The most beautiful of all the biological systems
May 25th, 2010
Week three in the neuroscience house. Well, lab. I just thought I’d tell you a bit about the project I’m doing, because quite a few people have been asking me what I’ve been up to. Truth is, I’ve not really known myself until fairly recently – it’s been a pretty sharp learning curve and I’ve not really had a chance to sit back and take things in. Sick of feeling like an absolute chimpanzee, having to be told everything, and not understanding why certain things are done the way they are, and what the whole damned point is anyway, I’ve not really been enjoying my project. However, after having a chat with one of the guys in the same lab, who explained step by nit-picking step with me, I finally feel a bit more comfortable.
Essentially, I’m looking at the actual events that take place that underlie learning and memory in the brain. As you know, the ability to learn and remember things declines quite markedly in old age, and this has been linked with a palpable change in cells of the brain – I’m looking at which molecules bring about this change. I guess you’re feeling a little bit lost; let me start at the beginning.
Brains are beautiful. Their complexity, magnificence and mystery have fascinated scientists for decades, and despite countless years and lifetimes of research, their secret workings still remain almost entirely elusive. Even at its most basic level, the brain is exquisitely complex. There are gross anatomical areas; each of which loosely controls a different function, or set of functions, and then within these areas there are smaller, but still discrete areas, which have their own circuits and interactions with other areas, and indeed, other parts of the brain. Smaller than these circuits, the very fundamental unit of the brain is the brain cell; the neurone, and it is the phenomenal complexity and precision with which these cells communicate with each other that permits us every movement, every action, every emotion; everything that makes us who and what we are.
Neurones are beautiful in their own right. Fascinatingly complex, beautifully simple, each has its own properties and role to play. The first time I saw a neurone – stained bright green – under a microscope, it literally took my breath away; I have never seen something so serene and beautiful.
So, how do they work? Neurones are loosely comprised a cell body, one or more long extensions known as axons, and lots of branches, called dendrites (I will add a picture if I can work out how...). A neurone is stimulated by a change in its VOLTAGE. This is a really beautiful mechanism, which I won’t explain here, but essentially this voltage change initiates a wave of electrical activity in the neurone, and this shoots down the axon at high speed. The axon of one cell typically makes contact with another neurone, and thus the cells can communicate with each other. When the impulse reaches the end of the axon, it reaches what is known as a SYNAPSE; a point where the axon of one cell comes into very close proximity with the cell body of another (they never touch, but come very very close). When the electrical impulse reaches the synapse, a neurotransmitter substance is released. This neurotransmitter then binds to its RECEPTORS on the second cell. This receptor binding causes another chain of events that causes the electrical impulse to be propagated in the SECOND cell.
So, to summarise:
It’s like a relay race. The first runner hears the stimulus, the gunshot, and he starts running as fast as he can. When he reaches the second runner, he passes over the baton, and the second then starts running as fast as he can. A cell is stimulated and fires an electrical impulse. The action potential shoots along the axon, and reaches a synapse with another cell. Neurotransmitter is released, and binds its receptors in the second cell. This triggers an impulse in the next cell, and so on, and so on.
This athletic analogy is very limited. Brains are complicated, man! Very complicated. I know how annoying it is when people do this, but I have to say that I have somewhat oversimplified this model. There are literally tens of different neurotransmitters which do different things, lots of different types of neurone with different dynamics, different transmission speeds, different strengths, different stimulus thresholds needed to fire.... They’re REALLY complicated. So you can imagine that the trillions of interactions of different neurones and networks of neurones with each other can (somehow) create enough computing power to carry out complex functions. We just have no idea how it does it!
One of the most mind-boggling functions of the brain is that, in the same way as a computer can, a brain can interpret integrate and interpret information, but it can also store information in the form of learning and memory. We still don’t really know how memory works at its most complex levels - why is it that I can remember what I did on my 6th birthday, but can’t remember where I put my keys when I got in? Why can I remember what I had for breakfast yesterday, but can’t remember what I had for dinner? Indeed, memory is a curious and compelling area of research, and at the moment our understanding is still sorely limited.
The current, most plausible paradigm for learning and memory concerns the STRENGTH of, and NUMBER of synapses in the brain (remember, synapses are the connections between neurones). By changing these two parameters, you can change the way that neurones behave, and by changing the way neurones behave on a long-term basis, you change the way the whole system behaves, and this is thought to underlie learning and memory.
Remember I said that a neurotransmitter binds to its receptors on the post-synaptic cell? Well, these receptors have everything to do with learning and memory – at least according to our current understanding. Loosely speaking, the more receptors that are at the synapse, the stronger and more sensitive that synapse is. Conversely, taking them away makes the synapse weaker.
If I’ve got a neurone, and I’m stimulating it with an electrical impulse, it will keep firing impulses until I stop stimulating it. If then, in the same cell, I suddenly start to stimulate it with a really high voltage, but without changing the frequency, the cell will recognise that the stimulus it is receiving must be quite important, and will change its activity accordingly. The cell puts PHYSICALLY MORE neurotransmitter receptors on the cell surface. This way, there are more receptors to respond to the stimulus, so the synapse becomes STRONGER. This is known as long term potentiation (LTP); a mechanism by which cells become more acutely wired to respond to a stimulus in future.
If you’re feeling a bit confused, think of this like the boy who cried wolf. If the boy were to run out of the woods and cry wolf once every two months, he might always get a response from the shepherd, who would put his sheep away. Yes? Say then, that suddenly two months later the whole of the local primary school run out of the woods and cry wolf – the shepherd is gunna think, “Ohh Man, this must be really important!”, and he will put away his sheep in double quick time. If this whole primary school were to continuously come out of the woods every 2 months and cry wolf, then very quickly, the shepherd might put in place some measures to make it easier for him to put the sheep away. He might build a closer pen, or he might buy some more sheepdogs. This is what the cell does with its receptors! It is a LONG-TERM, PALPABLE CHANGE IN CELL BEHAVIOUR.
Okay, now I’ve got another neurone, and I’m stimulating it again with an electrical impulse, and duly it is firing its action potentials. But then, I massively up the frequency, but not the amplitude of the impulse. The cell will call time out, and will take in some of receptors so that in future, it responds LESS STRONGLY to the same stimulus. This is long term depression (LTD).
Going back to my cute little analogy; if the boy who cried wolf suddenly started running out of the woods every day, instead of every two months, the shepherd would very quickly get fed up with it (On yer bike!!) and will stop responding to it, or will respond in a half-arsed manner. Now, this is also a long term, palpable change in behaviour, because now that the shepherd has been somewhat cheesed off, it’s going to take much more of a stimulus to get him to react in future. It might need all of the local primary school to cry wolf before he even reacts at all.
Okay, so now you’re at the cutting edge of what we understand about learning and memory. I’m not joking; we really don’t know much! My project is involved with looking at one aspect of LTD; dendritic spine shape.
Dendritic spines are these cute little structures also found on neurones which are the exact places where the cell RECEIVES a synapse from another cell – that’s where all the receptors are. Usually, they’re little mushroom-shaped knobs, but they vary, and THAT’S what I’m looking at.
Quite a marked change in shape and number of these spines can be seen in models of memory loss, so we’re interested in how that happens. It’s very complicated, but basically, the receptors are anchored to a scaffolding protein called actin, which keeps things nice and structured. Movement of this scaffolding protein is what allows the receptors to be added or removed from the cell surface, but it also causes CHANGES IN SPINE SHAPE. Now, specifically (you’re forgiven for being a bit lost at this point – it’s getting a bit hardcore) I’m looking at a protein called COFILIN, that is involved in the regulation of the way that actin moves.
I want to determine the PRECISE role that coflilin plays in the regulation of spine shape. How do I do that?! Well, I’m effectively messing around with cofilin in various different ways to see what the effects will be. Hopefully, HOPEFULLY, when I subsequently look at the neurones under the microscope, I will be able to see distinct changes in the shape of the spines, which will give me some idea about the role that cofilin plays. Well, that’s the plan, anyway – science is notorious for not working the way it should do! My task for the next few days is to analyse my results that I got last week: I’m counting dendritic spines until I’m blue in the face. Or green in the face, as it is, because they’re stained with Green-flourescent protein. I have a vague idea what I SHOULD see, but whether I will or not is another matter. Wish me luck!