Brain-Computer Interfaces (BCI): Restoration of Movement and Thought from Neuroelectric and Metabolic Brain Activity

  • Surjo R. Soekadar
  • Klaus Haagen
  • Niels Birbaumer
Part of the Understanding Complex Systems book series (UCS)


This chapter provides an overview of the scientific and clinical progress in the development of non-invasive and invasive brain-computer interfaces (BCI). BCI uses electric, magnetic or metabolic brain activity for the activation and control of external devices and computers. Clinically, until now it has been successfully used as a communication system for totally paralyzed patients (“locked-in patients”), in restoration of movement after stroke or spinal cord injury and the treatment of epilepsy for example. Here we emphasize that BCI technology is a powerful tool to systematically induce neuroplastic changes and therefore has a significant potential to promote innovative approaches in neurorehabilitation. After a short introduction, the mechanisms underlying BCI control will be outlined and an overview of the available invasive and non-invasive BCI systems will be given. The differences and challenges in the use of BCI technology in healthy and patients with neurological disorders will be sketched. Newly developed approaches (i.e., using functional magnetic resonance imaging (fMRI) and near infrared spectroscopy (NIRS) to manipulate very localized and subcortical brain changes) and diverse applications of BCIs will be introduced. Besides a critical discussion of limitations and problems in BCI research and clinical application, ethical and quality of life issues will be addressed. The chapter ends with some remarks on future directions in the development of BCI systems introducing invasive and non-invasive neurostimulation techniques that can coequally initiate, enhance or stabilize neuroplastic changes induced by BCI use resulting in behavioral benefits.


Amyotrophic Lateral Sclerosis Transcranial Magnetic Stimulation Deep Brain Stimulation Amyotrophic Lateral Sclerosis Patient Neuroplastic Change 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Albert S, Rabkin J, Del Bene M, Tider M, Mitsumoto H (2005) Wish to die in end-stage ALS. Neurology, 65:68–74CrossRefGoogle Scholar
  2. 2.
    Bandura A (1969) Social learning of moral judgements. Journal of Personality and Social Psychology, 11(3): 275–279CrossRefGoogle Scholar
  3. 3.
    Berger H (1929) Ueber das Elektrenkephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten, 87:527–570CrossRefGoogle Scholar
  4. 4.
    Birbaumer N (1999) Slow cortical potentials: Plasticity, operant control, and behavioral effects. The Neuroscientist, 5(2):74–78CrossRefGoogle Scholar
  5. 5.
    Birbaumer N (2006a) Brain-computer-interface research: Coming of age. Clinical Neurophysiology, 117:479–483CrossRefGoogle Scholar
  6. 6.
    Birbaumer N (2006b) Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control. Psychophysiology, 43:517–532CrossRefGoogle Scholar
  7. 7.
    Birbaumer N, Cohen LG (2007) Brain-computer interfaces: Communication and restoration of movement in paralysis. Journal of Physiology, 579:621–636CrossRefGoogle Scholar
  8. 8.
    Birbaumer N, Kimmel H (Eds.) (1979) Biofeedback and Self-Regulation. Hillsdale: ErlbaumGoogle Scholar
  9. 9.
    Birbaumer N, Schmidt RF (2005) Biologische Psychologie (6th ed). Berlin Heidelberg New York: SpringerGoogle Scholar
  10. 10.
    Birbaumer N, Elbert T, Rockstroh B, Lutzenberger W (1986) Biofeedback of slow cortical potentials in attentional disorders. In W.C. McCallum, R. Zappoli, and F. Denoth (Eds.), Cerebral Psychophysiology: Studies in Event-Related Potentials (pp. 440–442). Amsterdam: ElsevierGoogle Scholar
  11. 11.
    Birbaumer N, Elbert T, Canavan A, Rockstroh B (1990) Slow potentials of the cerebral cortex and behavior. Physiological Reviews, 70:1–41Google Scholar
  12. 12.
    Birbaumer N, Roberts L, Lutzenberger W, Rockstroh B, Elbert T (1992) Area-specific self-regulation of slow cortical potentials on the sagittal midline and its effects on behavior. Electroencephalography and Clinical Neurophysiology, 84:353–361CrossRefGoogle Scholar
  13. 13.
    Birbaumer N, Flor H, Cevey B, Dworkin B, Miller NE (1994) Behavioral treatment of scoliosis and kyphosis. Journal of Psychosomatic Research, 6:623–628CrossRefGoogle Scholar
  14. 14.
    Birbaumer N, Flor H, Lutzenberger W, Elbert T (1995) Chaos and order in the human brain. In G. Karmos and M. Molnar (Eds.), Perspectives of Event-Related Potentials Research (EEG Suppl. 44) (pp. 450–459). Amsterdam: ElsevierGoogle Scholar
  15. 15.
    Birbaumer N, Ghanayim N, Hinterberger T, Iversen I, Kotchoubey B, Kübier A, Perelmouter J, Taub E, Flor H (1999) A spelling device for the paralysed. Nature, 398:97–298CrossRefGoogle Scholar
  16. 16.
    Birbaumer N, Veit R, Lotze M, Erb M, Hermann C, Grodd W, Flor H (2005) Deficient fear conditioning in psychopathy: A functional magnetic resonance imaging study. Archives of General Psychiatry, 62:799–805CrossRefGoogle Scholar
  17. 17.
    Breitbart W, Rosenfeld B, Penin H (2000) Depression, hopelessness, and desire for hastened death in terminally ill patients with cancer. Journal of American Medical Association, 284:2907–2911CrossRefGoogle Scholar
  18. 18.
    Caria A, Veit R, Sitaram R, Lotze M, Weiskopf N, Grodd W, Birbaumer N (2007) Regulation of anterior insular cortex activity using real-time fMRI. NeuroImage, 35:1238–1246CrossRefGoogle Scholar
  19. 19.
    Cohen H, Kaplan Z, Kotier M, et al. (2004) Repetitive transcranial magnetic stimulation of the right dorsolateral prefrontal cortex in posttraumatic stress disorder: A double-blind, placebo-controlled study. American Journal of Psychiatry, 161:515–524CrossRefGoogle Scholar
  20. 20.
    Cuthbert B, Kristeller J, Simons R, Hodes R, Lang PJ (1981) Strategies of arousal control: Biofeedback, meditation, and motivation. Journal of Experimental Psychology: General, 110(4):518–546CrossRefGoogle Scholar
  21. 21.
    DeCharms RC, Maeda F, Glover GH, Ludlow D, Pauly JM, Soneji D, Gabrieli JD, Mackey SC (2005) Control over brain activation and pain learned by using real-time functional MRI. Proceedings of the National Academy of Sciences, USA, 102(51):18626–18631CrossRefGoogle Scholar
  22. 22.
    Donchin E (1981) Surprise!...Surprise? Psychophysiology, 18:493–513CrossRefGoogle Scholar
  23. 23.
    Donoghue JP (2002) Connecting cortex to machines: Recent advances in brain interfaces. Nature Neuroscience, 5:1085–1088CrossRefGoogle Scholar
  24. 24.
    Dworkin BR, Miller NE (1986) Failure to replicate visceral learning in the acute curarized rat preparation. Behavioral Neuroscience, 100:299–314CrossRefGoogle Scholar
  25. 25.
    Dworkin B, Miller NE, Dworkin S, Birbaumer N, Brines M, Jonas S, Schwentker E, Graham J (1985) Behavioral method for the treatment of idiopathic scoliosis. Proceedings of the National Academy of Sciences, USA, 82:2493–2497CrossRefGoogle Scholar
  26. 26.
    Elbert T, Rockstroh B, Lutzenberger W, Birbaumer N (Eds.) (1984) Self-Regulation of the Brain and Behavior. New York: SpringerGoogle Scholar
  27. 27.
    Engel BT (1981) Clinical biofeedback: A behavioral analysis. Neuroscience and Biobehavioral Reviews, 5(3):397–400CrossRefMathSciNetGoogle Scholar
  28. 28.
    Farwell LA, Donchin E (1988) Talking off the top of your head: Toward a mental prosthesis utilizing event-related brain potentials. Electroencephalography and Clinical Neurophysiology, 70:510–523CrossRefGoogle Scholar
  29. 29.
    Flor H, Birbaumer N (1993) Comparison of the efficacy of EMG biofeed-back, cognitive behavior therapy, and conservative medical interventions in the treatment of chronic musculoskeletal pain. Journal of Consulting & Clinical Psychology, 61(4):653–658CrossRefGoogle Scholar
  30. 30.
    Fregni F, Boggio PS, Mansur CG, Wagner T, Ferreira MJ, Lima MC, Rigonatti SP, Marcolin MA, Freedman SD, Nitsche MA, Liebetanz D, Antal A, Lang N, Tergau F, Paulus W (2003) Modulation of cortical excitability by weak direct current stimulation-technical, safety and functional aspects. Supplements of Clinical Neurophysiology, 56:255–276CrossRefGoogle Scholar
  31. 31.
    Fregni F, Simon DK, Wu A, Pascual-Leone A (2005) Non-invasive brain stimulation for Parkinson’s disease: A systematic review and meta-analysis of the literature. Journal of Neurology, Neurosurgery, and Psychiatry, 76:1614–1623CrossRefGoogle Scholar
  32. 32.
    Fuchs T, Birbaumer N, Lutzenberger W, Gruzelier JH, Kaiser J (2003) Neurofeed back training for attention-deficit/hyperactivity disorder in children: A comparison with methylphenidate. Applied Psychophysiology and Biofeedback, 28(1):1–12CrossRefGoogle Scholar
  33. 33.
    Gallese V, Keysers C, Rizzolatti G (2004) A unifying view of the basis of social cognition. Trends in Cognitive Sciences, 8(9):396–403CrossRefGoogle Scholar
  34. 34.
    Gastaut H (1952) Electrocorticographic study of the reactivity of rolandic rhythm. Review Neurologique (Paris), 87(2):176–182Google Scholar
  35. 35.
    Gastaut H, Terzian H, Gastaut Y (1952) Study of a little electroencephalographic activity: Rolandic arched rhythm. Marseille Medical, 89(6):296–310Google Scholar
  36. 36.
    Giacobbe P, Kennedy SH (2006) Deep brain stimulation for treatment-resistant depression: A psychiatric perspective. Current Psychiatry Reports, 8:437–444CrossRefGoogle Scholar
  37. 37.
    Henderson JM, Lad SP (2006) Motor cortex stimulation and neuropathic facial pain. Neurosurgical Focus, 15(21):E6Google Scholar
  38. 38.
    Hinterberger T, Veit R, Strehl U, Trevorrow T, Erb M, Kotchoubey B, Flor H, Birbaumer N (2003) Brain areas activated in fMRI during self regulation of slow cortical potentials (SCPs). Experimental Brain Research, 152:113–122CrossRefGoogle Scholar
  39. 39.
    Hinterberger T, Weiskopf N, Veit R, Wilhelm B, Betta E, Birbaumer N (2004) An EEG-driven brain-computer-interface combined with functional magnetic resonance imaging (fMRI). IEEE Transactions on Biomedical Engineering, 51(6):971–974CrossRefGoogle Scholar
  40. 40.
    Hinterberger T, Birbaumer N, Flor H (2005a) Assessment of cognitive function and communication ability in a completely locked-in patient. Neurology, 64:1307–1308Google Scholar
  41. 41.
    Hinterberger T, Veit R, Wilhelm B, Weiskopf N, Vatine J-J, Birbaumer N (2005b) Neuronal mechanisms underlying control of a brain-computer-interface. European Journal of Neuroscience, 21:3169–3181CrossRefGoogle Scholar
  42. 42.
    Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, Branner A, Chen D, Penn RD, Donoghue JP (2006) Neural ensemble control of prosthetic devices by a human with tetraplegia. Nature, 442:164–171CrossRefGoogle Scholar
  43. 43.
    Hoelzl R, Whitehead W (Eds) (1983) Psychophysiology of the Gastrointestinal Tract. New York: Plenum PressGoogle Scholar
  44. 44.
    Hoffman RE, Gueorguieva R, Hawkins KA, et al. (2005) Temporoparietal transcranial magnetic stimulation for auditory hallucinations: Safety, efficacy and moderators in a fifty patient sample. Biological Psychiatry, 58, 97–104CrossRefGoogle Scholar
  45. 45.
    Hummel FC, Cohen LG (2006) Non-invasive brain stimulation: A new strategy to improve neuro-rehabilitation after stroke? Lancet Neurology, 5, 708–712CrossRefGoogle Scholar
  46. 46.
    Hummel F et al. (2005) Effects of non-invasive cortical stimulation on skilled motor function in chronic stroke. Brain, 128:490–499CrossRefGoogle Scholar
  47. 47.
    Jackson A, Mavoori J, Fetz EE (2006) Long-term motor cortex plasticity induced by an electronic neural implant. Nature, 444:56–60CrossRefGoogle Scholar
  48. 48.
    Jorgensen HS, Nakayama H, Raaschou HO, Vive-Larsen, J, Stoier M, Olsen TS (1995a) Outcome and time course of recovery in stroke. Part II: Time course of recovery. The Copenhagen Stroke Study. Archives of Physical Medicine and Rehabilitation, 76:406–412. Doi: 10.1016/S0003-9993(95)80568-0CrossRefGoogle Scholar
  49. 49.
    Jorgensen HS, Nakayama H, Raaschou HO, Vive-Larsen J, Stoier M, Olsen TS (1995b) Outcome and time course of recovery in stroke. Part I: Outcome. The Copenhagen Stroke Study. Archives of Physical Medicine and Rehabilitation, 76:399–405CrossRefGoogle Scholar
  50. 50.
    Karim AA, Kammer T, Lotze M, Nitsche MA, Godde B, Hinterberger T, Cohen LG, Birbaumer N (2004) Effects of TMS and tDCS on the physiological Regulation of cortical excitability in a Brain-Computer Interface. Biomedical Engineering 49(l):55–57Google Scholar
  51. 51.
    Kennedy PR, Kirby MT, Moore MM, King B, Mallory A (2004) Computer control using human intracortical local field potentials. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 12(3):339–344CrossRefGoogle Scholar
  52. 52.
    Khedr EM, Ahmed MA, Fathy N, Rothwell JC (2005) Therapeutic trial of repetitive transcranial magnetic stimulation after acute ischemic stroke. Neurology, 65:466–468CrossRefGoogle Scholar
  53. 53.
    Kotchoubey B, Strehl U, Uhlmann C, Holzapfel S, König M, Fröscher W, Blankenhorn V, Birbaumer N (2001) Modification of slow cortical potentials in patients with refractory epilepsy: A controlled outcome study. Epilepsia, 42(3):406–416CrossRefGoogle Scholar
  54. 54.
    Kübler A, Kotchoubey B, Kaiser J, Wolpaw J, Birbaumer N (2001a) Braincomputer communication: Unlocking the locked-in. Psychological Bulletin, 127(3):358–375CrossRefGoogle Scholar
  55. 55.
    Kübler A, Neumann N, Kaiser J, Kotchoubey B, Hinterberger T, Birbaumer N (2001b) Brain-computer communication: Self-regulation of slow cortical potentials for verbal communication. Archives of Physical Medicine and Rehabilitation, 82:1533–1539CrossRefGoogle Scholar
  56. 56.
    Kübler A, Winter S, Ludolph AC, Hautzinger M, Birbaumer N (2005a) Severity of depressive symptoms and quality of life in patients with amyotrophic lateral sclerosis. Neurorehabilitation and Neural Repair, 19(3):182–193CrossRefGoogle Scholar
  57. 57.
    Kübler A, Nijboer F, Mellinger J, Vaughan TM, Pawelzik H, Schalk G, McFarland DJ, Birbaumer N, Wolpaw JR (2005b) Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. Neurology, 64:1775–1777CrossRefGoogle Scholar
  58. 58.
    Lang P, Bradley M, Cuthbert B (1999) International Affective Picture System. Gainesville, Fl: The Center for Research in Psychophysiology, University of FloridaGoogle Scholar
  59. 59.
    Lefaucheur JP (2004) Transcranial magnetic stimulation in the management of pain. Clinical Neurophysiology (Supplement), 57:737–748Google Scholar
  60. 60.
    Logothetis N, Pauls J, Augath M, Trinath T, Oeltermann A (2001) Neurophysiological investigation of the basis of the fMRI signal. Nature, 412:150–157CrossRefGoogle Scholar
  61. 61.
    Lulé D, Kurt A, Jürgens R, Kassubek J, Diekmann V, Kraft E, Neumann N, Ludolph AC, Birbaumer N, Anders S (2005) Emotional responding in amyotrophic lateral sclerosis. Journal of Neurology, 252:1517–1524CrossRefGoogle Scholar
  62. 62.
    Lutzenberger W, Birbaumer N, Elbert T (1980) Self-regulation of slow cortical potentials in patients with frontal lobe lesions. In: Kornhuber H, Deecke L (eds) Motivation, Motor and Sensory Processes of the Brain, Elsevier, AmsterdamGoogle Scholar
  63. 63.
    Mansur CG, Fregni F, Boggio PS et al. (2005) A sham stimulation-controlled trial of rTMS of the unaffected hemisphere in stroke patients. Neurology, 64:1802–1804CrossRefGoogle Scholar
  64. 64.
    McGrady A, Olson P, Kroon J (1995) Biobehavioral treatment of essential hypertension. In M. Schwartz (Ed.) Biofeedback (2nd ed), New York: GuilfordGoogle Scholar
  65. 65.
    Miller N (1969) Learning of visceral and glandular responses. Science, 163:434–445CrossRefGoogle Scholar
  66. 66.
    Miniussi C, Bonato C, Bignotti S et al. (2005) Repetitive transcranial magnetic simulation (rTMS) at high and low frequency: An efficacious therapy for major drug-resistant depression? Clinical Neurophysiology, 116:1062–1071CrossRefGoogle Scholar
  67. 67.
    Nicolelis MA (2003) Brain-machine interfaces to restore motor function and probe neural circuits. Nature Reviews Neuroscience, 4(5):417–422CrossRefGoogle Scholar
  68. 68.
    Pfurtscheller G, Neuper C, Birbaumer N (2005) Human brain-computer interface (BCI). In A. Riehle and E. Vaadia (Eds.), Motor Cortex in Voluntary Movements. A Distributed System for Distributed Functions (pp. 367–401). Boca Raton: CRC PressGoogle Scholar
  69. 69.
    Plewnia C, Reimold M, Najib A, Reischl G, Plontke SK, Gerloff C (2007) Moderate therapeutic efficacy of positron emission tomography-navigated repetitive transcranial magnetic stimulation for chronic tinnitus: A randomised, controlled pilot study. Journal of Neurology, Neurosurgery, and Psychiatry. 78:152–156CrossRefGoogle Scholar
  70. 70.
    Quill TE (2005) ALS, depression, and desire for hastened death: (How) are they related? Neurology, 65:1CrossRefGoogle Scholar
  71. 71.
    Rockstroh B, Elbert T, Birbaumer N, Lutzenberger W (1989) Slow Brain Potentials and Behavior (2. Aufl.). Baltimore, MD: Urban & SchwarzenbergGoogle Scholar
  72. 72.
    Rockstroh B, Elbert T, Birbaumer N, Wolf P, Düchting-Röth A, Reker M et al. (1993) Cortical self-regulation in patients with epilepsies. Epilepsy Research, 14:63–72CrossRefGoogle Scholar
  73. 73.
    Scherberger H et al. (2005) Cortical local field potentials encodes movement intentions in the posterior parietal cortex. Neuron, 46:347–354CrossRefGoogle Scholar
  74. 74.
    Schneider F, Rockstroh B, Heimann H, Lutzenberger W, Mattes R, Elbert T, Birbaumer N, Bartels M (1992) Self-regulation of slow cortical potentials in psychiatric patients: Schizophrenia. Biofeedback & Self-Regulation, 17(4):277–292CrossRefGoogle Scholar
  75. 75.
    Schwartz AB (2007) Useful signals from motor cortex. Journal of Physiology, 579:581–601CrossRefGoogle Scholar
  76. 76.
    Sellers EW, Donchin EA (2006) A P300 based brain-computer interface: Initial tests by ALS patients. Clinical Neurophysiology, 117(3):538–548CrossRefGoogle Scholar
  77. 77.
    Skinner F (1953) Science and Human Behavior. New York: MacmillanGoogle Scholar
  78. 78.
    Sterman MB (1977) Sensorimotor EEG operant conditioning: Experimental and clinical effects. The Pavlovian Journal of Biological Science, 12(2):63–92Google Scholar
  79. 79.
    Sterman MB (1981) EEG biofeedback: Physiological behavior modification. Neuroscience and Biobehavioral Reviews, 5:405–412CrossRefGoogle Scholar
  80. 80.
    Sterman MB, Clemente CD (1962a) Forebrain inhibitory mechanisms: Cortical synchronization induced by basal forebrain stimulation. Experimental Neurology, 6:91–102CrossRefGoogle Scholar
  81. 81.
    Sterman MB, Clemente CD (1962b) Forebrain inhibitory mechanisms: Sleep patterns induced by basal forebrain stimulation in the behaving cat. Experimental Neurology, 6:103–117CrossRefGoogle Scholar
  82. 82.
    Sterman MB, and Friar L (1972) Suppression of seizures in an epileptic following sensorimotor EEG feedback training. Electroencephalography and Clinical Neurophysiology, 33(l):89–95CrossRefGoogle Scholar
  83. 83.
    Strehl U, Leins U, Goth G, Klinger C, Hinterberger T, Birbaumer N (2006) Self-regulation of slow cortical potentials: A new treatment for children with attention-deficit/hyperactivity disorder. Pediatrics, 118:1530–1540CrossRefGoogle Scholar
  84. 84.
    Taylor DM, Tillery SI, Schwartz AB (2002) Direct cortical control of 3D neuroprosthetic devices. Science, 296:1829–1832CrossRefGoogle Scholar
  85. 85.
    Theodore WH (2003) Transcranial magnetic stimulation in epilepsy. Epilepsy Currents, 3:191–197CrossRefGoogle Scholar
  86. 86.
    Weiskopf N, Veit R, Erb M, Mathiak K, Grodd W, Goebel R, Birbaumer N (2003) Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): Methodology and exemplary data. Neurolmage, 19:577–586CrossRefGoogle Scholar
  87. 87.
    Weiskopf N, Scharnowsi F, Veit R, Goebel R, Birbaumer N, Mathiak K (2005) Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI). Journal of Physiology, Paris, 98:357–373CrossRefGoogle Scholar
  88. 88.
    Weiskopf N, Sitaram R, Josephs O, Veit R, Scharnowski F, Goebel R, Birbaumer N, Deichmann I, Mathiak K (2007) Real-time functional magnetic resonance imaging: Methods and applications. Magnetic Resonance Imaging 25:898–1003CrossRefGoogle Scholar
  89. 89.
    Wilhelm B, Jordan M, Birbaumer N (2006) Communication in locked-in syndrome: Effects of imagery on salivary pH. Neurology, 67:534–535CrossRefGoogle Scholar
  90. 90.
    Wolpaw JR (2007) Brain-computer interfaces as new brain output pathways. Journal of Physiology, 579:613–619CrossRefGoogle Scholar
  91. 91.
    Wolpaw JR, McFarland DJ (2004) Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the National Academy of Science USA, 101(51): 17849–17854CrossRefGoogle Scholar
  92. 92.
    Yoo SS, Fairneny T, Chen NK, Choo SE, Panych LP, Park H, Lee SY, Jolesz FA (2004) Brain-computer interface using fMRI: spatial navigation by thoughts. Neuroreport, 15:1591–1595CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Surjo R. Soekadar
    • 1
  • Klaus Haagen
    • 2
  • Niels Birbaumer
    • 3
    • 4
  1. 1.Neurostimulation Unit, Department of Psychiatry and PsychotherapyUniversity of TübingenTübingenGermany
  2. 2.Department of EconomyUniversity of TrentoTrentoItaly
  3. 3.Institute of Medical Psychology and Behavioral NeurobiologyUniversity of TübingenTübingenGermany
  4. 4.Human Cortical PhysiologyNational Institutes of Health (NIH), NINDSBethesdaUSA

Personalised recommendations