Dynamic systems theory (DST) is gaining influence in the world of movement rehab and performance as way to explain how motor learning is optimized. The basic premise is that movement behavior is the result of complex interactions between many different subsystems in the body, the task at hand, and the environment. Given this complexity, systems theory is an appropriate tool to analyze how movement behaviors change and how learning occurs.
In this post and a follow-up, I will review some basic concepts from DST, and how you can use them with clients. After reading this, you might conclude that DST helps explain some of the practices and intuitions of some great movement coaches.
(By the way, if you want more background on some of the concepts in this post, and how they apply in the context of pain, you might be interested in this post on A Systems Perspective on Chronic Pain.)
Complex systems, self –organization and top-down control
The major premise of DST is that the body is a complex system composed of millions of interacting parts. The intelligence that coordinates the body is not localized in any one particular part, but emerges from the complex interactions of all the different parts. Thus, unlike a simple machine such as a thermostat, complex systems exhibit behavior that is controlled without a central controller.
To describe this seeming paradox, DST uses terms like self-organization, emergence, and multi-causality. These terms sound pretty exotic, but there’s no magic involved. Self-organization doesn’t imply some sort of vital life energy that defies the laws of physics. But how can you have control without a controller?
Consider the intelligent behavior of a colony of insects, such as a beehive. There isn’t any one bee that knows how to do all the important things that need to be done: build a hive; make honey; raise babies; repel predators, etc. Instead, these jobs just get done as a result of the complex interactions between thousands of different bees, who are all just mindlessly following simple algorithms for behavior. Similarly, the intelligence controlling our movement emerges from complex interactions between millions of different body parts and the environment.
But what about the central nervous system? Isn’t it the central controller of the body? In some sense yes – the CNS issues all the commands that cause muscles to fire in meaningful patterns. But the CNS is itself a complex system composed of many parts. And its behavior depends on its interaction with many other systems in the body, like the immune system, endocrine system, musculoskeletal system, and the environment.
This is why DST deemphasizes the role of “top-down” determinants of movement like the CNS, or “motor programs”, and focuses more attention on “bottom-up” factors like the structure of the body, the environment, and the nature of the task at hand.
For an example of how much these factors matter for coordinated movement, check out this video of a robot walking without any onboard computers or even motors. The intelligence that controls the robot is built into its structure. When that structure is put in the right context, it just does its thing:
This robot didn't need to learn to walk, it just needed the right kind of environment (a sloped ground) and a little push from his Daddy. Are babies any different? Some interesting studies by Esther Thelen showed something similar about what gets babies walking.
Structure, environment, and stepping behavior
Esther Thelen was an innovative thinker in the field of developmental psychology. (Interesting sidenote: she also became a Feldenkrais practitioner after learning that the Feldenkrais Method was an effective practical application of many of her ideas.)
One of her key studies concerns changes in the stepping behavior of infants during development. Researchers have long observed that when young infants are held upright, they will start stepping, as if they wanted to walk. This behavior then disappears for a few months, but then reemerges later.
The prevailing theory to explain these changes refers to development of the nervous system. According to this view, infants somehow acquire then lose the motor control programs required for stepping, as reflexes are inhibited and different motor control patterns develop. But Thelen was able to create the stepping behavior in children who were thought to be lacking the necessary CNS maturity. She did this by partially submerging their legs in water, which made the legs effectively lighter, which caused them to start spontaneously stepping.
Thus, the decisive factor controlling the stepping behavior was not changes in “top-down” programming from the CNS, but “bottom-up" changes in the effective weight of the legs, which basically fatten up and get lazy for a while, and then slim down and get frisky.
Thelen was also able to change stepping behavior through altering the environment. Check out this video of an infant walking on a treadmill. Under the conventional view, this type of stepping behavior is supposedly impossible given his level of nervous system development. But put him on a treadmill and he is ready to rock.
For Thelen, this is a direct challenge to the idea that development has fixed rules or stages that infants must pass through. Instead, development is very individual, depends to a great extent on context, and has multiple pathways to success.
These ideas are in contrast to conventional views of development, which holds that optimal development must proceed stage by stage according to top-down, genetically determined, and CNS-mediated programs. Maybe not. There are many roads to Rome, and not all of them proceed through crawling town.
Phase shifts and movement pattern changes
Complexity theorists use the term “state” to refer to all the different ways that a complex system can arrange itself. Changes in state are often nonlinear, which means that small inputs to the system can produce large outputs, or vice versa.
A significant non-linear change is called a phase shift. For example, water doesn't change its behavior very much as it gets colder, but when it gets cold enough it suddenly undergoes a phase shift and turns into ice.
Here’s an example of a phase shift in motor control. As a horse increases the speed of its walking, the basic coordination pattern of the limbs remains the same. But when a critical speed is reached, the movement pattern suddenly shifts into a trot. Add more speed and gait will again remain the same for a while, but then will eventually shift again into a gallop. Here’s a vid:
You can experience something similar while walking. Try walking without using a cross lateral pattern of gait – in other words, your shoulders and arms are either motionless, or NOT turning opposite your hips and legs.
Now speed up your walking. When you increase your speed enough (you may need to move into a jog), you will find that the shoulders and arms start moving opposite the hips. The change in velocity causes a phase shift to a cross-lateral pattern of gait which is sudden and pretty much involuntary.
How to change movement patterns
From the perspective of a movement teacher, this should be interesting – we are looking to change the movement behavior of our clients, and the most interesting changes are in the nature of phase shifts – real qualitative changes in movement patterns.
The DST perspective emphasizes that phase shifts in movement behavior can happen without any specific intention by the student to change, or any specific instruction from the teacher. Instead, change can arise simply by changing the nature of the task or the environment. If we look around, we can see examples of this teaching approach everywhere.
For example, the recent interest in barefoot running is partly due to the fact that it will cause some runners to spontaneously change their foot strike pattern. This shows that deeply ingrained movement behaviors can be quickly altered by changing environmental or task constraints, even in the absence of direct instruction or "motor learning."
Many classic movement interventions are based on exactly this idea. Consider a goblet squat, made popular by Dan John.
Instead of telling someone to sit back into the squat and keep their chest up, you can simply have them squat with a weight held in front of the chest. This new task demand often causes a quick improvement in the squatting pattern, even without any specific instructions.
Here's another example. Gray Cook uses a corrective exercise strategy called RNT (Reactive Neuromuscular Training) that might work as follows. If someone is squatting with the knees collapsing inward, Cook will "feed the mistake" by placing a band around the knees, driving them further inward. This new constraint will immediately encourage the student to drive the knees more outward - no words necessary.
And let's go back to running. Check this video by Chris Johnson, showing how he changed the foot strike pattern of his client by having her increase stride frequency:
Again, an immediate phase shift in movement behavior without specific instruction.
I need to wrap this post up now because I fear it may run off into too many tangents (especially the work of Gabriel Wulf in showing the superiority of external cues over internal cues.)
In a future post I will review more DST concepts like attractor wells, control parameters, and the stability, flexibility and variability of movement patterns. But for now here's a proposed simple take away from this post.
Humans are complex systems that have an amazing capacity to self-organize. If you give them the right motivation, environment, and task to perform, they will find good movement solutions, often with great speed and efficiency. The proper role of a coach is often not so much about telling people how to move, but creating the right conditions for learning and then getting out of the way.
This model for teaching is actually very common sense, and many of the best coaches and teachers use it intuitively. DST may be a good theoretical model to explain why this approach works, and that is a good reason for me to continue learning and writing about it.
Let me know what you think in the comments!