Brain Signals From The Paralyzed or Injured Captured By Computer

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Society for Neuroscience News Release
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BRAIN SIGNALS FROM THE PARALYZED OR INJURED CAPTURED BY COMPUTER; GAINS IN
COMMUNICATION AND MOVEMENT MAY BE REALITY SOON FOR PATIENTS

November 9, 2003

NEW ORLEANS - Exciting new research into how signals from the brain
can be captured by a computer or other device to carry out an individual's
command may allow people with motor disabilities to more fully communicate
and function in their daily lives.

Over the past several years, scientists have begun to address the needs of
people with severe disabilities brought on by paralysis or injury by
developing brain-computer interfaces (BCIs). These systems allow people to
use signals directly from the brain for communication and control of
movement. The research has progressed to a point where clinical applications
can be anticipated, says Jonathan Wolpaw, MD, chair of the symposium,
"Brain-Computer Interfaces for Communication and Control."

Research in technologies for obtaining brain signals for BCI applications
has led to the development of implantable BCI devices that could be used by
people with severe motor disabilities. In other work, investigators report
advances in BCI-based movement control.

The BCIs already available and those under development differ greatly in the
brain signals they use, in how they detect those signals, in the methods
they use to translate the signals to carry out the person's commands, and in
the kinds of devices the signals control.

Groundbreaking work conducted by Douglas J. Weber, PhD, at the University of
Alberta, Edmonton, Canada, and his colleagues has led to the development of
an implantable microelectrode array that can record neural sensory responses
resulting from movements of the leg. The investigators have developed an
analysis technique that allows accurate prediction of leg positions from the
patterns of recorded neural activity.

The technique relies on the fact that multiple sensors acting together
provide the central nervous system with important feedback for controlling
movement. For example, sensors called muscle spindles that are embedded in
muscle fibers measure the length and speed of muscle stretch, while other
sensors in the skin respond to stretch and pressure. When an individual is
paralyzed by injury or disease, neural signals from these sensors cannot
reach the brain, and thus cannot be used to control motor responses.
Paralysis also keeps neural signals originating in the motor regions of the
brain from reaching the muscles.

The work of Weber and his colleagues shows that it is possible to extract
feedback information from the body's natural sensors that could then be used
to control a prosthetic device, allowing an individual to regain some
command and control of his or her own movements.

A sterile surgical procedure is used to implant arrays of 36 microelectrodes
into the dorsal root ganglion, part of the spinal nerve that contains the
nerve cell bodies that house these natural sensors. Historically, it was
difficult to record from these sensors because their cell bodies are located
in this difficult-to-reach nerve bundle entering the spinal cord.

The wires from the microelectrode array are led out through the skin to a
small electrical conductor. The procedure allows simultaneous recordings
from many sensory nerves during normal motor activities such as walking. A
digital camera tracks the position of the leg, and a mathematical analysis
relates the sensory activity to leg movement. The investigators found that
fewer than 10 neurons are needed to accurately predict the path of the leg.
This finding is encouraging because it suggests that a small number of
neurons could provide the feedback signals needed to control a prosthetic
device.

Other investigators are developing wireless devices for recording neural
activity. Groups from Brown University in Providence, R.I., and the Jet
Propulsion Laboratory (JPL) in Pasadena, Calif., have both developed
wireless implantable devices that use advanced microelectronic technology
that eliminates the shortfalls of currently available neural recording
systems.

According to JPL's Mohammad Mojarradi, PhD, the advantage of such wireless
devices is that they allow recording of neural signals while an individual
is moving and may pave the way for study of neural circuits responsible for
even more complex mobility functions.

"Present implantable neural recording systems are passive devices, using a
large bundle of wire and requiring the skull to stay still during the
recording session," said Mojarradi. "Wireless devices allow recording of
neural signals without restricting motion. Once this restriction is removed,
we can look at complex motor functions and the neural circuits involved and
potentially develop even larger highly advanced brain-machine systems."

The wireless device under development at JPL uses an array of analog,
low-noise amplifiers that amplify signals from microelectrodes, an on-board
processor, and a two-way radio link, which acts as a telemeter. A
microprocessor interacts with the two-way radio link and can be remotely
programmed to detect and sort the neural signals received by the prosthetic
device. The device is designed to be placed under the skin on the skull and
connected to recording electrodes in the cortex. These electrodes amplify
and transmit the recorded signals from the brain through the wireless
telemeter.

The researchers say the next step in their research is to create a single
system-on-a-chip device by combining the analog array of amplifiers with the
microprocessor and wireless link. Mojarradi and his team believe such a
highly miniaturized system could lead to the development of a permanent
implant to assist patients suffering from paralysis and other brain
disorders.

In other work, Cyberkinetics, Inc., in Foxborough, Mass., is working with
the Brown University team headed by Mijail D. Serruya, to develop an
implantable BCI called BrainGate for clinical use in human patients.
BrainGate is designed to enable patients who have lost the use of their
hands to master accurate, rapid control over a computer desktop. Such
control over a computer desktop could allow a patient to communicate online,
interface with the Internet, and possibly adjust lights or other devices in
his or her environment.

Cyberkinetics was founded by a team of researchers from Brown University led
by John Donoghue, PhD. Cyberkinetics is seeking to commercialize a neural
output device to help patients with severe motor impairment. All the authors
are Cyberkinetics employees and shareholders.

"The disadvantage of the computerized assistive devices used today is that
they require an individual to use substitute signals like voice or eye
movement to manipulate a mouse or keyboard," said Donoghue. "The advantage
of BrainGate is that it records directly from the brain and thus can
translate brain activity into the intended hand movement over mouse or
keyboard."

The BrainGate BCI consists of a microelectrode array sensor implanted into
the motor cortex, an external cart containing computer hardware, and
software that processes and decodes neural signals. Although no humans have
been implanted with BrainGate yet, the device has been designed to meet
human safety requirements.

Cyberkinetics hopes to start a pilot clinical trial with four to five
quadriplegic individuals in 2004. Once the BrainGate device has been shown
to record neural activity in paralyzed patients, then the team at
Cyberkinetics will explore how the signals can be translated into output
signals that could be used to control a computer.

In other work being presented at the symposium, Andrew Schwartz, PhD, will
show how his group at the University of Pittsburgh is extending their work
in cortical prostheses to robot control. Previously the group showed that
closed-loop control of a cortical prosthesis can produce excellent
brain-controlled movements in virtual reality. After showing that a monkey
can use direct brain control to control a robotic arm in 3D space while
watching the movement in virtual reality, the researchers are now moving on
to have the animal see and control the arm directly, without the virtual
reality display. Although learning to use the robot as a tool seems to be
more difficult for the animal, it has nevertheless learned to use the robot
to reach targets held by the investigator.

Jonathan Wolpaw's laboratory at the Wadsworth Center of the New York State
Department of Health is finding that a non-invasive BCI, using EEG activity
recorded from the scalp, can provide rapid multidimensional control of a
movement signal with precision and speed comparable to that achieved in
monkeys by invasive BCIs. This remarkable control by a non-invasive BCI
depends on an adaptive training algorithm that identifies and focuses on the
particular EEG features that the person is best able to control, and
encourages the person to improve that control further. These initial results
suggest that people with severe motor disabilities might use brain signals
to operate a robotic arm or a neuroprosthesis without the risks involved in
having electrodes implanted in their brains.

Andrea Kuebler, PhD, of the University of Tuebingen in Germany is exploring
the complex technical and human issues involved in providing severely
disabled people with BCI-driven communication and control devices. Her group
has compelling new data indicating that simple BCIs could greatly improve
the quality of life of people with the most severe disabilities. These data
imply that even people who are totally paralyzed can lead lives they enjoy
if they can communicate even to a limited extent with caregivers, family
members, and friends. By showing the potential clinical benefits of BCIs,
these surprising results provide new incentive for their continued
development and application.