Neural Grain network successfully records brain activity

While most existing brain-computer interface systems can only use one or two sensors for sampling, the latest neural interface system can coordinate the activity of hundreds of extremely small brain sensors. This result is a key step toward a new conceptual form of brain-computer interface. Brain-computer interfaces, an emerging assistive device, may one day help patients with brain or spinal cord damage regain the ability to move or communicate. Brain-machine interface systems rely on implantable sensors that record electrical signals in the brain and then use the signals to drive external devices such as computers or mechanical prostheses. Most current brain-machine interface systems use one or two sensors to sample up to a few hundred neurons, but neuroscientists have been hoping to collect data from a larger population of brain cells with more sensors.

This time, a team of researchers, including engineers from Brown University, Baylor University and other institutions, has taken a key step toward a new future form of brain-computer interfaces. The newly developed system uses a coordinated network of independent wireless micro-neural sensors, each about the size of a grain of salt, to record and stimulate brain activity. These sensors, called "neural grains," can independently record electrical impulses generated by excited neurons and send the signals wirelessly to an external hub for coordination and processing.

In the experiment, the team demonstrated significant success in recording rodent neural activity using 48 "neurograin" sensors. These "grains" were placed on the animal's cerebral cortex and successfully recorded characteristic neural signals associated with spontaneous brain activity, and the data suggest that the system in its current configuration can support up to 770 "neural grains. The team hopes it can eventually coordinate thousands of "neural grains" to provide a never-before-seen "picture" of brain activity.

The researchers say one of the big challenges in the field of brain-computer interfaces is to devise ways to detect as many points in the brain as possible. They believe that one day people will be able to record brain signals in unprecedented detail, leading to new insights into how the brain works and new treatments for people with brain or spinal cord injuries.