Researchers create nanoprinted electrodes for personalized treatment of neurological disorders

Carnegie Mellon University researchers have pioneered the CMU Array, a new type of microelectrode array for brain-computer interface platforms. It could change the way doctors can treat neurological diseases.

Ultra-high density microelectrode array (MEA), which is 3D printed at the nanoscale, is fully customizable. This means that one day patients suffering from epilepsy or loss of limb function due to stroke will be able to receive personalized treatment optimized for their individual needs.

The collaboration brings together the expertise of Rahul Panat, associate professor in the Department of Mechanical Engineering, and Eric Itri, associate professor in the Department of Biological Sciences. The team applied a state-of-the-art microfabrication technique, aerosol jet 3D printing, to produce arrays that address the major design barriers of other brain computer interface (BCI) arrays. The findings were published in Achievements of science.

“Aerosol jet 3D printing offers three main advantages,” Panath explained. “Users can customize their MEAs to suit specific needs; MEAs can operate in three dimensions in the brain; and the density of the MEA increases and thus becomes more robust.”

MEA-based BCIs are pluggable neurons in the brain with external electronics to monitor or stimulate brain activity. They are often used in applications such as neuroprosthetics, prostheses, and visual implants to transmit information from the brain to limbs that have lost functionality. BMIs also have potential therapeutic applications neurological diseases such as epilepsy, depression and obsessive compulsive disorder. However, existing devices have limitations.

There are two types of popular BCI devices. The oldest MEA is the Utah matrix, developed at the University of Utah and patented in 1993. This silicon-based array uses an array of tiny pins, or stems, that can be inserted directly into the brain to detect electrical discharges from neurons at the tip of each pin.

Another type is the Michigan array, which is printed on flat, fragile silicon chips. It reads the electrons as they fire across the chips. Due to design limitations, both of these arrays can only be written on a two-dimensional plane. This means that they cannot be customized to the needs of each patient or application.

The most important aspect of MEA is its density-limited three-dimensional sampling capability microelectrodes in an array and the ability to place these arrays in the place you want to feel. Current MEA fabrication technologies have made tremendous strides with respect to the density of these microelectrode arrays. Adding a third dimension greatly increases the sampling power of arrays. In addition, custom-made MEAs for each specific application allow for more precise and more accurate readings.

The researchers’ CMU array is the densest BCI, about one order of magnitude denser than the BCI of the Utah array.

Higher quality MES are in demand. MEAs used to control virtual actions on a computer or complex limb movements face limitations of current technology. More advanced applications require MEAs that are customized for each individual and are much more accurate than those currently available.

“Within days, we can produce a precision medical device tailored to the needs of the patient or experimenter,” says Itri, co-senior author of the study. Furthermore, while technologies such as visual stimulation of the cerebral cortex and control of artificial limbs have been successfully used by the public, the ability to personalize the control system in the brain can pave the way for huge advances in this field.

Panath predicts it could take five years to see human trials and even longer to see commercial use. The team is excited to bring this successful process to other researchers in the field to begin testing a wide range of applications.

The CMU Array’s architecture and manufacturing method are patent pending. The next step, Panat says, is to work with the National Institutes of Health (NIH) and other business partners to take these results to other labs as quickly as possible and apply for funding to commercialize the technology.