Asynchronous BCI Systems (2004)
  Silvia Chiappa and Samy Bengio
  in "European Symposium on Artificial Neural Networks ESANN", 2004 
  http://www.idiap.ch/~bengio/cv/publications/pdf/chiappa_2004_esann.pdf
   
• Enhancing Brain-Computer Interfaces by Machine Learning Techniques
  http://research.microsoft.com/workshops/MLUI03/blankertz_bbci_print.pdf 
   
• Virtual Keyboard 
  http://www.cis.gsu.edu/brainlab/papers/obermaier-muller-pfurt03-virtual%20keyboard.pdf 
    
• Oxford, UK
  http://www.robots.ox.ac.uk/~parg/publications.html 
   
• P. Sykacek, S. Roberts and M. Stokes (2002)
  Adaptive BCI based on variational Bayes: an empirical evaluation. Albany BCI workshop, June 2002 (BEST TECHNICAL PAPER
  AWARD). 
   
• A Local Neural Classifier for the Recognition of EEG Patterns Associated to Mental Tasks (2002)
  José del R. Millán, Josep Mouriño, Student Member, IEEE, Marco Franzé, Febo Cincotti, Markus, Varsta, Jukka Heikkonen, and Fabio Babiloni
  IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 13, NO. 3, MAY 2002 page 678
   
• Machine Learning Approaches For Brain-Computer Interfacing (2002)
  L. C. Pickup & S. J. Roberts 
  Undergraduate Final Year Project. Technical Report PARG-02-01, May 2002. 
   
• Cognitive Tasks for driving a Brain Computer Interfacing System: a pilot study (2001)
  E. Curran, P. Sykacek, M. Stokes, S. Roberts, W. Penny, I. Johnsrude, A. Owen 
  Technical Report PARG-01-07, March 2001. 
   
• On the Possibility of Developing a Brain-Computer Interface (BCI) (2001)
  OFelzer, T. Technical Report ( 27 pages) Short version of large parts of dissertation
  http://www.st.informatik.tu-darmstadt.de:8080/felzer/eeg.pdf 
   
• EEG-based communication: a pattern recognition approach (2000)
  W. Penny, S. Roberts, E. Curran & M. Stokes 
  IEEE Transactions on Rehabilitation Engineering 8(2), 214-216. 
   
• Independent Components Analysis (2000)
  Richard Everson & S. Roberts
  Technical report TR-99-8. May 1999. Draft of chapter in Artificial Neural Networks in Biomedicine, Lisboa, Ifeachor, Szczepaniak (Eds), Springer. Perspectives in Neural Computing. 
   
• EEG-based communication: a pattern recognition approach (1999)
  W. Penny, S. Roberts & M. Stokes
  Technical report TR-99-6. May 1999. 
   
• EEG-based communication via dynamic neural network models (1999)
  W. Penny & S. Roberts 
  Technical report TR-99-5. May 1999. Proceedings of International Joint Conference on Neural Networks. IJCNN-99. 
   
• Temporal and Spatial Complexity measures for EEG-based Brain-Computer Interfacing (1998)
  S.J. Roberts, W. Penny & I.Rezek 
  (draft 3.6 January 1998, revised version 4.3 March 1998): Medical & Biological Engineering & Computing, 37(1), 93-99. 
   
• Bayesian neural networks for detection of imagined finger movements from single-trial EEG (1997)
  Will Penny & Steve Roberts 
  Research report TR-97-2, May 1997 
   
• M. Krkic, S. J. Roberts, I. Rezek & C. Jordan
  S. J. Roberts 
  Proceedings of IEE colloquium on AI methods in biosignal analysis, April 1996, 1996/100 : 4/1-4/6. 
   
• EEG-based Assessment of Anaesthetic Depth using Neural Networks (1996)
  M. Krkic, S. J. Roberts, I. Rezek & C. Jordan
  Proceedings of IEE colloquium on AI methods in biosignal analysis, April 1996, 1996/100 : 10/1-10/6. 
   
• Parametric Models and Spectral analysis for Classification in Brain-Computer Interfaces (2002)
  S Kelly, D Burke, P de Chazal, R Reilly
  Proceedings of 14th International Conference on Digital Signal Processing, Greece, July 2002 
   http://ee.ucd.ie/~simon/DSP2002.pdf 
   
• Time-Frequency-Space Kernel for Single EEG-Trial Classification (2002)
  Gary Garcia Molina and Touradj Ebrahimi
  Nordic Signal Processing Symposium (NORSIG) 2002
  http://www.norsig.no/norsig2002/Proceedings/papers/cr1112.pdf 
   
• EEG-BASED BRAIN COMPUTER INTERFACE CONTROL IN AN IMMERSIVE  3-D GAMING ENVIRONMENT
  http://ee.ucd.ie/~rreilly/elevation/KellyIEI.pdf 
   
• Asynchronous BCI and Local Neural Classifiers: An Overview of the Adaptive Brain Interface Project
  http://ee.ucd.ie/~ray/thesis/UCD-MLE.pdf 
   
• Cognitive tasks for driving a Brain Computer Interfacing System: a pilot study (2004)
  E. Curran, P. Sykacek, S. Roberts, W. Penny, M. Stokes, I. Jonsrude & A. Owen
  IEEE Transactions on Rehabilitation Engineering, 12 (1): 48-5.
   
• Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation (2004)
  P. Sykacek, S. Roberts & M. Stokes 
  IEEE Transactions on Biomedical Engineering. 51(5). 719-729.
  http://www.robots.ox.ac.uk/~sjrob/Pubs/vkf_bci_tbme.ps.gz 
   
• Probabilistic Methods in BCI Research (2003)
  P. Sykacek, S. Roberts, M. Stokes, E. Curran, M. Gibbs, and L. Pickup
  IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL. 11, NO. 2, JUNE 2003
  http://www.robots.ox.ac.uk/~parg/pubs/bci2003.pdf 
   

• A Signal Processing Platform for Brain-Computer Interface Optimization (2004)
  Thomas M. Tirpak, Marcin Kadluczka, Peter C. Nelson, Weimin Xiao
  submitted to IEEE Transactions on Neural Systems & Rehabilitation Engineering, 2004
  http://www.cs.uic.edu/~mkadlucz/BCI_SPOP.PDF 
   

• BCI competition 2003 -- data set IIa: Spatial patterns of self-controlled brain rhythm modulations (2004)
  Gilles Blanchard and Benjamin Blankertz
  IEEE Trans. Biomed. Eng., 51(6):1062-1066, 2004.
  http://ida.first.fhg.de/publications/BlaBla04.pdf 
   

• The BCI competition 2003: Progress and perspectives in detection and discrimination of EEG single trials (2004)
  Benjamin Blankertz, Klaus-Robert Müller, Gabriel Curio, Theresa M. Vaughan, Gerwin Schalk, Jonathan R. Wolpaw, Alois Schlögl, Christa Neuper, Gert Pfurtscheller, Thilo Hinterberger, Michael Schröder, and Niels Birbaumer. 
  IEEE Trans. Biomed. Eng., 51(6):1044-1051, 2004.
  http://ida.first.fhg.de/publications/BlaMueCurVauSchWolSchNeuPfuHinSchBir04.pdf 
   

• Use of the Evoked Potential P3 Component for Control in a Virtual Apartment (2003)
  Jessica D. Bayliss
  IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, VOL. 11, NO. 2, JUNE 2003
  http://lobster.ls.huji.ac.il/jclub/Topics_and_References/Neuroprostheses/Bayliss-Use_evoked_potential_P3_control_virtual_apartment.pdf 
   

• Linear and non-linear methods for brain-computer interfaces (2003)
  Klaus-Robert Müller, Charles W. Anderson, and Gary E. Birch
  IEEE Trans. Neural Sys. Rehab. Eng., 11(2), 2003. 165-169
  http://ida.first.fhg.de/publications/MueAndBir03.pdf 
   

• The Berlin Brain-Computer Interface (BBCI) towards a new communication channel for online control of multimedia applications and computer games (2003)
  Roman Krepki, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller
  9th International Conference on Distributed Multimedia Systems (DMS’03)
  http://ida.first.fhg.de/publications/KreBlaCurMue03.pdf 
   

• A Local Neural Classifier for the Recognition of EEG Patterns Associated to Mental Tasks (2002)
  José del R. Millán, Josep Mouriño, Marco Franzé, Febo Cincotti, Markus Varsta, Jukka Heikkonen, and Fabio Babiloni
  IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 13, NO. 3, MAY 2002 page 678
  http://ieeexplore.ieee.org/iel5/72/21590/01000132.pdf 
   

• Brain–Computer Interface Technology: A Review of the First International Meeting (2000)
  Jonathan R.Wolpaw (Guest Editor), Niels Birbaumer,William J. Heetderks, Dennis J. McFarland, P. Hunter Peckham, Gerwin Schalk, Emanuel Donchin, Louis A. Quatrano, Charles J. Robinson, and Theresa M. Vaughan (Guest Editor) 
  IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, VOL. 8, NO. 2, JUNE 2000 
  http://www.ocf.berkeley.edu/~anandk/neuro/BCI%20Overview.pdf 
   

• Math Models for Learning and Discovery
  http://www.rpi.edu/~kunapg/mmld/  
   

 Interesting conferences on the topic