Advances in Clinical and Experimental Medicine

Title abbreviation: Adv Clin Exp Med
JCR Impact Factor (IF) – 2.1
5-Year Impact Factor – 2.2
Scopus CiteScore – 3.4 (CiteScore Tracker 3.4)
Index Copernicus  – 161.11; MEiN – 140 pts

ISSN 1899–5276 (print)
ISSN 2451-2680 (online)
Periodicity – monthly

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Advances in Clinical and Experimental Medicine

2019, vol. 28, nr 8, August, p. 1125–1135

doi: 10.17219/acem/103414

Publication type: review article

Language: English

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Methods of integrating the human nervous system with electronic circuits

Tymoteusz Skok1,A,B,C,D,E,F, Paweł Tabakow2,D,E,F, Krzysztof Chmielak2,D,E,F

1 Student Scientific Circle at the Department of Neurosurgery, Wroclaw Medical University, Poland

2 Department of Neurosurgery, Wroclaw Medical University, Poland

Abstract

In recent years, many attempts have been made to connect electrical circuits with the human nervous system. The objective of type of research was diverse – from the desire to understand the physiology of the nervous system, through attempting to substitute nervous tissue defects with synthetic systems, to creating an interface that allows computers to be controlled directly with one’s thought. Regardless of the original purpose, the creation of any form of such a combination would entail a series of subsequent discoveries, allowing for a real revolution in both theoretical and clinical neuroscience. Computers based on neurons, neurochips or mind prostheses are just some examples of technologies that could soon become part of everyday life. Despite numerous attempts, there is still no interface that meets all the expectations of the scholars. However, many scientific groups seem to be on the right track and their achievements raise extraordinary expectations. This paper evaluates historical theories and contemporary ideas about such interfaces to smoothly describe the major medical and scientific utility of the subject. Thus it presents the main issues surrounding the concept of integrating the human nervous system with electronic circuits.

Key words

brain–computer interface, biosensors, peripheral nerve interface

References (60)

  1. Cobb M. Timeline: Exorcizing the animal spirits. Jan Swammerdam on nerve function. Nat Rev Neurosci. 2002;3(5):395–400.
  2. Sleigh C. Jan Swammerdam’s frogs. Notes Rec R Soc Lond. 2012;66(4):373–392.
  3. Verkhratsky A, Parpura V. History of electrophysiology and the patch clamp. Methods Mol Biol. 2014;1183:1–19.
  4. Wallace W. The vibrating nerve impulse in Newton, Willis and Gassendi: First steps in a mechanical theory of communication. Brain Cogn. 2003;51(1):66–94.
  5. Verkhratsky A, Krishtal OA, Petersen OH. From Galvani to patch clamp: The development of electrophysiology. Pflugers Arch. 2006;453(3):233–247.
  6. Harrar JE. The potentiostat and the voltage clamp. Electrochem Soc Interface. 2013;22(4):42–44.
  7. McNamee MJ, Edwards SD. Transhumanism, medical technology and slippery slopes. J Med Ethics. 2006;32(9):513–518.
  8. Mudry A, Mills M. The early history of the cochlear implant: A retrospective. JAMA Otolaryngol Head Neck Surg. 2013;139(5):446–453.
  9. Durand DM. What is neural engineering? J Neural Eng. 2006;4(4). doi:10.1088/1741-2552/4/4/e01
  10. Finkel LH. Neuroengineering models of brain disease. Annu Rev Biomed Eng. 2000;2(1):577–606.
  11. Vidal JJ. Real-time detection of brain events in EEG. Proc IEEE Inst Electr Electron Eng. 1977;65(5):633–641.
  12. Shih JJ, Krusienski DJ, Wolpaw JR. Brain-computer interfaces in medicine. Mayo Clin Proc. 2012;87(3):268–279.
  13. Anupama HS, Cauvery NK, Lingaraju GM. Brain computer interface and its types – a study. IJASEAT. 2012;3(2):739–745.
  14. Nezamfar H, Salehi SSM, Moghadamfalahi M, Erdogmus D. A context-aware c-VEP-based BCI typing interface using EEG signals. IEEE J-STSP. 2016;10(5):932–941.
  15. Kaufmann T, Herweg A, Kübler A. Toward brain-computer interface based wheelchair control utilizing tactually-evoked event-related potentials. J Neuroeng Rehabil. 2014;11:7.
  16. Sirvent JL, Azorín JM, Iáñez E, Úbeda A, Fernández E. P300-based brain-computer interface for internet browsing. In: Trends in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing. 8th International Conference on Practical Applications of Agents and Multiagent Systems. 2010;615–622.
  17. Pires G, Torres M, Casaleiro N, Nunes U, Castelo-Branco M. Playing Tetris with non-invasive BCI. Paper presented at: the 2011 IEEE 1st International Conference on Serious Games and Applications for Health (SeGAH); November 16–18 2011; Braga, Portugal.
  18. Spüler M. A high-speed brain-computer interface (BCI) using dry EEG electrodes. PLoS One. 2017;12(2):e0172400.
  19. Sitaram R, Caria A, Veit R, et al. fMRI brain-computer interface: A tool for neuroscientific research and treatment. Comput Intell Neurosci. 2007;2007:25487.
  20. Mellinger J, Schalk G, Braun C, et al. An MEG-based brain-computer interface (BCI). Neuroimage. 2007;36(3):581–593.
  21. Schalk G, Leuthardt EC. Brain-computer interfaces using electrocorticographic signals. IEEE Rev Biomed Eng. 2011;4:140–154.
  22. Liu J, Fu T-M, Cheng Z, et al. Syringe-injectable electronics. Nat Nanotechnology. 2015;10(7):629–636.
  23. Kennedy PR, Bakay RA. Restoration of neural output from a paralyzed patient by a direct brain connection. Neuroreport. 1998;9(8):1707–1711.
  24. Brower V. When mind meets machine. EMBO Rep. 2005;6(2):108–110.
  25. Collinger JL, Wodlinger B, Downey JE, et al. High-performance neuroprosthetic control by an individual with tetraplegia. Lancet. 2013;381(9866):557–564.
  26. Jarosiewicz B, Sarma AA, Bacher D, et al. Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface. Sci Transl Med. 2015;7(313):313ra179.
  27. Ludwig, K.A. Neuroprosthetic Devices: Inputs and Outputs. Ph.D. Thesis, University of Michigan, Ann Arbor, MI, USA, 2009.
  28. Capogrosso M, Milekovic T, Borton, D, et al. A brain–spine interface alleviating gait deficits after spinal cord injury in primates. Nature. 2016;539(7628):284–288.
  29. Bouton CE, Shaikhouni A, Annetta NV, et al. Restoring cortical control of functional movement in a human with quadriplegia. Nature. 2016;533(7602):247–250.
  30. Dobelle WH. Artificial vision for the blind by connecting a television camera to the visual cortex. ASAIO J. 2000;46(1):3–9.
  31. Rachitskaya AV, Yuan A, Marino MJ, Reese J, Ehlers JP. Intraoperative OCT imaging of the Argus II Retinal Prosthesis System. Ophthalmic Surg Lasers Imaging Retina. 2016;47(11):999–1003.
  32. Stingl K, Bartz-Schmidt KU, Besch D, et al. Subretinal Visual Implant Alpha IMS: Clinical trial interim report. Vision Res. 2015;111(Pt B):149–160.
  33. Berger TW, Song D, Chan RHM, et al. A hippocampal cognitive prosthesis: Multi-input, multi-output nonlinear modeling and VLSI implementation. IEEE Trans Neural Syst Rehabil Eng. 2012;20(2):198–211.
  34. Griffith RW, Humphrey DR. Long-term gliosis around chronically implanted platinum electrodes in the Rhesus macaque motor cortex. Neurosci Lett. 2006;406(1–2):81–86.
  35. Waldert S. Invasive vs non-invasive neuronal signals for brain-machine interfaces: Will one prevail? Front Neurosci. 2016;10:295.
  36. Tyler DJ, Polasek KH, Schiefer MA. Chapter 63 – Peripheral nerve interfaces. In: Tubbs R, Rizk E, Shoja MM, Loukas M, Barbaro N, Spinner RJ, eds. Nerves and Nerve Injuries. San Diego, CA: Academic Press; 2015:1033–1054.
  37. Spearman BS, Desai VH, Mobini S, et al. Neural interfaces: Tissue-engineered peripheral nerve interfaces. Adv Funct Mater. 2018;28(12):1870076. doi:10.1002/adfm.201870076
  38. Naples GG, Mortimer JT, Scheiner A, Sweeney JD. A spiral nerve cuff electrode for peripheral nerve stimulation. IEEE Trans Biomed Eng. 1988;35(11):905–916.
  39. Foldes EL, Ackermann DM, Bhadra N, Kilgore KL, Bhadra N. Design, fabrication and evaluation of a conforming circumpolar peripheral nerve cuff electrode for acute experimental use. J Neurosci Methods. 2011;196(1):31–37.
  40. Tyler DJ, Durand DM. Chronic response of the rat sciatic nerve to the flat interface nerve electrode. Ann Biomed Eng. 2003;31(6):633–642.
  41. Dweiri YM, Stone MA, Tyler DJ, McCallum GA, Durand DM. Fabrication of high contact-density, flat-interface nerve electrodes for recording and stimulation applications. J Vis Exp. 2016;4(116).
  42. Yoshida K, Hennings K, Kammer S. Acute performance of the thin-film longitudinal intra-fascicular electrode. Paper presented at: the First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2006); February 20–22, 2006; Pisa, Italy.
  43. Boretius T, Badia J, Pascual-Font A, et al. A transverse intrafascicular multichannel electrode (TIME) to interface with the peripheral nerve. Biosens Bioelectron. 2010;26(1):62–69.
  44. Yoshida K, Stieglitz T, Qiao S. Bioelectric interfaces for the peripheral nervous system. Paper presented at: the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society; August 26–30 2014; Chicago, IL.
  45. Tyler DJ, Durand DM. A slowly penetrating interfascicular nerve electrode for selective activation of peripheral nerves. IEEE Trans Rehabil Eng. 1997;5(1):51–61.
  46. Clark GA, Ledbetter NM, Warren DJ, Harrison RR. Recording sensory and motor information from peripheral nerves with Utah slanted electrode arrays. Conf Proc IEEE Eng Med Biol Soc. 2011;2011:4641–4644.
  47. Birenbaum NK, MacEwan MR, Ray WZ. Interfacing peripheral nerve with macro-sieve electrodes following spinal cord injury. Neural Regen Res. 2017;12(6):906–909.
  48. Musick KM, Rigosa J, Narasimhan S, et al. Chronic multichannel neural recordings from soft regenerative microchannel electrodes during gait. Sci Rep. 2015;5:14363.
  49. Lotfi P, Garde K, Chouhan A, Bengali E, Romero M. Modality-specific axonal regeneration: Toward selective regenerative neural interfaces. Front Neuroeng. 2011;4:11.
  50. Clements IP, Mukhatyar VJ, Srinivasan A, Bentley JT, Andreasen DS, Bellamkonda RV. Regenerative scaffold electrodes for peripheral nerve interfacing. IEEE Trans Neural Syst Rehabil Eng. 2013;21(4):554–566.
  51. Cheesborough JE, Smith LH, Kuiken TA, Dumanian GA. Targeted muscle reinnervation and advanced prosthetic arms. Semin Plast Surg. 2015;29(1):62–72.
  52. Urbanchek MG, Kung TA, Frost CM, et al. Development of a regenerative peripheral nerve interface for control of a neuroprosthetic limb. Biomed Res Int. 2016;12:1–8.
  53. Kornreich BG. The patch clamp technique: Principles and technical considerations. J Vet Cardiol. 2007;9(1):25–37.
  54. Py C, Denhoff MW, Sabourin N, Weber J, Shiu M, Zhao P. Priming and testing silicon patch-clamp neurochips. N Biotechnol. 2014;31(5):430–435.
  55. Pine J. A history of MEA development. In: Taketani M, Baudry M, eds. Advances in Network Electrophysiology: Using Multi-Electrode Arrays. Boston, MA: Springer US; 2006:3–23.
  56. Rutten W, Mouveroux JM, Buitenweg J, et al. Neuroelectronic interfacing with cultured multielectrode arrays toward a cultured probe. Proc IEEE Inst Electr Electron Eng. 2001;89(7):1013–1029.
  57. Rabieh N, Ojovan SM, Shmoel N, Erez, H, Maydan E, Spira ME. On-chip, multisite extracellular and intracellular recordings from primary cultured skeletal myotubes. Scientific Reports. 2016;6:36498.
  58. Walsh KB, DeRoller N, Zhu Y, Koley G. Application of ion-sensitive field effect transistors for ion channel screening. Biosens Bioelectron. 2014;54:448–454.
  59. Fromherz P, Offenhausser A, Vetter T, Weis J. A neuron-silicon junction: A Retzius cell of the leech on an insulated-gate field-effect transistor. Science. 1991;252(5010):1290–1293.
  60. Liu Q, Wu C, Cai H, Hu N, Zhou J, Wang P. Cell-based biosensors and their application in biomedicine. Chem Rev. 2014;114(12):6423–6461.