Brain-machine interfaces: an overview

Mikhail Lebedev 1
  • 1 Duke University, Durham, North Carolina, USA

Abstract

Brain-machine interfaces (BMIs) hold promise to treat neurological disabilities by linking intact brain circuitry to assistive devices, such as limb prostheses, wheelchairs, artificial sensors, and computers. BMIs have experienced very rapid development in recent years, facilitated by advances in neural recordings, computer technologies and robots. BMIs are commonly classified into three types: sensory, motor and bidirectional, which subserve motor, sensory and sensorimotor functions, respectively. Additionally, cognitive BMIs have emerged in the domain of higher brain functions. BMIs are also classified as noninvasive or invasive according to the degree of their interference with the biological tissue. Although noninvasive BMIs are safe and easy to implement, their information bandwidth is limited. Invasive BMIs hold promise to improve the bandwidth by utilizing multichannel recordings from ensembles of brain neurons. BMIs have a broad range of clinical goals, as well as the goal to enhance normal brain functions.

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  • [1] Lebedev M.A., Nicolelis M.A., Brain-machine interfaces: past, present and future, 2006, Trends Neurosci., 29, 536–546 http://dx.doi.org/10.1016/j.tins.2006.07.004

  • [2] Nicolelis M.A., Lebedev M.A., Principles of neural ensemble physiology underlying the operation of brain-machine interfaces, Nat. Rev. Neurosci., 2009, 10, 530–540 http://dx.doi.org/10.1038/nrn2653

  • [3] Schwartz A.B., Cui X.T., Weber D.J., Moran D.W., Brain-controlled interfaces: movement restoration with neural prosthetics, Neuron, 2006, 52, 205–220 http://dx.doi.org/10.1016/j.neuron.2006.09.019

  • [4] McFarland D.J., Krusienski D.J., Wolpaw J.R., Brain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms, Prog. Brain Res., 2006, 159, 411–419 http://dx.doi.org/10.1016/S0079-6123(06)59026-0

  • [5] Hatsopoulos N.G., Donoghue J.P., The science of neural interface systems, Annu. Rev. Neurosci., 2009, 32, 249–266 http://dx.doi.org/10.1146/annurev.neuro.051508.135241

  • [6] Carmena J.M., Lebedev M.A., Crist R.E., O’Doherty J.E., Santucci D.M., Dimitrov D.F., et al., PloS Biol., 2003, 1, E42 http://dx.doi.org/10.1371/journal.pbio.0000042

  • [7] Tangermann M., Krauledat M., Grzeska K., Sagebaum M., Blankertz B., Vidaurre C., et al., Playing pinball with non-invasive BCI, Adv. Neural Inf. Process. Syst., 2009, 21, 1641–1648

  • [8] Lin C.T., Chang C.J., Lin B.S., Hung S.H., Chao C.F., Wang I.J., A real-time wireless brain-computer interface system for drowsiness detection, IEEE Trans. Biomed. Circuits Syst., 2010, 4, 214–222 http://dx.doi.org/10.1109/TBCAS.2010.2046415

  • [9] Lilly J.C., Distribution of’ motor’ functions in the cerebral cortex in the conscious, intact monkey, Science, 1956, 124, 937

  • [10] Evarts E.V., Motor cortex reflexes associated with learned movement, Science, 1973, 179, 501–503 http://dx.doi.org/10.1126/science.179.4072.501

  • [11] O’Doherty J.E., Lebedev M.A., Ifft P.J., Zhuang K.Z., Shokur S., Bleuler H., et al., Active tactile exploration using a brain-machine-brain interface, Nature, 2011, 479, 228–231 http://dx.doi.org/10.1038/nature10489

  • [12] Shannon R.V., Advances in auditory prostheses, Curr. Opin. Neurol., 2012, 25, 61–66 http://dx.doi.org/10.1097/WCO.0b013e32834ef878

  • [13] Wilson B.S., Dorman M.F., Cochlear implants: a remarkable past and a brilliant future, Hear. Res., 2008, 242, 3–21 http://dx.doi.org/10.1016/j.heares.2008.06.005

  • [14] Farah M.J., Emerging ethical issues in neuroscience, Nat. Neurosci., 2002, 5, 1123–1129 http://dx.doi.org/10.1038/nn1102-1123

  • [15] Vlek R.J., Steines D., Szibbo D., Kübler A., Schneider M.J., Haselager P., et al., Ethical issues in brain-computer interface research, development, and dissemination, J. Neurol. Phys. Ther., 2012, 36, 94–99 http://dx.doi.org/10.1097/NPT.0b013e31825064cc

  • [16] Andersen R.A., Hwang E.J., Mulliken G.H., Cognitive neural prosthetics. Annu. Rev. Psychol., 2010, 61, 169–190 http://dx.doi.org/10.1146/annurev.psych.093008.100503

  • [17] Berger T.W., Ahuja A., Courellis S.H., Deadwyler S.A., Erinjippurath G., Gerhardt G.A., et al., IEEE Eng. Med. Biol. Mag., 2005, 24, 30–44 http://dx.doi.org/10.1109/MEMB.2005.1511498

  • [18] Dennett D.C., Consciousness explained, Back Bay Books, New York, NY, USA, 1992 [This book contains a description of the pioneering demonstration of a brain-machine interface by Grey Walter]

  • [19] Frank K., Some approaches to the technical problem of chronic excitation of peripheral nerve, Ann. Otol. Rhinol. Laryngol., 1968, 77, 761–771

  • [20] Humphrey D.R., Schmidt E.M., Thompson W.D., Predicting measures of motor performance from multiple cortical spike trains, Science, 1970, 170, 758–762 http://dx.doi.org/10.1126/science.170.3959.758

  • [21] Schmidt E.M., Single neuron recording from motor cortex as a possible source of signals for control of external devices, Ann. Biomed. Eng., 1980, 8, 339–349 http://dx.doi.org/10.1007/BF02363437

  • [22] Fetz E.E., Operant conditioning of cortical unit activity, Science, 1969, 163, 955–958 http://dx.doi.org/10.1126/science.163.3870.955

  • [23] Brindley G.S., Lewin W.S., The sensations produced by electrical stimulation of the visual cortex, J. Physiol., 1968, 196, 479–493

  • [24] Dobelle W.H., Mladejovsky M.G., Girvin J.P., Artifical vision for the blind: electrical stimulation of visual cortex offers hope for a functional prosthesis, Science, 1974, 183, 440–444 http://dx.doi.org/10.1126/science.183.4123.440

  • [25] Chapin J.K., Moxon K.A., Markowitz R.S., Nicolelis M.A., Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex, Nat. Neurosci., 1999, 2, 664–670 http://dx.doi.org/10.1038/10223

  • [26] Wessberg J., Stambaugh C.R., Kralik J.D., Beck P.D., Laubach M., Chapin J.K., et al., Real-time prediction of hand trajectory by ensembles of cortical neurons in primates, Nature, 2000, 408, 361–365 http://dx.doi.org/10.1038/35042582

  • [27] Lebedev M.A., Carmena J.M., O’Doherty J.E., Zacksenhouse M., Henriquez C.S., Principe J.C., et al., Cortical ensemble adaptation to represent velocity of an artificial actuator controlled by a brainmachine interface, J. Neurosci., 2005, 25, 4681–4693 http://dx.doi.org/10.1523/JNEUROSCI.4088-04.2005

  • [28] Fitzsimmons N.A., Lebedev M.A., Peikon I.D., Nicolelis M.A., Extracting kinematic parameters for monkey bipedal walking from cortical neuronal ensemble activity, Front. Integr. Neurosci., 2009, 3, 3 http://dx.doi.org/10.3389/neuro.07.003.2009

  • [29] Ifft P.J., Shokur S., Li Z., Lebedev M.A., Nicolelis M.A., A brain-machine interface enables bimanual arm movements in monkeys, Sci. Transl. Med., 2013, 5, 210ra154 http://dx.doi.org/10.1126/scitranslmed.3006159

  • [30] Kennedy P.R., Bakay RA., Restoration of neural output from a paralyzed patient by a direct brain connection, Neuroreport, 1998, 9, 1707–1711 http://dx.doi.org/10.1097/00001756-199806010-00007

  • [31] Hochberg L.R., Serruya M.D., Friehs G.M., Mukand J.A., Saleh M., Caplan A.H., et al., Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 2006, 442, 164–171 http://dx.doi.org/10.1038/nature04970

  • [32] Hochberg L.R., Bacher D., Jarosiewicz B., Masse N.Y., Simeral J.D., Vogel J., et al., Reach and grasp by people with tetraplegia using a neurally controlled robotic arm, Nature, 2012, 485, 372–375 http://dx.doi.org/10.1038/nature11076

  • [33] Taylor D.M., Tillery S.I., Schwartz A.B., Direct cortical control of 3D neuroprosthetic devices, Science, 2002, 296, 1829–1832 http://dx.doi.org/10.1126/science.1070291

  • [34] Velliste M., Perel S., Spalding M.C., Whitford A.S., Schwartz A.B., Cortical control of a prosthetic arm for self-feeding, Nature, 2008, 453, 1098–1101 http://dx.doi.org/10.1038/nature06996

  • [35] Collinger J.L., Wodlinger B., Downey J.E., Wang W., Tyler-Kabara E.C., Weber D.J., et al., High-performance neuroprosthetic control by an individual with tetraplegia, Lancet, 2013, 381, 557–564 http://dx.doi.org/10.1016/S0140-6736(12)61816-9

  • [36] Mountcastle V.B., The sensory hand: neural mechanisms of somatic sensation, Harvard University Press, Cambridge, MA, USA, 2005

  • [37] Hubel D.H., Wiesel T.N., Brain and visual perception: the story of a 25- year collaboration, Oxford University Press, Oxford, UK, 2005

  • [38] Wise S.P., The primate premotor cortex: past, present, and preparatory, Annu. Rev. Neurosci, 1985, 8, 1–19 http://dx.doi.org/10.1146/annurev.ne.08.030185.000245

  • [39] Kalaska J.F., Scott S.H., Cisek P., Sergio L.E., Cortical control of reaching movements, Curr. Opin. Neurobiol., 1997, 7, 849–859 http://dx.doi.org/10.1016/S0959-4388(97)80146-8

  • [40] Georgopoulos A.P., Kalaska J.F., Caminiti R., Massey J.T., On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex, J. Neurosci., 1982, 2, 1527–1537

  • [41] Georgopoulos A.P., Lurito J.T., Petrides M., Schwartz A.B., Massey J.T., Mental rotation of the neuronal population vector, Science, 1989, 243, 234–236 http://dx.doi.org/10.1126/science.2911737

  • [42] Moritz C.T., Perlmutter S.I., Fetz E.E., Direct control of paralysed muscles by cortical neurons, Nature, 2008, 456, 639–642 http://dx.doi.org/10.1038/nature07418

  • [43] Quiroga R.Q., Reddy L., Kreiman G., Koch C., Fried I., Invariant visual representation by single neurons in the human brain, Nature, 2005, 435, 1102–1107 http://dx.doi.org/10.1038/nature03687

  • [44] Nicolelis M.A., Beyond boundaries: the new neuroscience of connecting brains with machines - and how it will change our lives, Times Books, New York, NY, USA, 2011

  • [45] Haykin S., Adaptive filter theory (4th Ed.), Prentice Hall, Upper Saddle River, New Jersey, 2001

  • [46] Li Z., O’Doherty J.E., Hanson T.L., Lebedev M.A., Henriquez C.S., Nicolelis M.A., Unscented Kalman filter for brain-machine interfaces, PLoS One, 2009, 4, e6243 http://dx.doi.org/10.1371/journal.pone.0006243

  • [47] Sussillo D., Nuyujukian P., Fan J.M., Kao J.C., Stavisky S.D., Ryu S., et al., A recurrent neural network for closed-loop intracortical brainmachine interface decoders, J. Neural Eng., 2012, 9, 026027 http://dx.doi.org/10.1088/1741-2560/9/2/026027

  • [48] Birbaumer N., Ghanayim N., Hinterberger T., Iversen I., Kotchoubey B., Kübler A., et al., A spelling device for the paralysed, Nature, 1999, 398, 297–298 http://dx.doi.org/10.1038/18581

  • [49] Birbaumer N., Murguialday A.R., Cohen L., Brain-computer interface in paralysis, Curr. Opin. Neurol., 2008, 21, 634–638 http://dx.doi.org/10.1097/WCO.0b013e328315ee2d

  • [50] Sherrington C.S., The integrative action of the nervous system, Charles Scribner’s Sons, New York, NY, USA, 1906

  • [51] Guertin P.A., The mammalian central pattern generator for locomotion, Brain Res. Rev., 2009, 62, 45–56 http://dx.doi.org/10.1016/j.brainresrev.2009.08.002

  • [52] Cordo P.J., Gurfinkel V.S., Motor coordination can be fully understood only by studying complex movements, Prog. Brain Res., 2004, 143, 29–38 http://dx.doi.org/10.1016/S0079-6123(03)43003-3

  • [53] Head H., Holmes G., Sensory disturbances from cerebral lesions, Brain, 1911, 34, 102–254 http://dx.doi.org/10.1093/brain/34.2-3.102

  • [54] Kawato M., Internal models for motor control and trajectory planning, Curr. Opin. Neurobiol., 1999, 9, 718–727 http://dx.doi.org/10.1016/S0959-4388(99)00028-8

  • [55] Feldman A.G., Ostry D.J., Levin M.F., Gribble P.L., Mitnitski A.B., Recent tests of the equilibrium-point hypothesis (lambda model), Motor Control, 1998, 2, 189–205

  • [56] Pfurtscheller G., Müller G.R., Pfurtscheller J., Gerner H.J., Rupp R., ‘Thought’—control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia, Neurosci. Lett., 2003, 351, 33–36 http://dx.doi.org/10.1016/S0304-3940(03)00947-9

  • [57] Ethier C., Oby E.R., Bauman M.J., Miller L.E., Restoration of grasp following paralysis through brain-controlled stimulation of muscles, Nature, 2012, 485, 368–371 http://dx.doi.org/10.1038/nature10987

  • [58] Pohlmeyer E.A., Oby E.R., Perreault E.J., Solla S.A., Kilgore K.L., Kirsch R.F., et al., Toward the restoration of hand use to a paralyzed monkey: brain-controlled functional electrical stimulation of forearm muscles, PLoS One, 2009, 4, e5924 http://dx.doi.org/10.1371/journal.pone.0005924

  • [59] Cheron G., Duvinage M., De Saedeleer C., Castermans T., Bengoetxea A., Petieau M., et al., From spinal central pattern generators to cortical network: integrated BCI for walking rehabilitation, Neural Plast., 2012, 375148

  • [60] Presacco A., Forrester L.W., Contreras-Vidal J.L., Decoding intralimb and inter-limb kinematics during treadmill walking from scalp electroencephalographic (EEG) signals, IEEE Trans. Neural Syst. Rehabil. Eng., 2012, 20, 212–219 http://dx.doi.org/10.1109/TNSRE.2012.2188304

  • [61] Courtine G., Gerasimenko Y., van den Brand R., Yew A., Musienko P., Zhong H., et al., Transformation of nonfunctional spinal circuits into functional states after the loss of brain input, Nat. Neurosci., 2009, 12, 1333–1342 http://dx.doi.org/10.1038/nn.2401

  • [62] Iriki A., Tanaka M., Iwamura Y., Coding of modified body schema during tool use by macaque postcentral neurones, Neuroreport, 1996, 7, 2325–2330 http://dx.doi.org/10.1097/00001756-199610020-00010

  • [63] Zacksenhouse M., Lebedev M.A., Carmena J.M., O’Doherty J.E., Henriquez C., Nicolelis M.A., Cortical modulations increase in early sessions with brain-machine interface, PLoS One, 2007, 2, e619 http://dx.doi.org/10.1371/journal.pone.0000619

  • [64] Chase S.M., Kass R.E., Schwartz A.B., Behavioral and neural correlates of visuomotor adaptation observed through a brain-computer interface in primary motor cortex, J. Neurophysiol., 2012, 108, 624–644 http://dx.doi.org/10.1152/jn.00371.2011

  • [65] Galán F., Nuttin M., Lew E., Ferrez P.W., Vanacker G., Philips J., et al., A brain-actuated wheelchair: asynchronous and non-invasive brain-computer interfaces for continuous control of robots, Clin. Neurophysiol., 2008, 119, 2159–2169 http://dx.doi.org/10.1016/j.clinph.2008.06.001

  • [66] Muller-Putz G.R., Pfurtscheller G., Control of an electrical prosthesis with an SSVEP-based BCI, IEEE Trans. Biomed. Eng., 2008, 55, 361–364 http://dx.doi.org/10.1109/TBME.2007.897815

  • [67] Nicolas-Alonso L.F., Gomez-Gil J., Brain computer interfaces, a review, Sensors (Basel), 2012, 12, 1211–1279 http://dx.doi.org/10.3390/s120201211

  • [68] Sellers E.W., Vaughan T.M., Wolpaw J.R., A brain-computer interface for long-term independent home use, Amyotroph. Lateral Scler., 2010, 11, 449–455 http://dx.doi.org/10.3109/17482961003777470

  • [69] Wolpaw J.R., McFarland D.J., Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans, Proc. Natl. Acad. Sci. USA, 2004, 101, 17849–17854 http://dx.doi.org/10.1073/pnas.0403504101

  • [70] Vialatte F.B., Maurice M., Dauwels J., Cichocki A., Steady-state visually evoked potentials: focus on essential paradigms and future perspectives, Prog. Neurobiol., 2010, 90, 418–438 http://dx.doi.org/10.1016/j.pneurobio.2009.11.005

  • [71] Farwell L.A., Donchin E., Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials, Electroencephalogr. Clin. Neurophysiol., 1988, 70, 510–523 http://dx.doi.org/10.1016/0013-4694(88)90149-6

  • [72] Millan J.R., Renkens F., Mouriño J., Gerstner W., Noninvasive brainactuated control of a mobile robot by human EEG, IEEE Trans. Biomed. Eng., 2004, 51, 1026–1033 http://dx.doi.org/10.1109/TBME.2004.827086

  • [73] Tavella M., Leeb R., Rupp R., Millán J. del R., Towards natural noninvasive hand neuroprostheses for daily living, Conf. Proc. IEEE Eng. Med. Biol. Soc., 2010, 126–129

  • [74] Fatourechi M., Bashashati A., Ward R.K., Birch G.E., EMG and EOG artifacts in brain computer interface systems: a survey, Clin. Neurophysiol., 2007, 118, 480–494 http://dx.doi.org/10.1016/j.clinph.2006.10.019

  • [75] Mellinger J., Schalk G., Braun C., Preissl H., Rosenstiel W., Birbaumer N., et al., An MEG-based brain-computer interface (BCI), Neuroimage, 2007, 36, 581–593 http://dx.doi.org/10.1016/j.neuroimage.2007.03.019

  • [76] Sitaram R., Caria A., Birbaumer N., Hemodynamic brain-computer interfaces for communication and rehabilitation, Neural Netw., 2009, 22, 1320–1328 http://dx.doi.org/10.1016/j.neunet.2009.05.009

  • [77] Schott G.D., Penfield’s homunculus: a note on cerebral cartography, J. Neurol. Neurosurg. Psychiatry, 1993, 56, 329–333 http://dx.doi.org/10.1136/jnnp.56.4.329

  • [78] Barton J.J., Disorder of higher visual function, Curr. Opin. Neurol., 2011, 24, 1–5 http://dx.doi.org/10.1097/WCO.0b013e328341a5c2

  • [79] Romo R., Hernández A., Zainos A., Brody C.D., Lemus L., Sensing without touching: psychophysical performance based on cortical microstimulation, Neuron, 2000, 26, 273–278 http://dx.doi.org/10.1016/S0896-6273(00)81156-3

  • [80] Fitzsimmons N.A., Drake W., Hanson T.L., Lebedev M.A., Nicolelis M.A., Primate reaching cued by multichannel spatiotemporal cortical microstimulation, J. Neurosci., 2007, 27, 5593–5602 http://dx.doi.org/10.1523/JNEUROSCI.5297-06.2007

  • [81] Zhang F., Aravanis A.M., Adamantidis A., de Lecea L., Deisseroth K., Circuit-breakers: optical technologies for probing neural signals and systems, Nat. Rev. Neurosci., 2007, 8, 577–581 http://dx.doi.org/10.1038/nrn2192

  • [82] Jones L.A., Tactile communication systems optimizing the display of information, Prog. Brain Res., 2011, 192, 113–128 http://dx.doi.org/10.1016/B978-0-444-53355-5.00008-7

  • [83] Sampaio E., Maris S., Bach-y-Rita P., Brain plasticity:’ visual’ acuity of blind persons via the tongue, Brain Res., 2001, 908, 204–207 http://dx.doi.org/10.1016/S0006-8993(01)02667-1

  • [84] Bach-y-Rita P., Kercel S., Sensory substitution and the humanmachine interface, Trends Cogn. Sci., 2003, 7, 541–546 http://dx.doi.org/10.1016/j.tics.2003.10.013

  • [85] Fernandes R.A., Diniz B., Ribeiro R., Humayun M., Artificial vision through neuronal stimulation, Neurosci. Lett., 2012, 519, 122–128 http://dx.doi.org/10.1016/j.neulet.2012.01.063

  • [86] O’Doherty J.E., Lebedev M.A., Hanson T.L., Fitzsimmons N.A., Nicolelis M.A., A brain-machine interface instructed by direct intracortical microstimulation, Front. Integr. Neurosci., 2009, 3, 20

  • [87] O’Doherty J.E., Lebedev M.A., Li Z., Nicolelis M.A., Virtual actual touch using randomly patterned intracortical microstimulation, IEEE Trans. Neural Syst. Rehabil. Eng., 2012, 20, 85–93 http://dx.doi.org/10.1109/TNSRE.2011.2166807

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