IEEE Spectrum September, 2014 - 43

as a patient moves or speaks under carefully controlled conditions, we record the ECoG signals and learn how the brain encodes
intentions and thoughts. Now we are beginning to use those signals to control computers, robots, and prostheses. the woman
in the hospital room didn't need any mind-controlled mechanical devices herself, but she was helping us develop technology
that could one day allow paralyzed patients to control robotic
limbs of their own.

he machine at the end of a brain-machine interface could be anything: over the past few decades,
researchers have experimented with using neural signals to control a computer cursor, a wheelchair, and
even a car. the dream of building a brain-controlled
prosthetic limb, however, has received particular attention.
in 2006 the U.s. Defense advanced research Projects agency
(DarPa) bankrolled a massive effort to build a cutting-edge prosthetic arm and to control it with brain signals. in the first phase of
this revolutionizing Prosthetics program, the Johns hopkins applied
Physics Laboratory developed a remarkable piece of machinery
called the Modular Prosthetic Limb, which boasts 26 degrees of
freedom through its versatile shoulder, elbow, wrist, and fingers.
to give amputees control of the mechanical arm, researchers first
tried out existing systems that register the electrical activity in the
muscles of the limb stump and transmit those signals to the prosthesis. But such systems offer very limited control, and amputees
don't find them intuitive to use. so DarPa issued its next revolutionizing Prosthetics challenge in 2009, asking researchers to control the
state-of-the-art prosthetic arm directly with signals from the brain.
several investigators answered that call by using brain implants
with penetrating electrodes. at Duke University, in Durham, N.C.,
and the University of Pittsburgh, researchers had already placed
microelectrodes in the brains of monkeys, using the resulting signals to make a robotic arm reach and grasp. Neuroscientists at
Brown University, in Providence, r.i., had implanted similar microelectrodes in the cortex of a paralyzed man and showed that
he could control a computer cursor using neural signals. another
paralyzed patient who underwent this procedure at Brown recently
controlled a robotic arm: she used it to raise a bottle to her lips to
take a drink, performing her first independent action in 14 years.
that work certainly demonstrated the feasibility of building a
"neural prosthesis." But using penetrating electrodes poses significant challenges. scar tissue builds up around the electrodes and

can reduce signal quality over time. also, the hardware, including
electrode arrays and low-power transmitters that send the signal
out through the skull, must operate reliably for many years. Finally,
these first demonstrations did not produce smooth, quick, or dexterous movements. some neuroscientists suggested that many more
electrodes should be implanted-but doing so would heighten the
risk of damaging brain tissue.
in light of those concerns, the United states' National institutes of
health challenged researchers to build a neural prosthesis with a less
invasive control mechanism. the ideal would be a system based on
EEG signals, simply using electrodes attached to the scalp. Unfortunately, the brain signals that external electrodes pick up are blurred
and attenuated by their passage through the skull and scalp. this
led our team to investigate the middle road: the use of ECoG signals.
ECoG systems provide a better signal-to-noise ratio than EEG,
and the data includes high-frequency components that EEG can't
easily capture. ECoG systems also do a better job of extracting the
most useful information from the brain, as an electrode placed over
the motor cortex can specifically listen in on the electrical activity
most relevant for controlling a prosthetic arm. similarly, electrodes
draped over the brain areas associated with speech can capture
signals associated with verbal communication.
raw ECoG signals appear to be a confused mess of squiggly lines
with little discernible pattern. to make sense of the data, our team
performs a spectral analysis to deconstruct the signal and find oscillations at certain specific frequencies. these are the brain waves you
may have heard about. Neuroscientists have learned that different
oscillation frequencies are associated with specific mental states,
such as deep sleep, focused attention, or meditative contemplation.
Just imagine what neural prostheses could do for people who
are severely paralyzed or for patients in the late stages of amyotrophic lateral sclerosis (also known as Lou Gehrig's disease).
these patients are essentially "locked in," with intact brains but
no ability to control their bodies, or even to speak. Could their
intentions, translated into ECoG signals, be captured and relayed
to robotic limbs?

EEG

iMPLAnt

ECoG

three ways to taP the brain To record the activity of brain
cells, neuroscientists can use implanted electrodes that penetrate
the cortex. This method provides the clearest signal, but it's also the
riskiest. In contrast, scalp electrodes for electroencephalography
(EEG) carry no risks, but the signal they capture is indistinct.
Electrocorticography (ECoG), which uses electrodes draped over the
surface of the cortex, may represent the "sweet spot," a compromise
between risk and clarity.

illustration by

Nicolas Rapp

SPEctrUm.iEEE.orG

North AmEricAN

SEP 2014

http://SPEctrUm.iEEE.orG

Table of Contents for the Digital Edition of IEEE Spectrum September, 2014