Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-07T11:58:53.437Z Has data issue: false hasContentIssue false

References

Published online by Cambridge University Press:  05 October 2013

Rajesh P. N. Rao
Affiliation:
University of Washington
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Brain-Computer Interfacing
An Introduction
, pp. 295 - 306
Publisher: Cambridge University Press
Print publication year: 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

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.CrossRefGoogle ScholarPubMed
Andersen, RA, Hwang, EJ, Mulliken, GH. Cognitive neural prosthetics. Annu Rev Psychol. 2010;61:169–90, C1–3.CrossRefGoogle ScholarPubMed
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
Barber, D. Bayesian Reasoning and Machine Learning. Cambridge University Press, 2012.Google Scholar
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.CrossRefGoogle Scholar
Bear, MF, Connors, BW, Paradiso, MA. Neuroscience: Exploring the Brain., 3rd ed., Lippincott Williams & Wilkins, Baltimore, MD, 2007.Google Scholar
Bell, AJ, Sejnowski, TJ. An information-maximization approach to blind separation and blind deconvolution. Neural Computation. 1995;7:1129–59.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Bellavista, P, Corradi, A, Giannelli, C. Evaluating filtering strategies for decentralized handover prediction in the wireless internet. Proc. 11th IEEE Symposium Computers Commun., 2006.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
Berger, H. Über das Elektroenkephalogram des Menschen. Arch. f. Psychiat. 1929;87: 527–70.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
Birbaumer, N, Cohen, LG. Brain-computer interfaces: communication and restoration of movement in paralysis. J Physiol. 2007;579(Pt 3):621–36.CrossRefGoogle ScholarPubMed
Bishop, CM. Pattern Recognition and Machine Learning. Springer, New York, 2006.Google Scholar
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.Google ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
Bles, M, Haynes, JD. Detecting concealed information using brain-imaging technology. Neurocase. 2008;14:82–92.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
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.Google Scholar
Braitenberg, V. Vehicles: Experiments in synthetic psychology. MIT Press, Cambridge, MA, 1984.Google Scholar
Breiman, L. Random Forests. Machine Learning. 2001;45(1):5–32.CrossRefGoogle Scholar
Brindley, GS, Lewin, WS. The sensations produced by electrical stimulation of the visual cortex. J Physiol. 1968;196(2):479–93.CrossRefGoogle ScholarPubMed
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.Google Scholar
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.Google ScholarPubMed
Bryson, AE, Ho, YC. Applied optimal control. New York: Wiley, 1975.Google Scholar
Burges, CJC. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery. 1998;2:121–67.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
Calhoun, GL, McMillan, GR. EEG-based control for human computer interaction. Proc. Annu. Symp. Human Interaction with Complex Systems. 1996, pp. 4–9.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.Google ScholarPubMed
Chung, M, Cheung, W, Scherer, R, Rao, RPN. A hierarchical architecture for adaptive brain-computer interfacing. Proceedings of IJCAI. 2011, pp.1647–52.Google Scholar
Citri, A, Malenka, RC. Synaptic plasticity: multiple forms, functions, and mechanisms. Neuropsychopharmacology. 2008;33: 18–41.CrossRefGoogle ScholarPubMed
Clausen, J. Man, machine and in between. Nature. 2009;457(7233): 1080–81.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Cooper, R, Osselton, JW, Shaw, JC. EEG Technology, 2nd ed., London: Butterworths, 1969.Google Scholar
Cortes, C, Vapnik, V. Support-Vector Networks. Machine Learning. 1995;20:273–297.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
Croft, RJ, Chandler, JS, Barry, RJ, Cooper, NR, Clarke, AR. EOG correction: a comparison of four methods. Psychophysiology. 2005;42:16–24.CrossRefGoogle ScholarPubMed
Dalbey, B. Brain fingerprinting testing traps serial killer in Missouri. The Fairfield Ledger. Fairfield, IA, 1999 August, p. 1.Google Scholar
Delgado, J. Physical Control of the Mind: Toward a Psychocivilized Society. Harper and Row, New York, 1969.Google Scholar
Denk, W, Strickler, JH, Webb, WW. Two-photon laser scanning fluorescence microscopy. Science. 1990;248, 73–76.CrossRefGoogle ScholarPubMed
Denning, T, Matsuoka, Y, Kohno, T. Neurosecurity: security and privacy for neural devices. Neurosurg Focus. 2009;27(1):E7.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
Farwell, LA, Donchin, E. The truth will out: interrogative polygraphy (“lie detection”) with event-related brain potentials. Psychophysiology. 1991;28(5):531–47.CrossRefGoogle ScholarPubMed
Farwell, LA. Brain fingerprinting: a comprehensive tutorial review of detection of concealed information with event-related brain potentials. Cognitive Neurodynamics. 2012;6: 115–54.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Fetz, EE. Operant conditioning of cortical unit activity. Science. 1969 Feb 28;163(870):955–58.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Finke, A, Lenhardt, A, Ritter, H. The mindgame: a P300-based brain-computer interface game. Neural Networks 2009;22: 1329–33.Google ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Foerster, O. Beitrage zur pathophysiologie der sehbahn und der spehsphare. J Psychol Neurol. 1929;39:435–63.Google Scholar
Fork, RL. Laser stimulation of nerve cells in Aplysia. Nature. 1971;171, 907–08.Google ScholarPubMed
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.CrossRefGoogle Scholar
Friedman, JH. Regularized discriminant analysis. J Amer Statist Assoc. 1989;84 (405):165–75.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Ganguly, K, Carmena, JM. Emergence of a stable cortical map for neuroprosthetic control. PLoS Biol. 2009 Jul;7(7):e1000153.CrossRefGoogle ScholarPubMed
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.Google ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
Gilmore, RL. American Electroencephalographic Society guidelines in electroencephalography, evoked potentials, and polysomnography, J. Clin. Neurophysiol. 1994;11.Google Scholar
Giridharadas, A. India’s novel use of brain scans in courts is debated. New York Times. 2008 Sept. 15. Section A, p10.Google Scholar
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.CrossRefGoogle Scholar
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
Haselager, P, Vlek, R, Hill, J, Nijboer, F. A note on ethical aspects of BCI. Neural Networks. 2009;22: 1352–57.CrossRefGoogle ScholarPubMed
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).Google Scholar
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.CrossRefGoogle ScholarPubMed
Hiraiwa, A, Shimohara, K, Tokunaga, Y. EEG topography recognition by neural networks. Engineering in Medicine and Biology. 1990;9(3): 39–42.CrossRefGoogle ScholarPubMed
Hjelm, S, Browall, C. Brainball – Using brain activity for cool competition. In Proceedings of NordiCHI, Stockholm. 2000.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.Google ScholarPubMed
Hyvärinen, A, Oja, E. Independent component analysis: algorithms and applications. Neural Networks. 2000;13(4–5): 411–430.CrossRefGoogle ScholarPubMed
Hyvärinen, A. Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks. 1999;10(3): 626–34.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
Jackson, A, Mavoori, J, Fetz, EE. Long-term motor cortex plasticity induced by an electronic neural implant. Nature. 2006;444(7115):56–60.CrossRefGoogle ScholarPubMed
Jahanshahi, M, Hallet, M. The Bereitschaftspotential: movement related cortical potentials. Kluwer Academic. 2002. New York.Google Scholar
Jasper, HH. Report of the Committee on Methods of Clinical Examination in Electroencephalography. Electroenceph. Clin. Neurophysiol. 1958;10:370–71.Google Scholar
Javaheri, M, Hahn, DS, Lakhanpal, RR, Weiland, JD, Humayun, MS. Retinal prostheses for the blind. Ann Acad Med Singapore. 2006;35(3):137–44.Google ScholarPubMed
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.Google Scholar
Jung, TP, Makeig, S, Stensmo, M, Sejnowski, TJ. Estimating alertness from the EEG power spectrum. IEEE Transactions on Biomedical Engineering. 1997;44:60–69.CrossRefGoogle ScholarPubMed
Kandel, ER, Schwartz, JH, Jessell, TM. Principles of Neural Science. Third edition. Elsevier, New York, 1991.Google Scholar
Kandel, ER, Schwartz, JH, Jessell, TM, Siegelbaum, SA, Hudspeth, AJ. Principles of Neural Science. Fifth Edition. McGraw Hill, New York, 2012.Google Scholar
Kern, DS, Kumar, R. Deep brain stimulation. The Neurologist. 2007;13: 237–52.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.Google Scholar
Koller, D., Friedman, N. Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009.Google Scholar
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.Google Scholar
Kringelbach, ML, Jenkinson, N, Owen, SLF, Aziz, TZ. Translational principles of deep brain stimulation. Nature Reviews Neuroscience. 2007;8:623–35.CrossRefGoogle ScholarPubMed
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.Google ScholarPubMed
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.CrossRefGoogle Scholar
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.Google ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Loeb, GE, Peck, RA. Cuff electrodes for chronic stimulation and recording of peripheral nerve activity. J Neurosci Methods. 1996 Jan;64:95–103.CrossRefGoogle ScholarPubMed
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.Google Scholar
Malmivuo, J, Plonsey, R. Bioelectromagnetism – Principles and Applications of Bioelectric and Biomagnetic Fields, Oxford University Press, New York, 1995.CrossRefGoogle Scholar
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
Mason, SG, Birch, GE. A brain-controlled switch for asynchronous control applications. IEEE Trans Biomed Eng. 2000 Oct;47(10):1297–307.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
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.Google ScholarPubMed
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.Google Scholar
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Moritz, CT, Fetz, EE. Volitional control of single cortical neurons in a brain-machine interface. J Neural Eng. 2011;8(2).CrossRefGoogle Scholar
Moritz, CT, Perlmutter, SI, Fetz, EE. Direct control of paralysed muscles by cortical neurons. Nature. 2008;456, 639–42.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Musallam, S, Corneil, BD, Greger, B, Scherberger, H, Andersen, RA. Cognitive control signals for neural prosthetics. Science. 2004 Jul 9;305(5681):258–62.CrossRefGoogle ScholarPubMed
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.Google Scholar
Nunez, PL. Electric Fields of the Brain: The Neurophysics of EEG, Oxford University Press, New York, 1981.Google Scholar
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.Google ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
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.Google ScholarPubMed
Orbach, HS, Cohen, LB, Grinvald, A. Optical mapping of electrical activity in rat somatosensory and visual cortex. J Neurosci. 1985;5:1886.CrossRefGoogle ScholarPubMed
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Pierce, JR. An Introduction to Information Theory. Dover, New York, 1980.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.Google Scholar
Pregenzer, M. DSLVQ. PhD thesis, Graz University of Technology, 1997.Google Scholar
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
Ranganatha, S, Hoshi, Y, Guan, C. Near infrared spectroscopy based brain-computer interface. Proceedings of SPIE Exp. Mech. 2005;5852:434–42.CrossRefGoogle Scholar
Rao, RPN, Scherer, R. Brain-computer interfacing. IEEE Signal Processing Magazine. 2010;27(4).CrossRefGoogle Scholar
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.Google Scholar
Rao, RPN. An optimal estimation approach to visual perception and learning. Vision Research. 1999;39(11):1963–89.CrossRefGoogle Scholar
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.Google Scholar
Riddle, DF. Calculus and Analytic Geometry, 3rd ed., Wadsworth Publishing, Belmont, CA, 1979.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
Rossini, L, Izzo, D, Summerer, L (eds.). Brain-machine interfaces for space applications: enhancing astronauts’ capabilities. International Review of Neurobiology. 2009;86, Elsevier, Amsterdam.Google Scholar
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.Google ScholarPubMed
Rush, S, Driscoll, DA. EEG-electrode sensitivity – An application of reciprocity. IEEE Trans. Biomed. Eng. 1969;BME-16:(1) 15–22.CrossRefGoogle ScholarPubMed
Russell, S, Norvig, P. Artificial Intelligence: A Modern Approach, 3rd ed., Prentice Hall, Upper Saddle River, NJ, 2009.Google Scholar
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.CrossRefGoogle Scholar
Salvini, P, Datteri, E, Laschi, C, Dario, P. Scientific models and ethical issues in hybrid bionic systems research. AI & Society. 2008;22:431–48.CrossRefGoogle Scholar
Santhanam, G, Ryu, SI, Yu, BM, Afshar, A, Shenoy, KV. A high-performance brain-computer interface. Nature. 2006 Jul 13;442(7099):195–98.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
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.Google Scholar
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.Google ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Shannon, CE, Weaver, W. The Mathematical Theory of Communication. Univ. Illinois Press, Urbana, IL, 1964.Google Scholar
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.Google Scholar
Shenoy, P. Brain-computer interfaces for control and computation. PhD thesis, Department of Computer Science and Engineering, University of Washington, 2008.Google Scholar
Shenoy, P, Miller, KJ, Ojemann, JG, Rao, RPN. Generalized features for electrocorticographic BCIs. IEEE Trans Biomed Eng. 2008 Jan;55(1):273–80.CrossRefGoogle ScholarPubMed
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.Google Scholar
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.Google Scholar
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.CrossRefGoogle ScholarPubMed
Skidmore, TA, HillJr., HW. The evoked potential human-computer interface. Proc. Annu. Conf. Engineering in Medicine and Biology. 1991:407–408.Google Scholar
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.CrossRefGoogle ScholarPubMed
Strang, G. Introduction to Linear Algebra, 4th ed., Wellesley-Cambridge Press, Wellesley, MA, 2009.Google Scholar
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).Google Scholar
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.CrossRefGoogle ScholarPubMed
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.Google Scholar
Tamburrini, G. Brain to computer communication: Ethical perspectives on interaction models. Neuroethics 2009;2: 137–49.CrossRefGoogle Scholar
Tan, DS, Nijholt, A. (eds.) Brain-Computer Interfaces: Applying our Minds to Human-Computer Interaction. Springer, London, UK, 2010.CrossRef
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.Google Scholar
Thomson, EE, Carra, R, Nicolelis, MA. Perceiving invisible light through a somatosensory cortical prosthesis. Nature Commun. 2013;4:1482.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
Vapnik, V.The Nature of Statistical Learning Theory. Springer-Verlag, New York, 1995.CrossRefGoogle Scholar
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Vidal, JJ. Toward direct brain-computer communication. Annu. Rev. Biophys. Bioeng. 1973;2:157–80.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Vidaurre, C, Sannelli, C, Müller, KR, Blankertz, B. Machine-learning-based coadaptive calibration for brain-computer interfaces. Neural Comput. 2011;23(3):791–816.CrossRefGoogle ScholarPubMed
Von Melchner, L, Pallas, SL, Sur, M. Visual behaviour mediated by retinal projections directed to the auditory pathway. Nature. 2000;404(6780):871–76.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Warwick, K. Cyborg morals, cyborg values, cyborg ethics. Ethics and Information Technology. 2003;5:131–37.CrossRefGoogle Scholar
Weiland, JD, Liu, W, Humayun, MS. Retinal prosthesis. Annu Rev Biomed Eng. 2005;7:361–401.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Wodlinger, B, Durand, DM. Peripheral nerve signal recording and processing for artificial limb control. Conf Proc IEEE Eng Med Biol Soc. 2010:6206–09.Google ScholarPubMed
Wolpaw, JR, Wolpaw, EW. (eds.) Brain-Computer Interfaces: Principles and Practice. Oxford University Press, 2012.CrossRef
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Wolpaw, JR, McFarland, DJ. Multichannel EEG-based brain-computer communication. Electroencephalogr Clin Neurophysiol. 1994 Jun;90(6):444–49.CrossRefGoogle ScholarPubMed
Wolpaw, JR, Birbaumer, N, McFarland, D, Pfurtscheller, G, Vaughan, T. Brain-computer interfaces for communication and control. Clinical Neurophysiology. 2002;113:767–91.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • References
  • Rajesh P. N. Rao, University of Washington
  • Book: Brain-Computer Interfacing
  • Online publication: 05 October 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139032803.021
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • References
  • Rajesh P. N. Rao, University of Washington
  • Book: Brain-Computer Interfacing
  • Online publication: 05 October 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139032803.021
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • References
  • Rajesh P. N. Rao, University of Washington
  • Book: Brain-Computer Interfacing
  • Online publication: 05 October 2013
  • Chapter DOI: https://doi.org/10.1017/CBO9781139032803.021
Available formats
×