I've added a category for brain stuff, so you can click below where it says "Brain" to read previous posts. Most recently, I mentioned the theory from the Red Queen, that human brains evolved via the battle of the sexes. Here's some fresh information on the issue, this time from the perspective of cooking.

Highlights:

• Human brains got bigger 2 million years ago, but there's no archaeological evidence of smarter humans until 150,000 years ago.
• "In most animals, the gut needs a lot of energy to grind out nourishment from food sources. But cooking, by breaking down fibers and making nutrients more readily available, is a way of processing food outside the body. Eating (mostly) cooked meals would have lessened the energy needs of our digestion systems, Khaitovich explained, thereby freeing up calories for our brains."

The battle between brain and gut for energy budget has been pointed to before; interesting to see it pop up again.

In The Red Queen, Matt Ridley popularized the theory that human intelligence is the byproduct of an evolutionary arms race of sexual selection. It goes something like this:

• fact: human brains are proportionately much larger than almost any other species, including any other primate
• fact: one proven catalyst for extreme evolutionary change is an arms race, where two sets of genes compete with all other things more or less equal. For example, a predator and its prey each get faster and faster, but relative to each other they stay competitive. This continues until all other things are no longer equal; e.g., the cost to be so fast can no longer be paid. For example, it is argued that humans and other primates pay for all of that metabolically expensive brain tissue with smaller digestive tracts, an tradeoff that clearly has limits.
• fact: sexual selection occurs, in which a trait which is not otherwise critical to fitness becomes attractive for purposes of attracting mates, leading to extreme exaggeration of that trait. Example: peacock tails.
• Theory: at some point displays of intelligence became important for proto-human males to attract females, and conversely female intelligence was required to select good male mates. This turned into an arms race, leading to dramatic increases in brain size, a byproduct of which was modern human intelligence.

This is not the only explanation for human brain size; social cooperation and language are also factors. Here's a more recent study which posits something similar: "... the balance of evidence now clearly favors the suggestion that it was the computational demands of living in large, complex societies that selected for large brains. However, recent analyses suggest that it may have been the particular demands of the more intense forms of pairbonding that was the critical factor."

Today's New York Times has an article about the search for genetic causes of schizophrenia, which is taking longer than expected because none of the big obvious causes pan out. Instead, it seems likely that "the genetic component of the disease is due to a large number of variants, each of which is very rare, rather than to a handful of common variants." What this means is that evolution has done a very good job of eliminating the big causes of (some kinds of) mental illness, leaving only lots of little things that aren't as simply selected for deletion. In other words, there is evolutionary pressure to have good brains. This is surprising to a lead researcher because "I would have thought the brain was a luxury organ when it comes to reproductive success."

I guess he's not current on the Red Queen and human sexual selection for brains. Chalk up a supporting point for Ridley's theory.

Although, an alternate explanation does occur to me. Perhaps we are being bred by brain-eating zombies for taste and flavor.

The second surprise was that the brain areas active in love are different from the areas activated in other emotional states, such as fear and anger. Parts of the brain that are love-bitten include the one responsible for gut feelings, and the ones which generate the euphoria induced by drugs such as cocaine. So the brains of people deeply in love do not look like those of people experiencing strong emotions, but instead like those of people snorting coke. Love, in other words, uses the neural mechanisms that are activated during the process of addiction. “We are literally addicted to love,” Dr Young observes. Like the prairie voles.

It's really hard to get good orange juice in Copenhagen. It's not that it's rare, it's just that there's lots of really awful orange juice and the packaging is very similar.

I bought a small white-board for my bathroom. It's something I've been thinking about for a long time, since I do much of my best thinking there. I suspect it's because of the relative sensory deprivation in a bathroom - there's just a lot less to distract the brain. So I got a white-board to mount on the wall to take notes. It paid off the very same day.

I was walking home with my new purchase and I had a great idea for the premise of a movie. I didn't have anywhere to write it down and although I was only five minutes from home, I knew that once I got in the door I would get distracted by the mail and dinner and probably lose all of my great ideas. Then I remembered I was carrying a whiteboard. I sat down on the bench under the next streetlight, unwrapped the board, and filled it completely with mad scribbling.

The next morning, I transcribed my notes to a computer and they seemed pretty stupid. Also, it turns out that whiteboards don't work in moist environments.

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They refinished the staircase at work. The building's almost a hundred and fifty years old, the staircase runs up six stories, and a very small elevator has been squeezed into what must have been a tidy little shaft around which the staircase climbs. For two weeks we had to take the back stairs or use the elevator. The elevator claims to hold three people, and technically three people can fit in it, but they can't all be tops.

I had a nice Thanksgiving, thank you. I inviting almost everybody I know in Copenhagen and their friends, which turned out to be almost a dozen people, and made about half of Tony's menu. The home-made tofurky was surprisingly simple to make and surprisingly tasty; three kilos of tofu and a marinade including miso and shitake. What sold it as good food, if not as turkey, was the gravy, which was superb. I don't really know how I made it because I was ad-libbing, but it did contain a ground-up pan-fried parnsnip. Who knew? Also, it was impossible to get any gourds other than zucchini, so I went ahead with a butternut squash soup recipe and, lo and behold, aside from being pale green instead of yellow, it tasted good in much the same way.

We (the company) went to Hamburg for two days for a coding bash to fix bugs in the open-source product we are working on. People came from as far as Munich and Berlin. I had a nice time because there were genuine nerds (Peter and Lars, despite being professional programmers, are not nerds, and they refuse even to feel bad about not being nerds). Timo noticed my totally cool Buffy hat sitting on a table (totally cool because it's cast-and-crew schwag I got via a Connection, not store-bought merchandise), which nobody ever does and so I often break down and point it out, which is stupid because if the other person didn't already notice it then they certainly won't care, and inquired of the room, "who hass de buhffy haht?" "Es ist mein Buffy hat!" I cheerfully replied.

And it was nice to be in Germany, where I'm at least 1% capable in the native language. On that note, Danish classes start next Monday, three hours each Monday, Wednesday, and Friday, and it's just in the nick of time. I've been in hermit mode, recovering from an overactively social summer and revelling in my first no-roommate, all-mine, more-than-three-months home in several years, but my ongoing laziness has made it a less productive hermitage than I had hoped. Relaxing, though.

Gerd Gigerenzer discusses risk and its applications in daily life, with examples from medicine, the O.J. Simpson trial and DNA testing in general, wife battering, AIDS counseling, and other fun avenues of life.

Executive Summary

The human brain has evolved several mechanisms that helped us survive in the African veldt but now hinder us from understanding our world. Our brains see in terms of certainties instead of chances - we round "unlikely" to never and "likely" to now. I can observe my own brain working this way, but the evolutionary benefit is not obvious to me and I would like to read more. We see patterns when there is noise. This could be a direct result of evolution: a bias towards false positives prevents catastrophe at the cost of paranoia, which is a perfectly good tradeoff for hominids who usually die by age twenty but is not so good for, say, rational stock trading. Or, this could be a side-effect of simply having powerful pattern-recognition mechanisms. We see cause and effect when it doesn't exist. And we think in terms of natural numbers, not percentages.

Two examples of our evolutionarily triggered false conclusions: (this part is not from the book). I read a true story (in another book about risk and math, I think) in which the narrator asked a bunch of senior military leaders how many generals were "great." They conferred and said, about five percent. He then asked, how many battles does one have to win in a row to be a great general. They answered, "five in a row." If the chance of winning a battle is 50%, then the chance of winning five in a row is 1/2^5, or 1 / (2*2*2*2*2), or 1 / 32, or about 3%. In other words, there's no reason to think the typical "great" general is anything other than lucky, at least not until they rack up a bigger lead over random chance. The other example was similar, and applied to sports. The chance that purely random performance - shooting baskets, getting hits - will read to streaks during the course of a season is easily calculated, and it turns out that many or even most streaks in most sports are as frequent as you would predict from random chance. In other words, most streaks are just random chance. Since our brains are geared to recognize patterns and attribute cause to effect, we falsely see that someone is performing especially well, probably because they ate their lucky pasta before the game.

Gigerenzer outlines a number of common statistical mistakes, and I'll repeat the interesting ones here, skipping boring ones like confusing a 50% chance of rain tomorrow with the expectation of 12 hours of rain.

Risks expressed as probabilities are less understandable than risks expressed as frequencies. Compare:

  The probability that an asymptomatic woman aged 40-50 in region X
  has breast cancer is 0.8 percent.  If a woman has breast cancer, the
  probably is 90 percent that she will have a positive mammogram.  If
  a woman does not have breast cancer, the probability is 7 percent
  that she will still have a postive mammogram.  Imagine a woman who
  has a positive mammogram.  What is the probability that she actually
  has breast cancer?

Write down your answer before proceeding to try the second question.

  Eight of every thousand women [aged 40-50 etc] have breast cancer.
  Of these eight with breast cancer, seven will have a positive
  mammogram.  Of the remaining 992 without breast cancer, about 70
  will have a (false) positive mammogram.  Imagine a sample of women
  with positive mammograms.  How many actually have breast cancer?

The correct answers are .008 / ((.008 * .9) + (.992 * .07)) = 0.104, and 8 / (7 + 70) = about one in ten.

It is the same problem expressed in two ways, and the second way is easier for most people. One thing that did confuse me in the book, though, is why Gigerenzer argues for physicians to use the second method instead of a third method:

  For every ten women with a positive mammogram, typically one
  actually has breast cancer.

It is then even easier to answer the question, "If you have a positive mammogram, what is the chance you actually have breast cancer?"

Expression of relative risks without a base rate. Example: Mammography screening starting at age 40 reduces the risk of death by breast cancer by 25%. This seems like a convincing case for screening. However, the overall chance of dying from breast cancer is actually quite low; screening reduces the risk of death from breast cancer in the next 10 years from 0.4% to 0.3%. Once the consequences of the high rate of false positives, from stress to unnecessary surgery, is accounted for, the case for mammography screening is slim, especially if the effort put into mammography screening could instead be put into finding the real killers (i.e., smoking, poor nutrition, and lack of exercise).

Prosecutor's fallacy, confusing the chance of a match with the chance that, given a match, the defendent is not guilty. This also involves ignoring the base rate: If your DNA matches DNA found at the scene with a one in a million chance of a false match, this does not mean that the chance that you are the real killer is 999,999 in a million. If the only evidence differentiating you from the other 10 million Los Angelenos is the DNA, then there are nine other people in LA who will match, and thus only a one in ten chance that you are the right match. (And this assumes that the other links in the chain are not broken - ie, no lab error, no planted evidence, no possibility that you were at the scene and left DNA before or after the crime, or during a crime you didn't commit.)

Given a Monty Hall situation, you should switch doors.