An Active, Multimodal Neural Interface for Real‐Time Monitoring of Cortical Electrical, Thermal, and Optical Dynamics
Chronic neurophysiological monitoring devices facilitate the timely diagnosis and treatment of episodic or recurrent neurological disorders. Compared with passive electrodes, silicon-based active transistors provide intrinsic signal amplification and, when combined with capacitive-coupling measurement mechanisms, enable high-density, high-fidelity recordings. However, most existing systems remain limited to single-modality electrical sensing and fail to address the growing demands of contemporary neurodynamic research. Here, a chronically implantable, large-area cortical interface capable of real-time multimodal monitoring of electrical, thermal, and photodynamic signals is presented. Building upon a silicon-transistor array for neural electrical detection, the device integrates thin-film metal resistors for temperature sensing while preserving mechanical flexibility sufficient for stable, long-term tissue contact. By leveraging the photoelectric effect of silicon transistors and functional multiplexing of active elements, the interface also achieves precise photodynamic measurement. In vitro experiments confirm long-term stability and channel isolation. In vivo evaluation in Sprague-Dawley rats, together with biocompatibility assessments, demonstrates reliable performance under physiological conditions. The technology used in this multifunctional platform has universal applicability in neural interfaces, offering continuous multimodal neurodynamic data acquisition with potential utility in monitoring, diagnosing, and treating chronic neurological conditions such as epilepsy and brain tumors.
Authors
- Dongqi An (ORCID: https://orcid.org/0000-0002-4824-0666)
- Enming Song
- Jin Lu (ORCID: https://orcid.org/0000-0001-5004-2741)
- Lianjie Zhou (ORCID: https://orcid.org/0000-0002-9285-2176)
- Rongjun Zhang (ORCID: https://orcid.org/0000-0002-1798-9922)
- Bofan Hu
- Yongfeng Mei (ORCID: https://orcid.org/0000-0002-3314-6108)
- Yuting Shao (ORCID: https://orcid.org/0000-0002-2654-7288)
- Faya Liang (ORCID: https://orcid.org/0000-0002-9515-9238)
- J D Liu (ORCID: https://orcid.org/0000-0002-3578-4066)
- Yifei Lü (ORCID: https://orcid.org/0000-0003-2268-2738)
- Jiahao Li (ORCID: https://orcid.org/0009-0003-6574-7455)
- Rui Li (ORCID: https://orcid.org/0000-0001-6051-4204)
- Yuhang Hu
- Lichao Ma
- Zhongzheng Li (ORCID: https://orcid.org/0000-0002-3380-2793)
- Yifan Ding (ORCID: https://orcid.org/0000-0002-0224-5058)
- Pengchuan Liu
- Ke Ding
Institutions
- Tongji University (CN)
- Fudan University (CN)
- Dalian University of Technology (CN)
- Robotics Research (United States) (US)
- Yiwu Science and Technology Research Institute (CN)
- Tongji Hospital (CN)
Publication Details
- Journal
- Advanced Science
- Published
- 2025-10-29
- DOI
- https://doi.org/10.1002/advs.202512114
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00