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DARPA To Support Development Of Human Brain-Machine Interfaces

Date:
August 21, 2002
Source:
Duke University
Summary:
Devices including "neuroprosthetic" limbs for paralyzed people and "neurorobots" controlled by brain signals from human operators could be the ultimate applications of brain-machine interface technologies developed under a $26 million contract to Duke University sponsored by the Defense Advanced Research Projects Agency (DARPA).

DURHAM, N.C. -- Devices including "neuroprosthetic" limbs for paralyzed people and "neurorobots" controlled by brain signals from human operators could be the ultimate applications of brain-machine interface technologies developed under a $26 million contract to Duke University sponsored by the Defense Advanced Research Projects Agency (DARPA). The contract is part of DARPA's Brain-Machine Interfaces Program (http://www.darpa.mil/dso/thrust/sp/bmi.htm), which seeks to develop new technologies for augmenting human performance by accessing the brain in real time and integrating the information into external devices.

Principal investigator for the DARPA project will be Professor of Neurobiology Miguel Nicolelis (www.nicolelislab.net). Co-PIs are Craig Henriquez, who is the W.H. Gardner Jr. Associate Professor of Biomedical Engineering; Professor of Neurosurgery Dennis Turner and Associate Professor of Biomedical Engineering Patrick Wolf. Other center collaborators include John Chapin of the State University of New York, Brooklyn, Jose Principe of the University of Florida, Mandayam Srinivasan of Massachusetts Institute of Technology and Harvey Wiggins of Plexon Inc. in Dallas.

The DARPA support will help launch Duke's Center for Neuroengineering, co-directed by Nicolelis and Henriquez, whose scientists and engineers will seek to pioneer a new technological era in which brain signals could control machines that augment and extend human capabilities in a way never before possible.

Besides development of brain-controlled prosthetic limbs, neurosurgeons could apply brain-mapping enabled by the new technologies to aid surgeons in distinguishing healthy brain tissue from that which is part of a tumor or a focus for epileptic seizures.

"This technology can immediately increase the resolution with which surgeons can map the extent of a tumor or a specific brain region," said Nicolelis. "Such improved mapping can translate into a better prognosis for the patient, since less tissue might have to be removed."

Beyond medical uses, brain-machine interfaces also could be applied to enhance the abilities of normal humans, said the researchers. As examples, they said, neurally controlled robots could enable remote search-and-rescue operations or exploration of hazardous or inaccessible environments.

The Duke center will consist initially of a collaboration of separate laboratories in the medical center's department of neurobiology and in the Pratt School of Engineering department of biomedical engineering. However, the researchers expect to unite the center's efforts in a new multidisciplinary engineering building now under construction.

As part of the DARPA support:

* Biomedical engineer Henriquez and his colleagues will coordinate development of equipment and methods for visualizing and analyzing the massive amounts of data produced from electrode arrays in the brains of experimental animals.

* Neurosurgeon Turner and his colleagues will investigate potential use of brain-machine interfaces in patients with neurological disorders.

* Biomedical engineer Patrick Wolf and his colleagues will develop a miniaturized "neurochip" for detecting and analyzing brain signals, as well as optical communications links between the chip and the control components of the interface.

* John Chapin's laboratory will develop the sensory feedback mechanism by which animals and humans can "feel" the actions of a neurorobotic arm or hand.

* Jose Principe and his colleagues will develop new computer algorithms for translating brain-derived signals into control commands to operate a robot arm.

* Mandayam Srinivasan's laboratory will develop new interfaces to provide visual and tactile feedback signals to animal subjects operating robot arms, and

* Harvey Wiggins of Plexon Inc. in Dallas will supply hardware and software that will enable development and testing of brain-machine interfaces.

According to Nicolelis, the initial concentration of the new center will be on neuroprosthetic arms for paralyzed people, based on the success of initial experiments with animals. "Last year, we reported experiments in primates showing that a brain-machine interface could, indeed, control a robot arm," said Nicolelis. "While this was a first-generation system, it proved to us that there was an enormous opportunity to pursue research leading to clinical applications. We are extremely grateful to DARPA for their vision in establishing a program that will provide the crucial support to launch this effort."

In 2000, Nicolelis and his colleagues tested a neural system on monkeys that enabled the animals to use their brain signals, as detected by implanted electrodes, to control a robot arm to reach for a piece of food. The scientists even transmitted the brain signals over the Internet, remotely controlling a robot arm 600 miles away. The technique they used, called "multi-neuron population recordings" was originally developed by center collaborator Chapin.

In the experiments, the scientists used arrays of up to 96 electrodes to sense signals from multiple areas of the brain, including the motor cortex from which movement is controlled. The scientists then recorded the output of these electrodes as the animals learned "reaching tasks," including reaching for small pieces of food.

The scientists fed the mass of neural signal data generated during many repetitions of these tasks into a computer, which analyzed the brain signals to detect tell-tale patterns that would enable researchers to predict the trajectory of the monkey's hand from the signals.

Then, by programming the computer connected to the robotic arm to sense these signal patterns emanating from the monkey's brain, the scientists could enable the monkey to, in effect, control the arm only via neural signals.

This proof-of-concept experiment showed the effectiveness of recording from multiple areas of the brain and then allowing the computer to "learn" brain signal patterns that triggered certain movements.

In the new center, Nicolelis, Henriquez and their colleagues will aim to increase the number of recording electrodes to more than 1,000 to enable control of more complex actions by robotic arms and other devices. The "neurochip" being developed by Wolf and his colleagues will greatly reduce the size of the circuitry required for sampling and analysis of brain signals.

"Our dream is to develop a palmtop-like device that routes the signals either to robotic devices, computers, or even to the physician, to alert the physician to some problem," said Nicolelis. According to Henriquez, the greater number of recording electrodes will also enable far more sophisticated analysis of brain signals.

"This research involves a major effort to decode how the brain manages information," said Henriquez. "Once we are able to use computation to decode such information, we can translate that understanding into an algorithm that can be incorporated into hardware." Ultimately, the researchers hope to be able to record and analyze such signals for long periods of time without damage to brain tissue, said the researchers. They have already shown that animals can tolerate the electrodes for periods of years without apparent harm.

According to Nicolelis, the technology and computational methods developed under the DARPA support also will lead to a deeper understanding of the brain itself.

"This research will provide us with a powerful new set of experimental tools and techniques to answer the question of how millions of brain cells come together to generate a particular behavior," he said. "Traditionally, the neurosciences have taken a reductionist approach, with investigators trying to understand individual neurons, molecules and genes. We are trying to understand the brain's function as a dynamic system."

Nicolelis, Henriquez and their colleagues are among researchers developing a theory that neurons are not hard-wired circuit elements permanently assigned to one computing task, like the microprocessor inside a computer. Rather, the new theory holds that neurons are adaptable, living entities that can participate in many processing tasks at once. Moreover, the theory holds that those tasks may change from millisecond to millisecond. For example, Nicolelis' experiments have revealed that the brain signals producing a single event, such as a monkey reaching out, are mirrored in many places in the same brain region -- as if the neurons "vote" on such actions.

In their current experiments, the center's scientists and engineers are developing "closed-loop" systems, in which movement of the robot arm generates tactile feedback signals in the form of pressure on the animals' skin. Also, they are providing visual feedback by allowing the animal to watch the movement of the arm.

Such feedback studies could also potentially improve the ability of paralyzed people to use such a brain-machine interface to control prosthetic appendages, said Nicolelis. In fact, he said, the brain could prove extraordinarily adept at using feedback to adapt to such an artificial appendage.

"One provocative, and controversial, question is whether the brain can actually incorporate a machine as part of the neural representation of the body," he said. "I truly believe that it is possible. The brain is continuously learning and adapting, and previous studies have shown that the body representation in the brain is dynamic. So, if you created a closed feedback loop in which the brain controls a device and the device provides feedback to the brain, I would predict that as people or animals learn to use the device, their brains will basically dedicate neuronal space to represent that device."

Development of the Duke center's brain-interface technologies also will involve collaborations with industry, said the researchers. The market for such devices should be considerable, they said. According to a market analysis commissioned by DARPA, the current worldwide market of about $270 million annually is projected to be $1.5 billion by 2005.

"In our discussion with corporations, we've found that, even though these technologies are in their infancy, the companies are emphasizing their commercial development," said Henriquez. "We believe that the Duke center will help propel development of the next generation of brain interface technologies. And the opportunities for their application seem almost boundless."

DARPA (www.darpa.mil) is the central research and development organization for the Department of Defense. It manages and directs selected basic and applied research and development projects for DoD, and pursues research and technology where risk and payoff are both very high and where success may provide dramatic advances for traditional military roles and missions.

The DARPA sponsored contract is being managed by the Space and Naval Warfare Systems Center in San Diego (http://enterprise.spawar.navy.mil).

Other useful links:

Center for Neuroengineering -- http://bmewww.mc.duke.edu/Research/Elecphys/Neuroeng/Neuro.htm

Miguel Nicolelis bio -- http://www.neuro.duke.edu/Faculty/Nicolelis.htm

Craig Henriquez bio -- http://bme-www.egr.duke.edu/fandr_indivprofiles.php?id=5


Story Source:

The above story is based on materials provided by Duke University. Note: Materials may be edited for content and length.


Cite This Page:

Duke University. "DARPA To Support Development Of Human Brain-Machine Interfaces." ScienceDaily. ScienceDaily, 21 August 2002. <www.sciencedaily.com/releases/2002/08/020820071329.htm>.
Duke University. (2002, August 21). DARPA To Support Development Of Human Brain-Machine Interfaces. ScienceDaily. Retrieved September 22, 2014 from www.sciencedaily.com/releases/2002/08/020820071329.htm
Duke University. "DARPA To Support Development Of Human Brain-Machine Interfaces." ScienceDaily. www.sciencedaily.com/releases/2002/08/020820071329.htm (accessed September 22, 2014).

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