Coaches preach it endlessly, “Always finish with the correct follow-through.” In baseball, football, tennis, golf, soccer or any sport requiring a skilled targeting movement, how your throw, swing or kick ends up can determine the ball’s speed and direction. But how can something you do after contact with an object affect its motion? Once a quarterback lets go of the football, the position of his arm after release seems meaningless. New research from the University of Cambridge has found the answer; the development of motor memories.
For most sports skills that require an athlete to propel or hit an object at a target, the follow-through has been emphasized to prevent injury. A baseball pitcher throwing a 90 mph fastball must also decelerate his arm after the release. Without proper mechanics, the wrist, elbow or shoulder could give in to the massive force applied by the motion.
Daniel Wolpert is absolutely certain about one thing. “We have a
brain for one reason and one reason only, and that’s to produce
adaptable and complex movements,” stated Wolpert, Director of the Computational and Biological Learning Lab
at the University of Cambridge. “Movement is the only way you have of
affecting the world around you.” After that assertive opening to his 2011 TED Talk,
he reported that, despite this important purpose, we have a long way to
go in understanding of how exactly the brain controls our movements.
Daniel Wolpert
The evidence for this is in how well we’ve learned to mimic our
movements using computers and robots. For example, take the game of
chess. Since the late 1990s, computer software has been playing
competitive matches and beating human master players by using programmed
tactics and sheer computing power to analyze possible moves. However,
Wolpert points out that a five-year-old child can outperform the best
robot in actually moving chess pieces around the board.
From a sports context, think of a baseball batter at the plate trying
to hit a fastball. It seems intuitive to watch the ball, time the
start of the swing, position the bat at the right height to intercept
the ball and send it deep. So, why is hitting a baseball one of the
most difficult tasks in sports? Why can’t we perform more consistently?
The problem is noise. Not noise as in the sense of sound but rather
the variability of incoming sensory feedback, in other words, what your
eyes and ears are telling you. In baseball, the location and speed of
the pitch are never exactly the same, so the brain needs a method to
adapt to this uncertainty. To do this, we need to make inferences or
beliefs about the world.
The secret to this calculation, says Wolpert, is Bayesian decision
theory, a gift of 18th century English mathematician and minister,
Thomas Bayes. In this framework, a belief is measured between 0, no
confidence in the belief at all, and 1, complete trust in the belief.
Two sources of information are compared to find the probability of one
result given another. In the science of movement, these two sources are
data, in the form of sensory input, and knowledge, in the form of prior
memories learned from your experiences.
Thomas Bayes
So, our brain is constantly doing Bayesian calculations to compute
the probability that the pitch that our eyes tell us is a fastball is
actually a fastball based on our prior knowledge. Every hitter knows
when this calculation goes wrong when our prior knowledge tells our
brain so convincingly that the next pitch will be a fastball, it
overrules the real-time sensory input that this is actually a nasty
curve ball. The result is either a frozen set of muscles that get no
instructions from a confused brain or a swing that is way too early.
Our actions and movements become a never-ending cycle of predictions.
Based on the visual stimuli of the approaching baseball, we send a
command to our muscles to swing at the pitch at a certain time. We
receive instant feedback from our eyes, ears and hands about our success
or failure in hitting the ball, then log that experience in our memory.
Wolpert calls this process our “neural simulator” which constantly
and subconsciously makes predictions of how our movements will influence
our surroundings. “The fundamental idea is you want to plan your
movements so as to minimize the negative consequence of the noise,” he
explained.
We can get a sense of what its like to break this action-feedback
loop. Imagine a pitcher aiming at the catcher’s mitt, releasing the
ball but then never being able to see where the pitch ended up. The
brain would not be able to store that action as a success or failure and
the Bayesian algorithm for future predictions would be incomplete.
Try this experiment with a friend. Pick up a heavy object, like a
large book, and hold it underneath with your left hand. If you now use
your right hand to lift the book off of your left hand, you’ll notice
that your left hand stays steady. However, if your friend lifts the
book off of your hand, your brain will not be able to predict exactly
when that will happen. Your left hand will rise up just a little after
the book is gone, until your brain realizes it no longer needs to
compensate for the book’s weight. When your own movement removed the
book, your brain was able to cancel out that action and predict with
certainty when to adjust your left hand’s support.
“As we go around, we learn about statistics of the world and lay that
down,” said Wolpert. “But we also learn about how noisy our own
sensory apparatus is and then combine those in a real Bayesian way.”
Our movements, especially in sports, are very complex and the brain
to body communication pathways are still being discovered. We’ll rely
on self-proclaimed “movement chauvinists” like Daniel Wolpert to
continue to map those routes. In the meantime, you can still brag about
the pure genius of your five-year-old hitting a baseball.
