Scientists from the Medical Center recently devised a way to predict the movements of monkeys by analyzing neural signals in their brains.
The team was led by Miguel Nicolelis, associate professor of neurobiology and biomedical engineering, and its report was co-authored by John Chapin of the State University of New York Health Science Center. Their findings-in the fields of neurobiology and biomedical engineering-will likely have important implications for individuals whose motor skills have been reduced by nerve damage.
The research was conducted on two owl monkeys whose brains were implanted with electrodes that could track changes in neural patterns. This procedure, the doctors say, is completely safe. In total, the monkeys received about 96 electrodes, each measuring no more than the diameter of a human hair. The monkeys were chosen for their particularly smooth cortex, which eased the process of accessing the brain.
On the neurobiological front, the team proved that large portions of the brain are simultaneously involved in activating movements of the body. Previous research had focused on tracking the responses of a single cell, and therefore was limited in its ability to uncover broad relationships, like the neurological means by which a monkey can move its arm.
Challenging a predominant neurobiology paradigm, the scientists implanted the electrodes across many regions of the brain's cortex and recorded the neural patterns that arose after the monkeys performed a variety of motor tasks. Their broadened approach paid off-the findings revealed that the monkeys' brains transferred information about bodily movements in a cortex-wide manner.
Nicolelis said he believes this phenomenon is a result of evolution.
"When information is vastly distributed [in the brain] the system is more robust," he said, adding that this increases the brain's resiliency to cell loss.
On the biomedical engineering front, Nicolelis and his team accomplished a first-ever transformation of a primate's brain signals into computer algorithms that could be used to direct a robot arm in three dimensions.
"We demonstrated a new concept," he said, "that you could use brain signals to extract meaningful information from the brain to control robotic devices."
As the animals performed various tasks, the data from their brains was fed into a computer for analysis. This allowed the researchers to develop algorithms that could predict the movement of the monkey's arm, explained Nicolelis. In other words, the researchers could almost immediately ascertain when and how a monkey's arm would move. So, to further test their finding, the scientists connected the monkeys' brains to a robot arm which responded to the changes in their neural patterns.
Over the two years the implants stayed in the monkeys' brains, the algorithms became advanced enough so that they could adapt to the brains over time-decreasing the delay between the robot arm's movement and the brain signal. Neurobiology research associate Johan Wessberg, also a member of the team, said the biggest challenge in this process was reliably recording the brain signals over such a long period of time.
The scientists set another precedent by using information extracted from the monkey's neural patterns to control a robotic arm in a lab at the Massachusetts Institute of Technology, some 600 miles way. Surprisingly, the transmission by an Internet connection introduced a delay of only eight-tenths of a second.
While such successes are still of a very limited nature, Nicolelis explained that the findings could have an important impact on people with spinal cord damage.
"We could bypass [the spinal cord] and send the movement information straight to the robotic device," he said.
Nicolelis noted that upcoming research will focus on utilizing monkeys with more complicated cortices and allowing the monkey to witness in real-time the changes its neural patterns, as interpreted by the computer, produced in the robot arm.