7 Subconscious Brain Functions that promote Learning

I won’t tell you what you can actively do to be smarter, but I will tell you what the brain does for you. The brain is a complex learning machine. While you can deliberately learn by using strategies, I will share with you what happens behind the scenes. The brain has a few specialized subconscious (or unconscious, or implicit, or subterranean) processes that make it an efficient learning organism.

Understanding how your brain senses, perceives, comprehends, learns, applies, and uses information is the first step in tapping into your highest learning potential. Appreciate the amazing brain functions & processes that make you uniquely you.

Brain-based learning is all about utilizing the brain’s core learning mechanisms to improve the quality of learning. This article is a snippet of the whole system. We’ll first look at what these learning mechanisms do in the human brain. These principles can be hijacked for improved learning.

Note: I’m making a clear distinction between 2 perspectives on learning:

1. The processes involved in the brain which let you learn (default brain functions)
2. What you can do about learning efficiently (actionable insights)

This article is about the first point. For the second point, I have other articles on the best study techniques, mental modeling, inquiry-based learning, worst study techniques, best memorization techniques, and the best observation techniques that are based on sound evidence.

Let us begin.

Cross-sensory correspondence: The thing that binds sensory information together

The idea that each sense gives information to the brain and the brain interprets it is not exactly true. If you thought it is similar to how a camera takes a photo and the computer processes that light ‘data’ to form an image file, you are probably wrong. The brain does something very different using its 10+ senses.

Our senses unify and combine at many different places in the brain and help create a single percept (a unit of perceived stuff). This means that your senses are going to mix, and mingle, and no longer remain separate inputs of information. Furthermore, information from one sense influences the interpretation of another sense. For example, Coffee from a steel glass will taste different than the same coffee from a plastic glass; triangular food will taste saltier than rounded food.

Our senses cross-talk, influence each other, and extract commonalities between 2 or more things. As this literature is dense and is one of my favorite topics, here is a dedicated post explaining the concept with an experiment. This line of evidence says we have an abstract layer of perception (governed by a common neural circuit) that can equate features of one sense to another feature. For example, we can equate salty to a triangle and sweet to a circle. We can equate loud to bright and bass to dim lights. We can even equate a warm soup to social intimacy, so much so that a warm soup can counter loneliness.

This means 1 thing for learning – it enables us to have metaphors, one of the most powerful knowledge tools. As the complexity of what we equate from one sense to another increases, we develop deeper concepts and compare them to other things we know. This is how we get analogizes for better learning. For example, comparing the brain to the internet is only possible because what you have perceived about the brain can correspond to what you know about the internet.

Transfer effect: Learning ‘A’ helps learning ‘B’

When we learn any skill, over time, the brain forms a network of neural connections that are dedicated to that skill. This network represents the contents and the process of that skill. Each skill is then made up of smaller sub-skills and the brain, as usual, forms an abstract process to enable that skill. This abstract process is often transferable^[1] to other similar skills or sub-skills. That means, when you learn one, you transfer some of that learning to the new skill automatically, making a new skill easier to learn (or simply improve it). Think about how cycling transfers to motorbike learning. Because of this, I recommend learning new things even when you don’t need them: the transfer effect might just help you in your job or academics.

A related brain function for learning is neural reuse^[2]. Your brain can utilize the neural circuit representing one thing for another thing. Kinda like how metaphors and analogies help you understand a new concept in an abstract way.

Priming: The unconscious information which nudges you

Oh, I love this word and what it entails. We are creatures that are almost always primed with something. That means, we have already received some type of information that influences our future behavior, thoughts, and information collection! The advantage of this mechanism is that priming can be used to strengthen learning and help guide the direction of learning^[4] in very subtle yet powerful ways. While attention is an explicit conscious awareness of information, priming remains largely implicit^[5]. There is a wealth of influence from the world that guides your behavior via priming. Advertisements prime you, emotions prime you, conversations prime you, etc. Almost anything can prime you to do something.

One theory of priming is that the brain readily organizes everything you learn in a network like a cobweb. And to recall some information (like a fact), it travels this network through (through a process called spreading activation). So in this network, if you activate the concept of Mercedez, you are in a network region that closely relates to cars and then you are primed to think with a focus on cars. This network is multi-dimensional, each part of the network connects to related things on multiple levels: time of learning, meaning of the concept, examples, structural similarity, similarity in spelling and sound, etc. So activating any of these levels enables priming. So Mercedes primes cars and Silk primes Milk.

Ask someone to say Silk 10 times rapidly and then answer a question immediately: Silk Silk Silk Silk Silk Silk Silk Silk Silk Silk. What does a cow drink? They’ll say Milk. Silk primed Milk, and a Cow also primed Milk. The brain unconsciously uses priming while thinking until we override it with deliberate analysis.

Fun fact: Did you know that priming your brain with new words while you sleep can improve your vocabulary usage?

Plasticity: Learning via structural and functional changes in the brain

The brain is very good at making sense of most information at the conceptual level. A testament to this is that any person can develop an intuitive sense and good judgment about any topic. How do you think that happens? The brain does it for you automatically. Learning means the brain modified its activity pattern, connections between neurons, or used neurons. This is why it’s called neuroplasticity – plastic means to be changeable.

Good learning takes place when you optimize your surroundings, get sufficient REM sleep, and take information in small meaningful chunks. Of course, there are many more factors like diet, hygiene, genetics, motivation, etc. but we’ll focus on the cognitive side of learning. The brain can adapt and learn by forming new neural connections up until old age. The plastic nature of the brain to learn new concepts, priming, the transfer effect, and cross-sensory perception, helps the brain create robust mental ‘modules’. These learning factors improve productivity, creativity, and mental capacity in general. This trains your brain for the better.

Apart from being plastic, the brain has the ability to make neural ‘conversations’ faster by adding extra fatty layers called the myelin sheath^[6] on the nerve fibers called ‘axons’. Regular practice increases the amount of this myelin sheath, and this directly improves physical and cognitive skills by making them precise, faster, and energy efficient.

Feedback: Making adjustments to learn efficiently

This seems obvious, but humans need feedback on what is happening, it is an essential aspect of growth. Nay, it is the most essential aspect of growth. Without feedback of some sort, we are all hollow plastic humans standing in a dark room with nothing to interact with. Feedback can be rewarding^[7] like ‘good job, now aim slightly to the left,’ or it can be of a more implicit form^[8] — the sensory response you get from some action you do. Let’s say a kid throws a ball. The thrown ball lands somewhere and the kid gets feedback on it through vision. This feedback represents ‘what just happened’. Now, learning starts occurring in the brain, and the kid can throw the ball differently to get some different feedback.

Another example is typing on a keyboard. We get feedback on the screen in the form of letters. Feedback confirms that an action has occurred, it creates a comparison between the desired state of learning and the current state of learning. One can then use this feedback to incrementally attain the desired state. For example, while learning how to speak a new language, feedback from listening to your own voice recordings would benefit in producing the correct pronunciations.

When it comes to physical performance, feedback on the characteristics of performance improve learning^[9] more than feedback about the superficial result. That is, knowing the details of your performance including feedback on your methods and approach is better than only the result of your performance.

Variance: Errors, trying out, nuances, changes, imperfections… variety.

This goes hand in hand with feedback, but I’d like to address this separately. Variance addresses the core aspect of brain-based learning with respect to what you try out and how you try it out. Variation in examples and learning inputs dramatically improves the generalizability of your learning. If throwing a dart at a dartboard is what you want to learn, the variance can be increased by changing the position you are throwing it from, the force with which you throw it, and changing the body posture for throwing. When you try out all these variants of throwing the dart, your brain starts doing its computation by using all of this data to approximate the best way to throw the dart. Variation in what you are learning and the context in which you are learning can be even more useful if you have some prior knowledge^[10].

Apart from the unconscious processes that take place, variance adds valuable feedback that you can use to make an informed judgment about how you throw the dart. Variance is increasing the range of different trials that you undertake to learn something. A variety of trials adds a variety of errors. These errors further help in fine-tuning your game/skill. And, to top it off, trial and error with high variance is a recipe for creative learning. There is evidence that the brain demonstrates conscious as well as unconscious error-correcting mechanisms^[11] which help us judge performance and learn. However, the pathways for conscious error detection and correction are different from the pathways of unconscious error monitoring, but they work hand-in-hand to improve accuracy through feedback and adjustments.

The scientific method: A child’s strategy for learning

This is perhaps the most incredible method to acquire information. And then we are less intuitive about it as an adult where opinions and past learning overpower raw learning. The scientific method, while deliberate in science, is actually an intuitive approach for a child. You might not realize it, but you can hone this skill.

The scientific method is straightforward (with the risk of oversimplifying):

• Make observations
• Record observations
• Create hypotheses with your best guesstimate (philosophical razors can help to make theories)
• Use hypotheses to make predictions
  * If the prediction holds true, your hypotheses about what is happening have a fair chance of being correct, collect more data and test more hypotheses.
  * If the prediction fails, your hypotheses need revision. Go back to the first step.
• Use a concrete framework that is objective, logical, and verifiable through experiments to explain your hypotheses & observations.

These experiments are a gold mine in terms of learning. When we experiment, we automatically account for variance, feedback, trials & errors.

So when you want to learn how to code or want to learn how to behave yourself, you make observations as to how it is done; you record your observations; then hypothesize that when you follow suit, a particular outcome is expected; then you try it out a few times; and then see what happens. If the desired outcome is seen, you are good to go. If it isn’t, something went wrong, and you should go back to your observations and start again. These little steps aren’t really that tedious to apply in your day-to-day living, they become a way of thinking, a way of progressing. Ultimately, an automatic process – a habit.

We’ve looked at 7 factors that influence learning in the brain. These factors can help educators, learners, coaches, etc. use brain-based learning systems which hijack these functions for accelerated learning & growth.

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