Motor learning is one of the subdisciplines of motor behavior, and its main aim is to understand how people acquire new motor skills. A lot of studies conducted by motor behaviorist research correct practice as one of the most important variables in learning motor skills, and one of the principles in motor learning states that correct practice improves performance and facilitates motor learning. However, new studies in the field were made possible by technology, and a lot of modern studies aim at researching the underlying mechanisms that make learning possible and the non-invasive neurological interventions that can be applied to facilitate learning.
Background
Motor development is a prerequisite for motor learning because genes influence the pace and accuracy of motor development. Development is not influenced by external factors during infancy, so that period is when fundamental motor patterns are formed, which create the basis for any further skill acquisition and improvements. Although every individual has a specific pace of motor development, researchers found that fundamental motor patterns are usually developed by the time children reach seven years of age (Haibach, Reid, & Collier, 2011). Once fundamental skills are developed, there are several models that aim to explain motor skill learning.
According to Fitts and Posner, there are three stages of skill acquisition. Their three-stage model disregards any previous experience because learning a new skill requires starting from the first stage every time (Haibach et al., 2011). Although jumping, running, and similar fundamental skills are learned at an early age, cognitive processes interfere with execution effectiveness when people try to repeat those same movements in a different sequence or context.
The beginner stage is when people need a lot of attention on executing fundamental movements, and a lot of their cognitive attention goes to executing the movement rather than the performance result. During the beginner stage of motor learning, it is expected that people will make gross errors, and their trainers need to offer visual models, verbal instructions, and constructive feedback to facilitate the performer’s skill learning process.
Once the performer learns to perform the basic movements, they are at the intermediate stage. During that stage, the person requires less supervision of motor learning progress and the new goal is to refine the movements learned during the beginner stage. Finally, at the advanced stage, the performers can also make strategic decisions when necessary because the cognitive processes no longer interfere with the movement execution and performance results. Only a few people reach this stage because frequent practice through several years is often required to attain this level of motor skill acquisition.
Although models explain the stages of development differently, they all have several common key points in their explanations how individuals learn motor skills. First, all models state that cognitive function is required at the beginning to help the performers in executing movements. Second, all models propose that the performer will eventually experience a separation of cognitive functions and movement performance, so their movements will become automated. Finally, all models agree that only correct training methods, such as constructive feedback, visual models, and staged skill learning methods, are able to assist learners in acquiring motor skills and reaching higher levels of movement automation and performance results.
Literature Review
A lot of contemporary research is dedicated to the neurophysiologic aspects of motor learning. One possible explanation is the advancement of technology and its application in scientific research. While scientist mainly used to explore motor learning through observations and developed models that described the process of motor skill learning, the access to neural imaging allowed scientists to explore the topic through new perspectives.
For example, transcranial direct current stimulation (tDCS) is a common intervention used in experiments and clinical contexts. The method is non-invasive, but its strong modulatory influence on the cognitive functions and motor behavior increased the academic community’s interest in exploring the method further. The intervention is of particular interest to motor behaviorists because when it is applied to the motor cortex in humans, anodal tDCS can facilitate motor skill learning (Fritsch et al., 2010).
The target of tDCS is usually the primary motor cortex, and it works by inducing a form of synaptic plasticity, but it is beneficial only when BDNF, a secretion released as a result of training, is present in the motor system to enhance the (Fritsch et al., 2010). Therefore, it is not possible to expect results from tDCS interventions alone, so training remain responsible for learning new skills while other interventions may only facilitate learning in combination with correct training methods.
The mechanism behind warming up for professional players is also closely related to skill learning rather than actually preparing the tissue. For example, professional athletes will often take up to an hour if possible to practice their strikes or shots before a match. A study by Ajemian, Ausilio, Moorman, and Bizzi (2010) found that the motor system changes every day, so professional athletes need to recalibrate the system by practicing the movements they need in a competition.
The practical implication of the study by Ajemian et al. (2010) is the improved understanding of warming up the body and its role in skill performance. Rather than affecting motor learning directly, warm-ups cannot facilitate sill learning, but their impact on the sensorimotor network helps performers restore those skills after resting periods.
However, resting periods are also an interesting topic for motor behaviorists. It is also evident that the human brain processes information after the initial input, so motor behaviorists are trying to understand the practical implications of this feature to motor learning. According to Albert, Robertson, and Miall (2009), motor learning modulates resting state networks in the neural system, and it is suggested that the changes in those networks are influenced by the brain's ability to consolidate short-term memories of past experiences during resting states.
Future Directions
While the models for motor skill acquisition have mainly remained unchanged for the past several decades, the underlying physiological mechanisms are still under investigation. Some motor system theoretical frameworks suggest that the motor system works as a single distributed network; other frameworks suggest that the motor system explicitly segregates neural resources (Ajemian et al., 2010). There is no absolute agreement in this area, and future development of frameworks should work towards identifying the amount of flexibility the motor system is granted to learn new motor skills and the impact of concurrent practice and interferences in practicing new motor skills.
Apart from establishing new theoretical frameworks, practical experiments are needed to understand the neural mechanisms for learning. Future research should explore how constraints in learning occur and how they can be mapped (Fiser, Berkes, Orbán, & Lengyel, 2010), how interventions, such as tDCS, should be combined with existing motor skill acquisition models to facilitate learning, and how the brain can process information more effectively during resting states to facilitate motor skill learning.
References
Ajemian, R., D’Ausilio, A., Moorman, H., & Bizzi, E. (2010). Why professional athletes need a prolonged period of warm-up and other peculiarities of human motor learning. Journal of Motor Behavior, 42(6), 381-388.
Albert, N. B., Robertson, E. M., & Miall, R. C. (2009). The resting human brain and motor learning. Current Biology, 19(12), 1023-1027.
Fiser, J., Berkes, P., Orbán, G., & Lengyel, M. (2010). Statistically optimal perception and learning: from behavior to neural representations: Perceptual learning, motor learning, and automaticity. Trends in Cognitive Sciences, 14(3), 119-130.
Fritsch, B., Reis, J., Martinowich, K., Schambra, H. M., Ji, Y., Cohen, L. G., & Lu, B. (2010). Direct current stimulation promotes BDNF-dependent synaptic plasticity: potential implications for motor learning. Neuron, 66(2), 198-204.
Haibach, P. S., Reid, G., & Collier, D. H. (2011). Motor learning and development. Champaign, IL: Human Kinetics.
