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Updated: Feb 12, 2026

Author Spotlight: Innovative Methodology for Implanting and Securing Neural Probes in the Rodent Spinal Cord
Published on: July 12, 2024
A nanofabricated optoelectronic probe for manipulating and recording neural dynamics
Bingzhao Li1, Kwang Lee2, Sotiris C Masmanidis2
1Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, United States of America.
Objective:
The convergence of optogenetic and large-scale neural recording technologies opens enormous opportunities for studying brain function. However, compared to the widespread use of optogenetics or recordings as standalone methods, the joint use of these techniques in behaving animals is much less well developed. A simple but poorly scalable solution has been to implant conventional optical fibers together with extracellular microelectrodes. A more promising approach has been to combine microfabricated light emission sources with multielectrode arrays. However, a challenge remains in how to compactly and scalably integrate optical output and electronic readout structures on the same device. Here we took a step toward addressing this issue by using nanofabrication techniques to develop a novel implantable optoelectronic probe.
Approach:
This device contains multiple photonic grating couplers connected with waveguides for out-of-plane light emission, monolithically integrated with a microlectrode array on the same silicon substrate. To demonstrate the device's operation in vivo, we record cortical activity from awake head-restrained mice.
Main Results:
We first characterize photo-stimulation effects on electrophysiological signals. We then assess the probe's ability to both optogenetically stimulate and electrically record neural firing.
Significance:
This device relies on nanofabrication techniques to integrate optical stimulation and electrical readout functions on the same structure. Due to the device miniaturization capabilities inherent to nanofabrication, this optoelectronic probe technology can be further scaled to increase the throughput of manipulating and recording neural dynamics.
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