Motor learning is a branch of the study of motor behavior. It cannot be separated from motor control such as muscle coordination among different body parts, e.g. eye-head-hand coordination, and the concept of executive control. There are various ways of defining motor learning:
Motor learning is defined as changes in internal processes or states, associated with repeated practice or experience, that determine a person's capability for producing a skillful movement.The definition above can be expanded into four properties. First, motor learning is a set of processes acquiring capability. Second, such processes are internal and not directly observable, so learning has to be probed systematically. If internal (psychological) states produce a set of motor behaviors, then behavioral changes are expected as a result of learning. Third, it is a result of repeated practice or experience (W. James called this a habit). Finally, these processes are relatively permanent, for example: a child who learns to play tennis is still able to do after a long period of break. Successful motor learning usually involves goal setting such that learners know what and how to perform a particular task.
Increased capability for moving skillfully in a particular situation defines learning. For example: the goal of learning tennis is to serve properly, make the ball enter the correct region, and direct the ball to a position difficult to reach by the opponent. The "quality" of the internal states that produce the movements is maximized as a result of motor learning. This definition is more specific, as opposed to a more general and cognitive definition of learning, i.e. a process that results in a change in behavior.
Strictly speaking, there is a distinction between motor performance and motor learning. Performance is talking about motor execution. Change in motor performance can also show changes that are not learning-related because it is only temporary, e.g. it decreases due to fatigue or is enhanced by dopping. People also make a distinction between ability vs. learning. Whereas ability can be due to growth or maturity and reflects personal traits, motor learning is especially due to repeated practices. The distinction between performance and motor learning is what makes us require a certain set of behavioral paradigms. Such paradigms allow us to measure an increase in performance even after a long pause or break of practice. See the next part: retention and transfer.
According to Fitts and Posner (1967), there are essentially 3 stages of motor learning:
- Cognitive stage: for a naive learner, the problem to be solved in the cognitive stage is understanding what to do. This stage is also known as the verbal-motor stage (Adams, 1971) as it involves the conveyance (verbal) and 'thinking' (cognition) of new information. There is a large gain, but inconsistent, the profile of performance.
- Associative stage: it is a stage of dwelling deeper into how to perform the skill; characterized as much less verbal information, smaller gains and conscious performance, a lot of corrective and adjustments. This stage is also called the motor stage proper (Adams, 1971). From the cognitive perspective, the novice is attempting to translate declarative knowledge into procedural knowledge. It's about transforming what to do into how to do.
- Autonomous stage: the final stage of motor acquisition where performance becomes largely automatic, where cognitive processing demands are minimal (no 'thinking'). For athletes, this is when they can grip it and rip it, look and automatically react, and enter a state of flow.
In a typical motor learning experiment, two or more groups of subjects practice a task under a different level of an independent variable, i.e. the behavior task. The most common method for analysis is using a learning curve. The learning curve can take different measured variables (dependent, response), which depend on the type of studies conducted, e.g. in terms of a reduction in reaction time in sec., increase in accuracy in cm, or the number of correct scores received. There are a few considerations in averaging learning curves. First, the learning curve should depict learning not merely performance. Finding the average is likely undermining between-subject differences and differences in strategy, the latter being a more difficult confound to take care of. Another aspect to consider is the within-subject variability caused by motor noise that may directly impact the measure of learning. Ceiling and floor effects also impair the measurement of learning such that further improvement or increase in performance is impossible. This is when learning has reached an asymptotic level or plateau.
The power law of practice states that the learning scores or index for a particular task increases linearly with the logarithm of the number of practice trials. The consequence of this law is that our trial-to-trial improvement isn't all the same or linear. This improvement is generally very quick during the first few trials, then it slows down. The law is generally true for all motor learning tasks if you take the average. There is an on-going debate whether the equation to model this is exponential or logarithmic, etc., and whether individual differences occur. One subject may reach a plateau more quickly than others.
There are a few practice paradigms to study motor learning. The first paradigm trains subjects at different levels of the independent variable then transferred to a common level of that variable. The design provides a separation between a relatively permanent effect (learning) and a task-dependent effect which is temporary and related more to performance. What happens when the ceiling or flooring is easily reached? One way is to incorporate a secondary task or measure related but different dependent variables. Another way is to measure motor automaticity and effort. After the learner reaches an asymptote, further improvement in accuracy is impossible. Another dependent variable is required, e.g. we can measure whether the reaction time improves (more automatic), or oxygen consumption reduces (less effort required).
Perhaps, as mentioned, the most fundamental way to probe motor learning is by studying it in terms of retention and transfer. Both tests are performed following a reasonable break or interval, after an initial "acquisition" or learning process. Retention is a measure of how well the changes persist following the initial learning of the same task. It is tested by calling the same subjects again after a long break of e.g. 5 or 10 days, to do the same task learned during "acquisition" earlier. Retention is related to saving, e.g. Ebbinghaus (1913), Nelson (1985), that is, a faster relearning. Motor generalization is related to the transfer of learning, that is, the effect of learning observed in another context. Technically, when generalization is beneficial, it is termed transfer (if not, it acts as interference). A practical example of transfer: if you learn to play tennis after a while, how is that skill useful for you in learning badminton? The specificity of the learning hypothesis says that we should attempt to match those conditions in practice with those used during the test or retention period.
Off-task and On-task Practices
Practice or training is the most important determinant of the so-called motor learning. There are some consequences of this statement. First: learners have to be motivated to practice. Second: to be motivated, they have to understand the goal or purpose. Psychologists found that goal-setting is a widely used motivational technique (e.g. Locke & Latham 1985). In sports psychology, specific and moderately difficult goals are more beneficial to learners. Third: in order to achieve a clear and unambiguous set of goals, verbal instructions are necessary. Instructions influence a certain level of attention that is task-specific. E.g. in a balancing study with both hands holding a tube, subjects that receive instructions to keep their hand horizontal (body parts, internal focus) and control group have the largest error, while instructions explicitly asking them to hold the tube horizontal yield the smallest error (Wuff et al. 2007). Factors mentioned above are called off-task practice conditions as they are indirect practices, that is, they aren't about actively performing the task itself. Other forms of off-task practice include mental practice and perceptual learning. In perceptual learning, a learner goes through a period of "experiencing" sensory events related to the task, e.g. what he/she will see, feel, and touch available during the task performance. A more specific form of perceptual learning is observational learning. This learning was originally more of a form of social learning in children proposed by Bandura and has been confirmed through animal studies on mirror neurons. In motor skill acquisition, observational learning happens when the learner watches an ideal model, skilled performer, or his/her instructor performing a demonstration of the task (for review, see a book chapter by Maslovat et al., 2010). Spatial structure and timing are the two most important components learned during learning by observing.
On-task practice conditions cover various types of practice with the aim of maximizing learning. For example, in terms of structure, distributed practice (broken up into a few shorter sessions over a long period of time) tends to show better learning than massed practice (done with longer sessions, or without an apparent break or rest in between) does, although these effects are seen to be stronger for the learning of continuous tasks. Refer to the figure below.
Other condition includes practice variability. It refers to the variety of movement and context characteristics the learner experiences while practicing a skill. Varying task sequences from trial to trial are more effective than constant practice conditions. In Shea & Kohl's experiments, subjects practiced creating a goal force by squeezing a handgrip connected to a force transducer. One group, the "constant group", experienced 100 trials of a constant task goal of 150 N. A second group, the "variable group", experienced a series of different task goals (100, 125, 175, 200 N, including 150 N!), hence a total of 500 trials. A third group practiced 150 N for the same # trials with the variable group. Although the variable group did the task rather poorly, they performed well during the retention period after a break. Shapiro & Schmidt observed an important phenomenon where children are always benefited from the variable task sequence, presumably because the schemas are not established yet.
In real life, motor skill learning usually involves various task goals that mimic the "variable" group mentioned above, e.g. physicians practice different motor skills related to surgery, musicians practice multiple songs at a time, tennis players practice serving and volleying as well as the more usual groundstrokes during a single session, and etc. Suppose a doctor has to learn suturing skills 1, 2, 3, and 4 How can we schedule them so as to maximize learning? There are two ways to do this: random practice (interleaved tasks 1, 2, 3, ...) and blocked practice. (complete practicing task 1 first, then proceed to 2, ... and so on). Note that these skills have one similarity or context, i.e. applying sutures. Although they have the same context, the motor components are not.
A term called contextual interference was introduced by W. Battig to name the effect of task differences while maintaining the same context (Shea & Morgan, 1979; a review by Brady 1998). Random practice design has high contextual interference. Several studies have shown that random practice has an impact on reducing the performance during the acquisition or learning phase but leads to more effective learning than blocked practice, as measured by the retention and transfer tests. Why is this so? Learning motor skills involve working memory of how to do the task well ("when forgetting improves remembering at a later time"?). Contextual interference has been replicated to a certain extent in more complex tasks and motor skills outside of the laboratory (e.g. Wulf & Shea, 2002; Goode & Magill, 1986; Albaret & Thon, 1998). Nevertheless, there is a limit to the generalization of contextual interference to motor tasks that are relatively simple.
Extrinsic Feedback: KR and KP
One of the most important features of practice or learning is the information the learner receives about their attempts to produce a movement. This is called movement-produced feedback and it tells the quality of our produced movements, the error or mistake, etc so that we can learn to correct them. There are basically two types of feedback:
(1) Internal or intrinsic feedback: somatosensory, visual, and other sensory feedback.
(2) External or extrinsic feedback or augmented feedback e.g. reward, verbal feedback.
The second type, augmented feedback, can be divided into KR and KP. A focus of this discussion is a type of external feedback called the knowledge of results (KR) where it provides post-movement information about the outcome of the movement in the environment. In practice, KR can appear in the form of a more abstract binary signal (right/wrong), visual or verbal reward signal ("Good job!"), or the amount of error produced ("the speed was too quick", "the endpoint was 2 cm too long"), etc. This is in contrast with the knowledge of performance (KP),: the information about how you perform the movements, e.g. "You bent your arm", "Your body was too stiff". In a practical sense, KP deals with how well you perform the movements, but what makes KR more popular than KP in studying motor learning? Because changes by KR is more easily measured.
The KR paradigm is used heavily in the field of behavioral and experimental psychology such as in studies by Pavlov, Thorndike, Tolman, etc. on conditioning and shaping. Thorndike is probably remembered for his KR/no-KR paradigm in motor learning. Essentially. the paradigm lets a participant learns a task with KR and then the same person is subjected to a transfer test where the KR is removed. This makes sense. For example, in the rehabilitation setting, patients are trained with KR given but tested without KR to simulate the real-life situation outside the clinical setting. For a review on KR in the rehabilitation setting, see Winstein C. (1991) and van Vliet &Wulf (2006).
Studies from the last century have shown how KR influences motor performance by giving "energizing" state, rewarding stimulus, and attentional reference. It provides guidance on what to do next (Salmoni et al, 1984) but has a limited effect on learning itself (e.g. see Szalma et al, 2006). But earlier works by Bilodeau et al. show that KR does not only influences performance but in itself a learning variable (an indirect way of saying KR causes learning). The authors trained a group of subjects without KR, another group with KR throughout, and the other group in between. During the practice period, the KR group had a rapid reduction in absolute movement error. The no-KR group consistently had a much higher error. Following this, the no-KR group performed another extra 5 trials with KR and their error performance is similar to the first 5 trials of the KR group.
KP may appear in various forms. An instructor can let the novice players see their own performance via video feedback. Dance instructors can include kinematic feedback such as "Move your arm to face sideways more quickly!". Kinematic feedback talks about motion trajectories and velocity, while kinetic feedback takes into account how much force exerted to perform the task. Some argue that KP directs the learners to focus on a more internal state of information, e.g. how they control their arm, versus KR which is more on the external state of information, e.g. "You are 10 mm undershoot the target location", "That's a good shot!". The effectiveness of kinematic KP compared to KR depends on the task goals. The importance of kinematic KP is seen when some movement patterns are otherwise too difficult to perceive. There is evidence showing that KP can contribute to learning specificity. E.g. a study by Levin et al (2006) shows that a group of patients that received KR improved in their aiming (spatial) accuracy but not speed. On the other hand, patients that received KP on their shoulder/elbow velocity improved the velocity accuracy. Lastly, another form of KP is biofeedback, the most popular of which uses EMG signals.
More about KR
Suppose one is doing a ballistic movement to a target. The KR can be in the form of endpoint error (quantitative) or the direction (more to the left, undershoot, etc) or both. Another KR type, called bandwidth KR (Sherwood, 1988), is determined by bandwidth or range about the target or movement goal. If the error is within the target bandwidth, a binary KR (qualitative) is sufficient. If the performance is so bad for a prolonged time, then the instructor would give both the amount of error and the direction that is shown to enhance learning. In his study, Sherwood asked participants to make rapid elbow movement within the desired movement time, (MT = 200 msec). One group was told the exact MT as a KR following each trial. A second and third group received a KR if their MT exceeds ±5% and ±10% bandwidth of the target MT = 200 msec. Note that KR here means an indication of a negative or error KR. After blocks of 25 trials, all groups went through a retention test. He found that the 10% bandwidth group showed the smallest temporal error. It seems that less frequent error KR helps motor learning better.
But is the improvement in retention due to less frequent error KR? Lee & Carnahan (1990) studied a similar paradigm using two groups: a bandwidth group and a yoked control group. The control group received error KR exactly on the same trials as the bandwidth group. The difference is that in the actual group, no KR indicates that the previous trial was correct, while in the control group, no KR has got anything to do with their movement outcomes. They found that the bandwidth group performed better in retention. This suggests that no KR (or correct KR) provides an additional boost to learning on top of the less frequent error KR. Moreover, bandwidth KR facilitates learning in the observational learning task, supporting a high cognitive component to the provision of “correct” feedback (Badets & Blandin, 2005).
The way learners interpret error or correct KR may differ across time. During acquisition or practice blocks, as learning continues, the proportion of correct KR and error KR ideally increases. Thus, providing a constant correct/error KR ratio is not an effective paradigm (Lai & Shea, 1999).
How often do we provide KR? Motor learning researchers contrasted the relative and absolute frequency of KR. The absolute frequency of KR refers to the number of trials KR is given. Suppose, there are 50 trials and of those trials, 35 trials are with KR. The absolute frequency is 35 but the relative frequency is 35/50 = 70%. If the total trials doubles, the absolute frequency becomes 70 but the relative frequency remains the same. Early researchers thought that the relative frequency of KR is an irrelevant variable of learning. Later studies using the transfer paradigm show that both frequencies are important factors, which means no KR trials contribute somewhat to learning. Decreasing relative frequency does not suppress learning but enhances it (Winstein & Schmidt, 1990). In their study, the authors found that 50% and 100% groups don't differ in their performance during acquisition but their 5 min and 24 hours retention test favored the 50% group. Giving KR that is too frequent deter the performance because while on the one hand, it gives a motivational and information boost, the learners become so dependent on it until they neglect other inherent feedback e.g. somatosensory information. The over-reliance on KR is detrimental during motor tests later when KR is absent.
When should we provide KR? Since Thorndike's era, people thought that delaying reinforcement degraded learning in general. It appears this is not the case in motor learning, where delaying the KR presentation has a non-significant impact. Interestingly, it was found that if KR is presented too early, it can have a detrimental effect to learning (Swinnen et al, 1990). Filling the gap with extra stimulus or activity during both KR delay and post-KR interval (the short gap between the presentation of KR and the next trial) also degrades learning. It is thought that this occurs because the learners are not able to process the information provided by the KR and also by their inherent feedback. This is when KR blocks other critical information required for learning. Another instance where learning is degraded is when KR causes maladaptive correction. This is the case, e.g. in fast-reaching to a target when learners have reached the asymptotic phase and no further accuracy can be achieved. Our motor system is noisy (motor variability) and KR is thought to introduce unnecessary correction of an error caused by this noise.
Two Major Theories of Motor Learning
Let's move back to the 80's. One major theory of motor learning comes from J. Adams who used a set of empirical laws of motor learning based on slow, linear-positioning movements. He believed that on-going feedback from the limb is a key to learning, making motor learning inherently a type of close-loop process. This feedback -- called the perceptual trace -- provides a reference of correctness that is stored in the memory. During practice, KR serves a purpose to strengthen this perceptual trace in the memory. The sense of correctness, or thus a sense of wrong directions, get accumulated as the trial continues. KR also helps to guide subsequent movements. The learner strives to close the gap between the on-going inherent feedback and the prior perceptual traces. He claimed that the error-detection capability occurs through comparing the on-going inherent feedback and the perceptual trace.
Soon after Adams, Schmidt proposed an improved model that can be applied to both slow and rapid movements. According to Schmidt, motor learning involves creating rules or motor schemas. Learning first starts by selecting a generalized motor program (GMP) containing muscle commands that have invariant features. Then, the learner adjusts various parameters to produce a necessary movement. After the movement is performed, there are 4 types of information available for storage in the memory:
1) Information about initial conditions: posture, the weight of an object thrown, etc.
2) Parameters assigned to the GMP.
3) Augmented feedback of the movement outcome.
4) Inherent feedback from the body: proprioception, visual, audio etc.
From these 4 sources of information, the learner then continuously build and update two schemas:
1) Recall schema: to produce subsequent movements (updating GMP parameters with time).
2) Recognition schema: to evaluate movements just performed (sensory consequences).
Thus, the theory consists of 3 components: GMP, recall, and recognition schemas. Evidence of schema theory in real life has been outlined by Schmidt (chapter 2, Motor Control: Issues and Trends, 1976). Both major theories mentioned are not without criticisms. I think this is because scientists strive to refine the motor learning models that are able to explain all behavioral principles. Another popular approach to model motor learning is through using cognitive principles and degree-of-freedom problems (that of Bernstein's).
Retention and Transfer
In cognitive science, the concepts of learning, memory, retention, and transfer are very closely related. Motor memory is the persistence of the acquired capability for doing the motor task. The retained portion can be measured directly through recall and recognition tests. Such tests are usually performed after a certain time interval. The retention of motor learning can also be measured indirectly by looking at saving. For example, if one requires 50 trials to reach a criterion performance during early learning, but 25 trials during the retention test, the saving is computed to be 50%.
By definition, losses in memory are called forgetting. While learning can be measured directly, forgetting is measured indirectly through the performance loss following a retention interval. Studies have shown the absolute-retention measure is the most useful one. But the interpretation of such measures can be not as straightforward. For example the decaying effect of forgetting following a retention interval of person-A is slower than that of person-B. But is unclear whether it's due to a slower learning of person-A (and thus slower forgetting) or more retention capability.
Is retention profile uniform across different motor tasks? It appears that continuous skills are retained nearly perfectly over a long retention interval, whereas discrete skills can exhibit marked losses during the same interval. To recap, examples of a discrete skill are kicking a ball, throwing a dart, rapid reaching to an object. Continuous skills include swimming, jogging, and tracking task. Why is this so? Perhaps this is due that continuous skills are more basic and low-level and learned more completely.
The loss of motor memory can be triggered by passive decay processes. It can be due to active interference in the form of proactive and retroactive. Consolidation studies suggest that the interfering effects of learning a competing task are time-dependent.
A variant of a learning experiment is a transfer experiment where the effect of the practice of one task on the performance of some other task is evaluated. A common paradigm would be as follows: there are 2 independent groups (treatment group versus control). In the treatment group, subjects practice task-A, but tested on task B. In the control group, subjects do not do any practice but tested on task B.
Transfer of learning can be near (among almost similar tasks) or far (more apparent differences in tasks). Although the general consensus is that motor transfer is small, it is still debatable whether the transfer characteristics of all types of motor learning are the same. In real life, e.g. practicing tennis aids you in learning badminton as both sports are using a racket. The transfer is often measured as a percentage, indicating the proportion of performance improvement in one task that was achieved by practice on the other task. Based on this, a positive transfer means the practice of a task helps in learning another task. A negative transfer means the practice of a task hinders the learning of another task.
Reference: The writing and diagrams are based on a textbook, "Motor Control & Learning: a Behavioral Emphasis, 5ed" by RA Schmidt & T Lee.
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