Researchers create transparent implant to decipher deep brain activity

Researchers have created a cutting edge transparent capable of offering precise insights into deep brain activity from its surface alone. Researchers at the University of California, San Diego, developed this implant using a high electrode density combined with machine learning. Importantly, this implant is non invasive and doesn't damage the brain's delicate tissues.

The specifications of the implant The newly developed implant has innovative design aspects, including a thin, flexible polymer strip loaded with small circular graphene electrodes. Each electrode has a diameter of around 20 micrometers and is connected to a circuit board via a micrometer thin graphene wire.

The team highlights that this implant represents a significant stride towards constructing a minimally invasive brain computer interface (BCI). According to the official release, it can provide high resolution data on deep neural activity when positioned on the brain's surface. "We are expanding the spatial reach of neural recordings with this technology," said study senior author Duygu Kuzum, a Department of Electrical and Computer Engineering professor at the UC San Diego Jacobs School of Engineering.

"Even though our implant resides on the brain's surface, its design goes beyond the limits of physical sensing in that it can infer neural activity from deeper layers,” added Kuzum. Implant tested on mice model The study team tested this implant on transgenic mice. Interestingly, the implant effectively captured two forms of brain activity: electrical and calcium.

It was positioned on the brain's surface and collected from neurons in the outer layers. The scientists used a two photon microscope to guide laser light through the implant, allowing them to image calcium spikes from neurons 250 micrometers below the surface. What distinguishes this implant is its capacity to capture both activities simultaneously.

"This new generation of transparent graphene electrodes embedded at high density enables us to sample neural activity with higher spatial resolution," said Kuzum. "As a result, the quality of signals improves significantly. What makes this technology even more remarkable is the integration of machine learning methods, which make it possible to predict deep neural activity from surface signals," explained Kuzum in the .

In recent years, brain implants have been claimed to play an important role in different sectors, contributing to improvements in medical and scientific realms. Neural implants could be used to treat neurological disorders such as epilepsy, Parkinson's disease, and chronic pain by modulating neural activity.

This neural implant offers a significant advancement in understanding and recording deep brain activity, with potential implications for improving brain computer interface technology and our knowledge of neurological processes. The details of this implant have been published in . Optically transparent neural microelectrodes have facilitated simultaneous electrophysiological recordings from the brain surface with the optical imaging and stimulation of neural activity.

A remaining challenge is to scale down the electrode dimensions to the single cell size and increase the density to record neural activity with high spatial resolution across large areas to capture nonlinear neural dynamics. Here we developed transparent graphene microelectrodes with ultrasmall openings and a large, transparent recording area without any gold extensions in the field of view with high density microelectrode arrays up to 256 channels.

We used platinum nanoparticles to overcome the quantum capacitance limit of graphene and to scale down the microelectrode diameter to 20 µm. An interlayer doped double layer graphene was introduced to prevent open circuit failures..