“How many particles are there in the known universe?,” you ask. Particles… protons, neutrons, electrons… that make up the atoms that make up the molecules in the uh, known universe. Billions of galaxies holding billions of stars and, evidently, planetary systems.
Well, there are apparently about 10 to the 87th particles out there. Ten to the 87th power. Ten multiplied by itself 87 times. That doesn’t seem like such a large number at all, does it? Yes, if I used a small typeface I could type the number onto one line of this page. Check me on this if you’d like. Google it. Subject the question to Wikipedia. Ask a smart friend. I know it’s quite a thought to think.
"Oh the thinks you can think!
Think and wonder and dream
Far and wide as you dare.
When your thinks have run dry,
In the blink of an eye
There's another think there!
If you open your mind
Oh, the thinks you will find
Lining up to get loose
Oh, the thinks you can think.... "
Thoughts, by the way, are now observable to the naked eye using a new machine called the fMRI. We can watch as circuits of neurons in the brain to fire in an instant corresponding to a cognition, image, smell or feeling. Since we have a billion neurons in our brains, with each neuron capable of connecting via little connectors called dendrites to a thousand or so other neurons at a time, there is a large number of possible “Hebbian nets” -- neural circuits – that a person might experience. How large a number? A recent estimate indicates the number of possible neural circuits in one person’s brain to be, listen to this now, ten to the millionth power. That’s a 1 followed by a million zeros. Now, just imagine the number of possible thinks that can be thunk when people multiply themselves as members of groups, teams, and organizations!
Yes, in a way of thinking, our brains are larger than the known universe. But we as individuals , as you know, are quite small. Here is a picture of a portion of the universe measuring roughly 2 billion light years in the shape of a cube.
The points of light are galaxies. Scientists could not find anyone willing to stand back far enough to snap this picture, so they roughed it out using a computer model. This is about what it would look like, though, as I understand it.
Now look at the picture below. What do you guess this is?
No, this is not the known universe looking from the other side. This is a picture of a neuron making connections to other neurons in a human brain. Remember, neurons are tiny. Each of our brains contains a hundred billion of these.
Both the big and small slices of the universe shown above are examples of systems, or networks. Obviously, the universe of galaxies and stars bears more than a passing likeness to the inner world we all carry around with us. We have only just begun understanding how these marvelous Hebbian nets work. A few axioms have become clear, though. Here are a few attributes of neurons and neural networks:
A neuron is built for connectivity.
The interesting things that happen in the brain are characterized by vast webs of neurons firing simultaneously or in sequence. As noted, each neuron has numerous dendrites capable of hooking up with other neurons. A neuron working on its own could behave something like a light switch or a thermostat, but would otherwise seem fairly unintelligent and unimpressive to us. A network of neurons, though, provides us with the magic of our human experience. The depiction to the left shows the way neurons reach out to one another.
Individual neurons serve as hubs. Thousands of neighboring neurons may connect through a neuron as a means of reaching thousands more.
The picture to the left is familiar to us a hubbing system. This, of course, is the air traffic system of the North American continent. Bright sections in the picture, analogous to neurons, are the “hub cities” through which people may connect as they travel from their originating city to their airport of destination.
Neural networks are constantly being updated and renewed.
Neural connections show plasticity. New connections are constantly being forged. Much of this reorganization and renewal is accomplished by the active brain while our bodies sleep.
Redundancy is a natural characteristic of Hebbian nets. An impulse may travel through a myriad of possible routes or pathways in order to connect one area of the brain with another. This avoids the bottle-necking that is observed in more limited systems. For example, there is really only one road I can take to reach the airport from my house. If there is a traffic tie-up, I’m sunk. A more natural network of roads, by which I might reach the airport from a variety of routes, would allow me to leave my house later when I travel. I could rest assured that if there is blockage somewhere in the system, I can get through some other way.
The internet works this way, by the way. As I send you an email, small packets of digital information leave my computer, depart from my house and travel separately through a variety web of connections, and are recombined at your house.
The image just above, by the way, is a depiction of the system, or network, that we know as the internet. You can see form this that there are indeed a lot of pathways that might connect my house with yours.
Any given neuron may become a part of any number of “networks” or “webs” that we experience of mental events.
Typically neurons that fire together (in close temporal proximity), wire together. It's thought that networks (representing memories, beliefs, mental events) are represented by such "Hebbian nets" as they're called. Of course, that's just the current thinking and people are still debating it all the time.
The graphic to the left shows four fMRI views of a single mental event. A brainstorm of sorts.
The flavor of a given mental experiece appears to be determeinnted by the parts of the brian through which the Hebbian maps itself. For example, neuroscientist Jessica Payne confirms that "most lasting memories probably do have limbic connections that give them emotional flavor." (We'll examine the nature of the limbic system in a futur post.)
Use it or lose it.
We'll make this the final principle, for the moment. My initial hypothesis was that if a neuron doesn’t get much “action,” its effectiveness diminishes and will not be available for future networks. Dr. Payne writes, though, that it is "not the neuron itself necessarily, but any given concept probably. If you've learned some bit of obscure knowledge and never think about it, it's availability will become diminished and will be unable to be woven into other networks (i.e. you won't be able to build on the knowledge)."
* * * * *
Remember, the purpose of this blog is to examine the workings of the brain as a vehicle for understanding, in an anological or metaphorical sense, the workings of complex orgaizations. Future posts will flesh this out. As a preview, though, I'll leave you with the following graphic showing a human network.
*** If you read this far, thanks for your visit! Please click the button below to SHARE it with your LinkedIn followers. Thanks!