Artificial intelligence-enhanced brain-computer interfaces (BCI) are expected to significantly improve the performance of traditional BCIs in multiple aspects, including usability, user experience, and user satisfaction, particularly in terms of intelligence. However, such AI-integrated or AI-based BCI systems may introduce new ethical issues. This paper first evaluated the potential of AI technology, especially deep learning, in enhancing the performance of BCI systems, including improving decoding accuracy, information transfer rate, real-time performance, and adaptability. Building on this, it was considered that AI-enhanced BCI systems might introduce new or more severe ethical issues compared to traditional BCI systems. These include the possibility of making users' intentions and behaviors more predictable and manipulable, as well as the increased likelihood of technological abuse. The discussion also addressed measures to mitigate the ethical risks associated with these issues. It is hoped that this paper will promote a deeper understanding and reflection on the ethical risks and corresponding regulations of AI-enhanced BCIs.
Brain-Computer Interfaces/ethics* ; Artificial Intelligence/ethics* ; Humans ; Deep Learning ; User-Computer Interface ; Electroencephalography

Objective:To analyze the genetic variant characteristics of primary immunodeficiency diseases (PID) in families from Henan Province.Methods:This study conducted a retrospective analysis of 19 PID pedigrees referred to the Prenatal Diagnosis Center at Henan Provincial People's Hospital between January 2016 and March 2024. Among the 19 families, 13 underwent prenatal diagnosis at our hospital, while the remaining six received genetic counseling based on third-party genetic testing reports (confirmed by our institution's laboratory). The clinical data from these families were analyzed, and descriptive statistical analysis was applied to the data.Results:Among the 19 PID families, there were seven cases of combined immunodeficiency, three immunodeficiency syndromes, three phagocyte deficiencies, three antibody-dominant immunodeficiencies, and three immunodysregulatory disorders, involving a total of 12 genes ( IL2RG, ADA, RAG2, STAT3, SMARCAL1, ATM, POLA1, CYBB, BTK, RAB27A, LRBA, IL10R). A total of 25 genetic variants were identified, including 11 novel variants not previously documented in the ClinVar and HGMD professional databases. The novel variants comprised: IL2RG gene mutations (Exon5_8del and c.903_904delinsCT leading to p.E302*), ADA gene mutation (c.884A>G resulting in p.D295G), RAG2 gene mutation (c.513dupA causing p.W172Mfs3), POLA1 gene mutation (c.25+5G>C), CYBB gene mutations (c.824G>A/p.G275D and c.472A>T/p.K158), BTK gene mutations (c.522_523insC/p.A175fs and c.142-2A>C), and RAB27A gene mutations (c.121delA/p.T41fs and c.272delA/p.D91fs). Among the 13 families undergoing prenatal diagnosis, genetic testing revealed that 11 fetuses carried wild-type genes, and these families elected to continue their pregnancies. One fetus exhibited identical genetic variants to the proband and received a clinical diagnosis consistent with the genetic disorder, while another fetus demonstrated chromosomal copy number variations. In both of these latter cases, the families opted for pregnancy termination. Conclusion:This study identified 11 unreported variants across seven genes, highlighting the need for further expansion of PID genetic variant databases.

Objective:To analyze the genetic variant characteristics of primary immunodeficiency diseases (PID) in families from Henan Province.Methods:This study conducted a retrospective analysis of 19 PID pedigrees referred to the Prenatal Diagnosis Center at Henan Provincial People's Hospital between January 2016 and March 2024. Among the 19 families, 13 underwent prenatal diagnosis at our hospital, while the remaining six received genetic counseling based on third-party genetic testing reports (confirmed by our institution's laboratory). The clinical data from these families were analyzed, and descriptive statistical analysis was applied to the data.Results:Among the 19 PID families, there were seven cases of combined immunodeficiency, three immunodeficiency syndromes, three phagocyte deficiencies, three antibody-dominant immunodeficiencies, and three immunodysregulatory disorders, involving a total of 12 genes ( IL2RG, ADA, RAG2, STAT3, SMARCAL1, ATM, POLA1, CYBB, BTK, RAB27A, LRBA, IL10R). A total of 25 genetic variants were identified, including 11 novel variants not previously documented in the ClinVar and HGMD professional databases. The novel variants comprised: IL2RG gene mutations (Exon5_8del and c.903_904delinsCT leading to p.E302*), ADA gene mutation (c.884A>G resulting in p.D295G), RAG2 gene mutation (c.513dupA causing p.W172Mfs3), POLA1 gene mutation (c.25+5G>C), CYBB gene mutations (c.824G>A/p.G275D and c.472A>T/p.K158), BTK gene mutations (c.522_523insC/p.A175fs and c.142-2A>C), and RAB27A gene mutations (c.121delA/p.T41fs and c.272delA/p.D91fs). Among the 13 families undergoing prenatal diagnosis, genetic testing revealed that 11 fetuses carried wild-type genes, and these families elected to continue their pregnancies. One fetus exhibited identical genetic variants to the proband and received a clinical diagnosis consistent with the genetic disorder, while another fetus demonstrated chromosomal copy number variations. In both of these latter cases, the families opted for pregnancy termination. Conclusion:This study identified 11 unreported variants across seven genes, highlighting the need for further expansion of PID genetic variant databases.

Brain-computer interface (BCI) is a revolutionizing technology that disrupts traditional human-computer interaction by establishing direct communication and control between the brain and computer, bypassing the peripheral nervous and muscular systems. With the rapid advancement of BCI technology, growing application demands, and an increasing need for specialized BCI professionals, a new academic major-BCI major-has gradually emerged. However, few studies to date have discussed the interdisciplinary nature and training framework of this emerging major. To address this gap, this paper first introduced the application demands of BCI, including the demand for BCI technology in both medical and non-medical fields. The paper also described the interdisciplinary nature of the BCI major and the urgent need for specialized professionals in this field. Subsequently, a training program of the BCI major was presented, with careful consideration of the multidisciplinary nature of BCI research and development, along with recommendations for curriculum structure and credit distribution. Additionally, the facing challenges of the construction of the BCI major were analyzed, and suggested strategies for addressing these challenges were offered. Finally, the future of the BCI major was envisioned. It is hoped that this paper will provide valuable reference for the development and construction of the BCI major.
Brain-Computer Interfaces/trends* ; Humans ; Electroencephalography ; User-Computer Interface