A recent study demonstrates that even after we “master” a physical skill, continuing to practice beyond perfection improves efficiency:
The study involved 15 right-handed test subjects who used a handle on a robotic arm, similar to a joystick, to control a cursor on a computer screen. The tasks involved starting from a set position to reach for a target on the screen and involved both inward and outward arm movements, Ahmed said.
As part of the study, test subjects had to exert more energy in some reaching movements when the robotic arm created a force field, making subjects “push back” as they steered the cursor toward the target. With repeated practice of moving the robotic arm against the force fields, the subjects learned the task by not only cutting down on errors, but effort as well, according to Ahmed.
The test subjects first performed a series of 200 reaching trials with no force field to push against, then two sets of 250 trials each when pushing back against the force field. The experiment ended with another 200 trials with no force field, said Ahmed. A metronome was used to signal the test subjects to move the robotic arm every two seconds toward the target during the trials.
Each of the test subjects wore a nose clip and breathed through a mouthpiece to chart the rates of oxygen consumption and carbon dioxide production, a measure of metabolism. The research team also collected surface electromyographic data by placing electrodes on the six upper limb muscles used during reaching tasks: the pectoralis major, the posterior deltoid, the biceps brachii, the triceps long head, the triceps lateral head and the brachioradialis.
“What is unique about our study is that we are the first group to measure metabolic cost in addition to muscle activity while performing a physical reaching task,” said Huang, who performed most of the research and was first author on the Journal of Neuroscience paper. “The results are very surprising and challenge the widely held assumption that muscle activity entirely explains changes in metabolic cost.”
The study suggests that efficient movements ultimately involve both efficient biomechanics and efficient neural processing, or thinking. “We suspect that the decrease in metabolic cost may involve more efficient brain activity,” Ahmed said. “The brain could be modulating subtle features of arm muscle activity, recruiting other muscles or reducing its own activity to make the movements more efficiently.”