Drum the tip of a finger on a typewriter key quickly “eeeeee.” Now, stop and type “e.” Take a moment, type “e” again. Take another moment, repeat. The motion in all cases is exactly the same, performed by the same finger.
But according to a study done by a USC neural specialist and colleagues, the brain processes that make them happen are completely different.
The insight may lead to better movement control by humanoid robots, new methods of movement rehabilitation for people and an understanding of the effect of music.
Stefan Schaal, associate professor of computer science in the USC Viterbi School of Engineering, led the international team that used functional Magnetic Resonance Imaging (fMRI) scans to test a longstanding question regarding “rhythmic” versus “discrete” movement.
“Rhythmic movements such as walking, chewing or scratching are found in many organisms, ranging from insects to primates,” said Schaal in a recent article published in Nature Neuroscience. “In contrast, discrete movements like reaching and kicking are behaviors that have reached sophistication in young species, particularly in primates.”
Schaal is a robotics expert with an extensive background in neuroscience who draws inspiration for robot controls from biological models. Researchers have historically treated the two different kinds of movement as fundamentally the same in terms of control, he said, considering one as being a special form of the other.
Thus specialists studying discrete movement have considered rhythm a subset of discrete movement – the same thing speeded up and repeated.
But behaviorists studying rhythmic movement such as walking have considered discrete movement as the same thing slowed and aborted after only a single act of rhythmic movement.
In a carefully arranged set of experiments, Schaal and coworkers from Pennsylvania State and ATR Computational Neuroscience Laboratories in Kyoto, Japan, showed that control mechanisms for the two types of movement are drastically distinct.
The study monitored 11 volunteer subjects, who performed a simple flex of the wrist while undergoing fMRI monitoring.
A visual signal instructed the subjects to do one of three actions: rhythm – flexing the wrist repeatedly at a comfortable pace, back and forth; discrete – flexing the wrist, pausing, flexing it back, and rest. Another set of experiments had the timing of the rhythm dictated to the subjects by a metronome.
The resulting fMRI records displayed far-reaching differences. Rhythmic motion created activity only in the motor areas of the opposite brain hemisphere and the cerebellum.
Discrete activity was much more extensive, including numerous areas on both sides of the brain and “planning areas” not directly connected with motor execution.
The difference held up even when careful controls made sure that the amount of actual activity – the number of up-and-down flexes and their velocity – was the same.
“We believe these results provide strong evidence to refute the hypothesis that rhythmic movement is generated with the help of the discrete movement system,” the authors wrote.
However, the opposite is not the case: the authors found that “discrete movement could indeed be generated with the help of the rhythmic movement system.”
“What our results indicate is that we really deal with two very separate systems in movement,” Schaal said. “There is an automatic system that, literally, functions without any thought; and a separate cognitive system that orchestrates more complex movement.
“Computational neuroscientists theorize that rhythmic movements are generated from oscillator circuits in the brain, and it may be that these inherently rhythmic neural systems make it to easy for us to swing to the rhythmic of music,” the scientist said.
Meanwhile, Schaal and his colleagues are working on converting their results to humanoid robot algorithms that capture such behavior and could give future robots a bit more “rhythm” in their stride.
“But don’t look for them right away in hip-hop videos,” Schaal said.
Dagmar Sternad of the Penn State department of Kinesiology and Rieko Osu and Mitsuo Kawato of ATR-Kyoto were coauthors of the study, which was funded by the National Science Foundation, Japanese Science and Technology Agency, and ATR.
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