SALT LAKE CITY, Sept. 7, 2010 – In an early step toward
letting severely paralyzed people speak with their thoughts,
University of Utah researchers translated brain signals into words
using two grids of 16 microelectrodes implanted beneath the skull
but atop the brain.
"We have been able to decode spoken words using only signals
from the brain with a device that has promise for long-term use in
paralyzed patients who cannot now speak," says Bradley Greger, an
assistant professor of bioengineering.
Because the method needs much more improvement and involves
placing electrodes on the brain, he expects it will be a few years
before clinical trials on paralyzed people who cannot speak due to
so-called "locked-in syndrome."
The Journal of Neural Engineering's September issue is
publishing Greger's study showing the feasibility of translating
brain signals into computer-spoken words.
The University of Utah research team placed grids of tiny
microelectrodes over speech centers in the brain of a volunteer
with severe epileptic seizures. The man already had a craniotomy
– temporary partial skull removal – so doctors could
place larger, conventional electrodes to locate the source of his
seizures and surgically stop them.
Using the experimental microelectrodes, the scientists recorded
brain signals as the patient repeatedly read each of 10 words that
might be useful to a paralyzed person: yes, no, hot, cold, hungry,
thirsty, hello, goodbye, more and less.
Later, they tried figuring out which brain signals represented
each of the 10 words. When they compared any two brain signals
– such as those generated when the man said the words "yes"
and "no" – they were able to distinguish brain signals for
each word 76 percent to 90 percent of the time.
When they examined all 10 brain signal patterns at once, they
were able to pick out the correct word any one signal represented
only 28 percent to 48 percent of the time – better than
chance (which would have been 10 percent) but not good enough for a
device to translate a paralyzed person's thoughts into words spoken
by a computer.
"This is proof of concept," Greger says, "We've proven these
signals can tell you what the person is saying well above chance.
But we need to be able to do more words with more accuracy before
it is something a patient really might find useful."
People who eventually could benefit from a wireless device that
converts thoughts into computer-spoken spoken words include those
paralyzed by stroke, Lou Gehrig's disease and trauma, Greger says.
People who are now "locked in" often communicate with any movement
they can make – blinking an eye or moving a hand slightly
– to arduously pick letters or words from a list.
University of Utah colleagues who conducted the study with
Greger included electrical engineers Spencer Kellis, a doctoral
student, and Richard Brown, dean of the College of Engineering; and
Paul House, an assistant professor of neurosurgery. Another
coauthor was Kai Miller, a neuroscientist at the University of
Washington in Seattle.
The research was funded by the National Institutes of Health,
the Defense Advanced Research Projects Agency, the University of
Utah Research Foundation and the National Science Foundation.
Nonpenetrating Microelectrodes Read Brain's Speech
Signals
The study used a new kind of nonpenetrating microelectrode that
sits on the brain without poking into it. These electrodes are
known as microECoGs because they are a small version of the much
larger electrodes used for electrocorticography, or ECoG, developed
a half century ago.
For patients with severe epileptic seizures uncontrolled by
medication, surgeons remove part of the skull and place a silicone
mat containing ECoG electrodes over the brain for days to weeks
while the cranium is held in place but not reattached. The
button-sized ECoG electrodes don't penetrate the brain but detect
abnormal electrical activity and allow surgeons to locate and
remove a small portion of the brain causing the seizures.
Last year, Greger and colleagues published a study showing the
much smaller microECoG electrodes could "read" brain signals
controlling arm movements. One of the epileptic patients involved
in that study also volunteered for the new study.
Because the microelectrodes do not penetrate brain matter, they
are considered safe to place on speech areas of the brain –
something that cannot be done with penetrating electrodes that have
been used in experimental devices to help paralyzed people control
a computer cursor or an artificial arm.
EEG electrodes used on the skull to record brain waves are too
big and record too many brain signals to be used easily for
decoding speech signals from paralyzed people.
Translating Nerve Signals into Words
In the new study, the microelectrodes were used to detect weak
electrical signals from the brain generated by a few thousand
neurons or nerve cells.
Each of two grids with 16 microECoGs spaced 1 millimeter (about
one-25th of an inch) apart, was placed over one of two speech areas
of the brain: First, the facial motor cortex, which controls
movements of the mouth, lips, tongue and face – basically the
muscles involved in speaking. Second, Wernicke's area, a little
understood part of the human brain tied to language comprehension
and understanding.
The study was conducted during one-hour sessions on four
consecutive days. Researchers told the epilepsy patient to repeat
one of the 10 words each time they pointed at the patient. Brain
signals were recorded via the two grids of microelectrodes. Each of
the 10 words was repeated from 31 to 96 times, depending on how
tired the patient was. Then the researchers "looked for patterns in
the brain signals that correspond to the different words" by
analyzing changes in strength of different frequencies within each
nerve signal, says Greger.
The researchers found that each spoken word produced varying
brain signals, and thus the pattern of electrodes that most
accurately identified each word varied from word to word. They say
that supports the theory that closely spaced microelectrodes can
capture signals from single, column-shaped processing units of
neurons in the brain.
One unexpected finding: When the patient repeated words, the
facial motor cortex was most active and Wernicke's area was less
active. Yet Wernicke's area "lit up" when the patient was thanked
by researchers after repeating words. It shows Wernicke's area is
more involved in high-level understanding of language, while the
facial motor cortex controls facial muscles that help produce
sounds, Greger says.
The researchers were most accurate – 85 percent – in
distinguishing brain signals for one word from those for another
when they used signals recorded from the facial motor cortex. They
were less accurate – 76 percent – when using signals
from Wernicke's area. Combining data from both areas didn't improve
accuracy, showing that brain signals from Wernicke's area don't add
much to those from the facial motor cortex.
When the scientists selected the five microelectrodes on each
16-electrode grid that were most accurate in decoding brain signals
from the facial motor cortex, their accuracy in distinguishing one
of two words from the other rose to almost 90 percent.
In the more difficult test of distinguishing brain signals for
one word from signals for the other nine words, the researchers
initially were accurate 28 percent of the time – not good,
but better than the 10 percent random chance of accuracy. However,
when they focused on signals from the five most accurate
electrodes, they identified the correct word almost half (48
percent) of the time.
"It doesn't mean the problem is completely solved and we can all
go home," Greger says. "It means it works, and we now need to
refine it so that people with locked-in syndrome could really
communicate."
"The obvious next step – and this is what we are doing
right now – is to do it with bigger microelectrode grids"
with 121 micro electrodes in an 11-by-11 grid, he says. "We can
make the grid bigger, have more electrodes and get a tremendous
amount of data out of the brain, which probably means more words
and better accuracy."
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