But the brain processes that make the two different streams of 'e's are utterly different, according to a study done by a University of Southern California neural specialist and colleagues.
The insight may lead to, among other things, better movement control by humanoid robots, but also new ways of movement rehabilitation. And perhaps it even offers some insight into the effect of music.
Dr. Stefan Schaal, an associate professor in the computer science department of 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 like walking, chewing or scratching are found in many organisms, ranging from insects to primates," notes Schaal in an article published in Nature Neuroscience Sept. 26. "In contrast, discrete movements like reaching and kicking are behaviors that have reached sophistication in young species, particularly in primates."
Schaal, a robot expert with a deep background in neuroscience who draws inspiration for robot controls from biological models, notes that researchers have historically treated both kinds of movement as fundamentally the same in terms of control -- to say that one is a special form of the other.
Thus specialists studying discrete movement have considered rhythm a subset of discrete movement -- the same thing speeded and repeated -- while behaviorists studying rhythmic movement like walking have considered discrete movement just the same thing slowed and aborted after only a short piece of rhythmic movement.
But in a carefully arranged set of experiments, Schaal and co-workers from Pennsylvania State, and ATR Computational Neuroscience Laboratories in Kyoto, Japan showed that control mechanisms for the two types of movement are quite drastically distinct.
The study monitored eleven 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 activity created activity only in the motor areas of the opposite brain hemisphere and in the cerebellum.
Discrete activity was much more extensive, including numerous areas on both sides of the brain, including "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 that 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 find 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," says Schaal. "There is an automatic system that, literally, functions without any thought; and a separate cognitive system that orchestrates more complex movement.
And music? "Computational neuroscientist 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," said the scientist.
Meanwhile, Schaal and his colleagues are working on converting their results to humanoid robot algorithms that capture such behavior, and perhaps even give future robots a bit more rhythm in their stride -- "but don't look for them right away in hip-hop music videos," he says.
Dagmar Sternad of the Penn State department of Kinesiology and Rieko Osu and Mitsuo Kawato of ATR-Kyoto were co-authors of the study, which was funded by the National Science Foundation, Japanese Science and Technology Agency, and ATR.
The full text of the paper, with illustrations, can be found at:
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