Electrical engineering and computer sciences professor Rikky Muller (Photo by Adam Lau/Berkeley Engineering)Q+A on neurotechnologies
Imagine tiny devices that can sense when you’re drowsy, deliver a dose of medication or communicate wirelessly with the brain — all while using almost no power. That’s the vision driving Rikky Muller (Ph.D.’13 EECS), associate professor of electrical engineering and computer sciences, and her team at the Muller Lab, where researchers are building complete end-to-end devices for neurological applications that are smarter, safer and smaller than ever.
What major challenges do you face designing these types of devices?
One challenge that we’re focusing on right now is making devices that are more intelligent and individualized. There’s a huge degree of variability between people, both in terms of the signals that we record and in terms of the responses to therapy — such as neurostimulation or drug delivery — so we really want to close the loop. We want to build devices that can make continuous observations, that extract biomarkers of aberrant states and that can autonomously determine the best therapy for a patient. Hopefully, that’s going to lead to better outcomes, faster timeframes and lower costs.
What’s different about creating a device for the human body?
The human body is a harsh environment for electronics. First, it’s made of water, which doesn’t mix well with electronics. Second, it’s always trying to reject foreign objects. Third, it’s sensitive to increases in temperature, which can result in tissue death. And fourth, it’s prone to infection. So we need to make the electronics extremely small to reduce foreign body response and wireless to reduce infection risk. We also have to make them out of biocompatible materials, make sure that they’re flexible and compliant so that they don’t cause any tissue damage, and make sure they dissipate miniscule amounts of power so that they don’t chronically heat the tissue. At the same time, we need to put a lot of functionality — and now intelligence — onto these devices, which is a major technical challenge.
How could devices address obesity or diabetes?
A major theme in my lab is closing the loop around therapeutic devices, incorporating sensing to make sure that the therapy is doing what it’s supposed to be doing. We’re applying that idea to drug delivery. Today’s GLP-1 [diabetes and weight-loss] drugs require a once-a-week injection. The dose remains in your body and fluctuates throughout the week until your next injection. Our aim is to use an implantable device to produce a sustained drug delivery dose over a long period of time. While you can genetically engineer cells to synthesize biologic drugs like insulin and GLP-1s, you can also modify these cells to produce fluorescent proteins. Our implantable device will use fluorescence sensing to measure the delivered drug dose, enabling closed-loop control to ensure a consistent dosage.
You’re working with professors Laura Waller and Hillel Adesnik on a project to use holograms to communicate with the brain. What insights do you hope to gain?
In just one cubic millimeter of the cerebral cortex, there are about 50,000 neurons. There is no tool available today that allows us to communicate bidirectionally with all 50,000 neurons and at their natural timescales of communication without making total Swiss cheese of the brain. We’re now aiming to do that with light. The idea is that we can modify neurons to emit light signals through fluorescence and to be receptive to light signals — a technique known as optogenetics. We’re developing an instrument that generates points of light in 3D patterns, also known as point-cloud holograms. That allows us to shine light in specific places and time points to communicate with specific neurons without disturbing the neural tissue. We can also switch through these patterns quickly, enabling communication with a very large number of neurons in a small period of time. Because we can switch very, very quickly, we can essentially talk to these neurons and get signals from them at the natural speeds at which they communicate. So you can think of this like a high-speed optical I/O to the brain.
There’s no instrument today that can do that for tens of thousands or hundreds of thousands of neurons, and that’s what we’re aiming to do. It could profoundly change our understanding of basic neuroscience, to be able to understand how neural circuits form, evolve and function — and how disease progresses.
How will AI advance neurotechnologies?
Our ability to now put AI on the device or on a single chip will bring intelligence directly on the device itself, rather than having to stream out to a computer and do inference in the cloud. That’s going to push the field forward, since [individual] devices will be able to make autonomous decisions in real time, in situ. In my lab, we think of it as having a tiny doctor in the device. I really believe that’s the future.
Learn more: With these devices, the doctor is always in