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Brain organoid−based multimodal brain−computer interface platform and integration of key technologies
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Min DAI1, Shiping LIU2, Quanxin YUN3, Jiahong DING4
Science & Technology Review | 2026, 44(15) : 16 - 24
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Science & Technology Review | 2026, 44(15): 16-24
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Brain organoid−based multimodal brain−computer interface platform and integration of key technologies
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Min DAI1, Shiping LIU2, Quanxin YUN3, Jiahong DING4
Affiliations
  • 1BGI Research, Hangzhou 310030, China
  • 2State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Hangzhou 310030, China
  • 3State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Shenzhen 518083, China
  • 4BGI, Shenzhen 518083, China
Published: 2026-08-13 doi: 10.3981/j.issn.1000-7857.2025.07.00064
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Brain−computer interface (BCI) is a frontier technology that enables bidirectional information exchange between neural tissues and external devices. Broadly speaking, the term "neural tissue" includes not only the human brain itself but also artificially constructed neural tissue models, such as in vitro brain organoids. Through precise sensing and dynamic feedback of neural structural and functional states, BCI is becoming an important technological pathway for advancing experimental paradigms in neuroscience and exploring brain−inspired intelligence. However, current in vitro brain organoid culture still relies on manual operations and therefore suffers from limited stability and consistency; meanwhile, mainstream BCI technologies are still largely restricted to single−modality data acquisition and processing, making it difficult to achieve multidimensional analysis of complex neural network activity. To address these issues, this paper proposes a high−throughput multimodal BCI platform integrating four core modules: closed−loop fully automated brain organoid culture, neuroelectrophysiological interaction, in situ gene detection, and optical imaging. We systematically describe the key technologies and system−integration strategies of this platform, analyze the strengths and bottlenecks of each module, propose feasible paths for technical fusion, and further discuss its potential applications in brain−inspired computing, mechanistic studies of brain diseases, drug screening, and precision medicine.

brain−computer interface  /  brain organoid  /  gene detection  /  electrophysiological interaction  /  optical imaging
Min DAI, Shiping LIU, Quanxin YUN, Jiahong DING. Brain organoid−based multimodal brain−computer interface platform and integration of key technologies[J]. Science & Technology Review, 2026 , 44 (15) : 16 -24 . DOI: 10.3981/j.issn.1000-7857.2025.07.00064
Year 2026 volume 44 Issue 15
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doi: 10.3981/j.issn.1000-7857.2025.07.00064
  • Receive Date:2025-07-11
  • Online Date:2026-08-31
  • Published:2026-08-13
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  • Received:2025-07-11
  • Revised:2026-05-13
Affiliations
    1BGI Research, Hangzhou 310030, China
    2State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Hangzhou 310030, China
    3State Key Laboratory of Genome and Multi-omics Technologies, BGI Research, Shenzhen 518083, China
    4BGI, Shenzhen 518083, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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