This study aimed to investigate the relationship between the progression of motor learning in jump landing movements and BP, and to compare the brain activity patterns of fast and slow learners to clarify the differences between them.
The Eight healthy males (mean age: 23.1 ± 2.6 years, height: 169.6 ± 4.1 cm) performed 20 drop jumps, aiming to align their big toes with a marker 45 cm in front of them. EEG was recorded from 28 scalp sites using the International 10-10 System, and noise was removed using independent component analysis. Foot-off was detected using a pressure sensor. BP during the 3s before each jump was analyzed, and the change in the error distance for each jump was calculated as a learning curve. The relationship between BP and the slope of the learning curve was evaluated using the Spearman’s correlation coefficient. Subjects were divided into fast and slow learning groups based on the median slope of the learning curve, and brain activity was compared using the sLORETA analysis.
A significant negative correlation (r = -0.762, p 0.05) was observed between BP and the slope of the learning curve. The group that learned quickly showed predominant activity in the right parietal lobe (BA7, 4, 6), while the group that learned slowly showed predominant activity in the left frontal lobe (BA46, 13, 10, 11) and right occipital lobe (BA30, 23, 18) (t=3.424, p 〉 0.05). 3, 10, 11) and right occipital lobe (BA30, 23, 18) (t=3.424, p 〉0.05).
The negative correlation between the slope of the learning curve and BP suggests that premovement brain activity is involved in motor learning. Fast learners accurately grasp the environment and body position through activation of the right parietal lobe, which is then effectively utilized by the motor cortex to prepare and execute movements, resulting in efficient learning. In contrast, slow learners rely more on visual images and cognitive processing, as indicated by the dominant activity in the left frontal and right occipital lobes. This reliance may hinder their ability to develop and execute optimal motor plans.
The findings of this study contribute to our understanding of the neural basis of motor learning and have implications for the development of targeted interventions to enhance learning outcomes. Longitudinal studies with larger and more diverse samples are needed to fully elucidate the complex relationships between brain activity, motor learning, and individual differences in learning effectiveness. Despite these limitations, the current study provides valuable insights into the neural mechanisms underlying motor learning, and highlights the potential for developing targeted interventions to enhance learning outcomes in rehabilitation settings.
Motor Learning
brain activity
