Neuromuscular Interactions
a Bridge between Mind and Technology
Abstract
This study delves into the fundamentals of neuromuscular interactions, with a primary focus on the detection of electrical signals from the human nervous system. The application of electromyographic and electroencephalographic signals for controlling computer systems is investigated, encompassing tasks such as virtual object manipulation and decoding mental commands. The paper underscores the applications in medicine and rehabilitation, emphasizing the revolutionary potential for enhancing the lives of individuals with physical disabilities. Additionally, it examines challenges such as signal decoding precision and raises ethical and privacy concerns. The conclusion points towards the future of this field, highlighting ongoing innovations and the possibilities it opens for a direct link between the human mind and technology.
References
2. Lebedev M.A. et al. Cortical ensemble adaptation to represent velocity of an artificial actuator controlled by a brain-machine interface. Journal of Neuroscience. 2006;26(6):1486-1497. https://doi.org/10.1523/JNEUROSCI.4088-04.2005
3. Lebedev M.A., Nicolelis M.A.L. Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation. Physiological Reviews. 2017;97(2):767-837. https://doi.org/10.1152/physrev.00027.2016
4. Duchateau J., Enoka R.M. Human motor unit recordings: Origins and insight into the integrated motor system. Brain Research. 2011;1409:42-61. https://doi.org/10.1016/j.brainres.2011.06.011
5. Sudhof T.C. Neurotransmitter release: The last millisecond in the life of a synaptic vesicle. Neuron. 2013;80(3):675-690. https//:doi.org/10.1016/j.neuron.2013.10.022
6. Rizzoli S.O., Betz W.J. Synaptic vesicle pools. Nature Reviews Neuroscience. 2005;6(1):57-69. https://doi.org/10.1038/nrn1583
7. Malenka R.C., Bear M.F. LTP and LTD: An embarrassment of riches. Neuron. 2004;44(1):5-21. https://doi.org/10.1016/j.neuron.2004.09.012
8. Huxley H.E. The mechanism of muscular contraction. Science. 1969;164(3886):1356-1365. https://doi.org/10.1126/science.164.3886.1356
9. Ebashi S., Endo M. Calcium ion and muscle contraction. Progress in Biophysics and Molecular Biology. 1968;18:123-183. https://doi.org/10.1016/0079-6107(68)90023-0
10. Gordon A.M., Homsher E., Regnier M. Regulation of contraction in striated muscle. Physiological Reviews. 2000;80(2):853-924. https://doi.org/10.1152/physrev.2000.80.2.853
11. Rayment I., Rypniewski W.R., Schmidt-Base K., Smith R., Tomchick D.R. Three-dimensional structure of myosin subfragment-1: A molecular motor. Science. 1993;261(5117):50-58. https://doi.org/10.1126/science.8316857
12. Cannon S.C. Channelopathies of Skeletal Muscle Excitability. Comprehensive Physiology. 2018;2(2):761-790. https://doi.org/ 10.1002/cphy.c140062
13. Kuo I.Y., Ehrlich B.E. Signaling in Muscle Contraction. Cold Spring Harbor Perspectives in Biology. 2015;7:a006023. https://doi.org/ 10.1101/cshperspect.a006023
14. Hasselmo M.E., Sarter M. Modes and models of forebrain cholinergic neuromodulation of cognition. Neuropsychopharmacology. 2011;36(1):52-73. https://doi.org/10.1038/npp.2010.104
15. Holtmaat A., Svoboda K. Experience-dependent structural synaptic plasticity in the mammalian brain. Nature Reviews Neuroscience. 2009;10(9):647-658. https://doi.org/10.1038/nrn2699
16. Krakauer J.W., Mazzoni P. Human sensorimotor learning: adaptation, skill, and beyond. Current Opinion in Neurobiology. 2011;21(4):636-644. https://doi.org/10.1016/j.conb.2011.06.012
17. Citri A., Malenka R.C. Synaptic plasticity: Multiple forms, functions, and mechanisms. Neuropsychopharmacology. 2008;33(1):18-41. https://doi.org/10.1038/sj.npp.1301559
18. Cramer S.C., Sur M., Dobkin B.H. et al. Harnessing neuroplasticity for clinical applications. Brain. 2011;134(6):1591-1609. https://doi.org/10.1093/brain/awr039
19. Jackson A., Fetz E.E. Interfacing With the Computational Brain. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2011;19(5):534-541. https://doi.org/10.1109/TNSRE.2011.2158586
20. Ienca M., Haselager P. Hacking the brain: Brain-computer interfacing technology and the ethics of neurosecurity. Ethics and Information Technology. 2016;18(2):117-129. https://doi.org/10.1007/s10676-016-9398-9
21. Vlek R.J., Steines D., Szibbo D., Kübler A., Schneider M.-J., Haselager P., Nijboer F. Ethical Issues in Brain-Computer Interface Research, Development, and Dissemination. Journal of Neurologic Physical Therapy. 2012;36(2):94-99. https://doi.org/10.1097/NPT.0b013e31825064cc
22. Hochberg L.R., Bacher D., Jarosiewicz B. et al. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature. 2012;485(7398);372-375. https://doi.org/10.1038/nature11076
23. Donati A.R.C., Shokur S., Morya E. et al. Long-term training with a brain-machine interface-based gait protocol induces partial neurological recovery in paraplegic patients. Scientific Reports. 2016;(6):30383. https://doi.org/10.1038/srep30383
24. Ajiboye A.B. et al. Restoration of reaching and grasping movements through brain-controlled muscle stimulation in a person with tetraplegia: a proof-of-concept demonstration. The Lancet. 2017;389(10081):1821-1830. https://doi.org/10.1016/S0140-6736(17)30601-3
25. Nishimura Y., Perlmutter S.I., Fetz E.E. Restoration of upper limb movements via artificial corticospinal and musculospinal connections in a monkey with spinal cord injury. Frontiers in Neural Circuits. 2013;7:57. https://doi.org/10.3389/fncir.2013.00057
26. Pfurtscheller G., Neuper C. Motor imagery and direct brain-computer communication. Proceedings of the IEEE. 2001;89(7):1123-1134. https://doi.org/10.1109/5.939829
27. Birbaumer N., Cohen L. G. Brain-computer interfaces: Communication and restoration of movement in paralysis. Journal of Physiology. 2007;579(3):621-636. https://doi.org/10.1113/jphysiol.2006.125633
28. Stahl B.C., Timmermans J., Flick C. Ethics of Emerging Information and Communication Technologies: On the implementation of responsible research and innovation. Science and Public Policy. 2017;44(3):369-381. https://doi.org/10.1093/scipol/scw069
29. Warwick K., Gasson M., Hutt B. et al. Thought communication and control: A first step using radiotelegraphy. IEE Proceedings Communications. 2003;2(2):219-222. https://doi.org/10.1049/ip-com:20040409
30. Lebedev M.A., Nicolelis M.A.L. Brain-machine interfaces: past, present and future. Trends in Neurosciences. 2006;29(9):536-546. https://doi.org/10.1016/j.tins.2006.07.004
31. Ramos-Murguialday A., Broetz D., Rea M. et al. Brain-machine interface in chronic stroke rehabilitation: A controlled study. Annals of Neurology. 2013;74(1):100-108. https://doi.org/10.1002/ana.23879
32. Galán F., Nuttin M., Lew E. et al. A brain-actuated wheelchair: Asynchronous and non-invasive brain computer interfaces for continuous control of robots. Clinical Neurophysiology. 2008;119(9):2159-2169. https://doi.org/10.1016/j.clinph.2008.06.001
33. Wolpaw J.R., Birbaumer N., McFarland D.J., Pfurtscheller G., Vaughan T.M. Brain-computer interface technology: A review of the first international meeting. IEEE Transactions on Rehabilitation Engineering. 2002;8(2):164-173. https://doi.org/10.1109/tre.2000.847807
34. Kübler A., Furdea A., Halder S., Hammer E.M., Nijboer F., Kotchoubey B. A brain-computer interface controlled auditory event-related potential (P300) spelling system for locked-in patients. Annals of the New York Academy of Sciences. 2009;1157(1):90-100. https://doi.org/10.1111/j.1749-6632.2008.04122.x
35. Paninski L., Cunningham J.P. Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience. Current Opinion in Neurobiology. 2018;50:232-241. https://doi.org/10.1016/j.conb.2018.04.007
36. Lebedev M.A., Tate A.J., Hanson T.L. et al. Future developments in brain-machine interface research. Clinics (Sao Paulo). 2011;66(1):25-32[ 2]. https://doi.org/10.1590/S1807-59322011001300004
37. Macpherson N. et al. Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research. Neural Networks. 2021;144:603-613. https://doi.org/10.1016/j.neunet.2021.09.018
38. Slater M., Spanlang B., Sanchez-Vives M.V., Blanke O. First Person Experience of Body Transfer in Virtual Reality. PLOS ONE. 2010;5(5):e10564. https://doi.org/10.1371/journal.pone.0010564

This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication policy of the journal is based on traditional ethical principles of the Russian scientific periodicals and is built in terms of ethical norms of editors and publishers work stated in Code of Conduct and Best Practice Guidelines for Journal Editors and Code of Conduct for Journal Publishers, developed by the Committee on Publication Ethics (COPE). In the course of publishing editorial board of the journal is led by international rules for copyright protection, statutory regulations of the Russian Federation as well as international standards of publishing.
Authors publishing articles in this journal agree to the following: They retain copyright and grant the journal right of first publication of the work, which is automatically licensed under the Creative Commons Attribution License (CC BY license). Users can use, reuse and build upon the material published in this journal provided that such uses are fully attributed.