“If she was using this system in everyday life, it would be reliable to a certain
extent,” Donoghue says.
Still, researchers are working hard to
make implantable devices that do more.
BrainGate’s robotic arm could reach
and grasp an object, but it didn’t have
the maneuverability of a typical arm. A
human arm uses dozens of independent
muscles to move up-down or left-right
and control the positions of the shoulder, elbow, forearm and wrist. Hands
also require many independent muscle
movements, or “degrees of freedom,” to
pinch, grasp, hold and squeeze.
At the University of Pittsburgh,
Schwartz is preparing to test in people a
thought-controlled arm with 17 degrees
of freedom. The arm will have a full
range of motion in the shoulder, elbow
and wrist, with a hand capable of curling around a coffee mug or picking up a
small item such as a pencil.
“This will allow us to start trying to do
dexterous tasks, things that have never
been attempted before,” Schwartz says.
Already, monkeys have used a version of
this remote arm, as Schwartz reported
in February at the annual meeting of the
American Association for the Advancement of Science.
In order to get the brain signals to
do all of this, Schwartz’s group will
record firings from twice the number
of neurons as used in the BrainGate
studies. Three patients will have two
Tic Tac–sized arrays implanted into
their brains. Each array will contain
In recent years, researchers have found
ways to capture electrical signals from
the brain without having to poke anything into the brain tissue.
Daniel Moran of Washington University in St. Louis is among the scientists
tapping into these signals. The approach
“The better we
get at moving
arms out to
things, the
more we need
to work on the
sensors to allow
us to feel those
things.”
KRISHNA SHENOY
is based on electrocortico-graphy, or ECoG, a method
used by doctors to detect
electrical activity in the
brain. Making an incision
in the scalp and removing
a portion of the skull are
still required; surgeons
then place the electrode
grids directly on the surface of the dura mater, a
thin leatherlike membrane
covering the brain.
From this location,
With training, the neural groups can
adjust themselves to signal for specific
movements. For example, patients can
be taught to move a cursor on a screen
in a specific direction as they think
about wiggling their fingers. As the brain
adapts, subjects no longer have to imagine wiggling digits; they simply think
“cursor right” and the neural group connected to their fingers will automatically
signal its intention.
Moran first tested this approach for
extracting signals from the motor cortex
in 2004 on a handful of patients being
monitored for epileptic seizures. Doctors had placed the ECoG grids on the
patients’ brains to figure out which areas
were causing seizures. After connecting
the sensors to a computer, the scientists picked up on the signals and taught
patients to use the signals to move cursors and play computer games.
Since these early experiments, Moran’s
S. ACHARYA ET AL/J. NEURAL ENG. 2010
100 microelectrodes, making it possible
to record from about 200 neurons at the
same time. The implants will remain in
the patients for one year.
Ultimately, scientists hope to implant
patients with wireless devices that can
beam brain signals out to control a
prosthetic without the need for wires
or cables. The system
would be on all the time,
available to patients when
they want it. Such wireless
systems could someday
help amputees in addition to paralyzed patients,
says Stanford University
engineer Krishna Shenoy.
Shenoy and colleagues
have been building wireless
systems that can transmit
signals from single neurons to nearby receivers.
Researchers have used the devices to
monitor the brains of monkeys moving
around their cages or walking on a treadmill. In April, Shenoy’s team presented
details on the studies in Cancún, Mexico,
at the International IEEE EMBS Conference on Neural Engineering.
Further work is needed to make such
feats practical for people, Shenoy says.
Scientists know how to extract the
necessary signals from the brains of
paralyzed patients, but haven’t yet
worked out the details of how to pick
out particular signals from the brains of
amputees, which might be busy directing
other movements.
Surface waves Some brain-computer devices attempt to capture the activity of groups of neurons using grids of electrodes on the surface of the brain, rather than deeply implanted electrodes.
The circles on the brains of two patients below show electrode locations. Solid circles indicate a
motor response during electrical stimulation, while X-ed circles indicate a sensory response.
