In this TED-talk neuro-scientist Daniel Wolpert did an incredible job, introducing his research to a wide audience in an accessible manner. Yet in this fairly short talk he outlines some extremely powerful and important ideas for anyone interested in human movement and motor-learning!
For that reason I decided to do a commentary on some sections of this talk, outlining the key take-away points, to make sure no important information slips under your radar.
In the following you will watch clips of his talk, followed by my commentary. This way I will “guide” you through this talk and will try to emphasize important bits of information for coaches or athletes.
I recommend to re-watch the whole talk afterwards, since it is extremely information-dense and interesting!
Why do we have brains?
“We have a brain for one reason and one reason only and that is to produce adaptable and complex movements.”
In this segment Daniel Wolpert goes on to expand on why he believes that the brain’s only function is to produce movements.
If the brain’s only reason is to produce movement is (philosophically) debatable but the primary importance of motor-control is not!
The take-away for us coaches or athletes who are interested in teaching or learning movements is:
You can not understand the brain without movement and you can not understand movement without the brain!
Playing chess vs moving chess pieces
Lets try to understand how the brain controls movement or in other words, how it regulates and monitors muscle contractions.
A good way to gauge our understanding on brain function and movement are computers and robots. Because we can basically put our scientific theories into algorithms and see how well the computer or robot does (compared to humans)!
In the next section Professor Wolpert shows how well computers do at purely analytical tasks, like playing chess, but how poorly they perform even simple movement tasks compared to a 5 year old.
Spoiler: Movement is way more complex than chess!
Noise and Variability
In this section Daniel Wolpert outlines how humans control movement:
- neural signal to contract muscles (output)
- your body moves (process)
- you get sensory feedback of your actions (to regulate new outputs) (input)
To make things (alot) more complicated, we have to add noise to the neural signals which contract our muscles and to the sensory feedback of our perception. Additionally our task (like pouring a tea-pot) is usually also extremely variable, adding even more uncertainty and complexity to the process.
Human motor-control and movements are adaptable and auto-regulated solutions to extremely variable tasks, mediated by noisy feedback.
Or how Professor Wolpert put it: “a sensory-movement-task soup of noise”
But how is it even possible that we can successfully navigate through this soup of noise and still perform such sensitive and miraculous movements?
Probabilities and predicitons
One way to deal with uncertainty, noise and variability is to make decisions based on mere probabilities.
In this section Professor Wolpert discusses how Bayesian Decision Theory might help to understand human movement and decision making. A small outline of Bayesian decision theory might look like this:
- “We generate believes about the world” based on
- Data (sensory input)
- Prior knowledge (memory)
- These beliefs are represented by probabilities
- Based on these believes we make predictions about the most probable outcome
- We act based on this prediction
- (We gather feedback of our action and update our memory)
In other words: Our actions are guided by guesses about the world based on our present perception and past experiences.
This means we have to create more experiences and improve our perception if we want to make more accurate guesses and consequently better decisions!
Tickling, time-delays and why we all move (almost) alike.
I want to stop my commentary here because I feel like we already discussed enough incredibly important information for one post. I hope I was able to outline the relevance of Daniel Wolpert’s research for coaches, athletes or anybody interested in movement and motor-learning.
At some point I will do a commentary on the second half of this talk, as it is also packed with super significant information.
You can check out my post on feedback and autoregulation and I recommend you to further research the concepts and theories you encoutered in this talk!
Special thanks to Steve Morris for first sharing this talk and pointing out the significance of Wolperts research for fighting and combat sports.
Enjoy the rest of the talk!