Skip to main content Accessibility help
×
  • Cited by 153
Publisher:
Cambridge University Press
Online publication date:
October 2013
Print publication year:
2013
Online ISBN:
9781139032803

Book description

The idea of interfacing minds with machines has long captured the human imagination. Recent advances in neuroscience and engineering are making this a reality, opening the door to restoration and augmentation of human physical and mental capabilities. Medical applications such as cochlear implants for the deaf and neurally controlled prosthetic limbs for the paralyzed are becoming almost commonplace. Brain-computer interfaces (BCIs) are also increasingly being used in security, lie detection, alertness monitoring, telepresence, gaming, education, art, and human augmentation. This introduction to the field is designed as a textbook for upper-level undergraduate and first-year graduate courses in neural engineering or brain-computer interfacing for students from a wide range of disciplines. It can also be used for self-study and as a reference by neuroscientists, computer scientists, engineers, and medical practitioners. Key features include questions and exercises in each chapter and a supporting website.

Reviews

‘Rajesh P. N. Rao has written the perfect introduction to the exciting world of brain-computer interfaces. The book is remarkably comprehensive – not only including full descriptions of classic and current experiments but also covering essential background concepts, from the brain to Bayes and back. Brain-Computer Interfacing will be welcomed by a wide range of intelligent readers interested in understanding the first steps toward the symbiotic merger of brains and computers.'

Eberhard E. Fetz - University of Washington

‘Brain-computer interfacing is one of the fastest growing areas of neuroengineering and Rajesh P. N. Rao has written the go-to book for anyone who wants an introduction and a clear overview of the field. The book includes questions and exercises at the end of each chapter to help students master the material and a mathematical appendix to make the technical aspects more accessible to all.'

Terrence Sejnowski - Howard Hughes Medical Institute Investigator and Francis Crick Professor at the Salk Institute for Biological Studies, California

Refine List

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
×

Contents

References
Acharya, S, Fifer, MS, Benz, HL, Crone, NE, Thakor, NV. Electrocorticographic amplitude predicts finger positions during slow grasping motions of the hand. J Neural Eng. 2010 Aug;7(4):046002.
Andersen, RA, Hwang, EJ, Mulliken, GH. Cognitive neural prosthetics. Annu Rev Psychol. 2010;61:169–90, C1–3.
Anderson, C, Sijercic, Z. Classification of EEG signals from four subjects during five mental tasks. In Solving Engineering Problems with Neural Networks: Proceedings of the Conference on Engineering Applications in Neural Networks (EANN’96), 1996, Bulsari, AB, Kallio, S, and Tsaptsinos, D (eds.), pp. 407–14.
Ayaz, H, Shewokis, PA, Bunce, S, Schultheis, M, Onaral, B. Assessment of cognitive neural correlates for a functional near infrared-based brain computer interface system. Augmented Cognition, HCII, 2009;LNAI 5638, pp. 699–708.
Babiloni, C, Carducci, F, Cincotti, F, Rossini, PM, Neuper, C, Pfurtscheller, G, Babiloni, F. Human movement-related potentials vs desynchronization of EEG alpha rhythm: a high-resolution EEG study. Neuroimage. 1999 Dec;10(6):658–65.
Barber, D. Bayesian Reasoning and Machine Learning. Cambridge University Press, 2012.
Bayliss, JD. Use of the evoked potential P3 component for control in a virtual apartment. IEEE Trans Neural Syst Rehabil Eng. 2003;11(2):113–16.
Bear, MF, Connors, BW, Paradiso, MA. Neuroscience: Exploring the Brain., 3rd ed., Lippincott Williams & Wilkins, Baltimore, MD, 2007.
Bell, AJ, Sejnowski, TJ. An information-maximization approach to blind separation and blind deconvolution. Neural Computation. 1995;7:1129–59.
Bell, CJ, Shenoy, P, Chalodhorn, R, Rao, RPN. Control of a humanoid robot by a noninvasive brain-computer interface in humans. J Neural Eng. 2008 Jun;5(2):214–20.
Bellavista, P, Corradi, A, Giannelli, C. Evaluating filtering strategies for decentralized handover prediction in the wireless internet. Proc. 11th IEEE Symposium Computers Commun., 2006.
Bensch, M, Karim, A, Mellinger, J, Hinterberger, T, Tangermann, M, Bogdan, M, Rosenstiel, W, Birbaumer, N. Nessi: an EEG controlled web browser for severely paralyzed patients. Comput. Intell. Neurosci. 2007;Article ID 71863.
Berger, H. Über das Elektroenkephalogram des Menschen. Arch. f. Psychiat. 1929;87: 527–70.
Berger, T, Hampson, R, Song, D, Goonawardena, A, Marmarelis, V, Deadwyler, S. A cortical neural prosthesis for restoring and enhancing memory. Journal of Neural Engineering. 2011; 8(4):046017.
Birbaumer, N, Cohen, LG. Brain-computer interfaces: communication and restoration of movement in paralysis. J Physiol. 2007;579(Pt 3):621–36.
Bishop, CM. Pattern Recognition and Machine Learning. Springer, New York, 2006.
Blakely, T, Miller, KJ, Rao, RPN, Holmes, MD, Ojemann, JG. Localization and classification of phonemes using high spatial resolution electrocorticography (ECoG) grids. Conf Proc IEEE Eng Med Biol Soc. 2008;4964–67.
Blakely, T, Miller, KJ, Zanos, SP, Rao, RPN, Ojemann, JG. Robust, long-term control of an electrocorticographic brain-computer interface with fixed parameters. Neurosurg Focus. 2009 Jul;27(1):E13.
Blankertz, B, Losch, F, Krauledat, M, Dornhege, G, Curio, G, Müller, KR. The Berlin brain-computer interface: accurate performance from first-session in BCI-naïve subjects. IEEE Trans Biomed Eng. 2008 Oct;55(10):2452–62.
Blankertz, B, Tangermann, M, Vidaurre, C, Fazli, S, Sannelli, C, Haufe, S, Maeder, C, Ramsey, L, Sturm, I, Curio, G, Müller, KR. The Berlin brain-computer interface: non-medical uses of BCI technology. Front Neurosci. 2010;4:198.
Blankertz, B, Tomioka, R, Lemm, S, Kawanabe, M, Müller, KR. Optimizing spatial filters for robust EEG single-trial analysis. IEEE Signal Processing Magazine. 2008;25(1):41–56.
Bles, M, Haynes, JD. Detecting concealed information using brain-imaging technology. Neurocase. 2008;14:82–92.
Blumhardt, LD, Barrett, G, Halliday, AM, Kriss, A. The asymmetrical visual evoked potential to pattern reversal in one half field and its significance for the analysis of visual field effects. Br. J. Ophthalmol. 1977;61: 454–61.
Boser, BE, Guyon, IM, Vapnik, VN. A training algorithm for optimal margin classifiers. Proceedings of the fifth annual workshop on computational learning theory, ACM, New York, 1992, 144–52.
Braitenberg, V. Vehicles: Experiments in synthetic psychology. MIT Press, Cambridge, MA, 1984.
Breiman, L. Random Forests. Machine Learning. 2001;45(1):5–32.
Brindley, GS, Lewin, WS. The sensations produced by electrical stimulation of the visual cortex. J Physiol. 1968;196(2):479–93.
Bryan, M, Nicoll, G, Thomas, V, Chung, M, Smith, JR, Rao, RPN. Automatic extraction of command hierarchies for adaptive brain-robot interfacing. Proceedings of ICRA 2012, 2012 May 5–12.
Bryan, MJ, Martin, SA, Cheung, W, Rao, RPN. Probabilistic co-adaptive brain-computer interfacing. Proceedings of Fifth International Brain-Computer Interface Meeting, Asilomar, CA, 2013 June 3–7.
Bryson, AE, Ho, YC. Applied optimal control. New York: Wiley, 1975.
Burges, CJC. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery. 1998;2:121–67.
Buttfield, A, Ferrez, PW, Millán J del, R.Towards a robust BCI: error potentials and online learning. IEEE Trans Neural Syst Rehabil Eng. 2006;14(2):164–68.
Calhoun, GL, McMillan, GR. EEG-based control for human computer interaction. Proc. Annu. Symp. Human Interaction with Complex Systems. 1996, pp. 4–9.
Chapin, JK, Moxon, KA, Markowitz, RS, Nicolelis, MA. Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex. Nat Neurosci. 1999 Jul;2(7):664–70.
Cheng, M, Gao, X, Gao, S, Xu, D. Design and implementation of a brain-computer interface with high transfer rates. IEEE Trans Biomed Eng. 2002 Oct;49(10):1181–86.
Cheung, W, Sarma, D, Scherer, R, Rao, RPN. Simultaneous brain-computer interfacing and motor control: expanding the reach of non-invasive BCIs. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:6715–8.
Chung, M, Cheung, W, Scherer, R, Rao, RPN. A hierarchical architecture for adaptive brain-computer interfacing. Proceedings of IJCAI. 2011, pp.1647–52.
Citri, A, Malenka, RC. Synaptic plasticity: multiple forms, functions, and mechanisms. Neuropsychopharmacology. 2008;33: 18–41.
Clausen, J. Man, machine and in between. Nature. 2009;457(7233): 1080–81.
Collinger, JL, Wodlinger, B, Downey, JE, Wang, W, Tyler-Kabara, EC, Weber, DJ, McMorland, AJ, Velliste, M, Boninger, ML, Schwartz, AB. High-performance neuroprosthetic control by an individual with tetraplegia. The Lancet. 2013 Feb 16;381(9866):557–64.
Cooper, R, Osselton, JW, Shaw, JC. EEG Technology, 2nd ed., London: Butterworths, 1969.
Cortes, C, Vapnik, V. Support-Vector Networks. Machine Learning. 1995;20:273–297.
Coyle, S, Ward, T, Markham, C, McDarby, G. On the suitability of near-infrared (NIR) systems for next-generation brain computer interfaces. Physiol Meas. 2004;25:815–22.
Croft, RJ, Chandler, JS, Barry, RJ, Cooper, NR, Clarke, AR. EOG correction: a comparison of four methods. Psychophysiology. 2005;42:16–24.
Dalbey, B. Brain fingerprinting testing traps serial killer in Missouri. The Fairfield Ledger. Fairfield, IA, 1999 August, p. 1.
Delgado, J. Physical Control of the Mind: Toward a Psychocivilized Society. Harper and Row, New York, 1969.
Denk, W, Strickler, JH, Webb, WW. Two-photon laser scanning fluorescence microscopy. Science. 1990;248, 73–76.
Denning, T, Matsuoka, Y, Kohno, T. Neurosecurity: security and privacy for neural devices. Neurosurg Focus. 2009;27(1):E7.
Dhillon, GS and Horch, KW. Direct neural sensory feedback and control of a prosthetic arm. IEEE Trans Neural Syst Rehabil Eng. 2005;13:468–72.
Diester, I, Kaufman, MT, Goo, W, O’Shea, DJ, Kalanithi, PS, Deisseroth, K, Shenoy, KV. Optogenetics and brain-machine interfaces. Proc. of the 33rd Annual International Conference IEEE EMBS. 2011, Boston, MA.
DiGiovanna, J, Mahmoudi, B, Fortes, J, Principe, JC, Sanchez, JC. Coadaptive brain-machine interface via reinforcement learning. IEEE Trans Biomed Eng. 2009;56(1):54–64.
Dobelle, WH. Artificial vision for the blind by connecting a television camera to the visual cortex. American Society for Artificial Internal Organs Journal. 2000;46:3–9.
Dobkin, BH. Brain-computer interface technology as a tool to augment plasticity and outcomes for neurological rehabilitation. J Physiol. 2007;579(Pt 3):637–42.
Donoghue, JP, Nurmikko, A, Black, M, Hochberg, LR. Assistive technology and robotic control using motor cortex ensemble-based neural interface systems in humans with tetraplegia. J Physiol. 2007 Mar 15;579(Pt 3):603–11.
Dornhege, G, Millán, JR, Hinterberger, T, McFarland, DJ, Müller, KR. (eds.) Towards Brain-Computer Interfacing. MIT Press, Cambridge, MA, 2007.
Duda, R, Hart, P, Stork, D. Pattern Classification (2nd ed.). Wiley Interscience, New York, 2000.
Fagg, AH, Ojakangas, GW, Miller, LE, Hatsopoulos, NG. Kinetic trajectory decoding using motor cortical ensembles. IEEE Trans Neural Syst Rehabil Eng. 2009 Oct;17(5):487–96.
Farwell, LA, Donchin, E. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr Clin Neurophysiol. 1988 Dec;70(6):510–23.
Farwell, LA, Donchin, E. The truth will out: interrogative polygraphy (“lie detection”) with event-related brain potentials. Psychophysiology. 1991;28(5):531–47.
Farwell, LA. Brain fingerprinting: a comprehensive tutorial review of detection of concealed information with event-related brain potentials. Cognitive Neurodynamics. 2012;6: 115–54.
Fatourechi, M, Bashashati, A, Ward, RK, Birch, GE. EMG and EOG artifacts in brain computer interface systems: A survey. Clin Neurophysiol. 2007 Mar;118(3):480–94.
Fetz, EE. Operant conditioning of cortical unit activity. Science. 1969 Feb 28;163(870):955–58.
Fetz, EE. Volitional control of neural activity: implications for brain-computer interfaces. J Physiol. 2007 Mar 15;579(Pt 3):571–9. Epub 2007 Jan 18.
Finke, A, Lenhardt, A, Ritter, H. The mindgame: a P300-based brain-computer interface game. Neural Networks 2009;22: 1329–33.
Fitzsimmons, NA, Lebedev, MA, Peikon, ID, Nicolelis, MA. Extracting kinematic parameters for monkey bipedal walking from cortical neuronal ensemble activity. Front Integr Neurosci. 2009;3:3.
Foerster, O. Beitrage zur pathophysiologie der sehbahn und der spehsphare. J Psychol Neurol. 1929;39:435–63.
Fork, RL. Laser stimulation of nerve cells in Aplysia. Nature. 1971;171, 907–08.
Freund, Yoav, Schapire, Robert E.A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1):119–139, 1997.
Friedman, JH. Regularized discriminant analysis. J Amer Statist Assoc. 1989;84 (405):165–75.
Furdea, A, Halder, S, Krusienski, DJ, Bross, D, Nijboer, F, Birbaumer, N, Kübler, A. An auditory oddball (P300) spelling system for brain-computer interfaces. Psychophysiology. 2009;46(3):617–25.
Galán, F, Nuttin, M, Lew, E, Ferrez, PW, Vanacker, G, Philips, J, Millán J del, R.A brain-actuated wheelchair: asynchronous and non-invasive brain-computer interfaces for continuous control of robots. Clin Neurophysiol. 2008;119(9):2159–69.
Ganguly, K, Carmena, JM. Emergence of a stable cortical map for neuroprosthetic control. PLoS Biol. 2009 Jul;7(7):e1000153.
Gao, X, Xu, D, Cheng, M, Gao, S. A BCI-based environmental controller for the motion-disabled. IEEE Trans Neural Syst Rehabil Eng. 2003 Jun;11(2):137–40.
Garrett, D, Peterson, DA, Anderson, CW, Thaut, MH. Comparison of linear, nonlinear, and feature selection methods for EEG signal classification. IEEE Trans Neural Syst Rehabil Eng. 2003 Jun;11(2):141–44.
Georgopoulos, AP, Kettner, RE, Schwartz, AB. Primate motor cortex and free arm movements to visual targets in three-dimensional space. II. Coding of the direction of movement by a neuronal population. J of Neurosci. 1988;8(8):2928–37.
Gerson, AD, Parra, LC, Sajda, P. Cortically coupled computer vision for rapid image search. IEEE Trans Neural Syst Rehabil Eng. 2006;14(2):174–79.
Gilja, V, Chestek, CA, Diester, I, Henderson, JM, Deisseroth, K, Shenoy, KV. Challenges and opportunities for next-generation intra-cortically based neural prostheses. IEEE Transactions on Biomedical Engineering. 2011;58:1891–99.
Gilmore, RL. American Electroencephalographic Society guidelines in electroencephalography, evoked potentials, and polysomnography, J. Clin. Neurophysiol. 1994;11.
Giridharadas, A. India’s novel use of brain scans in courts is debated. New York Times. 2008 Sept. 15. Section A, p10.
Gollakota, S, Hassanieh, H, Ransford, B, Katabi, D, Fu, K. They can hear your heartbeats: non-invasive security for implantable medical devices. In Proceedings of the ACM SIGCOMM 2011 conference (SIGCOMM ‘11). 2011. ACM, New York, NY, pages 2–13.
Graimann, B, Allison, B, Pfurtscheller, G. (eds.) Brain-Computer Interfaces: Revolutionizing Human-Computer Interaction. Springer, Berlin, 2011.
Grimes, D, Tan, DS, Hudson, S, Shenoy, P, Rao, RPN. Feasibility and pragmatics of classifying working memory load with an electroencephalograph. In Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems (CHI 2008). 2008;835–44.
Halder, S, Rea, M, Andreoni, R, Nijboer, F, Hammer, EM, Kleih, SC, Birbaumer, N, Kübler, A. An auditory oddball brain-computer interface for binary choices. Clin Neurophysiol. 2010;121(4):516–23.
Hanks, TD, Ditterich, J, Shadlen, MN. Microstimulation of macaque area LIP affects decision-making in a motion discrimination task. Nat Neurosci. 2006;9: 682–89.
Haselager, P, Vlek, R, Hill, J, Nijboer, F. A note on ethical aspects of BCI. Neural Networks. 2009;22: 1352–57.
Hill, NJ, Lal, TN, Bierig, K, Birbaumer, N, Schölkopf, B. An auditory paradigm for brain-computer interfaces. In Advances in Neural Information Processing Systems 17, 569–76. (Eds.) Saul, L.K., Weiss, Y. and Bottou, L., MIT Press, Cambridge, MA, USA (2005).
Hinterberger, T, Kübler, A, Kaiser, J, Neumann, N, Birbaumer, N. A brain-computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device. Clin Neurophysiol. 2003;114(3): 416–25.
Hiraiwa, A, Shimohara, K, Tokunaga, Y. EEG topography recognition by neural networks. Engineering in Medicine and Biology. 1990;9(3): 39–42.
Hjelm, S, Browall, C. Brainball – Using brain activity for cool competition. In Proceedings of NordiCHI, Stockholm. 2000.
Hochberg, LR, Bacher, D, Jarosiewicz, B, Masse, NY, Simeral, JD, Vogel, J, Haddadin, S, Liu, J, Cash, SS, van der Smagt, P, Donoghue, JP. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature. 2012;485(7398):372–75.
Hochberg, LR, Serruya, MD, Friehs, GM, Mukand, JA, Saleh, M, Caplan, AH, Branner, A, Chen, D, Penn, RD, Donoghue, JP. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature. 2006 Jul 13; 442(7099):164–71.
Hwang, EJ, Andersen, RA. Cognitively driven brain machine control using neural signals in the parietal reach region. Conf Proc IEEE Eng Med Biol Soc. 2010;3329–32.
Hyvärinen, A, Oja, E. Independent component analysis: algorithms and applications. Neural Networks. 2000;13(4–5): 411–430.
Hyvärinen, A. Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks. 1999;10(3): 626–34.
Iturrate, I, Antelis, J, Minguez, J. Synchronous EEG brain actuated wheelchair with automated navigation. In Proc. 2009 IEEE Int. Conf. Robotics Automation, Kobe, Japan. 2009.
Jackson, A, Mavoori, J, Fetz, EE. Long-term motor cortex plasticity induced by an electronic neural implant. Nature. 2006;444(7115):56–60.
Jahanshahi, M, Hallet, M. The Bereitschaftspotential: movement related cortical potentials. Kluwer Academic. 2002. New York.
Jasper, HH. Report of the Committee on Methods of Clinical Examination in Electroencephalography. Electroenceph. Clin. Neurophysiol. 1958;10:370–71.
Javaheri, M, Hahn, DS, Lakhanpal, RR, Weiland, JD, Humayun, MS. Retinal prostheses for the blind. Ann Acad Med Singapore. 2006;35(3):137–44.
Jung, TP, Humphries, C, Lee, TW, Makeig, S, McKeown, MJ, Iragui, V, Sejnowski TJ. Extended ICA removes artifacts from electroencephalographic recordings. Adv Neural Inf Process Syst. 1998;10:894–900.
Jung, TP, Makeig, S, Stensmo, M, Sejnowski, TJ. Estimating alertness from the EEG power spectrum. IEEE Transactions on Biomedical Engineering. 1997;44:60–69.
Kandel, ER, Schwartz, JH, Jessell, TM. Principles of Neural Science. Third edition. Elsevier, New York, 1991.
Kandel, ER, Schwartz, JH, Jessell, TM, Siegelbaum, SA, Hudspeth, AJ. Principles of Neural Science. Fifth Edition. McGraw Hill, New York, 2012.
Kern, DS, Kumar, R. Deep brain stimulation. The Neurologist. 2007;13: 237–52.
Kherlopian, AR, Song, T, Duan, Q, Neimark, MA, Po, MJ, Gohagan, JK, Laine, AF. A review of imaging techniques for systems biology. BMC Syst Biol. 2008;2:74.
Kim, SP, Simeral, JD, Hochberg, LR, Donoghue, JP, Black, MJ. Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia. J Neural Eng. 2008 Dec;5(4):455–76.
Kohlmorgen, J, Dornhege, G, Braun, M, Blankertz, B, Müller, K-R, Curio, G, Hagemann, K, Bruns, A, Schrauf, M, Kincses, W. Improving human performance in a real operating environment through realtime mental workload detection. In Toward Brain–Computer Interfacing (eds. Dornhege, G., del R. Millán, J., Hinterberger, T., McFarland, D. J., and Müller, K.-R.). MIT Press, Cambridge, MA. 2007;409–22.
Koller, D., Friedman, N. Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009.
Krepki, R, Blankertz, B, Curio, G, Müller, KR. The Berlin brain–computer interface (BBCI): towards a new communication channel for online control in gaming applications. J Multimed. Tool Appl. 2007;33:73–90.
Kringelbach, ML, Jenkinson, N, Owen, SLF, Aziz, TZ. Translational principles of deep brain stimulation. Nature Reviews Neuroscience. 2007;8:623–35.
Kübler, A, Kotchoubey, B, Hinterberger, T, Ghanayim, N, Perelmouter, J, Schauer, M, Fritsch, C, Taub, E, Birbaumer, N. The thought translation device: a neurophysiological approach to communication in total motor paralysis. Exp Brain Res. 1999 Jan;124(2):223–32.
Kuiken, TA, Miller, LA, Lipschutz, RD, Lock, BA, Stubblefield, K, Marasco, PD, Zhou, P, Dumanian, GA. Targeted reinnervation for enhanced prosthetic arm function in a woman with a proximal amputation: a case study. Lancet. 2007;369:371–80.
Lalor, EC, Kelly, SP, Finucane, C, Burke, R, Smith, R, Reilly, R, McDarby, G. Steady-state VEP-based brain-computer interface: Control in an immersive 3D gaming environment. EURASIP Journal on Applied Signal Processing. 2005;19:3156–64.
Leuthardt, EC, Miller, KJ, Schalk, G, Rao, RPN, Ojemann, JG. Electrocorticography-based brain computer interface – the Seattle experience. IEEE Trans Neural Syst Rehabil Eng. 2006 Jun;14(2):194–98.
Leuthardt, EC, Schalk, G, Wolpaw, JR, Ojemann, JG, Moran, DW. A brain-computer interface using electrocorticographic signals in humans. J Neural Eng. 2004 Jun;1(2):63–71.
Li, Z, O’Doherty, JE, Hanson, TL, Lebedev, MA, Henriquez, CS, Nicolelis, MA. Unscented Kalman filter for brain-machine interfaces. PLoS One. 2009 Jul 15;4(7):e6243.
Liang, SF, Lin, CT, Wu, RC, Chen, YC, Huang, TY, Jung, TP. Monitoring driver’s alertness based on the driving performance estimation and the EEG power spectrum analysis. Conf Proc IEEE Eng Med Biol Soc. 2005;6:5738–41.
Lins, OG, Picton, TW, Berg, P, Scherg, M. Ocular artifacts in recording EEGs and event-related potentials. II: source dipoles and source components. Brain Topogr. 1993;6:65–78.
Loeb, GE, Peck, RA. Cuff electrodes for chronic stimulation and recording of peripheral nerve activity. J Neurosci Methods. 1996 Jan;64:95–103.
Makeig, S, Enghoff, S, Jung, TP, Sejnowski, TJ. Moving-window ICA decomposition of EEG data reveals event-related changes in oscillatory brain activity. In Proc. Second International Workshop on Independent Component Analysis and Signal Separation. 2000; 627–32.
Malmivuo, J, Plonsey, R. Bioelectromagnetism – Principles and Applications of Bioelectric and Biomagnetic Fields, Oxford University Press, New York, 1995.
Mappus, RL, Venkatesh, GR, Shastry, C, Israeli, A, Jackson, MM. An fNIR based BMI for letter construction using continuous control. ACM CHI 2009 Human Factors in Computing Systems Conference Work in Progress Paper. 2009;2:3571–76.
Marcel, S, Millán J del, R.Person authentication using brainwaves (EEG) and maximum a posteriori model adaptation. IEEE Trans Pattern Anal Mach Intell. 2007;29(4):743–52.
Mason, SG, Birch, GE. A brain-controlled switch for asynchronous control applications. IEEE Trans Biomed Eng. 2000 Oct;47(10):1297–307.
Mavoori, J, Jackson, A, Diorio, C, Fetz, E. An autonomous implantable computer for neural recording and stimulation in unrestrained primates. J Neurosci Methods. 2005;148(1):71–77.
Mellinger, J, Schalk, G, Braun, C, Preissl, H, Rosenstiel, W, Birbaumer, N, Kübler, A. An MEG-based brain-computer interface (BCI). Neuroimage. 2007;36(3):581–93.
Middendorf, M, McMillan, G, Calhoun, G, Jones, KS. Brain computer interfaces based on the steady-state visual-evoked response. IEEE Trans. Rehab. Eng. 2000;8:211–14.
Millán, JJdel, R, Galán, F, Vanhooydonck, D, Lew, E, Philips, J, Nuttin, M. Asynchronous non-invasive brain-actuated control of an intelligent wheelchair. Conf. Proc. IEEE Eng. Med. Biol Soc. 2009;3361–64.
Millán, JR, Ferrez, PW, Seidl, T. Validation of brain-machine interfaces during parabolic flight. In Rossini, L., Izzo, D., Summerer, L. (eds.), “Brain-machine interfaces for space applications: enhancing astronauts’ capabilities.” International Review of Neurobiology. 2009;86.
Miller, KJ, Leuthardt, EC, Schalk, G, Rao, RPN, Anderson, NR, Moran, DW, Miller, JW, Ojemann, JG. Spectral changes in cortical surface potentials during motor movement. J Neurosci. 2007;27(9):2424–32.
Miller, KJ, Schalk, G, Fetz, EE, den Nijs, M, Ojemann, JG, Rao, RPN. Cortical activity during motor execution, motor imagery, and imagery-based online feedback. Proc. Natl. Acad. Sci. USA. 2010 Mar 2;107(9):4430–35.
Miller, KJ, Zanos, S, Fetz, EE, den Nijs, M, Ojemann, JG. Decoupling the cortical power spectrum reveals real-time representation of individual finger movements in humans. J Neurosci. 2009 Mar 11;29(10):3132–37.
Moritz, CT, Fetz, EE. Volitional control of single cortical neurons in a brain-machine interface. J Neural Eng. 2011;8(2).
Moritz, CT, Perlmutter, SI, Fetz, EE. Direct control of paralysed muscles by cortical neurons. Nature. 2008;456, 639–42.
Müller, KR, Anderson, CW, Birch, GE. Linear and nonlinear methods for brain-computer interfaces. IEEE Trans Neural Syst Rehabil Eng. 2003;11(2):165–69.
Müller, KR, Tangermann, M, Dornhege, G, Krauledat, M, Curio, G, Blankertz, B. Machine learning for real-time single-trial EEG-analysis: From brain-computer interfacing to mental state monitoring. J Neurosci Methods. 2008;167(1):82–90.
Musallam, S, Corneil, BD, Greger, B, Scherberger, H, Andersen, RA. Cognitive control signals for neural prosthetics. Science. 2004 Jul 9;305(5681):258–62.
Mussa-Ivaldi, FA, Alford, ST, Chiappalone, M, Fadiga, L, Karniel, A, Kositsky, M, Maggiolini, E, Panzeri, S, Sanguineti, V, Semprini, M, Vato, A. New perspectives on the dialogue between brains and machines. Front Neurosci. 2010;4:44.
Nunez, PL. Electric Fields of the Brain: The Neurophysics of EEG, Oxford University Press, New York, 1981.
O’Doherty, JE, Lebedev, MA, Hanson, TL, Fitzsimmons, NA, Nicolelis, MA. A brain-machine interface instructed by direct intracortical microstimulation. Front Integr Neurosci. 2009;3:20.
O’Doherty, JE, Lebedev, MA, Ifft, PJ, Zhuang, KZ, Shokur, S, Bleuler, H, Nicolelis, MA. Active tactile exploration using a brain-machine-brain interface. Nature. 2011;479(7372):228–31.
Ohki, K, Chung, S, Ch’ng, YH, Kara, P and Reid, RC. Functional imaging with cellular resolution reveals precise microarchitecture in visual cortex. Nature. 2005;433:597–603.
Ojakangas, CL, Shaikhouni, A, Friehs, GM, Caplan, AH, Serruya, MD, Saleh, M, Morris, DS, Donoghue, JP. Decoding movement intent from human premotor cortex neurons for neural prosthetic applications. J Clin Neurophysiol. 2006 Dec;23(6):577–84.
Onton, J, Makeig, S. Information-based modeling of event-related brain dynamics. In Neuper, C. and Klimesch, W., (eds.) Progress in Brain Research. 2006;159. Elsevier, Amsterdam.
Orbach, HS, Cohen, LB, Grinvald, A. Optical mapping of electrical activity in rat somatosensory and visual cortex. J Neurosci. 1985;5:1886.
Paranjape, RB, Mahovsky, J, Benedicenti, L, Koles, Z. The electroencephalogram as a biometric. In Proceedings of the Canadian Conference on Electrical and Computer Engineering. 2001;2:1363–66.
Paul, N, Kohno, T, Klonoff, DC. A review of the security of insulin pump infusion systems. J Diabetes Sci Technol. 2011;5(6):1557–62.
Pfurtscheller, G, Guger, C, Müller, G, Krausz, G, Neuper, C. Brain oscillations control hand orthosis in a tetraplegic. Neurosci Lett. 2000 Oct 13;292(3):211–14.
Pfurtscheller, G, Neuper, C, Guger, C, Harkam, W, Ramoser, H, Schlögl, A, Obermaier, B, Pregenzer, M. Current trends in Graz brain-computer interface (BCI) research. IEEE Trans Rehabil Eng. 2000 Jun;8(2):216–19.
Pfurtscheller, G, Neuper, C, Müller, GR, Obermaier, B, Krausz, G, Schlögl, A, Scherer, R, Graimann, B, Keinrath, C, Skliris, D, Wörtz, M, Supp, G, Schrank, C. Graz-BCI: state of the art and clinical applications. IEEE Trans Neural Syst Rehabil Eng. 2003 Jun;11(2):177–80.
Pierce, JR. An Introduction to Information Theory. Dover, New York, 1980.
Pistohl, T, Ball, T, Schulze-Bonhage, A, Aertsen, A, Mehring, C. Prediction of arm movement trajectories from ECoG-recordings in humans. J Neurosci Methods. 2008 Jan 15;167(1):105–14.
Poulos, M, Rangoussi, M, Chrissicopoulos, V, Evangelou, A. Person identification based on parametric processing on the EEG. In Proceedings of the Sixth International Conference on Electronics, Circuits and Systems (ICECS99), Pafos, Cyprus. 1999;1:283–86.
Pregenzer, M. DSLVQ. PhD thesis, Graz University of Technology, 1997.
Puikkonen, J, Malmivuo, JA. Theoretical investigation of the sensitivity distribution of point EEG-electrodes on the three concentric spheres model of a human head – An application of the reciprocity theorem. Tampere Univ. Techn., Inst. Biomed. Eng., Reports. 1987;1(5):71.
Ramoser, H, Muller-Gerking, J, Pfurtscheller, G. Optimal spatial filtering of single trial EEG during imagined hand movement. IEEE Trans. on Rehab. 2000;8(4):441–46.
Ranganatha, S, Hoshi, Y, Guan, C. Near infrared spectroscopy based brain-computer interface. Proceedings of SPIE Exp. Mech. 2005;5852:434–42.
Rao, RPN, Scherer, R. Brain-computer interfacing. IEEE Signal Processing Magazine. 2010;27(4).
Rao, RPN, Scherer, R. Statistical pattern recognition and machine learning in brain-computer interfaces. In Oweiss, K. (ed.), Statistical Signal Processing for Neuroscience and Neurotechnology. Academic Press, Burlington, MA, 2010.
Rao, RPN. An optimal estimation approach to visual perception and learning. Vision Research. 1999;39(11):1963–89.
Rebsamen, B, Burdet, E, Teo, CL, Zeng, Q, Guan, C, Ang, M, Laugier, C. A brain control wheelchair with a P300-based BCI and a path following controller. In Proc. 1st IEEE/RAS-EMBS Int. Conf. Biomedical Robotics andBiomechatronics, Pisa, Italy, 2006.
Riddle, DF. Calculus and Analytic Geometry, 3rd ed., Wadsworth Publishing, Belmont, CA, 1979.
Rissman, J, Greely, HT, Wagner, AD. Detecting individual memories through the neural decoding of memory states and past experience. Proc. Natl. Acad. Sci. USA. 2010;107(21):9849–54.
Rosenfeld, JP, Cantwell, G, Nasman, VT, Wojdac, V, Ivanov, S, Mazzeri, L. A modified, event-related potential-based guilty knowledge test. International Journal of Neuroscience. 1988;24:157–61.
Rosenfeld, JP, Soskins, M, Bosh, G, Ryan, A. Simple, effective countermeasures to P300-based tests of detection of concealed information. Psychophysiology. 2004;41(2):205–19.
Rossini, L, Izzo, D, Summerer, L (eds.). Brain-machine interfaces for space applications: enhancing astronauts’ capabilities. International Review of Neurobiology. 2009;86, Elsevier, Amsterdam.
Rouse, AG, Moran, DW. Neural adaptation of epidural electrocorticographic (EECoG) signals during closed-loop brain computer interface (BCI) tasks. Conf Proc IEEE Eng Med Biol Soc. 2009;5514–17.
Rush, S, Driscoll, DA. EEG-electrode sensitivity – An application of reciprocity. IEEE Trans. Biomed. Eng. 1969;BME-16:(1) 15–22.
Russell, S, Norvig, P. Artificial Intelligence: A Modern Approach, 3rd ed., Prentice Hall, Upper Saddle River, NJ, 2009.
Sajda, P, Pohlmeyer, E, Wang, J, Parra, LC, Christoforou, C, Dmochowski, J, Hanna, B, Bahlmann, C, Singh, MK, and Chang, SF. In a blink of an eye and a switch of a transistor: cortically coupled computer vision. Proc. IEEE. 2010;98:462–78.
Salvini, P, Datteri, E, Laschi, C, Dario, P. Scientific models and ethical issues in hybrid bionic systems research. AI & Society. 2008;22:431–48.
Santhanam, G, Ryu, SI, Yu, BM, Afshar, A, Shenoy, KV. A high-performance brain-computer interface. Nature. 2006 Jul 13;442(7099):195–98.
Schalk, G, Kubánek, J, Miller, KJ, Anderson, NR, Leuthardt, EC, Ojemann, JG, Limbrick, D, Moran, D, Gerhardt, LA, Wolpaw, JR. Decoding two-dimensional movement trajectories using electrocorticographic signals in humans. J Neural Eng. 2007 Sep;4(3):264–75.
Schalk, G, Miller, KJ, Anderson, NR, Wilson, JA, Smyth, MD, Ojemann, JG, Moran, DW, Wolpaw, JR, Leuthardt, EC. Two-dimensional movement control using electrocorticographic signals in humans. J Neural Eng. 2008;5(1):75–84.
Scherer, R, Lee, F, Schlögl, A, Leeb, R, Bischof, H, Pfurtscheller, G. Towards self-paced brain-computer communication: Navigation through virtual worlds. IEEE Trans Biomed Eng. 2008;55(2):675–82.
Scherer, R, Mohapp, A, Grieshofer, P, Pfurtscheller, G, Neuper, C. Sensorimotor EEG patterns during motor imagery in hemiparetic stroke patients. International Journal of Bioelectromagnetism. 2007;9(3):155–62.
Scherer, R, Schlögl, A, Lee, F, Bischof, H, Janša, J, Pfurtscheller, G. The self-paced Graz brain-computer interface: Methods and applications. Computational Intelligence and Neuroscience. 2007;Article ID 79826: 9 pages.
Scherer, R, Zanos, SP, Miller, KJ, Rao, RPN, Ojemann, JG. Classification of contralateral and ipsilateral finger movements for electrocorticographic brain-computer interfaces. Neurosurg Focus. 2009;27(1):E12.
Scherer, R, Rao, RPN. Non-manual control devices: Direct brain-computer interaction. In Pereira, J. (ed.), Handbook of Research on Personal Autonomy Technologies and Disability Informatics. IGI Global, Hershey, PA, 2011.
Sellers, EW, Kübler, A, Donchin, E. Brain-computer interface research at the University of South Florida Cognitive Psychophysiology Laboratory: the P300 Speller. IEEE Trans Neural Syst Rehabil Eng. 2006 Jun;14(2):221–24.
Serruya, MD, Hatsopoulos, NG, Paninski, L, Fellows, MR, Donoghue, JP. Instant neural control of a movement signal. Nature. 2002 Mar 14;416(6877):141–42.
Shannon, CE, Weaver, W. The Mathematical Theory of Communication. Univ. Illinois Press, Urbana, IL, 1964.
Sharbrough, F, Chatrian, G-E, Lesser, RP, Lüders, H, Nuwer, M, Picton, TW. American Electroencephalographic Society guidelines for standard electrode position nomenclature. J. Clin. Neurophysiol. 1991;8:200–202.
Shenoy, P. Brain-computer interfaces for control and computation. PhD thesis, Department of Computer Science and Engineering, University of Washington, 2008.
Shenoy, P, Miller, KJ, Ojemann, JG, Rao, RPN. Generalized features for electrocorticographic BCIs. IEEE Trans Biomed Eng. 2008 Jan;55(1):273–80.
Shenoy, P, Miller, KJ, Ojemann, J, Rao, RPN. Finger movement classification for an electrocorticographic BCI. In Proc. of 3 International IEEE EMBS Conf. Neur Eng 2007; 192–195.
Shenoy, P, Rao, RPN. Dynamic Bayesian networks for brain-computer interfaces. In Saul, L.K., Weiss, Y., and Bottou, L. (eds.), Advances in Neural Information Processing System (NIPS). 2005;17:1265–1272, MIT Press, Cambridge, MA.
Simeral, JD, Kim, SP, Black, MJ, Donoghue, JP, Hochberg, LR. Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array. J Neural Eng. 2011 Apr;8(2):025027.
Skidmore, TA, HillJr., HW. The evoked potential human-computer interface. Proc. Annu. Conf. Engineering in Medicine and Biology. 1991:407–408.
Stosiek, C, Garaschuk, O, Holthoff, K, Konnerth, A. In vivo two-photon calcium imaging of neuronal networks. Proc. Natl Acad. Sci. USA. 2003;100, 7319–24.
Strang, G. Introduction to Linear Algebra, 4th ed., Wellesley-Cambridge Press, Wellesley, MA, 2009.
Suihko, V, Malmivuo, JA, Eskola, H. Distribution of sensitivity of electric leads in an inhomogeneous spherical head model. Tampere Univ. Techn., Ragnar Granit Inst. 1993;Rep. 7:(2).
Suminski, AJ, Tkach, DC, Fagg, AH, Hatsopoulos, NG. Incorporating feedback from multiple sensory modalities enhances brain-machine interface control. J Neurosci. 2010 Dec 15;30(50):16777–87.
Szafir, D, Mutlu, B. Pay attention! Designing adaptive agents that monitor and improve user engagement. In Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems (CHI 2012). 2012;11–20.
Tamburrini, G. Brain to computer communication: Ethical perspectives on interaction models. Neuroethics 2009;2: 137–49.
Tan, DS, Nijholt, A. (eds.) Brain-Computer Interfaces: Applying our Minds to Human-Computer Interaction. Springer, London, UK, 2010.
Tangermann, M, Krauledat, M, Grzeska, K, Sagebaum, M, Blankertz, B, Vidaurre, C, Müller, KR. Playing pinball with non-invasive BCI. In Advances in Neural Information Processing Systems, 2009;21:1641–48. MIT Press, Cambridge, MA.
Thomson, EE, Carra, R, Nicolelis, MA. Perceiving invisible light through a somatosensory cortical prosthesis. Nature Commun. 2013;4:1482.
Tufail, Y, Matyushov, A, Baldwin, N, Tauchmann, ML, Georges, J, Yoshihiro, A, Tillery, SI, Tyler, WJ. Transcranial pulsed ultrasound stimulates intact brain circuits. Neuron. 2010 Jun 10;66(5):681–94.
Van den, Brand R, Heutschi, J, Barraud, Q, DiGiovanna, J, Bartholdi, K, Huerlimann, M, Friedli, L, Vollenweider, I, Moraud, EM, Duis, S, Dominici, N, Micera, S, Musienko, P, Courtine, G. Restoring voluntary control of locomotion after paralyzing spinal cord injury. Science. 2012;336:1182–85.
Vapnik, V.The Nature of Statistical Learning Theory. Springer-Verlag, New York, 1995.
Vargas-Irwin, CE, Shakhnarovich, G, Yadollahpour, P, Mislow, JM, Black, MJ, Donoghue, JP. Decoding complete reach and grasp actions from local primary motor cortex populations. J Neurosci. 2010 Jul 21;30(29):9659–69.
Velliste, M, Perel, S, Spalding, MC, Whitford, AS and Schwartz, AB. Cortical control of a prosthetic arm for self-feeding. Nature. 2008; 453:1098–1101.
Vidal, JJ. Toward direct brain-computer communication. Annu. Rev. Biophys. Bioeng. 1973;2:157–80.
Vidaurre, C, Scherer, R, Cabeza, R, Schlögl, A, Pfurtscheller, G. Study of discriminant analysis applied to motor imagery bipolar data. Med Biol Eng Comput. 2007; 45(1):61–68.
Vidaurre, C, Sannelli, C, Müller, KR, Blankertz, B. Machine-learning-based coadaptive calibration for brain-computer interfaces. Neural Comput. 2011;23(3):791–816.
Von Melchner, L, Pallas, SL, Sur, M. Visual behaviour mediated by retinal projections directed to the auditory pathway. Nature. 2000;404(6780):871–76.
Warwick, K, Gasson, M, Hutt, B, Goodhew, I, Kyberd, P, Andrews, B, Teddy, P, Shad, A. The application of implant technology for cybernetic systems. Arch Neurol. 2003;60:1369–73.
Warwick, K. Cyborg morals, cyborg values, cyborg ethics. Ethics and Information Technology. 2003;5:131–37.
Weiland, JD, Liu, W, Humayun, MS. Retinal prosthesis. Annu Rev Biomed Eng. 2005;7:361–401.
Weiskopf, N, Veit, R, Erb, M, Mathiak, K, Grodd, W, Goebel, R, Birbaumer, N. Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data. Neuroimage. 2003;19(3):577–86.
Wessberg, J, Stambaugh, CR, Kralik, JD, Beck, PD, Laubach, M, Chapin, JK, Kim, J, Biggs, SJ, Srinivasan, MA, Nicolelis, MA. Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature. 2000 Nov 16;408(6810):361–65.
Wodlinger, B, Durand, DM. Peripheral nerve signal recording and processing for artificial limb control. Conf Proc IEEE Eng Med Biol Soc. 2010:6206–09.
Wolpaw, JR, Wolpaw, EW. (eds.) Brain-Computer Interfaces: Principles and Practice. Oxford University Press, 2012.
Wolpaw, JR, Birbaumer, N, Heetderks, WJ, McFarland, DJ, Peckham, PH, Schalk, G, Donchin, E, Quatrano, LA, Robinson, CJ, Vaughan, TM. Brain-computer interface technology: a review of the first international meeting. IEEE Trans Rehabil Eng. 2000;8(2):164–73.
Wolpaw, JR, McFarland, DJ, Neat, GW, Forneris, CA. An EEG-based brain-computer interface for cursor control. Electroencephalogr Clin Neurophysiol. 1991 Mar;78(3):252–59.
Wolpaw, JR, McFarland, DJ. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proc Natl Acad Sci USA. 2004 Dec 21;101(51):17849–54.
Wolpaw, JR, McFarland, DJ. Multichannel EEG-based brain-computer communication. Electroencephalogr Clin Neurophysiol. 1994 Jun;90(6):444–49.
Wolpaw, JR, Birbaumer, N, McFarland, D, Pfurtscheller, G, Vaughan, T. Brain-computer interfaces for communication and control. Clinical Neurophysiology. 2002;113:767–91.
Wu, W, Gao, Y, Bienenstock, E, Donoghue, JP, Black, MJ. Bayesian population decoding of motor cortical activity using a Kalman filter. Neural Comput. 2006 Jan;18(1):80–118.
Zhuang, J, Truccolo, W, Vargas-Irwin, C, Donoghue, JP. Decoding 3-D reach and grasp kinematics from high-frequency local field potentials in primate primary motor cortex. IEEE Trans Biomed Eng. 2010;57(7):1774–84.

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Book summary page views

Total views: 0 *
Loading metrics...

* Views captured on Cambridge Core between #date#. This data will be updated every 24 hours.

Usage data cannot currently be displayed.