Neural Dust, A Platform for Neural Interfaces

The emerging field of bioelectronic medicine seeks methods for deciphering and modulating electrophysiological activity in the body to attain therapeutic effects at target organs. Current approaches to interfacing with peripheral nerves and muscles rely heavily on wires, creating problems for chronic use, while emerging wireless approaches lack the size scalability necessary to interrogate small-diameter nerves. Furthermore, conventional electrode-based technologies lack the capability to record from nerves with high spatial resolution or to record independently from many discrete sites within a nerve bundle. Recently, we demonstrated neural dust, a wireless and scalable ultrasonic backscatter system for powering and communicating with implanted bioelectronics. We show that ultrasound is effective at delivering power to mm-scale devices in tissue; likewise, passive, battery-less communication using backscatter enables high-fidelity transmission of electromyogram (EMG) and electroneurogram (ENG) signals from anesthetized rats. These results highlight the potential for an ultrasound-based neural interface system for advancing future bioelectronics-based therapies.
Michel Maharbiz is Professor of Electrical Engineering and Computer Sciences at UC Berkeley. His current research centers on building micro/nano interfaces to cells and organisms and exploring bio-derived fabrication methods. His research group is also known for developing the world’s first remotely radio-controlled cyborg beetles; this was named one of the top 10 emerging technologies of 2009 by MIT’s Technology Review (TR10) and was among Time magazine’s Top 50 Inventions of 2009. His long-term goal is understanding developmental mechanisms as a way to engineer and fabricate machines.

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