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Home Exclusive Cognitive Science

How cognitive and physical demands interact when learning to play the piano

by Eric W. Dolan
April 27, 2024
Reading Time: 4 mins read
(Photo credit: Adobe Stock)

(Photo credit: Adobe Stock)

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Learning new skills involves intricate brain processes that scientists are still working to fully understand. A recent study published in the journal Brain Sciences examines how older adults learn motor sequences—such as playing a musical instrument—and how their cognitive and motor abilities support this learning over time. The research provides insights into the connections between mental and physical capabilities and their roles in learning new tasks.

Previous studies have established that motor learning is not a one-size-fits-all process. Different types of motor learning—like learning to play the piano—involve distinct brain systems and stages. Researchers have long been interested in how various cognitive abilities contribute to these stages of learning. Studies indicate that while some abilities are crucial at the beginning of learning a new skill, others become more important as one gains proficiency.

“Learning new skills, such as reading and writing, driving a car or mastering a handstand, requires cognitive processes. We wanted to know whether the cognitive requirements are stable or whether they change when older people learn to play the piano,” said study author Florian Worschech, a cognitive neuroscience researcher at the Institute of Music Physiology and Musicians’ Medicine and the Hanover University of Music, Drama and Media.

The study involved 86 older adults, with an average age of 72.5 years, including both men and women. These participants were selected based on their general health and absence of neurological, psychological, or significant motor issues. Among them, 37 had some piano playing experience, though anyone with over 4000 hours of piano practice was excluded to maintain a novice level among subjects.

The primary tasks involved learning motor sequences through repeated trials. Initially, participants engaged in a piano-related sequence task using a Yamaha MIDI piano. This task required participants to press keys in a specified order, which was visually displayed and had to be executed as quickly and accurately as possible. The sequence was designed to be looped, creating a continuous task flow.

Subsequently, the participants performed a piano-unrelated task on a response pad, pressing keys in an alternating pattern with their index fingers. Similar to the piano task, the sequence was repeated across several trials to assess learning over time.

Each motor task consisted of 20 trials of 20 seconds each, with a 30-second break between trials to minimize fatigue. The entire experimental session lasted approximately 100 minutes.

The researchers found that both the piano-related and piano-unrelated tasks exhibited typical learning curves, which could be best described by exponential models. These curves showed that while participants initially improved quickly, the rate of improvement slowed as they continued practicing. This pattern suggests a rapid gain in familiarity with the tasks followed by a more gradual refining of skills.

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“The level of cognitive and motor demands depends on the learning phase,” Worschech told PsyPost. “With our task, we have shown that the requirements increase exponentially during the learning process and approach a plateau.”

One of the key findings was the varying contribution of different cognitive and motor abilities to task performance. Initially, processing speed, psychomotor speed, and dexterity were strongly correlated with how well participants performed the motor sequences. However, as participants became more practiced, the influence of these abilities on performance decreased, indicating that other factors began to play more significant roles as the tasks became more familiar.

The researchers also examined gaze behavior as an indicator of cognitive load and task familiarity. They found that the number of gaze shifts decreased significantly within the first few trials. This decrease suggests that participants required less visual information to perform the tasks as they became more accustomed to the sequences, reflecting a shift from more conscious, deliberate control to more automatic processing.

Error analysis provided further insights into learning efficiency. Both tasks showed a reduction in errors as the trials progressed. Interestingly, the rate of error reduction was correlated with dexterity, underscoring the role of motor control in learning new sequences. The fact that dexterity continued to influence error rates throughout the experiment suggests that motor precision remains crucial even as the task becomes more familiar.

Contrary to some existing theories that suggest well-practiced tasks become almost automatic, this study found that task difficulty and cognitive demands did not diminish even after multiple repetitions. Instead, the need for cognitive engagement seemed to increase, highlighting the persistent challenge these tasks posed to the participants. This finding is particularly important because it challenges the notion that repetition leads to automaticity, suggesting instead that continuous cognitive and motor engagement is required for performance improvement.

“Traditionally, it is assumed that the execution of skills becomes ‘automatic’ with increasing practice, with minimal cognitive load,” Worschech explained. “Our study results were surprising, as they show that under certain circumstances the cognitive demands can also increase during practice.”

Overall, the study underscored the interplay between cognitive functions and motor performance during the learning process. The findings suggest that while certain abilities are crucial in the early stages of learning a new motor sequence, a shift toward other cognitive resources occurs as proficiency increases. This nuanced understanding of motor sequence learning could have significant implications for designing cognitive and physical interventions aimed at older adults.

“The aim of this project was to lay the foundation for the development of a comprehensive cognitive process theory of music making,” Worschech said. “The results emphasize the potential of learning a music instrument to produce positive cognitive transfer effects, for example to support healthy aging. However, the interventions should be sufficiently long so that the transfer potential can be fully exploited.”

The study, “What Does It Take to Play the Piano? Cognito-Motor Functions Underlying Motor Learning in Older Adults,” was authored by by Florian Worschech, Edoardo Passarotto, Hannah Losch, Takanori Oku, André Lee, and Eckart Altenmüller.

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