Reorganizing the Athlete’s Brain - Adding Noise as a Function of Neuroplasticity

Key Points

Instructional language serves as noise for the motor system.
Differential learning enhances exploration.
Existing theoretical perspectives do not accommodate evidence demonstrating motivational and attentional effects on performance and learning.
Stop coaching what should happen rather than what actually does happen.

We marvel at the creativity of action. Yet, this abstract representation of the limitlessness of the human body is often boiled down to “muscle memory,” a made up summation of the craft that beautifies the power of the brain and its relevancy.

Needless to say, it is not that simple.

The philosophy and science of motor learning has developed numerous theories over the past few decades about how effective motor performance is achieved, much of which has focused primarily on certain practice conditions that affect task relevant information processing. Early motor learning theories also tended to stress the significance of numerous repetitions, highlighting the false 10,000-hour rule of deliberate practice towards expertise. Then, the variability of practice approach focused on variation of parameters in order to automize invariant features of a movement class. This was seen as variability of outcomes measured with averages and standard deviations indicating error, or mechanisms of movement indicating how the movement was being achieve. For example, when learning how to hit a volleyball, a coach may vary:

Distance
Net height
Number of steps
Ball set height
Ball tossed height
And more.

Later, the contextual interference approach advocated for alternate practice of at least two movements corresponding to variations of invariants. For example, blocked or randomized training of hitting and serving a volleyball. While the evolution of motor skill acquisition has seen several different avenues of thoughts with experimental evidence giving us a reason to believe, what remains common amongst all approaches is how the idea of noise and variability is interpreted and applied. In fact, the idea of skilled performance was evident back in the early 1960’s, exhibiting characteristics of spatial-temporal patterning, continuous interaction of response processes with input and feedback processes, and learning. Essentially, to achieve performance goals in competitive sport, there needs to be a balance between movement pattern stability and variability because although performers need to be consistent in their outcomes, they also need to be able to successfully adapt their movements to changes in the performance environment which includes informational and instructional cues. The purpose of this article is to shed light on the misconception that ability is constrained within how the muscles function and not how muscles are constrained by instructional cues. It’s a call to the myth that the same cause leads to the same effect, an assumption that the central nervous system is an executive organizer and prescriber of motor programs with a task of producing and reproducing stable movement patterns from an individual’s effector landscape. To better understand this concept, let’s first define a couple key terms.

Noise is unstructured variability or unavoidable deviations from a given target movement during movement repetition (Shollhorn and Beckmann, 2006). While we can’t physically observe noise in practice, it is inherent in temporal structure of movement variability (Newell, 1986). To put it into context, we can’t physically see our heart rate increase when we are stressed, but we know its there and if we were to measure it, we could see it. In other words, random irrelevant movement components added to the target skill constitute as noise to the motor system. Thereby, consisting of continuous changes in movement executions, avoidance of repetitions, and an emphasis on discovery learning. For example, allowing athletes in a slalom dribbling task to select their own technique as compared to restricting them to the optimal or medial part of the foot. As a result, noise is also instruction, and phrases like “I need you to” actually may constrain the movement system. For example, the research shows us that different verbal instructions expose movement characteristics that may be risky or optimal. Often times as coaches and practitioners, we form these acute interventions to ace a movement screening or test which may lead to chronic adaptation engraining risky (or optimal) movement behavior.

Variability is an umbrella term for all series of observations that are non-constant , associated with intended changes of movement invariants or variable movement parameters considered as different exercises. In other words, variability is a description of the noise which are fluctuations indexing stability by promoting a flexible and adaptable motor system, encouraging free exploration. As described above, allowing exploration will allow performer’s to gain information about future performance and not just to differentiate immediate performances of a skill. It is important to note that this information can be derived from all kinds of movements that surround an idealized motor solution, which may be considered by coaches as movement errors. In essence, noise is a function of variability just like our increase in heart rate is a function of psychological stress. Noise makes us act in certain ways. An increase in heart rate makes us sit down for example. In the context of sport, movement variability is our response to noise. As a result, while we focus our efforts on outcomes, it is important to realize that our instructional and informational cues as coaches is noise and that movement variability is how we exploit this noise.

However, we still remain stuck in the era of linearization where deviation from ‘perfect’ is considered detrimental. This ‘ideal movement’ is understood as a person-independent model fulfilling momentarily within the relative narrow borders of the most effective solution of a methodical series of exercises. For which, consistency in outcome remains the main attribute to current coaching and rehabilitation models. In other words, we break down a skill on the simple to complex continuum hoping that the complex pattern is achieved through a smaller outcome based approach. We are coaching for what should happen rather than what actually does happen.

If I’m teaching a volleyball player to hit a ball, I will have my athlete first go through the footwork, than according to my own inference, I will start tossing a ball or have a setter involved as we “progress” to the next step. However, as many coaches do, we will constrain our setter to set one foot off the net from a perfect tossed ball when in reality, passes in a game may be five feet off the net which aren’t’ perfect. But is progressing to the next step our way as coaches to assure a concept of ability? or our way of increasing task difficulty?

While the work of Bernstein and the constraints led approach has done an excellent job in aiding a new dialogue of how noise and variability is varied throughout the learning continuum, we have yet to look at the performer dependent model of motor learning; where motivation and attention attribute to how coordinated skilled movement is executed, thereby optimizing motor performance. After all, decision making in sport is reliant on selective attention and anticipation, both performer-dependent. Skill learning is an interaction between cognitive aspects (understanding the movement), perceptual aspects (how to make critical discriminations), coordination (timing of body movements) and tension-relaxation (movement patterns). All of which are embedded within the motivation and attention attribute to how coordinated skilled movement is executed.

“We have yet to look at the performer dependent model of motor learning where motivation and attention are considered in the role of skill execution”

The behaviorists studied what was observable, while the structuralists studied action through the lens of intention and consciousness. Both were very successful in aiding the revolution of theory. However, neuroplasticity, or the idea of variability and noise as an informative biological feature of movement remained obsolete. While the popular definition of neuroplasticity still exists around experience and the structural brain changes resulting from the formation of new connections by dendritic spine growth and enhanced internal representations, is creativity simply a result of muscle memory coming from this plasticity of experience or a unique interplay between motivational and attentional information processes? or both?

Traditionally, the idea of movement variability was outcome dependent. As a result, any deviation from an intended movement pattern was constituted as error. For example, 2+2 will always equal 4. It wasn’t until much later that researchers found such deviations to be potential sources of information in the process of analyzing and monitoring biomechanical qualities. For example, (2+6) -4 will also always equal 4.

The difference between these examples is how the individual goes about achieving the intended goal. While “muscle memory” confuses adaptation, learning, and performance as simple global parameters which define output, we tend to forget that variability is present in kinetic and kinematic parameters which control basic output, thereby, creating a system which represents low outcome variability as a resultant of high movement coordination variability. Hence, there is a lot of different ways (muscles fired, forces used, etc) to accomplish a free throw shot for example. This ability of our system to achieve a task goal through different patterns of coordination defines the compensatory and flexible nature of our ability to actively engage in our perceptual-motor landscape.

In fact, it is within this variability that noise is honed in what we call neuroplasticity. There will always be noise within the temporal and spatial domain but as performer’s, our job is to make noise matter less (i.e novice – expert continuum) and our job as coaches and practitioners is to create search strategies through an interplay between challenge and success.

For example, add a live defender rather than a cone. Let the player figure out how s/he wants to score the basket rather than telling them to go around the cone before scoring the basket. It’s also appalling when basketball teams warmup and do layup lines. Do we really think they’re warming up for competition?

Transfer is a topic for another day, but as coaches we want to see our players take whatever they’re learning and doing in practice into competition. The bottom line is that everything transfers, good or bad. Learning is optimal only when processing activities promoted by practice conditions are similar to processing activities required by transfer. In other words, practicing ‘game like’ or what actually happens as referenced above. As coaches and practitioners, we think that movement automaticity is prescriptive stable movement patterns in response to preplanned stimuli, rather than stable movement solutions as a result of adaptation. For example, a common misconception is that ladder drills improve footwork in competition. Yet, a ladder drill is a preplanned stimuli which will always create stable movement patterns within the speed/accuracy domain. Of course, this bottom up approach to automaticity is exactly why repeating to be learned or preplanned movement patterns is the direct cause of de-automatization. For context, automated motor processes can be disrupted if they are consciously controlled through task relevant declarative knowledge, or ‘prescriptive.’ For more research on this, the theory of reinvestment (Masters and Maxwell, 2008), and the constrained action hypothesis (Wulf, 2013) are good places to start.

In fact, Bernstein says, “the goal of a task and anticipation of the desired outcome serves as invariants on the regulation of movements.” There are three common invariant features all of which are embedded within how we use instruction and feedback. These include:

Relative timing
Relative force used
Sequence of actions or components

Think about when you write your signature. Regardless of how you write it, there are several features that remain constant. If variability is the intended changes of movement invariants, why aren’t we focusing on mechanisms that actually affect motor performance (intrinsic motivation and attention) rather than structuring a practice condition that adheres to a same outcome, same movement, approach? In fact, external focus of attention increases movement frequency which allows stochastic (random) noise to be utilized more efficiently. So in a competition, I can tell my volleyball players to serve to a specific zone, or allow the player to choose between two zones. The concept of choice gives the athlete a little more control. When designing a basketball play, many young players freeze when their teammate isn’t open after coming off the ball screen. It’s a good idea to add options here too. What i’m trying to say is that instruction and feedback is additional noise that the motor system has to work with in the confines of the movement. We are forgetting this concept:

“Regardless of how you sign your name, there are several features that remain constant“

The realm of sport performance and rehabilitation has been very structured in the past. From sets and reps to a linear progression of more complex movement, and to the use of garbage cans, cones, ladders, and whatever else that has no relevancy to skill acquisition. Instead, props like these calibrate and attune the performer to the wrong interventions, many of which won’t transfer.

For example, a hurdle jump will not make a volleyball blocker jump higher when there is no ball, transition, visual cue, etc. The assumption of such motor program structures (hurdle vertical jump will make me a better blocker) is that similar movement outcomes are the result of the same motor program with added noise in the periphery. And this noise in the periphery is disregarded as a bad set (my feet got caught in the hurdle or I landed with increased flexion). When the motor system is changing all the time and research tells us that no repetition is ever the same (i.e ‘repetition without repetition’), it seems plausible to provide a training regime that allows the performer to cope with the same problem under changed conditions of noise and variability. This would be changes in the following:

Attentional demands
Challenge/success
Differential learning (referenced below)
Autonomy supportive language (“let’s try” vs. “listen, you have to”)
Increase positive feedback even on unsuccessful performance

Creative movement is not just the interaction between different body parts, but an interaction with the environment through perturbation and adaptation which result from motivation and attentional effects. Think about when an athlete has the ‘hot hand’ or is ‘in the zone.’

In fact, as Orth et al., (2017) says, it’s adaptive variability. As animals, we have been resourceful since the onset of our evolution, constantly trying to solve motor problems rather than repeat solutions. We don’t look for creative solutions, we discover them according to the various task relevant and irrelevant changing demands of the organism-environment interaction. A big part of this, again, is motivational and attentional influences.

Yes, memory plays a role in the performer’s ability to interpret this interaction. Memory is generally split between long term, short term, and working memory.

Long term memory – A vast resource that represents, or models, regularities in the co-occurrence of elements of information (Cowan, 2008)
Short term memory– The capacity to keep a small amount of information in mind in an active, readily available state for a short period of time (Cowan, 2008).
Working memory – Processing resource of limited capacity, involved in the preservation of information while simultaneously processing the same or other information retained primarily in a short period of time (Olesen et al., 2003)

A muscle clearly can’t store memory. Muscle fibers do not have a separate independent mind of their own. Of course, when accepted as truth by a large number of people without proper investigation, a myth can create cultural change. The idea behind muscle memory is that muscles can function to produce a more receptive motor cortex through its ability to adapt to different training loads and cognitive demands. This happens through our brain’s capacity to store information, strategize, and create effective solutions. It is an interplay of emotion, expectations, autonomy, instruction, motivation, and attention. All of which are direct results of an athlete dependent model of how a skill is learned and executed. Again, we never forget how to ride a bicycle, but a violinist needs to practice every day to not lose their skill. Although not studied enough, memory formation remains an interest to sport scientists today.

None of this is originates in the muscle itself. It comes down to how coordinated and skilled movement is executed. By deliberately adding noise and variability to the motor system (each repetition is structured differently), differential learning has shown to facilitate early consolidation indicated by post-training increases in theta and alpha activity (Henz and Shollhorn, 2016). This is good because brain activation patterns like this indicate working memory processes where attentional resources are allocated in processing of somatosensory information (conscious perception of position and movement which arise from the muscles and joints). Differential learning is a fairly new concept based on the ideas of artificial neural net, dynamical systems, and stochastic resonance. The basic idea is is the enlargement of differences between subsequent movements in order to produce additional information for the motor system (Shollhorn et al., 2006).

Again, reiterating here that language (i.e instruction) is indeed a constraint on the motor system. While differential learning provides a variability practice condition that allows for noise to be utilized, noise is also instruction and so it is crucial we as coaches and practitioners understand the motivational and attentional effects on performance.

There is a unique correlation between our ability to use noise for adaptation and flexibility. A simple example is when you go up for a layup and are hit on all sides of your body but still find a way to be coordinate and control your brain and body movement effect relationship. Yet, in terms of motor learning and skill acquisition, constant repetition of repeating a target movement as often as possible despite the numerous structural similarity breakdown of skills, remains to be a popular trend.

Sure, sets and reps are important, but so are new avenues of thought. Our assumption is that stability is a direct correlate to plasticity. Meaning that a stable movement pattern is an indication of a learned motor skill that is capable of adapting to any context. How does a performer adapt to new information without overwriting old information?

A single task, lets call this A, can be perfected, but learning an additional task may interfere with task A. The only way this is resolved is by using high levels of noise, where inducing instability allows the motor system to achieve a stable end point through variability within the null space (joint angles, muscle activation, etc.)

Think about when you learned how to write a bicycle. This instability doesn’t necessarily have to be in physical conditions, they can also be through deliberate instructional changes. In fact, research has shown that inducing an external focus of attention increases vertical jump height with a decrease in EMG activity indicating movement efficiency (Wulf and Dufek 2010).

“Research has shown an external focus of attention increases vertical jump height with a decrease in EMG activity”

Moreover, enhanced expectancies or conditions that enhance learners’ performance expectancies (success), shows greater improvement on balance (Lewthwite and Wulf, 2010b), perceived task difficulty increases success during practice (Trempe et al., 2012), and autonomy support, or allowing performers to exercise control over the environment through language and incidental choice enhances motor skill learning (Wulf, 2007b), to name just a few.

Yet, the problem may just be in the teaching of a single task. Performers are rarely in a setting where their focus is the single task at hand. Like the example alluded to before, a basketball player’s intent is not only to make the layup but focus on dealing with all the bodies being thrown at him on the way up. So there seems to be an intention and attention paradigm that again, is performer-dependent not independent.

So the question proposed in the beginning was how does an elite level athlete activate cognitive control processes (adaptation) during complex and constrained motor performance?

In other words, is creativity simply a result of muscle memory coming from this plasticity of experience? My hope is you can formulate that answer yourself with the information above. The motor learning literature is filled with work on practice conditions, stages of learning, contextual interference, motor control, measuring performance, action preparation, feedback, retention, and transfer, all of which play a significant role in adaptive variability.

However, one thing I do want to briefly mention is the role of language in all this. Applicable to coaches, is the way we instruct and facilitate learning and practice. Numerous studies have been conducted on the role of attentional focus, autonomy support, and enhanced expectancies (i.e perceived task difficulty, social comparative feedback, and conceptions of ability) which are inherent attributes to cueing. Whether it’s providing choice (task relevant or irrelevant), directing performers to engage in an external focus, or providing social-comparative feedback, sport performance is not just the training load. It is the cognitive constraint that your language has on a performer’s resultant movement strategy. We need to put ourselves as coaches, teachers, and practitioners in performer-dependent models of learning, where its not just the outcome that matters, but the motivational and attentional effects that attribute to how learning and performance is strengthened. At the end of the day, we want to prevent self and non-task focused states which may constrain the motor system. Unfortunately, we are in the midst of doing just that.

Muscle memory is the adaptive variability that fluctuates the perceptual motor landscape. And neuroplasticity is the long-term retention of this adaptive variability. To sum up, this is just an introduction to many other topics that are relatable, and I think its important to realize that as coaches and practitioners, we aren’t inducing muscle memory through what we like to refer to as linear progression. We are reorganizing our ability to consolidate memory from differential practice in order to satisfy a coalition of organismic, task, and environmental constraints. In simpler terms, adding perturbations (a form of noise) to movement repetitions in the form of additional tasks, will force athletes to adapt consistency to new tasks. As a result, the search for the most effective learning approach can be considered as the search for optimum noise (stability in the midst of instability) that enhances goal action coupling. My hope is to break down aspects of motivational and attentional effects on motor performance and learning in the future. At the same time, I just want to shed some light on a philosophical battle we face as teaching facilitators. In my opinion, we’re boggled up with a deductive reasoning approach, where a valid argument may have false premises making the conclusion false or true, depending upon what you put in. We establish generalizations because of this. As compared to induction where we infer from observations to support hypotheses that would explain some phenomena. A practical example is deductive when we observe Steph Curry’s jump shot. Because of this quick release, we assume that the new way of teaching is a quicker release. As compared to an inductive approach where Steph Curry’s jump shot has a quicker release coming off a screen to this left shoulder as compared to his right shoulder.

In conclusion, there is noise and variability present at all times. The difference between all the theories is how much the noise differs in terms of amplitude and frequency. Novices may show better learning with low contextual interference while experts are more successful with high contextual interference. Movement repetition for novices may have larger variability or noise that would lead to more degraded learning if additional noise was induced during practice. Conversely, experts have reduced variability within movement repetition thereby requiring additional noise in search for more stable solutions. Deliberately adding noise by changing the demands of every repetition in the form of the differential learning approach may be an avenue for future practice. However, to facilitate this type of approach, a performer dependent model is necessary where motivational and attentional factors are incorporated to the learning and execution of how to bring coordinated control of complex movement.

About Harjiv Singh

Harjiv is currently a PhD student within the Interdisciplinary Health Sciences (Motor Learning and Control) Program at UNLV, researching the role movement variability within the scope of motivational and attentional effects on performance and learning. He is a former collegiate and professional volleyball player with a Bachelor of Science degree in Kinesiology from Rutgers University and a Master of Arts degree in Motor Learning from Columbia University. After completing his PhD, he intends to work within the movement science domain for teams and individuals looking to bridge the gap and specifically understand how the brain and body correlate seamlessly to coordinate skilled movement behavior. He is an avid hiker, reader, beach go-er and coffee enthusiast. Feel free to reach out Harjiv, as he loves to collaborate with different ideas and thoughts!

References

Cowan, N. (2008). What are the differences between long-term, short-term, and working memory?. Progress in brain research, 169, 323-338.

Henz, D., & Schöllhorn, W. I. (2016). Differential training facilitates early consolidation in motor learning. Frontiers in behavioral neuroscience, 10, 199.

Lewthwaite, R., & Wulf, G. (2010). Social-comparative feedback affects motor skill learning. The Quarterly Journal of Experimental Psychology, 63(4), 738-749.

Masters, R., & Maxwell, J. (2008). The theory of reinvestment. International Review of Sport and Exercise Psychology, 1(2), 160-183.

Orth, D., van der Kamp, J., Memmert, D., & Savelsbergh, G. J. (2017). Creative motor actions as emerging from movement variability. Frontiers in psychology, 8, 1903.

Olesen, P. J., Westerberg, H., & Klingberg, T. (2004). Increased prefrontal and parietal activity after training of working memory. Nature neuroscience, 7(1), 75.

Schollhorn, W. I., Beckmann, H., Michelbrink, M., Sechelmann, M., Trockel, M., & Davids, K. (2006). Does noise provide a basis for the unification of motor learning theories?. International journal of sport psychology, 37(2/3), 186.

Trempe, M., Sabourin, M., & Proteau, L. (2012). Success modulates consolidation of a visuomotor adaptation task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38(1), 52.

Wulf, G. (2007). Self-controlled practice enhances motor learning: implications for physiotherapy. Physiotherapy, 93(2), 96-101.

Wulf, G. (2013). Attentional focus and motor learning: a review of 15 years. International Review of Sport and Exercise Psychology, 6(1), 77-104.

Wulf, G., Dufek, J. S., Lozano, L., & Pettigrew, C. (2010). Increased jump height and reduced EMG activity with an external focus. Human movement science, 29(3), 440-448.

Reorganizing the Athlete’s Brain – Adding Noise as a Function of Neuroplasticity

Free Training Guides!