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Home News

BMI Enables Monkeys to Move Two Virtual Arms

by The O&P EDGE
November 12, 2013
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Large-scale brain activity from a rhesus monkey was decoded and used to simultaneously control reaching movements of both arms of a virtual monkey avatar towards spherical objects in virtual reality. Image courtesy of the laboratory of Miguel Nicolelis, MD, PhD, Duke Center for Neuroengineering.

In a study led by researchers from Duke University, Durham, North Carolina, monkeys have learned to control the movement of both arms on an avatar using just their brain activity. This work advances efforts to develop bilateral movement in brain-controlled prosthetic devices for patients with severe paralysis. The findings were published November 6 in the journal Science Translational Medicine.

“Bimanual movements in our daily activities-from typing on a keyboard to opening a can-are critically important,” said senior author Miguel Nicolelis, MD, PhD, professor of neurobiology, biomedical engineering, and psychology and neuroscience codirector of the Center for Neuroengineering, Duke University School of Medicine. “Future brain-machine interfaces aimed at restoring mobility in humans will have to incorporate multiple limbs to greatly benefit severely paralyzed patients.”

Nicolelis and his colleagues studied large-scale cortical recordings of monkeys to see if they could provide sufficient signals to brain-machine interfaces (BMI) to control bimanual movements accurately. They recorded nearly 500 neurons from multiple areas in both cerebral hemispheres of the animals’ brains, which is the largest number of neurons recorded and reported to date. The monkeys were trained in a virtual environment within which they viewed realistic avatar arms on a screen and were encouraged to place their virtual hands on specific targets in a bimanual motor task. The monkeys first learned to control the avatar arms using a pair of joysticks, but were able to learn to use just their brain activity to move both avatar arms without moving their own arms.

As the animals’ performance in controlling both virtual arms improved over time, the researchers observed widespread plasticity in cortical areas of their brains. These results suggest that the monkeys’ brains may incorporate the avatar arms into their internal body image, a finding reported by the same researchers in August in the journal Proceedings of the National Academy of Sciences. The researchers also found that cortical regions showed specific patterns of neuronal electrical activity during bimanual movements that differed from the neuronal activity produced for moving each arm separately. The researchers said the study suggests that very large neuronal ensembles-not single neurons-define the underlying physiological unit of normal motor functions. Small neuronal samples of the cortex may be insufficient to control complex motor behaviors using a brain-machine interface.

“When we looked at the properties of individual neurons, or of whole populations of cortical cells, we noticed that simply summing up the neuronal activity correlated to movements of the right and left arms did not allow us to predict what the same individual neurons or neuronal populations would do when both arms were engaged together in a bimanual task,” Nicolelis said. “This finding points to an emergent brain property-a nonlinear summation-for when both hands are engaged at once.”

Nicolelis is incorporating the study’s findings into the Walk Again Project, an international collaboration working to build a brain-controlled neuroprosthetic device. The Walk Again Project plans to demonstrate its first brain-controlled exoskeleton, which is currently being developed, during the opening ceremony of the 2014 Fédération Internationale de Football Association (FIFA) World Cup.

Related posts:

  1. Monkeys “Move and Feel” Virtual Objects Using Only Their Brains
  2. Examining the Uses of Virtual Reality in Prosthetic Rehabilitation
  3. BMI Helps People With Paralysis Regain Movement
  4. Monkeys Drive Wheelchairs Using Only Their Thoughts
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