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Home  /  About  /  News  /  Ultrasound Enables Less-Invasive Brain–Machine
Interfaces



ULTRASOUND ENABLES LESS-INVASIVE BRAIN–MACHINE INTERFACES

November 30, 2023

Brain–machine interfaces (BMIs) are devices that can read brain activity and
translate that activity to control an electronic device like a prosthetic arm or
computer cursor. They promise to enable people with paralysis to move prosthetic
devices with their thoughts.

Many BMIs require invasive surgeries to implant electrodes into the brain in
order to read neural activity. However, in 2021, Caltech researchers developed a
way to read brain activity using functional ultrasound (fUS), a much less
invasive technique.

Now, a new study is a proof-of-concept that fUS technology can be the basis for
an "online" BMI—one that reads brain activity, deciphers its meaning with
decoders programmed with machine learning, and consequently controls a computer
that can accurately predict movement with very minimal delay time.

The study was conducted in the Caltech laboratories of Richard Andersen, James
G. Boswell Professor of Neuroscience and director and leadership chair of the
T&C Chen Brain–Machine Interface Center; and Mikhail Shapiro, Max Delbrück
Professor of Chemical Engineering and Medical Engineering and Howard Hughes
Medical Institute Investigator. The work was a collaboration with the laboratory
of Mickael Tanter, director of physics for medicine at INSERM in Paris, France.

"Functional ultrasound is a completely new modality to add to the toolbox of
brain–machine interfaces that can assist people with paralysis," says Andersen.
"It offers attractive options of being less invasive than brain implants and
does not require constant recalibration. This technology was developed as a
truly collaborative effort that could not be accomplished by one lab alone."

"In general, all tools for measuring brain activity have benefits and
drawbacks," says Sumner Norman, former senior postdoctoral scholar research
associate at Caltech and a co-first author on the study. "While electrodes can
very precisely measure the activity of single neurons, they require implantation
into the brain itself and are difficult to scale to more than a few small brain
regions. Non-invasive techniques also come with tradeoffs. Functional magnetic
resonance imaging [fMRI] provides whole-brain access but is restricted by
limited sensitivity and resolution. Portable methods, like
electroencephalography [EEG] are hampered by poor signal quality and an
inability to localize deep brain function."

Ultrasound imaging works by emitting pulses of high frequency sound and
measuring how those sound vibrations echo throughout a substance, such as
various tissues of the human body. Sound waves travel at different speeds
through these tissue types and reflect at the boundaries between them. This
technique is commonly used to take images of a fetus in utero, and for other
diagnostic imaging.

Because the skull itself is not permeable to sound waves, using ultrasound for
brain imaging requires a transparent "window" to be installed into the skull.
"Importantly, ultrasound technology does not need to be implanted into the brain
itself," says Whitney Griggs (PhD '23), a co-first author on the study. "This
significantly reduces the chance for infection and leaves the brain tissue and
its protective dura perfectly intact."

"As neurons' activity changes, so does their use of metabolic resources like
oxygen," says Norman. "Those resources are resupplied through the blood stream,
which is the key to functional ultrasound." In this study, the researchers used
ultrasound to measure changes in blood flow to specific brain regions. In the
same way that the sound of an ambulance siren changes in pitch as it moves
closer and then farther away from you, red blood cells will increase the pitch
of the reflected ultrasound waves as they approach the source and decrease the
pitch as they flow away. Measuring this Doppler-effect phenomenon allowed the
researchers to record tiny changes in the brain's blood flow down to spatial
regions just 100 micrometers wide, about the width of a human hair. This enabled
them to simultaneously measure the activity of tiny neural populations, some as
small as just 60 neurons, widely throughout the brain.

The researchers used functional ultrasound to measure brain activity from the
posterior parietal cortex (PPC) of non-human primates, a region that governs the
planning of movements and contributes to their execution. The region has been
studied by the Andersen lab for decades using other techniques. The animals were
taught two tasks, requiring them to either plan to move their hand to direct a
cursor on a screen, or plan to move their eyes to look at a specific part of the
screen. They only needed to think about performing the task, not actually move
their eyes or hands, as the BMI read the planning activity in their PPC.

"I remember how impressive it was when this kind of predictive decoding worked
with electrodes two decades ago, and it's amazing now to see it work with a much
less invasive method like ultrasound," says Shapiro.

The ultrasound data was sent in real-time to a decoder (previously trained to
decode the meaning of that data using machine learning), and subsequently
generated control signals to move a cursor to where the animal intended it to
go. The BMI was able to successfully do this to eight radial targets with mean
errors of less than 40 degrees.

"It's significant that the technique does not require the BMI to be recalibrated
each day, unlike other BMIs," says Griggs. "As an analogy, imagine needing to
recalibrate your computer mouse for up to 15 minutes each day before use."

Next, the team plans to study how BMIs based on ultrasound technology perform in
humans, and to further develop the fUS technology to enable three-dimensional
imaging for improved accuracy.

The paper is titled "Decoding motor plans using a closed-loop ultrasonic
brain–machine interface" and appears in the journal Nature Neuroscience on
November 30. Whitney Griggs (PhD '23), UCLA-Caltech MD/PhD student, and Sumner
Norman, former postdoctoral scholar now of Forest Neurotech, are the study's
first authors. In addition to Griggs, Norman, and Andersen, Caltech coauthors
are graduate student Geeling Chau and Vasileios Christopoulos, visiting
associate in biology and biological engineering. Other coauthors are Charles Liu
of USC; and Mickael Tanter, Thomas Deffieux, and Florian Segura of INSERM in
Paris, France. Funding was provided by the National Eye Institute, a Josephine
de Karman Fellowship, the UCLA-Caltech MSTP, the Della Martin Foundation, the
National Institute of Neurological Disorders and Stroke, the National Institutes
of Health, the T&C Chen Brain-Machine Interface Center, and the Boswell
Foundation.

Written by
Lori Dajose
Contact
Lori Dajose
(626) 395‑1217
ldajose@caltech.edu
Ultrasound is used to image two-dimensional sheets of the brain, which can then
be stacked together to create a 3-D image. Credit: Courtesy of W. Griggs
Unlocking Movement: Helping Paralyzed People Use Thought to Control Computers
and Robotic Limbs The vasculature of the posterior parietal cortex as measured
by functional ultrasound neuroimaging. Credit: Courtesy of W. Griggs
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