Episode Two: How to Play “in the Zone”, and Why You Want to be There (Part One)
“I was playing out of my head”
“It was like the banjo was playing itself”
“I was in the zone”
Ask a master – regardless of domain – what it feels like when they’re performing at their very best, and these are the kind of descriptions you’re apt to hear. The words may be different, but the underlying sentiment is almost always the same: an alternate state of consciousness has been reached, allowing for effortless and optimal performance.
Over the years, different names have been used to describe this state of being: “the zone”, “flow state”, “zen-like”. In these moments, the conscious mind is quiet, sometimes leaving the player with the impression that they’re no longer involved in the playing. He or she may even feel a bit sheepish about taking credit for the resultant performance.
But the zone isn’t territory reserved just for masters. On the contrary, these moments of effortless execution can happen to anyone, at any stage in the learning process. In fact, you’d be wise to make it a habit of seeking them out often, just as the masters do.
The Bird’s Eye View of Learning
Nobody is born knowing how to play the banjo. This is obvious. Even Earl had to build his own banjo playing brain.
This means that every component of playing the banjo, from plucking a string cleanly to fretting notes with the fingers to forming chord shapes, must be learned.
More specifically, this means that a dedicated neural network – a set of instructions for how to perform that particular skill, written in the language of neurons – needs to be created for each and every technical component of banjo picking. The brilliant thing about the human brain is that it can create those instructions for itself, based entirely on the inputs it’s given through practice (which in reality are the inputs it provides itself…consider your mind blown).
In Chess and Tai Chi master Josh Waitzkin’s book The Art of Learning, he likens the learning process to hacking a path through dense jungle with a machete. At first the task is arduous and taxing, with great expense of time and effort.
During this stage, the conscious mind is fully engaged, frantically trying to cobble together an ad hoc motor program (i.e. a set of instructions for movement) out of existing multi-purpose neural machinery. All cognitive resources are brought to bear on the task at hand.
If we place a subject at this stage of learning in a functional brain imaging scanner, we see brain activity all over the place (indicated by the colors, which signify increased blood flow to the corresponding areas):
With repeated practice over time, things change. A lot. Ultimately, if the learning process goes well, the brain creates a customized neural network for the learned activity. When the task is performed now, we see both a shift in the location of the brain activity, along with a marked reduction in the number of neurons involved:
This neural network that’s been created not only consumes fewer resources, but much of it also now exists beneath the cortex (it is “subcortical”). Thinking back to our jungle analogy, a path has now been cleared, allowing us to walk down it effortlessly, without any contribution from the conscious mind. Through practice, a new pathway has literally been carved in the brain.
The Purpose of Practice
So what might this have to do with playing “in the zone”?
Everything. Playing “in the zone” can only happen after these paths have been cleared, after we’ve built neural networks specific to the corresponding activity through effective practice.
The truth is, you enter the zone all the time, everyday. Walking down the street, brushing your teeth, driving a car, fixing a sandwich – these are all learned skills you can perform while your conscious mind is engaged in something else (we take these activities, complicated as they are, for granted, precisely because they feel so effortless). Each of these activities has its own pathway carved in the brain, a dedicated neural network containing its set of instructions, built and reinforced through years of experience.
Creating these neural pathways is the reason we practice. Which brings us to the second law of Brainjo:
Brainjo law 2: The primary purpose of practice is to provide your brain the data it needs to build a neural network.
The goal of practice is not to get better right then and there. The goal is to signal the brain that we want it to change, and provide it the inputs it needs to do so effectively.
But this raises a critical point. If our brain is building new networks based on the inputs we provide, then we need to ensure that we’re providing it with the right kinds of inputs, at the right time. The brain will build a network, a set of task specific instructions, based on any type of repeated input. Provide the wrong kind of input, and we end up with the wrong kind of network.
Practice a sloppy forward roll over and over again, for example, and guess what you’ll end up with?
A “sloppy-forward-roll” neural network, that’s what. You’ve successfully carved a path, but the problem is it leads to the wrong place.
Knowing When (and When Not) to Move On
In the beginning, the temptation is always to go too fast. We’re excited and eager to start picking some good music, and we want to play it now!
But the danger here in going too quickly is that you move to more advanced techniques before the basic ones they’re grounded in have fully developed, before those pathways, which serve as the foundation, have been laid. Rinse and repeat this process, and you end up with a bunch of networks that don’t do what you want them to do. The result is frustration, and the only remedy is to start over from scratch.
But what if there were a way we could know when those pathways were fully formed, a way to know when it was safe for us to move onward to the next hurdle? As it turns out, there is.
In neuroscience parlance, when a skill no longer requires our conscious mind for its execution, it is said to have become “automatic”. This can be tested for experimentally by having a subject perform the skill in question while their attention is diverted elsewhere. If there’s no decline in performance, then the skill meets the criteria for automaticity. If performance declines, then more practice is needed.
So if we want to test for automaticity ourselves, we can steal this same strategy, which brings us to the 3rd law of Brainjo:
Brainjo Law #3: Work on one new skill at a time until it becomes automatic.
Now, I know what you’re probably thinking: How do I tell if a skill has become automatic?
As I mentioned above, automaticity is tested for experimentally by having a subject perform a learned task while paying attention to something else. Is there a way, then, for us to test this for ourselves, without any fancy high-tech equipment?
You bet there is! In part two of this series, we’ll cover a foolproof and indispensable method for testing for automaticity.