Japanese Scientists Successfully Created A Model That Mimics The Learning Process Humans Undergo When Learning New Motor Skills

kiuikson - stock.adobe.com - illustrative purpose only, not the actual person
kiuikson - stock.adobe.com - illustrative purpose only, not the actual person

Some of the most simple-seeming motor skills– including walking, kicking, and lifting up an item– are incredibly complex for humans to perform.

Even swallowing just one bite of food requires the coordination of over fifty pairs of muscles.

Still, scientists have relied on little information about how exactly humans learn and successfully perform these movements.

In turn, researchers from the University of Tsukuba in Japan have recently proposed a new motor learning model based on numerous theories to help further our understanding of brain processes.

Their study was published last month in Neural Networks and revealed that the proposed model could actually simulate humans’ motor learning quite accurately.

In making the model, the team first developed a mathematical algorithm to mimic the learning process that humans undergo when first performing new motor tasks.

The model was designed to imitate the numerous processes that are believed to occur when learning a skill.

Then, once satisfied with their model, the researchers tested it by simulating the results of three recently conducted motor skill studies in humans.

Professor Jun Izawa, the study’s senior author, explained how the model closely reflected the studies’ outcomes.

kiuikson – stock.adobe.com – illustrative purpose only, not the actual person

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“We were surprised at how well our simulations managed to reproduce many of the results of previous studies in humans,” Izawa said.

“With our model, we were able to bridge the gap between a number of different proposed mechanisms of motor learning, such as motor exploration, redundancy solving, and error-based learning.”

The study also found that more motor exploration, also known as movement variability, helped the brain correct itself. In other words, errors in movement were interpreted as corrections, much like trial and error.

This breakthrough has provided the research team with hope regarding further research studies and future applications of the technology.

“Our success at simulating real results from human studies is encouraging,” said Lucas Rebelo Dal’Bello, the study’s first author.

To read the research team’s complete findings, visit the study linked here.

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Katharina Buczek graduated from Stony Brook University with a degree in Journalism and a minor in Digital Arts. Specializing ... More about Katharina Buczek

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