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.

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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
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article

An Active, Multimodal Neural Interface for Real‐Time Monitoring of Cortical Electrical, Thermal, and Optical Dynamics

Dongqi An, Enming Song, Jin Lu, Lianjie Zhou et al.
Advanced Science
Neuroscience and Neural Engineering
article

An Active, Multimodal Neural Interface for Real‐Time Monitoring of Cortical Electrical, Thermal, and Optical Dynamics

Dongqi An, Enming Song, Jin Lu, Lianjie Zhou, Rongjun Zhang, Bofan Hu, Yongfeng Mei, Yuting Shao, Faya Liang, J D Liu, Yifei Lü, Jiahao Li, Rui Li, Yuhang Hu, Lichao Ma, Zhongzheng Li, Yifan Ding, Pengchuan Liu, Ke Ding
article en

Abstract

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.

Advanced ScienceVol. 13(3)
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)
Openalex Percentile: Top 66%
Neuroscience and Neural Engineering
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