The Brain is for Movement: Part Two

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In a recent post I linked to a TED talk by neuroscientist Daniel Wolpert about how the brain controls movement. As promised, here are some more thoughts on Wolpert’s explanation, and how this relates to the Feldenkrais Method. (If you haven’t watched the video yet, I recommend watching before reading this post, but it’s not necessary. If you watched it and then forgot most of it, that’s OK, read on.)

Controlling movement is hard

One major takeaway that I got from Wolpert’s talk was that controlling movement is inherently difficult given the hardware that the brain must work with.

First, there are a staggering number of variables to control. The body has hundreds of joints, many of which are capable of wide ranges of movement at many angles. As Wolpert points out, for even the simplest tasks, there are nearly an infinite number of possible joint configurations to get the job done. And, for any particular set of joint movements, there are nearly an infinite variety of possible muscular contractions. Remember that there are around 400 muscles in the body and thousands of motor units per muscle.

With such an amazing number of variables to calculate and analyze, it’s no wonder that even the most powerful computers are complete overwhelmed with the complexity of performing even the simplest motor tasks with any dexterity.

The second challenge is that sensory signalling from the body to the brain is not transmitted and received with total precision. There is always some degree of “noise” in the signal which prevents the brain from knowing with certainty where the body parts are located. Wolpert uses the example of placing a finger under a table and trying to locate its position with the other finger – chances are you will be off by at least a few centimeters.

The third major problem in controlling movement is that there is also quite a bit of noise in the signals that the brain sends to muscle fibers telling them to contract. Because of this, a given command may result in different patterns of muscular contraction. For example, if I tell my finger to a do a particular thing three times, each time I will get slightly different movement, because of signaling errors.

Given these difficulties, trying to control the movement of your body is a little like trying to play a video game with a couple hundred thousand joy sticks. And a fuzzy TV screen and random errors in the commands you send to Super Mario. So, how does the brain deal with all these uncertainties?


According to Wolpert, the brain deals with uncertainty by using Bayesian reasoning, which involves some complicated math and statistics. This is all unconscious of course. Wolpert doesn’t go into the details of how the math works (although he does here in case you are interested.) But the gist is that Bayesian inferences provide an elegant way for the brain to calculate optimal movement solutions in the absence of any certainty about the accuracy of the data, based on a statistical analysis of various probabilities. According to Wolpert, the right movement command is the one which will “minimize the negative consequences of variability in the outcomes.”

So why do we care about any of this? I think this a great framework to analyze what we need to do to acquire movement skill.

The unconscious movement genius

One insight is that movement genius resides in the unconscious brain, not the conscious brain. The unconscious brain has an almost unimaginably staggering capacity of computation and analysis in regard to choosing the most efficient movement patterns. Apparently it knows Bayesian statistics and can calculate probabilities based on a monstrous amount of variables. Almost instantly. For example, my unconscious brain knows what degree of contraction in the soleus is necessary to prevent me from falling forwards when I raise my arm in front of me and thereby shift my center of mass a little forward of my base of support. It’s almost like there is some unconscious movement genius living in my brain solving problems of incredible complexity.

My conscious brain can’t do that. And this is part of the reason I don’t want my conscious brain too involved in selecting the muscle activation patterns that will be used in a particular movement. For example, I don’t try to consciously suck in my gut or activate my core muscles or clench my glutes when doing a movement, because some expert said that is the right way to do the movement. My unconscious brain has a much better chance of finding the perfect form for me.

So what is the job of the conscious brain, and what should it do if this supposed movement genius seems to be moving in a very inefficient way?

In my opinion the role of the conscious mind in refining movement patterns is in providing the unconscious brain with the information it needs to make good predictions and good decisions. That’s it. Good movement decisions are based on good information, therefore all we can do to help is to provide good information. We can’t go back there and start crunching the numbers ourselves. So what information does the unconscious need and how do we provide it?

Wolpert’s talk makes clear exactly what information the brain needs to make good movement decisions. First, sensory data about the position of the relevant body parts, and second, memories which store data from past experience about the results of certain motor commands. Let’s look at these factors in turn.

Pay attention to sense data

I have written many articles about the importance of accurate body maps and a good proprioceptive sense for better movement. The basic point is that we can all improve our movement by using various coordination exercises such as the Feldenkrais Method or Z-Health to clarify our body maps. For example in Feldenkrais Awareness Through Movement lessons, before doing any movement at all you will probably spend some time trying to sense the locations of certain body parts. This is not as easy as it sounds, and you are sure to find some surprising gaps in your awareness.

Clarifying smudged body maps should be of great general benefit for all your movements, since this data is always useful. For example, a better sense of the ankle will be probably be helpful for any task in which the ankle is involved.

In regard to the performance of any particular task, it will be helpful to focus conscious attention on the sensory data which is most relevant to that task. This will be a very small part of the whole. The amount of sensory data that we are bombarded with at any one moment is overwhelming. The brain will filter data based on where conscious attention is placed. Therefore, the focus of our attention helps determines the information that the unconscious has available to do it’s Bayesian reasoning thing and make good decisions.

So by paying attention to the sensation associated with a particular movement, you can affect the quality of the movement. In other words, if you really pay attention to how a movement feels as you are doing it, you will necessarily do it differently.

One of the basic techniques in a Feldenkrais Awareness Through Movement class is to encourage students to do the same movement many times, and each time focus on a different sensation – how it feels in the spine, or the pelvis, or the sternum, etc. Students are directed to notice that with each change in attention, the movement changes as well, even without any conscious intention to alter it.

This is why you perform better when you are actually paying attention to what you are doing, and why people crash their cars more often when their attention is on the cell phone.

So those are some conscious steps you can take to maximize the quality of the sense data that the unconscious brain uses to make good movement decisions. In the next post, I’ll discuss ways to maximize the quality of the other key source of information that the unconscious needs – past memories of the outcomes of particular motor programs.

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9 Responses to The Brain is for Movement: Part Two

  1. i like wolpert’s explanations, fits in nicely with bernstein’s original degrees of freedom problem and alain berthoz’ current work with movement and the brain.

    “The degrees of freedom problem or motor equivalence problem in motor control states that there are multiple ways for humans to perform a movement in order to achieve the same goal. In other words, under normal circumstances, no simple one-to-one correspondence exists between a motor problem (or task) and a motor solution to the problem. The motor equivalence problem was first formulated by the Russian neurophysiologist Nikolai Bernstein: “It is clear that the basic difficulties for co-ordination consist precisely in the extreme abundance of degrees of freedom, with which the [nervous] centre is not at first in a position to deal.”[1]

    Although the question of how the nervous system selects which particular degrees of freedom (DOFs) to use in a movement may be a problem to scientists, the abundance of DOFs is almost certainly an advantage to the mammalian nervous system. The human body has redundant anatomical DOFs at (muscles and joints), redundant kinematic DOFs (movements can have different trajectories, velocities, and accelerations and yet achieve the same goal), and redundant neurophysiological DOFs (multiple motoneurons synapsing on the same muscle, and vice-versa).

    How the nervous system “chooses” a subset of these near-infinite DOFs is an overarching difficulty in understanding motor control and motor learning.

    t was Bernstein who articulated the DOF problem in its current form. In Bernstein’s formulation, the problem results from infinite redundancy, yet flexibility between movements; thus, the nervous system apparently must choose a particular motor solution every time it acts. In Bernstein’s formulation, a single muscle never acts in isolation. Rather, large numbers of “nervous centres” cooperate in order to make a whole movement possible. Nervous impulses from different parts of the CNS may converge on the periphery in combination to produce a movement; however, there is great difficulty for scientists in understanding and coordinating the facts linking impulses to a movement. Bernstein’s rational understanding of movement and prediction of motor learning via what we now call “plasticity” was revolutionary for his time.

    In Bernstein’s view, movements must always reflect what is contained in the “central impulse”, in one way or another. However, he recognized that effectors (feed-forward) were not the only important component to movement; feedback was also necessary. Thus, Bernstein was one of the first to understand movement as a closed circle of interaction between the nervous system and the sensory environment, rather than a simple arc toward a goal. He defined motor coordination as a means for overcoming indeterminacy due to redundant peripheral DOFs. With increasing DOFs, it is increasingly necessary for the nervous system to have a more complex, delicate organizational control.[1]

    Because humans are adapted to survive, the “most important” movements tend to be reflexes–pain or defensive reflexes needed to be carried out in very short time scales in order for ancient humans to survive their harsh environment. Most of our movements, though, are voluntary; voluntary control had historically been under-emphasized or even disregarded altogether. Bernstein saw voluntary movements as structured around a “motor problem” where the nervous system needed two factors to act: a full and complete perception of reality, as accomplished by sensory integration, and objectivity of perception through constant and correct recognition of signals by the nervous system. Only with both may the nervous system choose an appropriate motor solution.”

    larry goldfarb wrote this great article on the DOF problem, coordination and feldenkrais awhile ago: “why robots fall down”



  2. Dwight,

    Thanks for the great excerpt, right on point. I have been meaning to reread this article and do a post on the DOF problem. Perhaps soon.

  3. Todd, thank you for presenting information in the way that an ‘ordinary’ person (as myself) can understand. I have always followed in the path of trust, faith and instinct as my teachers and mentors before me.
    However I believe that your explanations allow a greater understanding to arrive from another quarter … using active intelligence to provide a greater illumination on the body method of why and how we move … thankyou, thank you!

  4. Great post, thank you Todd!

    May I add 2 things?

    > And, for any particular set of joint movements, there are nearly an infinite variety of possible muscular contractions

    I don’t think so. This is a cute assumption by Daniel Wolpert, but faulty. It’s like saying, for mating, there are nearly an infinite variety of possible women/men on the planet. Mathematically correct, but far from real life.

    > Noise

    Radiating the knee, last ATM by MF. There’s more to bodily signals than electricity running down some wires.

    > Daniel Wolpert

    People who cannot give Functional Integration are cute, like Kitten. But by no means taken seriously on such questions.

    That’s like Mathematicians talking about Tennis, without having ever touched a tennis racket or played any sport at all.

    • Thanks for stopping by Alfons.

      About the infinite variety of muscle contractions to accomplish a given set of joint movements, Wolpert didn’t say that, that is my claim. But I’m not sure why it wouldn’t be true – of course the possible combinations are not infinite, but they are vast. And I don’t get why you would say the math is right but in real life it’s wrong.

      And, no offense, but I don’t really understand the rest of your post concerning kittens, FI, electricity, tennis and math. If you are suggesting that Wolpert thinks about movement better than he moves, then I assume that is true. But that doesn’t mean we should not take him seriously on the subject or that he is cute like kitten.

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