A Monolithically Integrated Multimodal Low‐Artifact Neural Probe for Optogenetic Applications
ABSTRACT In optogenetic neural probes, stimulus light intensity monitoring, thermal safety assessment, and stimulation artifact suppression are of critical importance for achieving cell‐type‐specific optical modulation and high‐fidelity neural signal recording. Here, micro light‐emitting diode (µLED) stimulation sources and photodetectors (PDs) were fabricated on a GaN‐based blue LED epitaxial structure on a sapphire substrate, and resistance temperature detectors (RTDs) and metal recording electrodes were monolithically integrated to form a multimodal neural probe. A dual electromagnetic shielding cage formed by metal layers and the n + ‐GaN layer encloses the LED drive and recording interconnects. The RTD‑equipped LED delivers an irradiance of 26.5 mW mm −2 at 0.2 mA, and the PD yields a response voltage of 0.036 V in a brain‑mimicking agar phantom. The RTD exhibits a temperature sensitivity of 2.601 Ω °C −1 , and the local temperature rise stays below 1°C. Under irradiance above 50 mW mm −2 , the dual cage combined with transient pulse shaping reduces the average artifact from 260 to 8.75 µV, approaching the system noise floor. In vitro simulated recordings in PBS demonstrate stable recording and basic discrimination of simulated neural‐like waveforms under LED stimulation. This work lays a foundation for multimodal integration and low‐artifact recording in optogenetic neural probes.
Authors
- Xilei Huang
- Sio Hang Pun (ORCID: https://orcid.org/0000-0002-8648-2092)
- Xien Yang (ORCID: https://orcid.org/0000-0002-7524-8268)
- Baijun Zhang (ORCID: https://orcid.org/0000-0002-4343-0858)
- Ye Wen
- Jiefeng Weng
- Wenbo Zhao
- Yanyuan Ding (ORCID: https://orcid.org/0009-0002-0519-6340)
- Xin Cao
- Xiaodong Li
- Zeyi Li
- Haoran Li
- Yang Li
Institutions
- Sun Yat-sen University (CN)
- University of Macau (MO)
- State Key Laboratory of Optoelectronic Materials and Technology
Publication Details
- Journal
- Small Methods
- Published
- 2026-10-09
- DOI
- https://doi.org/10.1002/smtd.71108
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00