Inside Salk - June 2008 - page 10

INST I TUTE NEWS
10
Inside Salk June 2008
IT’S 3:30 P.M. ON A WEEKDAY AFTERNOON AND MEMBERS
of the Salk’s Computational Neurobiology Laboratory (CNL) are starting
to migrate toward their daily meeting place.
The area has a freshwater fish tank, two long sofas arranged in an L
and a round table spread with crackers, chocolate covered almonds
and hot tea for everyone.
It’s a place where they converge to relax and talk about what’s on
their minds—a conference, an interesting article, their experiments,
and in some cases, their plans to turn research into products that will
benefit the public.
Recently, these conversations were about SoftMax, a company
acquired in December by wireless communications giant Qualcomm
for its proprietary noise reduction technology. The algorithm behind
the technology was developed in the CNL and is used to suppress
background noise andmake phone calls more intelligible.
But what does a basic biological research lab at Salk have to
do with cell phones?
Terry Sejnowski,
professor and head of the
CNL, explains.
“Our research is primarily focused on learning about the
human brain and what it can do, and it’s about learning how to
make computers that are able to mimic these processes. It’s a
two-way street.”
The noise-reduction algorithm that led to SoftMax is based on
independent component analysis (ICA), a type of mathematical formula
developed by Tony Bell, a former postdoctoral fellow in Sejnowski’s lab.
The algorithm solved the cocktail party problem: How to separate out a
single sound source frommixtures of recorded signals.
SoftMax independently developed a version of ICA that mimics the
human auditory system. It uses a pair of microphones in a cell phone
headset, much like a pair of ears, to measure differences in loudness
and timing to separate the source of a voice from the background.
“It identifies a speaker’s voice from every other sound, and simply
intensifies the voice signal while dampening the others,” explains
Sejnowski, who was on SoftMax’s scientific board.
Alternative ICA algorithms for sound reduction exist, he notes, but
the SoftMax version is more robust because it can be used with two,
10, or 100microphones for better sound resolution.
ICA can be used with any type of signal, not just sound. One day, for
example, it may helpmachines read electrocardiograms to reduce the
time cardiologists spend with paper recordings and computers. It’s
already being used to understand what segments of our DNA are being
transcribed, and what simply represents interfering background noise.
Philip Low is a postdoctoral fellow in the CNL who has been using
electroencephalograms (EEG) to study sleep in birds and humans.
With Sleep Parametric EEG Automated Recognition System (SPEARS),
an algorithm he created at CNL during his doctorate studies, Low has
been able to study brain activity using only two electrodes placed on
the scalp, not the dozens that are normally placed all over the head
and body in sleep studies.
Furthermore, using SPEARS, he has identified a new range of
electrical activity, or “sleep state,” that was previously masked by the
low frequency waves produced during sleep. This new technology has
led Drs. Low and Sejnowski to formNeuroVigil, a company that
revolutionizes the way brain electrical activity is both recorded
and analyzed.
Through a collaborative consortium withmajor academic
institutions, NeuroVigil plans to perform basic research for the iBrain,
an iPod for the brain, which will monitor people’s health in real-time.
“I’ve been very fortunate because the members of my lab are
exceptionally talented,” says Sejnowski. “We form an eclectic team,
with backgrounds inmathematics, physics, electrical engineering,
psychology, and even philosophy. But this is what’s required to even
approach solving the big problems of how the brain works.”
I’ve been very fortunate because the
members of my lab are exceptionally
talented. We form an eclectic team,
with backgrounds inmathematics,
physics, electrical engineering,
psychology, and even philosophy.
But this is what’s required to even
approach solving the big problems
of how the brain works.
– TERRY SEJNOWSKI
Researchers Develop Algorithms toMake Sense of andMimic the Brain
Philip Low (from left), programmer TomBartol, and Terry Sejnowski.
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