Researchers have developed neurograins, a form of brain-computer interface that creates a network of independent, wireless microscale neural sensors to record and stimulate brain activity.
Brain-computer interfaces (BCIs), emerging assistive devices that could help people with brain or spinal injuries to move or communicate, depend on implantable sensors that record electrical signals in the brain and use those signals to drive external devices like computers or robotic prosthetics.
Most current BCI systems use one or two sensors to sample up to a few hundred neurons, but neuroscientists are said to be interested in systems that gather data from much larger groups of brain cells.
The new neurograins, each about the size of a grain of salt, could overcome this current limitation by independently recording the electrical pulses made by firing neurons and sending the signals wirelessly to a central hub, which coordinates and processes the signals.
In a study published in Nature Electronics, the research team – including experts from Brown University, Baylor University, the University of California at San Diego and Qualcomm – demonstrated the use of nearly 50 neurograins to record neural activity in a rodent.
The results, the researchers said, are a step toward a system that could one day enable the recording of brain signals in exceptional detail, leading to new insights into how the brain works and new therapies for people with brain or spinal injuries.
“One of the big challenges in the field of brain-computer interfaces is engineering ways of probing as many points in the brain as possible,” said Arto Nurmikko, a professor in Brown’s School of Engineering and the study’s senior author. “Up to now, most BCIs have been monolithic devices — a bit like little beds of needles. Our team’s idea was to break up that monolith into tiny sensors that could be distributed across the cerebral cortex. That’s what we’ve been able to demonstrate here.”
The challenge was two-fold, Nurmikko said in a statement. The first part required shrinking the electronics involved in detecting, amplifying and transmitting neural signals into the neurograin chips. The team first designed and simulated the electronics computationally and went through several fabrication iterations to develop operational chips.
The second challenge was developing the body-external communications hub that receives signals from the chips. The device is a thin patch that attaches to the scalp that employs a network protocol to coordinate the signals from the neurograins, each of which has its own network address. The patch also supplies power wirelessly to the neurograins, which are designed to operate using a minimal amount of electricity.
“This work was a true multidisciplinary challenge,” said Jihun Lee, a postdoctoral researcher at Brown and the study’s lead author. “We had to bring together expertise in electromagnetics, radio frequency communication, circuit design, fabrication and neuroscience to design and operate the neurograin system.”
The goal of this new study was to demonstrate that the system could record neural signals from a living brain. The team placed 48 neurograins on a rodent’s cerebral cortex and successfully recorded characteristic neural signals associated with spontaneous brain activity.
According to Brown, the team also tested the devices’ ability to stimulate the brain as well as record from it. Stimulation is done with tiny electrical pulses that can activate neural activity. The stimulation is driven by the same hub that coordinates neural recording and could one day restore brain function lost to illness or injury, researchers hope.
The size of the animal’s brain limited the team to 48 neurograins for this study, but the data suggest that the current configuration of the system could support up to 770. Ultimately, the team envisions scaling up to many thousands of neurograins, which would provide a currently unattainable picture of brain activity.
“It was a challenging endeavour, as the system demands simultaneous wireless power transfer and networking at the mega-bit-per-second rate, and this has to be accomplished under extremely tight silicon area and power constraints,” said Vincent Leung, an associate professor in the Department of Electrical and Computer Engineering at Baylor.
There is more work to be done to make that complete system a reality, but researchers said this study represents a key step in that direction.