PDF (2.1 MB)
Collect
Submit Manuscript
Show Outline
Outline
Abstract
Keywords
References
Show full outline
Hide outline
Publishing Language: Chinese

Brain-Computer Interface: A Revolutionary Technology Expanding the Frontiers of the Human Brain and the Future of Neurosurgery

Beijing Tiantan Hospital, Capital Medical University, National Clinical Research Center for Neurological Diseases, Beijing 100070, China
Show Author Information

Abstract

The brain-computer interface (BCI) is not merely an advanced technology but also represents a profound revolution spanning neuroscience, artificial intelligence, computer science, philosophy, and sociology. The core value of BCI lies in its ability to break through the informational barriers between the brain and the external world, endowing humans with novel capabilities for information interaction and propelling the evolution of an intelligent society. As a disruptive technological innovation, BCI fundamentally alters the way humans interact with the world, and its applications will profoundly influence our understanding of cognition, consciousness, and even self-existence. For neurosurgery, BCI is not only a revolutionary therapeutic tool but also an opportunity to reshape traditional medical paradigms. From repairing neural damage to modulating brain functions, from enhancing human intelligence to shaping the future of human-machine integration, BCI offers unprecedented possibilities for neurosurgery. The development of this technology not only aids in a deeper understanding of brain functions but also provides robust support for future intelligent healthcare. The impact of BCI extends far beyond medicine, influencing the transformation of future computing paradigms, the proliferation of intelligence augmentation, the scrutiny of social ethics, the deployment of national strategies, the dynamics of economic development, and the safeguarding of national security.

CLC number: R741;R749;R651 Document code: A Article ID: 1674-9081(2025)02-0269-08

References

[1]

Isa T, Fetz E E, Müller K R. Recent advances in brain-machine interfaces[J]. Neural Netw, 2009, 22(9): 1201-1202.

[2]

Hofmann U G, Stieglitz T. Why some BCI should still be called BMI[J]. Nat Commun, 2024, 15(1): 6207.

[3]

Karami M M. Neuroscience and brain-computer-interface: bridging medicine and technology for advancing patients care[J]. Pharmacophore, 2024, 15(1): 6-13.

[4]

Nijboer F, Clausen J, Allison B Z, et al. The Asilomar survey: stakeholders' opinions on ethical issues related to brain-computer interfacing[J]. Neuroethics, 2013, 6(3): 541-578.

[5]

Awuah W A, Ahluwalia A, Darko K, et al. Bridging minds and machines: the recent advances of brain-computer interfaces in neurological and neurosurgical applications[J]. World Neurosurg, 2024, 189: 138-153.

[6]

Zhao J Z. Current status and prospects of brain computer interface research[J]. Chin Med News, 2023, 38(8): 8.

[7]

Musk E, Neuralink. An integrated brain-machine interface platform with thousands of channels[J]. J Med Internet Res, 2019, 21(10): e16194.

[8]

Gao X R, Wang Y J, Chen X G, et al. Interface, interaction, and intelligence in generalized brain-computer interfaces[J]. Trends Cogn Sci, 2021, 25(8): 671-684.

[9]

He Q H, Yang Y, Ge P C, et al. The brain nebula: minimally invasive brain-computer interface by endovascular neural recording and stimulation[J]. J Neurointerv Surg, 2024, 16(12): 1237-1243.

[10]
Alcaide R, Agarwal N, Candassamy J, et al. EEG-based focus estimation using Neurable's Enten headphones and analytics platform[DB/OL ]. (2021-06-23)[2024-02-20]. https://www.biorxiv.org/lookup/doi/10.1101/2021.06.21.448991.
[11]
Khan S, Mian A, Newaz G. Thin film coatings as electrodes in neuroscience[M]//NAZARPOUR S. Thin Films and Coatings in Biology. Dordrecht: Springer, 2013: 301-330.
[12]

Lorach H, Galvez A, Spagnolo V, et al. Walking naturally after spinal cord injury using a brain-spine interface[J]. Nature, 2023, 618(7963): 126-133.

[13]

Biasiucci A, Leeb R, Iturrate I, et al. Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke[J]. Nat Commun, 2018, 9(1): 2421.

[14]

Kruse A, Suica Z, Taeymans J, et al. Effect of brain-computer interface training based on non-invasive electroencephalography using motor imagery on functional recovery after stroke- a systematic review and meta-analysis[J]. BMC Neurol, 2020, 20(1): 385.

[15]

Willett F R, Kunz E M, Fan C F, et al. A high-performance speech neuroprosthesis[J]. Nature, 2023, 620(7976): 1031-1036.

[16]

Metzger S L, Littlejohn K T, Silva A B, et al. A high-performance neuroprosthesis for speech decoding and avatar control[J]. Nature, 2023, 620(7976): 1037-1046.

[17]

Qiu W C, Ma L, Guo H Y, et al. The implementation, clinical progress and technical challenges of implantable brain-computer interface systems[J]. Prog Biochem Biophys, 2024, 51(10): 2478-2497.

[18]

Wang S, Zhu G Y, Shi L, et al. Closed-loop adaptive deep brain stimulation in Parkinson's disease: procedures to achieve it and future perspectives[J]. J Parkinsons Dis, 2023, 13(4): 453-471.

[19]

An Q, Yin Z X, Ma R Y, et al. Adaptive deep brain stimulation for Parkinson's disease: looking back at the past decade on motor outcomes[J]. J Neurol, 2023, 270(3): 1371-1387.

[20]

Li A, Huynh C, Fitzgerald Z, et al. Neural fragility as an EEG marker of the seizure onset zone[J]. Nat Neurosci, 2021, 24(10): 1465-1474.

[21]

Leite J, Morales-Quezada L, Carvalho S, et al. Surface EEG-transcranial direct current stimulation (tDCS) closed-loop system[J]. Int J Neural Syst, 2017, 27(6): 1750026.

[22]

Roy D S, Arons A, Mitchell T I, et al. Memory retrieval by activating engram cells in mouse models of early Alzheimer's disease[J]. Nature, 2016, 531(7595): 508-512.

[23]

Pan J H, Xiao J, Wang J, et al. Brain-computer interfaces for awareness detection, auxiliary diagnosis, prognosis, and rehabilitation in patients with disorders of consciousness[J]. Semin Neurol, 2022, 42(3): 363-374.

[24]

He Q H, He J H, Yang Y, et al. Brain-computer interfaces in disorders of consciousness[J]. Neurosci Bull, 2023, 39(2): 348-352.

[25]

Merk T, Peterson V, Köhler R, et al. Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation[J]. Exp Neurol, 2022, 351: 113993.

[26]

Gordon E C, Seth A K. Ethical considerations for the use of brain-computer interfaces for cognitive enhancement[J]. PLoS Biol, 2024, 22(10): e3002899.

Medical Journal of Peking Union Medical College Hospital
Pages 269-276
Cite this article:
ZHAO J. Brain-Computer Interface: A Revolutionary Technology Expanding the Frontiers of the Human Brain and the Future of Neurosurgery. Medical Journal of Peking Union Medical College Hospital, 2025, 16(2): 269-276. https://doi.org/10.12290/xhyxzz.2025-0152
Metrics & Citations  
Article History
Copyright
Return