Seth’s blog

All excited about my two new reaction-time tests — one involving letter counting (if I see GADZ I type “2″), the other involving naming (if I see 8 I type “8″) — I did both of them in close succession this morning. Each has 4 blocks of 50 trials each. After the second test my left wrist hurt. Too much typing. Now I must reduce typing to a minimum for a few days.

Computer chip designers have a tradition of putting very tiny pictures on their chips. Often pictures of animals.

A cheetah:

A hummingbird:

A gallery.

The better they control their materials, the better the picture. More evidence that art = material science.

I am collecting more self-experimental data than ever before. Partly because I am excited by the prospect of doing food-brain experiments that take just a few days (measuring effects of flaxseed oil and other foods that last a few hours) and partly because I learned how to get R to respond to single keystrokes. (Via the command getGraphicsEvent. Thanks to Greg Snow at Intermountain Healthcare.) This allows for much better reaction-time experiments; no longer do I need to respond and then hit Enter. Because the new method uses graphic windows, I have much better stimulus control.

I converted my letter-counting test (how many ABCD’s in GDKM? for example) to use the new command. Because the new command is so wonderful, I also used it to make a new test involving naming: The task is to type “1″ when I see a 1, “2″ when I see a 2, and so on. With eight possible stimuli (1, 2, 3, 4, 7, 8, 9, 0) and eight possible answers, there should be few anticipation errors. Accuracy should be high. The task takes advantage of the fact that I have already learned to type “1″ when I see a 1, which means there should be less problem with slow learning curves — learning (getting faster) continuing for a long time. The experiments I want to do need a steady baseline.

After running into Greg Niemeyer a few days ago, I realized it would help if I made these tests more game-like — then they would be more fun. I’m not sure how to do this so I hope to talk to Greg about it.

Human experimental psychologists are in a most curious position. Their subject — the human brain — is obviously the most complicated thing studied by any science. Its components (neurons) are not only very numerous and densely-connected they are also very inaccessible. Moreover brains soak up their environments in a way that other objects of study do not. It isn’t impossible to do experiments, but it isn’t easy. You can’t keep a supply of humans in your lab, for example. The difficulty of human experimental psychology is the main reason I decided to study animal experimental psychology. But the complexity of the brain is not only a difficulty but also an advantage: It means there is the most to be learned.

It is also easy to argue that human experimental psychologists study the most important subject of any science. Advances in understanding the human brain go “straight to the bottom line” — namely, human welfare and happiness — in a way that is true for few other sciences. Mood disorders and learning problems — not to mention obesity and poor sleep — cause a huge amount of suffering. Brain dysfunction is behind all of them. Norman Temple and I have argued that the sort of low-tech vary-the-environment type of research done by experimental psychologists is the most likely to produce useful results.

Given such a task, human experimental psychologists are lucky to be able to use an unusual tool: self-experimentation. Self-experimentation makes it remarkably easy to study topics with practical value (as I have). Because our world is already built around requirements of the human brain, self-experimentation requires no special equipment, no laboratory, and can be done at almost no cost. No other science, except human nutrition, has anything like this.

But human experimental psychologists don’t do self-experimentation! (There are a few exceptions, such as psychophysics.) The standard arguments for the avoidance don’t withstand scrutiny. Standard argument #1: Experimenter bias. The experimenter’s expectations may influence the results. Rebuttal: The human experimental psychologists who say this don’t practice what they preach: They don’t run their experiments blinded. Very few psychology experiments are run blinded. Standards argument #2: Lack of generalizability. You don’t know how general the results will be. Rebuttal: Yes you do. Typical psychology experiments have on the order of 8 subjects. They can be so small and still get reliable results because all the subjects change in the same direction. This means that if you know how one subject has changed you can predict how the others will change. In other words, the whole history of human experimental psychology — tens of thousands of experiments, a vast amount of data — shows that yes, you can safely generalize from one subject.

Because the stated reasons for not doing self-experimentation are so easy to rebut, the actual reasons may have more to do with human nature. My guess is that they are some combination of: (a) Fear of being different — different from other psychologists (the who-goes-first problem) and, especially, different from scientists in other areas, few of whom can self-experiment. (b) Desire for prestige. A large grant, a large lab, and activities in which others follow your orders are inherently more prestige-enhancing than doing something all by yourself.

This is why human experimental psychology, as currently practiced, really is science with one hand behind your back. Too bad it matters so much.

Thanks to Saul Sternberg for a thought-provoking discussion.

The chocolates of Poco Dolce (which means “not too sweet”) have been named “top ten” in America by Saveur. One of Poco Dolce’s products is a bittersweet chocolate square with double-roasted almonds.

“Why double-roasted?” I asked Kathy Wiley, who makes the chocolates, at the San Francisco Chocolate Salon. Double roasting — roast, cool, roast again — produces a better flavor, she said. “Why not just roast them longer?” I asked. Because you are more likely to over-cook them. There are special ovens for roasting nuts but she doesn’t have one.

This is basic material science. Wiley wants to maximize the concentration of certain molecules (that produce a roasted almond flavor) while minimizing the concentration of other molecules (that produce a burnt flavor). By trial and error she has figured out how. She was able to do the trial and error — i.e., research — because her business is successful. Her business is successful in large part because of connoisseurship and gift rituals. People give her products as gifts.

I believe we have genetic tendencies toward connoisseurship and gift-giving holidays and rituals because, long ago, these tendencies supported research in material science. Pleasure from finely-made things and desire for gifts supported artists and artisans, who by trial and error learned better control of their materials. Poco Dolce is a latter-day example.