Next Generation Brain-Computer Interface System

The latest BCI systems use one or two sensors to sample up to a few hundred neurons, but neuroscientists are interested in systems capable of collecting data from larger brain cell groups
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Now, a group of researchers has taken a critical step towards the new concept of the future BCI system-the system uses a coordinated network composed of independent wireless micro-neural sensors, each sensor is only about the size of a grain of salt to record And stimulate brain activity
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These sensors, called "nerve particles," independently record the electrical impulses triggered by neurons, and wirelessly send the signals to the central center that coordinates and processes the signals

In a study published in the journal Nature Electronics on August 12, the research team demonstrated the use of nearly 50 such autonomic nerve particles to record the nerve activity of rodents
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The researchers say this result is a step towards a system that one day can record brain signals in unprecedented detail, which will bring new insights into the working principle of the brain and provide new treatments for patients with brain or spinal cord injuries.
Method
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Arto Nurmikko, a professor at Brown University’s School of Engineering and the lead author of the study, said: “A major challenge in the field of brain-computer interfaces is to use engineering methods to detect as many points in the brain as possible
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So far, Most BCIs are monolithic devices-kind of like small needle beds

The team includes experts from Brown University, Baylor University, University of California, San Diego, and Qualcomm, and began developing the system about four years ago
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Nurmiko is affiliated with Brown's Carney Institute for Brain Science, and he said the challenge is twofold

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The second challenge is to develop an in vitro communication center that can receive signals from tiny chips
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The device is a thin patch the size of a thumb fingerprint, attached to the scalp outside the skull

"This work is a real multidisciplinary challenge," said Jihun Lee, a postdoctoral researcher at Brown University and the first author of the study
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"We must combine expertise in electromagnetics, radio frequency communications, circuit design, manufacturing, and neuroscience to design and operate neuroparticle systems

The goal of this new study is to prove that the system can record neural signals from a living brain—in this case, the brain of a rodent
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The research team placed 48 nerve particles on the animal's cerebral cortex (the outer layer of the brain) and successfully recorded the characteristic neural signals associated with spontaneous brain activity

The team also tested the ability of these devices to stimulate and record the brain
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Stimulation uses tiny electrical impulses to activate nerve activity

The size of the animal brain limited the research team’s 48 nerve particles in this study, but the data shows that the current configuration of the system can support 770
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Ultimately, the team envisions expanding it to thousands of nerve particles, which will provide images of brain activity that are currently unavailable

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Vincent Leung, associate professor of Baylor Electronics and Computer Engineering, said: "This is a challenging task because the system requires simultaneous wireless power transmission and networking at a rate of megabits per second, and this must be done in an extremely tight silicon area.
And power constraints
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Our team promotes the development of distributed neural implants
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To make this complete system a reality, there is still a lot of work to be done, but the researchers said that this research is a key step in this direction
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Nurmiko said: "We hope to eventually develop a system that will provide new scientific insights to the brain and provide new treatments to help those affected by severe trauma
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Jihun Lee, Vincent Leung, Ah-Hyoung Lee, Jiannan Huang, Peter Asbeck, Patrick P.
Mercier, Stephen Shellhammer, Lawrence Larson, Farah Laiwalla, Arto Nurmikko.
Neural recording and stimulation using wireless networks of microimplants .
Nature Electronics , 2021; DOI : 10.
1038/s41928-021-00631-8