Transparent Sapphire Optrodes

Electrodes record electrical activity from the brain. This is a very important first step in understanding how the brain works, because the brain processes information by sending small electric events called action potentials or spikes between neurons. Understanding how these electrical events relate to brain function is one of the main approaches to understanding how the brain works.

Brain cells can also be controlled with light. While these cells are not naturally light sensitive, this property can be introduced with genetic manipulations. Through the introduction of different genes, neurons express excitatory or inhibitory channels and other proteins, such that neurons can be turned on or off with different types of light. Once that is done, the next challenge is to find methods to get the appropriate light stimulus into the brain and to the correct location at the correct time. This can be done with optical fibers or LEDs that are advanced into the brain. And optrode is a combination of an electrode and a light source (an optical device) and allows an investigator to record neural activity and at the same time send light stimuli into the brain during an optogenetic manipulation. The simplest way to do construct an optrode is to attach an optical fiber to the electrode and connect that fiber to a laser or LED light source at the other end. More sophisticated approaches involve an LED directly placed inside the brain, directly next to the recording site(s). Both techniques require significant manipulation by the users and proper equipment and skills are required to create these custom optrodes.

At PopNeuron, we fabricate our “transparent” optrodes by laying an array of recording channels on a sapphire substrate. Subsequently, one or more high-brightness blue light LEDs are grown directly on top of the sapphire substrate, creating a durable and user-friendly optrode for simultaneous electrophysiology recording and optogenetic stimulation. The advantage of this approach is that arbitrary arrangements of recording sites and LED sites can be designed, which is important for complete and more uniform illumination of brain areas with challenging layouts. Technical details: Most semiconductor-based neural recording probes use silicon as their substrate. However, silicon’s low mechanical strength makes these probes brittle and prone to breakage during insertion into or extraction from the brain tissue. Additionally, silicon does not fluoresce, making it challenging to grow LEDs directly on silicon-based neural probes. This necessitates flat-mounting external LEDs or integrating external optical fibers into the optrode for optogenetic stimulation. By contrast, sapphire boasts greater mechanical strength, allowing for multiple insertions and extractions into/from brain tissues without affecting the quality of the recording. Furthermore, sapphire is transparent and its mechanical properties allow LEDs to be grown directly on the sapphire substrate, significantly reducing the complexity of creating these optrodes. Sapphire’s unique optical transparency facilitates optogenetic stimulation of neurons, even if located on the backside of the optrodes, providing greater flexibility for experimental designs.

The illumination intensity is between 5 and 10 mW (keep in mind that ALL that light illuminates brain tissue, there are zero losses at optical fiber interfaces etc) and the recording sites can be manufactured with different resistances which are typically in the low MOhm range. Our initial transparent sapphire optrodes come in 1, 4, and 16 recording channel configurations, with a ~480nm LED for optogenetic stimulation of most channelrhodospins. Future optrodes will offer higher channel configurations and ~580nm LEDs for optogenetic inhibition through halorhodpsin, as well as multiple configurations.

Related Publication:

Double-Sided Sapphire Optrodes with Conductive Shielding Layers to Reduce Optogenetic Stimulation Artifacts.  Junyu Shen, Yanyan Xu, Zhengwen Xiao, Yuebo Liu, Honghui Liu, Fengge Wang, Chaokun Yan, Liyang Wang, Changhao Chen, Zhisheng Wu, Yang Liu, Peng Un Mak, Mang I. Vai, Sio Hang Pun, Tim C. Lei and Baijun Zhang Micromachines 2022, 13, 1836. https://doi.org/10.3390/ mi13111836