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Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces

Authors: Canbiao Wu; Nayu Chen; Tuo Sun; Ping Tan; Peng Wang; Guangli Li;

Synergizing DeepSeek's artificial intelligence innovations with brain–computer interfaces

Abstract

AbstractThe 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.

Country
Netherlands
Related Organizations
Keywords

SDG 3 - Good Health and Well-being, open-source AI, brain–computer interface, ESSB PSY, neural signal processing, open‐source AI, neurotechnology, Neurology. Diseases of the nervous system, artificial intelligence, DeepSeek, RC346-429

  • BIP!
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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    2
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
gold