Post No.: 0143
Continuing from Post No.: 0128 and our exploration into the topic of memory – when learning new things, new information will compete with and potentially push out existing information when it concerns our short-term or working memories; hence we can, on average, only store around seven discrete, random and unrelated items at the same time before we start to potentially push items out of our working memories. (A good tip is to therefore group those items into larger discrete groups e.g. if trying to memorise the string of numbers 75243644 – try to memorise them as 75, 24, 36 and 44 instead of 7, 5, 2, 4, 3, 6, 4 and 4.) Note that ‘working memory’ and ‘short-term memory’ are terms that are often used interchangeably, but our short-term memory is just the temporarily-stored material passively held in memory, whilst our working memory also involves the use, manipulation or organisation of such stored material held in memory.
However, our long-term memory works in kind of the opposite way – the more knowledge we have in a domain, the more ways our brains can link new information up with existing memories, and therefore the stronger those links become and the easier the understanding and retrieval of that information. So never worry about learning too much!
The more you learn, the more you’ll probably want to learn more and can learn more. The brain is a network of connections rather than a mere set of disconnected parts, and the more connections between neurons there are, the more one can make even more connections between ideas and concepts. It’s metaphorically like a scaffolding – where the more existing structure that is up, the more places there are to ‘hang on’ or link new pieces of structure onto it, and so forth.
Long-term memories are stored throughout the cortex as groups of neurons that are primed to fire together in the same pattern that created the original experience. A memory may even be encoded with redundancies so that if one ‘engram’ (memory trace) is lost, there are alternative pathways through which it may still be retrievable. Basically, the more neuronal links or connections involved in an experience or piece of knowledge there are, the more likely it’ll be retained in long-term memory and the less easily it’ll be forgotten. This can be achieved by repeating or revising something more often and/or having more sensory information or emotions involved in an experience (involving more of the senses is why those explosive science or practical hands-on experiments tend to be the most memorable lessons from school).
There doesn’t practically seem to be a capacity limit to long-term memory (or at least no one has apparently ever maxed out that limit yet), and long-term memories can potentially last a lifetime (unless one has a memory disorder). We can only physically fit a finite number of neurons and connections within a finite-sized cranium though, so it suggests there must be a physical limit. What probably more likely happens is that neurons involved in memory traces that don’t get fired in a long time will just get used for making new memories.
Now regarding cognitive processing ability rather than long-term memory capacity, it’s important to note that – unlike muscles, where stronger muscles show greater activation – more expertly brains (for a given task) will show lesser activation and more energy efficiency. When we train muscles, they tend to become larger, but when we train the brain, the regional activation seems to get smaller. Mastery therefore results in efficiency (a higher ‘signal-to-noise ratio’ in the brain – people with higher IQs tend to have fewer activated dendrites in the cerebral cortex when performing IQ tests). So it’s not the case that smarter brains work harder – they actually work less hard because they are more efficient at a given task. Simply, when we find a task difficult (e.g. our first driving lessons), we’ll use a lot of mental energy, but when we find a task easy (e.g. driving after many years of driving), we’ll use far less mental energy (this example of the progression from novice to relative mastery when driving also shows that all it often takes is practise to get better at a given task – so just keep at it and it’ll eventually get easier! It’s usually not the case of ‘those who can and those who can’t’ but ‘those who try again and persist and those who don’t’). Reaching the state of effortlessness requires putting in a lot of effort first. Meow!
The more you already know, the more easily you can associate new knowledge with existing knowledge to reinforce each other, form more robust memories (e.g. if asked to memorise the number ‘88’, it’d be easier to remember it if that number already meant something to you that you already knew, such as it’s your year of birth) or discover novel connections between them – for which creativity, imagination or originality is arguably the ability to discover novel connections between seemingly disparate concepts.
So to help something stick in your mind and improve your long-term memory – make a little effort to link it to your everyday experiences or to what you already know, think of an example or two of that thing, try to extend it by learning even more about it, and of course periodically revise and repeat it. Try taking knowledge that you’ve learnt in one context and apply it to another. Be active in any way you can in the encoding of the information into your long-term memory. Don’t be like a passive colander where the information seems to stick for a moment but then disappears again over a short amount of time – be like an active baker putting in the effort to use those ingredients to solidify them into a tasty cake! Getting enough sleep and exercise matters too.
It’s natural to try to hang new knowledge onto what we already know. For example, if one always believed in creationism, then discovering dinosaur skeletons from under the ground would likely lead one to believe that they were simply animals that didn’t fit on Noah’s Ark hence died with the flood. But the more and more we learn, the more we can explore other possibilities that could present stronger and more likely theories.
Modern neuroscience is still fairly young because many advanced brain-imaging technologies are only relatively new and some of the latest kit is also expensive for all neuroscientists to get to use to replicate and check studies; but that’ll improve over time. Maybe the overall takeaway is that the goal is to have more, but only highly efficient, neuronal connections, if simultaneously possible? (Time/effort and opportunity are probably the only barriers to being a ‘jack of all trades, master of all’?) Whatever the case and whatever’s happening inside the brain, the practical real-world implications remain the same – if you want to get smarter then learn more new things, as well as continually practise and revise some of the same things.