Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces
Abstract The integration of artificial intelligence (AI) and brain–computer interfaces (BCIs) represents a significant advancement in neurotechnology, with broad potential applications in healthcare, communication, and human augmentation. This study examines the synergy between DeepSeek, a leader in...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | Brain-X |
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| Online Access: | https://doi.org/10.1002/brx2.70035 |
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| _version_ | 1839646505143631872 |
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| author | Canbiao Wu Nayu Chen Tuo Sun Ping Tan Peng Wang Guangli Li |
| author_facet | Canbiao Wu Nayu Chen Tuo Sun Ping Tan Peng Wang Guangli Li |
| author_sort | Canbiao Wu |
| collection | DOAJ |
| description | Abstract The integration of artificial intelligence (AI) and brain–computer interfaces (BCIs) represents a significant advancement in neurotechnology, with broad potential applications in healthcare, communication, and human augmentation. This study examines the synergy between DeepSeek, a leader in efficient, open‐source AI models, and next‐generation BCI technologies. We analyze DeepSeek's contributions to model training efficiency, adaptive reasoning, and open‐source accessibility, and propose a framework for BCI development that incorporates these innovations. Additionally, we explore how AI‐driven neural signal processing, hardware optimization, and ethical AI–BCI systems can address the critical limitations of current BCI technologies, including signal fidelity, scalability, and real‐world applicability. Finally, we offer recommendations for interdisciplinary collaboration, regulatory improvements, and equitable technology dissemination to foster the sustainable development of AI–BCI technology. |
| format | Article |
| id | doaj-art-1fa46a1cc03f4bbf95cca788fd35e36e |
| institution | Matheson Library |
| issn | 2835-3153 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Brain-X |
| spelling | doaj-art-1fa46a1cc03f4bbf95cca788fd35e36e2025-06-30T13:22:39ZengWileyBrain-X2835-31532025-06-0132n/an/a10.1002/brx2.70035Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfacesCanbiao Wu0Nayu Chen1Tuo Sun2Ping Tan3Peng Wang4Guangli Li5Hunan Key Laboratory of Biomedical Nanomaterials and Devices School of Biological Science and Medical Engineering Hunan University of Technology Zhuzhou Hunan ChinaHunan Key Laboratory of Biomedical Nanomaterials and Devices School of Biological Science and Medical Engineering Hunan University of Technology Zhuzhou Hunan ChinaHunan Key Laboratory of Biomedical Nanomaterials and Devices School of Biological Science and Medical Engineering Hunan University of Technology Zhuzhou Hunan ChinaXiangjiang Laboratory Changsha Hunan ChinaDepartment of Language, Literature and Communication Faculty of Social Sciences and Humanities Vrije Universiteit Amsterdam Amsterdam NetherlandsHunan Key Laboratory of Biomedical Nanomaterials and Devices School of Biological Science and Medical Engineering Hunan University of Technology Zhuzhou Hunan ChinaAbstract The integration of artificial intelligence (AI) and brain–computer interfaces (BCIs) represents a significant advancement in neurotechnology, with broad potential applications in healthcare, communication, and human augmentation. This study examines the synergy between DeepSeek, a leader in efficient, open‐source AI models, and next‐generation BCI technologies. We analyze DeepSeek's contributions to model training efficiency, adaptive reasoning, and open‐source accessibility, and propose a framework for BCI development that incorporates these innovations. Additionally, we explore how AI‐driven neural signal processing, hardware optimization, and ethical AI–BCI systems can address the critical limitations of current BCI technologies, including signal fidelity, scalability, and real‐world applicability. Finally, we offer recommendations for interdisciplinary collaboration, regulatory improvements, and equitable technology dissemination to foster the sustainable development of AI–BCI technology.https://doi.org/10.1002/brx2.70035artificial intelligencebrain–computer interfaceDeepSeekneural signal processingneurotechnologyopen‐source AI |
| spellingShingle | Canbiao Wu Nayu Chen Tuo Sun Ping Tan Peng Wang Guangli Li Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces Brain-X artificial intelligence brain–computer interface DeepSeek neural signal processing neurotechnology open‐source AI |
| title | Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces |
| title_full | Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces |
| title_fullStr | Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces |
| title_full_unstemmed | Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces |
| title_short | Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces |
| title_sort | synergizing deepseek s artificial intelligence innovations with brain computer interfaces |
| topic | artificial intelligence brain–computer interface DeepSeek neural signal processing neurotechnology open‐source AI |
| url | https://doi.org/10.1002/brx2.70035 |
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