The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning (22 page)

Read The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning Online

Authors: Daniel Bor

BOOK: The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning
7.59Mb size Format: txt, pdf, ePub
Not only this, but there’s evidence that we actually see things more vibrantly, too, under the amplifying power of attention. If you attend to the location where a clearly visible object is about to appear, that object will be perceived to have more contrast than if you are not attentionally preparing for it to turn up at that location.
Attention, then, clearly boosts awareness. It allows us to consciously see things that otherwise would have been too faint to detect, and it really does make things appear more vivid.
THE ATOMS OF THOUGHT
 
But how does attention filter and boost the incoming signal and shunt this output into awareness? Although this chapter is primarily a psychological one, insights about the mind can often gain clarity if examined in the context of corresponding brain processes. Attention definitely falls into this category.
While some key details are yet to be discovered, the generally accepted view of how attention works in the brain involves a certain kind of battle between neurons, with the direction of our attention emerging from the outcome of this collective neuronal war. In this situation, the parallels with biological natural selection are very apparent, although the winners and losers in this particular survival of the fittest aren’t organisms or even neurons—no neurons actually die in these fights. Instead, the clashes emerge a level above that of the neurons, with competing sources of information all jostling for finite attentional resources.
In order to explain this fierce neuronal competition in greater detail, I need to provide some background about how neurons interact to process information.
Journalists appear to fall over themselves to cover any result of the formula, “Scientists have discovered the brain region for X.” While mapping brain regions according to function does provide useful clues to how we think, and ultimately how we might be conscious, there can be a danger in mistaking a real model of the mechanism of thought for what sometimes appears little more than stamp collecting. But if such labels aren’t a sufficient explanation for how our thinking is put together, what is?
In 1961 the celebrated theoretical physicist Richard Feynman was asked to take over the introductory physics lectures at Caltech. As he was not particularly known for his interest in students, this was a slightly surprising request, but the Caltech physics lectures had become so antiquated and piecemeal, and Feynman’s didactic skills so renowned, that it seemed the natural choice. The result was the most famous student physics lectures—and subsequent textbooks—of all time:
The Feynman Lectures on Physics
. Toward the beginning of the very first lecture, Feynman told his packed class of fresh-faced undergraduates:
If, in some cataclysm, all of scientific knowledge were to be destroyed, and only one sentence passed on to the next generation of creatures, what statement would contain the most information in the fewest words? I believe it is the atomic hypothesis that
all things are made of atoms—little particles that move around in perpetual motion, attracting each other when they are a little distance apart, but repelling upon being squeezed into one another.
In that one sentence, you will see, there is an enormous amount of information about the world, if just a little imagination and thinking are applied.
 
In neuroscience, our atomic equivalent is the neuron, and the one neuroscientific sentence we might want to pass on to that next generation of creatures, before we all perished in that cataclysm, might be:
All conscious and unconscious mental processing equates to the electrical activity of vast collections of neurons—information-processing brain cells, each of which has a biological version of thousands of input and output wires connected to other neurons, thus allowing each neuron to influence, and be influenced by, the activity of many others
.
A single neuron is essentially a simple node in our biological computational network. It has a multitude of branches surrounding its cell body, each ending in a single wire that receives an input from another connected neuron. The neuron also has a long tail that splits up into many output wires, sometimes counted in the thousands, allowing it to send a signal out to an extensive selection of other neurons. The signal is usually a simple electrical firing at a standard voltage, so basically a binary code, with no firing being a 0 and firing being a 1. Almost all other neurons will be working with the same binary language. One more key fact: The wires between these neurons usually do not actually touch. Instead, when a neuron fires, it releases a small amount of a chemical known as a neurotransmitter in the gap between the wires, and it is this chemical signal that the other neuron picks up. There are many different types of such chemicals in the brain—some are designed to suppress activity, while others may enhance it.
Let’s expand on the e-mail analogy of Chapter 1 to illustrate certain features of this neural system: Say I am a manager in a large company, a Fortune 500 conglomerate. Because we’re so cutting-edge, we’ve done away with phones and rely exclusively on e-mail. As a result of this “enlightened” decision, I’m constantly deluged with e-mails. I cannot respond to every single one. So I set up a rule that if and only if I receive more than 100 e-mails on a particular topic (they
all
have the same topic of “FIRE,” or 1, but we’ll ignore this for the moment), then I will pass it on to everyone in my address book. It happens that I receive a lot of e-mails from one particular person, N. Uron. And I actually find myself frequently writing to him as well—strangely, he seems to be either active or twiddling his thumbs just when I am. It would therefore make sense to prioritize this closely similar employee’s e-mails above the others, and if I get an e-mail from him, class it as the same as 10 other people, so that I need fewer e-mails on a topic, if he’s one of the senders, before I decide to pass it on.
There are some times when I’m feeling rather less productive than others. If we all have to work nights, then I’m going to feel tired and resentful that I’m stuck in this damn office without overtime. At those times, I simply ignore half the e-mails I receive. So to get me bothered enough to forward some message, I’m going to have to receive it 200 times. And in the middle of the night, everyone else around me is exhausted, despondent, and not exactly glowing with company pride. So everyone becomes quieter at night, and messages tend to die soon after they are sent. On the other hand, in the morning, 20 minutes after the coffee break, we’re all buzzing and almost begging for some activity to latch onto. At these times, just fifty messages of the same topic, on average, will make me forward the information to those around me. And because everyone else is also buzzing, much information flows around the company building, at breakneck speed.
 
This analogy illustrates the flexibility in a network of neurons. A neuron will only fire if it receives a certain number of firing outputs from other neurons, but this number can be increased or decreased in the short term, depending on what signaling chemicals are used in the gaps between neurons (the tiredness of night versus the caffeine fueled morning). These chemicals normally flood large collections of neurons indiscriminately. And if two neurons co-fire frequently, this in itself will physically strengthen the connections between the neurons and make it more likely that they will fire together in the future (the regular e-mails between the narrator and N. Uron). This leads to the famous neuroscience dictum that “neurons that fire together, wire together” (this is known as Hebb’s law, after the pioneer of the computational study of networks of neurons). This easing of information transmission between similarly behaving connected neurons is thought to be the main microscopic mechanism for learning and memory.
If we learn, say, that the word “square” corresponds to the visual input of a square, the neurons that visually represent an object with four equal sides at right angles to each other are becoming e-mail friends with those that hear the sound “square”—they prioritize their e-mails between each other, or, in other words, the visual square population of neurons collectively strengthen their connections with the sound “square” neurons. If there is any location to this learning, it is in the enhanced sensitivity between these groups of neurons, enabling them to activate each other more easily.
When I was a first-year undergraduate, my intuition was that there may be one or a few neurons that recognized my grandmother’s face, another local set that recognized a hammer, and so on. I naively saw the brain rather like a gigantic group of filing cabinets, with familiar buildings, say, neatly placed in one filing cabinet and the plots of novels I’d read alphabetized in another.
When I was told that in fact information is distributed throughout a network of neurons, that it is encoded partly in the strengths of the connections
between
neurons in huge networks spanning millions of neurons, that it isn’t really localized at all, but is a pattern of activity, I found this account shocking. It is in some ways the single most difficult neuroscientific concept to accept, but because of the way evolution works, it can’t be any other way. This system of neurons learning by building links with other neurons in a distributed fashion is a framework that can start small, but scale up exponentially, while some filing-cabinet version of the brain could only be made with a prospective plan by some god, not by evolution. It may be that a nematode worm, with its minuscule network of 302 neurons, can only learn a handful of things in its few weeks of existence, while I, with my 85 billion neurons, can learn many thousands of facts in my set of decades—but we nevertheless closely share the same underlying neuronal mechanisms for information processing (these worms even use many of the same neurotransmitter chemicals that we do).
This apparently simple neural system allows for incredible flexibility, especially in its larger forms. Just as DNA is written in a language understood by all life on earth, this ubiquitous neuronal binary language is potentially understood by the whole brain, which, for instance, allows for the easy exchange of information between regions. This helps explain why ferret brains can be rewired so that the auditory cortex can start to “see” if given input from the eyes, and why the visual cortex in blind people can easily adapt to process Braille.
ATTENTION AS A BRUTAL NEURONAL WAR
 
The semi-chaotic activity of our 85 billion neurons undergoes a kind of temporary natural selection every moment of our waking lives, as attention shapes the contents of consciousness. Rival coalitions of neurons compete with one another to be heard the loudest. Those with the most powerful voice recruit others to their cause, and suppress any dissenters, until the strongest thought is carried by millions of neurons, all with one voice—for instance, to look for the black hair of your lover as she approaches down the street. Every time you have a new thought, that idea has become the dominant clan of your internal world, following a violent battle between jostling, screaming tribes.
To illustrate just how attention shapes consciousness at the neural level, let me return to the e-mail analogy: Now I mentioned before that I’m a manager in a large company. In point of fact, I happen to work within the security department, and it’s my job to see that certain unwanted types keep well clear of the office building. Each security executive specializes in a single color (there is a visual color-processing region in the human brain, known as V4, with individual neurons firing most strongly for specific colors). My color happens to be a particular shade of yellow. If the junior boys at the back of the building (primary visual cortex, the first cortical station from the eyes) send me an e-mail that they’ve spotted my own lovely shade of yellow on the street, then a few e-mails from them will get me jumping up and down in my seat. I want to tell everyone I know that
my
color is around, so I fire off my e-mails quick as a flash, with lots of exclamation marks at the end of each sentence. The guy in the cubicle next to me is responsible for the color black. Now if we
both
start sending e-mails madly that our colors are around, then the security guy a level above me, down the corridor, just needs one or two e-mails from us both together for all hell to break loose. You see, if he learns that both black and yellow are on the jackets of those outside from even a few e-mails, he sends high-priority e-mails to everyone he knows—and he knows some pretty senior people. (Further into the visual stream, for instance in the inferotemporal cortex in the temporal lobes, there are neurons that are responsive to combinations of features, or even specific objects, by the connections they’ve made with other neurons. In the neural equivalent of the current example, a wasp has been detected, and the person is allergic to them.)
Although people rarely listen to me, when the security manager responsible for yellow and black combinations sends e-mails about what he’s detected, they
always
listen to him. Everyone in the entire building passes on his information without question as soon as they get it. Thanks to a flurry of focused e-mails on the topic, all the security cameras swing to the sight of the spy, everyone discusses what to do with this enemy and what it might mean, and any guards outside get ready to move the interloper along, if need be. Almost immediately, absolutely the whole building knows about the spy, with his yellow and black clothes. The guys in my office who are responsible for any colors that aren’t yellow or black basically go for a break, as they know no one is going to listen to their e-mails for a while. I, for a change, become important, along with the guy sitting next to me who is responsible for black. Our e-mails are given priority—they are read first and acted on more often than not—as we report on the latest whereabouts of this probable spy to the security guy in the next corridor.

Other books

Magical Acts: (Skeleton Key) by Michele Bardsley, Skeleton Key
By Chance by Sasha Kay Riley
Heartbreaker by Linda Howard
Precocious by Joanna Barnard
Finding Cassie Crazy by Jaclyn Moriarty
June Calvin by The Dukes Desire
Flood Tide by Stella Whitelaw