The simplest concepts have the deepest roots. We can take this as a truism for a self-evident reason: Nothing is simple. When something is as simple to us as pouring water into a glass, even when upside down we understand that its inherent complexity is negated to our perception because we are extremely adept at performing it. It is only when we have to design an automata to perform this ‘simple’ task that we begin to realize the underlying level of complexity that remains, usually, hidden from view.
The same principle is applied to learning. To explain how we learn we have to resort to concepts and phraseology like “Hebbian engrams and cell assembly theory” and discuss Hebbian space and what lies beyond it for neural networks. The language is dense out of necessity. Learning requires structural and conceptual changes to take place in the brain in response to empirical behavior in the real world.
By looking at how the disrupted brain functions we hope to be better able to understand what it is that makes us learn faster and better. The evidence so far points to the reward centers in the brain that seem to guide so much of our motivation and activity.
Neuroscience points to the fact that everything we do is based upon emotion and learning is no exception here. The reason we are looking at how a learning brain functions is the same as to why we want to understand how brains function in general: it is only by understanding their workings that we can measure their effectiveness and device ways to improve them. Constant self-improvement is key not to just learning but also the creation of better social constructs such as educational establishments that function in better conditions and deliver recognizably better results.
We are, right this moment in our history, balancing on the point where we know that everything is connected but have yet to devise strategies and tactics that allow us to put this understanding to proper use. The paradox of our age is that we are only beginning to understand better how we function because we are having to learn how to create automata that operate like we do.
In creating self-learning neural networks and robots that need to navigate the real world via a decision-tree, we have to consider moments where we have failed to learn and examine how we can augment learning strategies (through, perhaps communal and associative learning theories) that better utilize the neural networks inside our head.
Reward circuits in the brain and a goal-orientated, model-based approach are key, apparently to controlling compulsive behaviors that can lead to addiction (including social media addiction). Self-regulation is key to controlling addictive behavior, achieving emotional regulation and making better decisions. Self-regulation is a really hard thing to do when we are on our own. It requires advanced situational awareness skills, critical thinking, an analytical mindset and a brain that has been trained to think differently.
Anyone who has ever taken up martial arts, ballet or tried to learn any type of dancing like, for instance, Psy’s Gangnam Style moves, will understand this process: We try things, awkwardly at first, making lost of mistakes and feeling foolish and then, as we persevere, we make fewer and fewer mistakes and become more certain in the way we move and, with practice, we finally get it.
While all this goes on in the physical world this is what goes on in the mental world behind our eyes: Our brain devises a goal-orientated approach towards a specific outcome (this is why our motivation is important). It then creates a model-based approach to learning where each complex sequence of physical moves that takes us towards the outcome we want to achieve is rewarded (and remembered) and each wrong one is deleted and forgotten. We learn, in other words, because our brain can make the right choices and forget the wrong ones. By the same token we will be unable to learn (or we will learn way slower) if we are unwilling to make mistakes and, in the case of physical moves, be willing to look stupid for a while.
The ability to embrace failure apparently also lies at the heart of progress and even when someone is a trained scientist there is no guarantee of using the brain right unless they are specifically trained to do so by understanding why it goes wrong.
The universe, life, our world and everything associated with it or us. Everything around us; is open to our questioning. Getting the answers we need demands that we don’t just ask the right questions but that we learn that alone we are limited, restricted, circumscribed, diminished. To our Aristotelian, intuitive selves, it runs against the grain to share our most prized thoughts and ideas with the crowd, to open ourselves to ridicule (perhaps), to openly share a question instead of intellectually bludgeoning everyone with a brilliant answer to a problem.
We have been Aristotelians, in the traditional sense of intuitive thinking, for a long time. We face unprecedented problems and incredibly complex questions. We can try to go round and round in circle sin our thinking or we can admit it is time we tried something different.
You, of course, have learnt all the right things and made the most important connections. Coffee is at hand and you are staring at a pile of yummy donuts, croissants, cookies and chocolate cake. Have an awesome Sunday, wherever you are.