The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning (60 page)

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Authors: Daniel Bor

BOOK: The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning
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exploiting
 
hunger for
 
music and
 
searching for
 
self-organizing
 
toxic thought and
 
Subjectivity
 
Subliminal messages
 
Superstitious beliefs
 
Survival
 
machines
 
reproduction and
 
Synesthesia
 
 
Tammet, Daniel
 
Tang, Yi-Yuan
 
Technology
 
Telepathy, technological equivalent of
 
Temporal lobes
 
Terrace, Herbert
 
Thalamus
 
consciousness and
 
vegetative state and
 
Theories of consciousness
 
Thomas, Robert
 
Thought
 
aberrant/upsetting structures of
 
atoms of
 
brain and
 
complex
 
conscious
 
decisions and
 
experience without
 
higher-order
 
memory and
 
unconscious
 
Thought experiments.
See also
Philosophy
 
Tononi, Giulio
 
Tools, adaptive use of
 
Transcranial magnetic stimulation (TMS)
 
Turing’s Nemesis
 
Tversky, Amos
 
 
Unconsciousness
 
anesthesia and
 
automatic habits and
 
calculation and
 
cause and effect and
 
chunks and
 
consciousness and
 
control by
 
Self-consciousness
 
decision making and
 
information and
 
learning and
 
understanding and
 
Understanding
 
conscious
 
consciousness and
 
performance and
 
unconsciousness and
 
Unipolar depression.
See
Depression
 
 
Vegetative state.
See
Persistent Vegetative State
 
Vicary, James
 
Vision.
See also
Visual cortex
 
blindsight and
 
color
 
peripheral
 
Visual cortex
 
blindsight and
 
color-processing region (V4)
 
consciousness and
 
neurons and
 
 
Wallis, Terry
 
Waroquier, Laurent
 
Wechsler Intelligence Scales, IQ test
 
Weiskrantz, Larry
 
Wetware
 
“What Is It Like to Be a Bat?” (Nagel)
 
Wiener, Norbert
 
Wiltshire, Stephen
 
Wittgenstein, Ludwig
 
Woolf, Virginia
 
Working memory
 
ADHD and
 
analyzing/manipulating
 
attention and
 
boosting
 
capacity for
 
chunking and
 
consciousness and
 
diminished
 
flexible
 
information and
 
limits of
 
meditation and
 
objects of
 
overloading
 
prefrontal parietal network and
 
schizophrenia and
 
spatial
 
verbal
 
World Economic Forum
 
World Health Organization (WHO)
 
 
Yantis, Steven
 
 
Zeidan, Fadel
 
Zinacantecos babies/toddlers
 
Zolpidem
 
1
Throughout this book, I will assume that “awareness” and “consciousness” have the same meaning.
2
Actually, some blind humans do learn a form of echolocation sufficiently advanced, they claim, to distinguish between the front and back of a parked car. For an interesting article describing this, see “Echo Vision: The Man Who Sees with Sound,” by Daniel Kish, in the April 11, 2009, edition of the
New Scientist
.
3
A marginally more believable version of this philosophical argument is to keep the comparison within the same person. For instance, imagine that I had some bizarre surgery to rewire my color brain centers so that what I used to experience as red I now experience as blue and vice versa. But my objections still apply here. Even without any surgery, my perception of red today will not be my perception of red tomorrow: My experiential history and all the other senses and feelings that occur as I see red will be different each time, as my brain will be. So there is absolutely no hope for this much more radical surgical change.
4
Currently, every year computer “chatterboxes” compete for the Loebner Prize, which provides a forum for programs to attempt to pass the Turing Test, and convince a sufficient proportion of ordinary people that they are text-chatting to a human and not software. Every example of software to date has been an obvious simulation, not anything anyone would consider conscious. Nevertheless, these chatterboxes can maintain surprisingly realistic conversations, thanks to some very clever programming. To read more and try chatting to a few of the winners yourself, go to
www.loebner.net/Prizef/loebner-prize.html
.
5
That’s a 1 with 80 zeroes after it, or, in words, a hundred million trillion trillion trillion trillion trillion trillion. If we hadn’t put a limit on the sentence size, then the number of possible sentences would have been infinite.
6
Whether or not this is practicable, efforts to reach this goal are already underway. For instance, in one project, the mouse brain is being mapped at a resolution of 5 nanometers, which is sufficient to capture the detail of every cell in the brain. See
www.mcb.harvard.edu/lichtman/ATLUM/ATLUM_web.htm
.
7
This system is an amazingly powerful and efficient way of storing information, bearing marked similarities to conventional computers, despite the apparently meager alphabet of four letters. This may sound terribly limiting for an information processing device, but you can in principle code for an infinite variety of things with it. A standard computer can manage with just two options: a 1 and a 0. These two alternative digits can nevertheless represent huge quantities of different types of information, as long as the sequence of these 1’s and 0’s is long enough. If there’s just one digit, it can hold just two different possible pieces of information (2
1
—either a 1 or a 0). If I have two digits, that’s four possible pieces (2
2
—00, 01, 10, and 11). If I have ten digits, that’s increasing handsomely, to 1,024 possible states (2
10
—0000000000, 0000000001, 0000000010, and so on up to 1111111111). RNA (and DNA) works in a similar way, just with two extra number types in addition to 1 and 0. These four RNA possibilities could easily be labeled 0, 1, 2, and 3, but instead are commonly labeled A, G, C, and U to reflect the names of the actual chemical bases that these letters stand for. These are adenine, guanine, cytosine, and uracil. These are identical bases to DNA, except that the U (uracil) is a substitute for T (thymine) in DNA.
Why does this code utilize three letter words? A triplet sequence of any three letters allows for sixty-four (4
3
) different combinations, more than enough for each possible three-letter word to represent the twenty amino acids, while two-letter sequences would fall short at sixteen (4
2
) possibilities. That’s why DNA/RNA words to code for amino acids in the recipe for proteins are three letters long.
8
The human genome includes around 23,000 genes—making it far smaller than that of many other organisms and surprisingly minuscule compared to what you might expect for an organism that contains the most complex organ on the planet—the human brain. However, by using many clever techniques—one gene coding for many proteins, hierarchies of controlling genes, and so on—we make the most of our meager genetic lot. A better index of organism complexity than number of genes is probably the range of proteins that an organism makes—and on those terms we are indeed heavy hitters.
9
In actual fact, most animals have a second active form of internal evolution, via their immune systems. Because the range of parasites we face is vast, and their frequency is incredibly high, the risk of death from these invaders is very real. Therefore, we need an immune system that can cope with virtually any eventuality. The way our immune systems can “learn” to combat invaders is very similar to standard natural selection—or brain processes. The immune system creatively generates many alternative possibilities, has those alternatives interact with the pathogens, and then, when some particular possibility finds a match (i.e., it has learned something), the hypothesis that such enemies are around is classed as well founded, and this successful antibody effectively breeds, so that it becomes a prominent feature of the immune system itself.
10
This result has now been loudly amplified within popular culture, with newspaper articles written all over the world, including titles such as “Want to Make a Complicated Decision? Just Stop Thinking.” It also is the major theme of Malcolm Gladwell’s book
Blink: The Power of Thinking Without Thinking
, in which he argued that immediate instinctive decisions can often be superior to long deliberation.
11
Another reason, possibly, that Dijksterhuis’s study has lent itself so easily to media coverage is that it appears to explain our “eureka” moments, when flashes of insight seem to appear suddenly, as if by magic, from the darkest depths of our unconscious. But is that really how it is? If our insights were truly unconscious, all we’d need to do would be to frame a complex problem, then stick our pens on some clean white paper and let our unconscious minds take control. Of course, if we did this, we’d be left with a dense nest of random lines, and we’d certainly be no nearer to the solution. Instead, most sparks of insight require a heavy investment of conscious thought. We need to develop strategies for exploring the terrain of possibilities, we need painstakingly to try each worthy permutation of the multitude of parameters, and finally, we need to have sufficient
conscious
understanding of the field to know when we’ve actually arrived at the solution. It’s true that sometimes merely diverting ourselves, going for a walk, or having a nap seems somehow to dislodge our thoughts and make insights more likely. But is that because of the unbridled power of the unconscious, or instead because the break has allowed us to consciously take a fresh angle when we return to the problem?
12
These actions by the CIA and the U.S. government are themselves iconic examples of poor, knee-jerk decision making, and they emphasize how choice quality can be improved by pausing, deliberating carefully and consciously, and relying as much as possible on proper scientific data, such as peer-reviewed publications, with good evidence of effects being repeated in different labs.

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