This paper explores the fundamental system design trade-offs and ultimate size, power, and bandwidth scaling limits of neural recording systems.
A network of tiny implantable sensors could function like an MRI inside the brain, recording data on nearby neurons and transmitting it back out. The smart dust particles would all contain an extremely small CMOS sensor capable of measuring electrical activity in nearby neurons. The researchers envision a piezoelectric material backing the CMOS capable of generating electrical signals from ultrasound waves. The process would also work in reverse, allowing the dust to beam data back via high-frequency sound waves. The neural dust would also be coated with polymer. (Source)
Their idea is to sprinkle electronic sensors the size of dust particles into the cortex and to interrogate them remotely using ultrasound. The ultrasound also powers this so-called neural dust.
Each particle of neural dust consists of standard CMOS circuits and sensors that measure the electrical activity in neurons nearby...
The neural dust is interrogated by another component placed beneath the scale but powered from outside the body. This generates the ultrasound that powers the neural dust and sensors that listen out for their response, rather like an RFID system.
The system is also tetherless–the data is collected and stored outside the body for later analysis. (source, MIT)
That’s why Seo and co have chosen ultrasound to send and receive data. They calculate that the power required to use electromagnetic waves on the scale would generate a damaging amount of heat because of the amount of energy the body absorbs and the troubling signal-to-noise ratios at this scale.
By contrast, ultrasound is a much more efficient and should allow the transmission of at least 10 million times more power than electromagnetic waves at the same scale. (emphasis added).