Academic Journal
Repetitive training enhances the pattern recognition capability of cultured neural networks.
| Τίτλος: | Repetitive training enhances the pattern recognition capability of cultured neural networks. |
|---|---|
| Συγγραφείς: | Shao WW; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Shao Q; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Xu HH; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Qiao GJ; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Wang RX; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Ma ZY; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Meng WW; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Yang ZB; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Zang YL; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China., Li XH; Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.; Haihe Laboratory of Brain - Computer Interaction and Human-Machine Integration, Tianjin, China.; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin University, Tianjin, China. |
| Πηγή: | PLoS computational biology [PLoS Comput Biol] 2025 Apr 22; Vol. 21 (4), pp. e1013043. Date of Electronic Publication: 2025 Apr 22 (Print Publication: 2025). |
| Τύπος έκδοσης: | Journal Article; Research Support, Non-U.S. Gov't |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: San Francisco, CA : Public Library of Science, [2005]- |
| Ιατρικοί όροι (MeSH): | Nerve Net*/physiology , Pattern Recognition, Physiological*/physiology , Pattern Recognition, Automated*/methods , Neural Networks, Computer*, Neurons/physiology ; Animals ; Computational Biology ; Rats ; Microelectrodes ; Cells, Cultured |
| Περίληψη: | Cultured neural networks in vitro have demonstrated the biocomputing capability to recognize patterns. However, the underlying mechanisms behind information processing and pattern recognition remain less understood. Here, we developed an in vitro neural network integrated with microelectrode arrays (MEAs) to explore the network's classification capability and elucidate the mechanisms underlying this classification. After applying different stimulation patterns using MEAs, the network exhibited structural alterations and distinct electrical responses that recognized various stimulation patterns. Alongside the reshaping of network structures, repeated training increased recognition accuracy for each stimulation pattern. Additionally, it was reported for the first time that spontaneous networks after stimulation are more closely related to the structures of evoked networks. This work provides new insights into the structural changes underlying information processing and contributes to our understanding of how cultured neural networks respond to different patterns. (Copyright: © 2025 Shao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.) |
| Competing Interests: | The authors have declared that no competing interests exist. |
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| Grant Information: | National Key Research and Development Program of China; National Natural Science Foundation of China |
| Entry Date(s): | Date Created: 20250422 Date Completed: 20250510 Latest Revision: 20260910 |
| Update Code: | 20260910 |
| PubMed Central ID: | PMC12064202 |
| DOI: | 10.1371/journal.pcbi.1013043 |
| PMID: | 40262075 |
| Βάση Δεδομένων: | MEDLINE |
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