Current neural implant technologies suffer from various limitations. For instance, existing surface arrays are minimally invasive, although they are unable to capture information beyond the brain’s outer layers. In contrast, electrode arrays with thin needles that penetrate the brain can probe deeper layers but often cause inflammation and scarring, thus compromising signal quality over time. Now, a thin, flexible implant when placed on the surface of the brain enables researchers to capture high-resolution information about neural activity deep inside the brain without causing any damage to its delicate tissue.

Researchers at the University of California San Diego (La Jolla, CA, USA) have developed a groundbreaking neural implant that can provide information about deep brain activity while being non-invasively positioned on the brain's surface. This innovative device consists of a slim, flexible polymer strip embedded with a densely packed array of graphene electrodes, each with a diameter of 20 micrometers. All the electrodes are connected by a micrometers-thin graphene wire to a circuit board. This technological advancement, successfully trialed in transgenic mice, marks significant progress toward creating a less invasive brain-computer interface (BCI). Such an interface would be capable of providing detailed insights into deep neural activities through recordings made on the brain's surface.

In experimental applications on transgenic mice, this neural implant demonstrated its ability to capture high-resolution data on two distinct types of neural activities: electrical and calcium activities, simultaneously. When positioned on the surface of the brain, the implant recorded electrical signals from the neurons in the outer layers. Concurrently, the researchers employed a two-photon microscope, projecting laser light through the implant to visualize calcium spikes from neurons up to 250 micrometers beneath the surface. They discovered a notable correlation between the electrical signals captured from the surface and the calcium spikes occurring in deeper layers. This correlation was significant as it allowed the team to train neural networks to accurately predict calcium activity.

This prediction was not just limited to large groups of neurons but extended to individual neurons at varying depths. The capability to predict calcium activity based on electrical signals addresses the constraints of conventional imaging experiments. Typically, imaging calcium spikes requires the subject's head to be immobilized under a microscope in experiments spanning just one or two hours. However, this new implant technology offers a more dynamic and prolonged approach to studying brain activities, overcoming these limitations and paving the way for more advanced and continuous neural monitoring.

“We are expanding the spatial reach of neural recordings with this technology,” said study senior author Duygu Kuzum, a professor in the Department of Electrical and Computer Engineering 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.” 

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