If words have definitions, they have odd definitions

Last night, when the KU-Memphis NCAA basketball championship went into overtime, one of the announcers remarked, "Kansas knows what it's like to be in an overtime championship game."

This struck me as an odd statement, since they had mentioned only a few minutes ago that there hadn't been overtime in an NCAA basketball championship since 1997. A few moments later, we learned that the announcer was referring to a triple-overtime game in the 1950s.

The 1950s! There may have been some in the audience who remember that game, but I doubt anybody directly associated with the KU basketball team does.

You may be willing to view this as announcers spewing nonsense as they usually do, but it's actually an example of an incredibly odd feature of language (or, perhaps, of the way we think). Chomsky's favorite example is London, which has existed for a thousand years, during which nearly every pebble has been replaced. You could tear down London and rebuild it across the Thames a thousand years from now, and it would still be London.

More colloquially, there is a joke about an farmer who says, "This is an excellent hammer. I've had it for years. I've only had to replace the head three times and the handle twice."

This problem applies to people as well. It turns out (I don't remember where I read this, unfortunately) that every molecule in your body is replaced every few years, such that nothing that is in your body now was in it a decade ago. Yet you still believe you are the same person.

Clearly, humans are comfortable with the notion that the object remains constant even if all the parts change. This interestingly squares well with work in developmental psychology which suggests that infants recognize objects based on spatial cohesiveness (objects don't break apart and reform) and spatial continuity (objects don't disappear and reappear elsewhere). However, they are perfectly comfortable with objects that radically change shape -- for instance, from a duck into a truck. It isn't until about the time that children begin to speak that they expect ducks to stay ducks and trucks to stay trucks.

Publishing papers is slow

The bread and butter of scientific communication is the peer-reviewed journal. For those who are not familiar with the process, when a scientist (me for instance) wants to report some data, he writes it up and sends it to a journal. The editors of the journal ask a few other scientists who are experts in the same field to read the article and decide if it's any good.

This process has been criticized for being arbitrary and for being unable or unwilling to catch fraud. For all that, I honestly believe that peer review serves to improve the quality of papers. At least in psychology, it is rare for a journal to accept a paper on the first round. Instead, the reviewers suggest changes and additional experiments. Since they are experts in the field and bring a fresh eye to the problem, they often have good ideas.

There is one issue with peer review, however, that drives me nuts. That is how long the process takes. In January, a collaborator and I submitted short paper to a journal that promises extra-fast reviews of short papers. Three months later, we our expected rejection along with suggestions from the reviewers.

The thing is, in the three months that have passed, we've gotten busy with other things. I had to reread the paper a few times because I had forgotten all the details (for some reason, January feels like it was years ago). I spent the last week figuring out how to edit the experiment software, because it required some fancy programing that I had forgotten how to do.

Without further complaining, I'd like to announce the re-launch of The Video Experiment. If you have already participated (this is the only experiment I have ever run that involved a video), please do not participate in this version.* First of all, you'll be bored, because this is only a slight variation on the old experiment, and the video is the same. But more importantly, knowing what the experiment is about could affect your results.

That said, if you've never participated in the video experiment -- if you've never seen the "Bill et John" video or the "Kiwi" bird animation, you haven't participated -- please do so. It only takes 5-7 minutes, and it's easily the most entertaining experiment I've run online. Plus you get to see your own results at the end. With any luck, I can collect all the data we need within a few weeks, and then we can resubmit this paper.



*If you really want to participate, go ahead, but be sure to mark on the demographic form that you participated in the past.

Do words have definitions?

Defining a word is notoriously difficult. Try to explain the difference between hatred and enmity, or define chair in such a way that includes bean bag chairs but excludes stools.

This is an annoyance for lexicographers and a real headache for philosophers and psychologists. Several centuries ago, British philosophers like Hobbes worked out what seemed like a very reasonable theory that explained human knowledge and how we acquire it. However, this system is based on the idea that all words can be defined in terms of other words, except for a few basic words (like blue) which are defined in terms of sensations.

This difficulty led at least one well-known philosopher, Jerry Fodor, to declare that words cannot be defined in terms of other words because word meaning does not decompose into parts the way a motorcycle can be disassembled and reassembled. You can't define chair as an artifact with legs and a back created for sitting in because chair is not a sum of its parts. The problem with this theory is that it makes learning impossible. Fodor readily acknowledges that if he is correct, babies must be born with the concept airplane and video tape, and in fact all babies who have ever been born were born with every concept that ever has or ever will exist.

This seems unlikely, but Fodor is taken seriously partly because his arguments against definitions have been pretty convincing.

Ray Jackendoff, a linguist at Tufts University, argued in his recent Foundations of Knowledge, that words do in fact have definitions. However, those definitions themselves are not made up of words composed into sentences.

Observing (correctly) that one usually cannot find airtight definitions that work all of the time, Fodor concludes that word meanings cannot be decomposed. However, his notion of definition is the standard dictionary sort: a phrase that elucidates a word meaning. So what he has actually shown is that word meanings cannot be built by combining other word meanings, using the principles that also combine words into phrases. (p. 335)

That is, there are ways that words can be combined in sentences to achieve meaning that is greater than the sum of the meanings of the words (compare dog bites man to man bites dog). This is called phrasal semantics. Although linguists still haven't worked out all the rules of phrasal semantics, we know that there are rules, and that these allow for certain combinations and not others.

Jackendoff has proposed that a very different system (lexical semantics) using different rules is employed when we learn the meanings of new words by combining little bits of meaning (that themselves may not map directly on to any words).

I think that this is a very attractive theory, in that it explains why definitions have been so hard to formulate: we were using phrasal semantics, which is just not equipped for the task. However, he hasn't yet proven that words do have definitions in terms of lexical semantics. He has the sketch of a theory, but it's not yet complete.

Field psychology

Most psychology experiments are performed in a laboratory setting. This leads critics to wonder about their ecological validity: that is, just because somebody acts one way in the lab, do you know that is how they would act in real life.

There is another problem, summarized very nicely in a recent paper by Sugiyama and colleagues. In a footnote explaining some "oddities" in the results of their study of one of the world's most remote civilizations (the Shiwiar of the Amazon), they note:

Experimentation under field conditions injects higher levels of error variance into results than are obtainable under well-controlled laboratory conditions. More significant than factors such as added distractions, interruptions, and language difficulties is the extreme cultural strangeness of experimental testing itself, with its unfamiliar necessity of adhering to formal, abstract, and seemingly arbitrary behavioral and communicative constraints. Shiwiar subjects had no prior experience with experimental test-taking situations. This situation introduces confusion into the communicative pragmatics inherent in the task situation, and error variance into results. Restricting one's responses to the question explicitly asked, and ignoring information (such as who may be exhibiting generosity to whom) that is relevant to real life but not to a test problem, is a skill one learns in classrooms and courtrooms.

I have run into this in less exotic locales than the Amazon. As part of my ongoing study of reading, I have tested a number of native Chinese speakers who reside in the US -- mostly graduate students at Harvard. Even though these were smart, well-educated people, a number of them had great difficulty understanding how to do the experiment. Colleagues of mine who study visual perception have had similar difficulties when dealing with Chinese participants. The fact is that psychology experiments are relatively new and relatively rare in Asia, and so fewer people are familiar with what to do. No doubt we American scientists also design our experiments in ways that are culturally familiar to us (and thus not to the Chinese).


Sugiyama, L.S., Tooby, J., Cosmides, L. (2002). Cross-cultural evidence of cognitive adaptations for social exchange among the Shiwiar of Ecuadorian Amazonia. Proceedings of the National Academy of Sciences of the United States of America, 99(17), 11537-11542.

Who gets National Science Foundation fellowships?

The National Science Foundation awards around 900 graduate fellowships each year to a wide variety of sciences, including everything from linguistics and mathematics to physics. These fellowships are a big deal, being both very hard to get and making a significant impact on the finances of the awardees.

NSF has not yet officially contacted awardees for 2008, but word is spreading rapidly. Last night, some enterprising hopefully applicants hacked the NSF website to get the list of awardees. By morning, a number of applicants had logged on to the NSF applicant website and found an "accept fellowship" link on their applicant homepage. A little later in the morning, the list was made available on the website, though the page itself claimed that the awards list was still not available (that has now, as of this afternoon, been fixed).

So, which universities cleaned up? This is an incomplete survey of the 913 awards made:

Berkeley: 87
Stanford: 58
MIT: 40
Harvard: 36
University of Washington: 25
Cornell: 23
University of Michigan: 22
Princeton: 21
Columbia: 19
Yale: 18
UC-San Francisco: 17
Northwestern: 17
UT-Austin: 16
CalTech: 16
Rice: 14
University of Wisconsin-Madison: 13
University of Chicago: 12
Carnegie Mellon: 11
University of Florida: 11
Duke: 12
UCLA: 10

This doesn't list universities that got fewer awards, and it also doesn't account for 73 entering graduate students who did not list what university they will be attending, or any number of entering graduate students who haven't made up their minds and may switch universities. But it is a rough count.

What matters most, though, of the list, is that Oberlin beat Swarthmore 5 to 3.

The DaVinci stereogram

A few posts ago, I described how to make stereograms. At the end of the post, I showed a second type of stereogram, in which an illusionary white box appears to float in front of a background of Xs, and I promised to explain how that one was done.

This type of stereogram, discovered by Nakayama and colleagues, is called a "DaVinci stereogram" in honor of the famous artist/engineer who worked out the logic centuries ago (though he didn't, to my knowledge, consider building any stereograms).

The idea works like this: Look at an object (such as your computer monitor). Your left eye can
"see around" the left side of the object a bit more than can your right eye, while your right eye can see more of what is behind the object than can your left eye. It turns out that this information alone is sufficient to induce a perception of depth.









Consider that final stereogram (reproduced here). In both images, there is a white box in the center. However, the left image (the one presented to the right eye, if you use the divergence method) has four extra Xs on the right side of the box, while the right image (the one presented to the left eye) has two extra Xs on the left side of the box. This results in the perception of a white box floating above the background.

Getting a job in psychology

Several friends are applying to be research assistants in psychology labs this coming academic year and have been asking me advice. It occurred to me that there may be readers of this blog who are also interested in advice. With the caveat that this advice is based only on my experience and the experience of a few friends, here it goes.

First, if you are considering a PhD in experimental psychology (by which I mean not psychotherapy), I recommend spending some time as a research assistant (either during college or after) before applying to graduate school. There are at least three reasons:

1) You'll almost certainly get into a better school if you have research experience.

2) You'll have a better sense of what type of psychology you want to study, as well as whether you really want to do research at all. Many people quit PhD programs, or graduate and then decide to do something else.

3) You'll probably be more productive in graduate school, because you'll come in with some valuable skills. This may help you get a leg up on the competition (or possibly prevent them from having a leg up on you).

Of course, many brilliant psychologists started graduate school with little or no background in psychology, much less research experience. Einstein got bad grades in math, but that doesn't mean getting bad grades in math is a recommended strategy for becoming a physics genius.

So where are research assistant positions advertised? I have no idea. I got every RA position I've had (5, counting 2 in high school) by contacting a professor directly and asking if they had an opening. But I have noticed that professors sometimes advertise open positions on their websites.

Finally, it seems like RA positions are usually filled between late February and early April. So if you are interested, now is the time to apply.


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PS If anybody else in the field has anything to add, please use the comments.

Calling all language learners

I looked at the calendar and realized that I have to present data from an experiment to the lab in a few week and to the department in about a month. I took a look, and I have nowhere near enough participants.

So if you have 5 minutes, please participate in this experiment. I've been running it for a while, so do be sure you haven't already participated. The experiment is called "Learning the names of things," and it involves listening to a person mention different objects. You have to figure out which object he is referring to. It's also the only experiment I've done which involves any sound.

You can find it here.

If you are wondering why I don't have enough participants, the answer is simple. There have actually been several versions of this experiment. The data from each version has been very helpful, but I haven't yet quite answered the question I set out to answer. Unfortunately, each version is similar enough to the older versions that it wouldn't be appropriate to test the same people over and over. If you previously participated and want to see what the new version looks like, you can do so, but do be sure to indicate that you have previously participated in the experiment when asked.

Should scientists drink beer?

Apparently not. The more beer you drink, the less you publish and the less your articles are cited...at least, if you are a Czech biologist.

Snake oil and Neuroscience

Readers of this blog know how I feel about neuroscience reporting (here, here and here). One consistent problem is that reporters enthusiastically relate findings that involve brain scans, while ignoring the original and groundbreaking behavioral work.

A truism in psychology, however, is to never trust your impressions of a situation. So often our intuitions (e.g., the average American wouldn't torture an innocent bystander to death just because someone in a lab coat told them to) turn out to be completely incorrect. So I was very happy to hear that a group at Yale actually tested the hypothesis that people will believe basic behavioral findings more (like the existence of cognitive dissonance) more if brain-related words are mentioned.

In brief, it appears that the average non-expert does, in fact, believe it more if there is a picture of the brain somewhere. However, students who have taken an introductory neuroscience class are not only immune to this effect, but they actually find explanations that include references to brain anatomy less compelling. So perhaps this research explains not only why the average reader (and reporter) likes the typical neuroscience reportage as why people like myself (and Dan Gilbert) dislike it.

Cognitive Daily has an excellent in-depth description of the article here.



Weisberg, D.S., Keil, F.C., Rawson, .J., Gray, J.R. (2008). The seductive allure of neuroscience explanations. Journal of Cognitive Neuroscience, 20(3), 470-477.

Monkey language -- better every year

For many years we've been saying that monkey calls were non-decompositional. That is, you can't break them into parts, each of which has its own meaning (as you can do with this sentence, for instance).

New research suggests that this monkey calls are more complex than we thought. Click here to learn more.

Try this at home: Make your own stereogram

Have you ever wanted to make your own 3D movie? Your own Magic Eye Stereogram? This post will teach you to create (and see) your own 3D images.

Magic Eye Stereograms are a relatively new technology, but they grew out of the classic stereograms created in 1838 by Charles Wheatstone. For those of you who don't know what a stereogram is, the word broadly refers to a 3D-like image produced by presenting different images to each eye.

The theory is pretty straight-forward. Focus on some object in your room (such as your computer). Now close one eye, then the other. The objects in your field of vision should shift relative to one another. The closer or father from you they are (relative to the object you are focusing on), the more they should shift.

When you look at a normal photograph (or the text on this screen), this difference is largely lost. The objects in the picture are in the same position relative to one another regardless of which eye you are looking through. However, if a clever engineer rigs up a device so as to show different images to each eye in a way that mimics what happens when you look at natural scenes, you will see the illusion of depth.

For instance, she might present the drawing below on the left to your right eye, and the drawing on the right to your left eye:










If the device is set up so that each picture is lined up perfectly with the other (for instance, if each is in the center of the field of vision of the appropriate eye), you would see the colored Xs in the center at different depths relative to one another. Why? The green X shifts the most between the two images, so you know it is either the closest or the farthest away. Importantly, because it's farther to the left in the image shown to the right eye, it must be closer than the blue or red Xs.

You can demonstrate this to yourself using a pencil. Hold a pencil perfectly vertical a foot or two in front of your face. It should still look vertical even if you look with only one eye. Now, tilt the pencil so that the bottom part points towards your chest (at about a 45 degree angle from the floor). Close your right eye and move the pencil to the right or the left until the pencil appears to be perfectly vertical. Now look at the pencil with your right eye instead. It should appear to slope down diagonally to the left. That is exactly what is happening in the pictures above.

A device that would fuse these two images for you isn't hard to make, but it's even easier to learn how to fuse them simply by crossing your eyes. There are two ways of crossing your eyes -- making them point inwards towards your nose, and making them point outwards. One way will make the green X closer; one will make it farther away. I'll describe how to use the first method, because it's the own I typically use.

Look at the two images and cross your eyes towards your nose. This should cause each of the images to double. What you want to do is turn those four images into three by causing the middle two to overlap. This takes some practice. Try focusing on the Xs that form the rectangular frames of the images. Make each of those Xs line up exactly with the corresponding X from the frame of the other image. If you do this, eventually the two images should fuse into a single image, and you will see the colored Xs in depth. One tip: I find this harder to do on a computer screen than in print, so you might try printing this out.

That is the basic technique. You should be able to make your own and play around with it to see what you can do. For instance, this example has a bar pointing up out of the page, but you can also make a bar point into the page. You also might try creating more complicated objects. If you want, you can send me any images you make (coglanglab_AT_gmail_DOT_com), and I will post them (you can try including them as comments, but that is tricky).

One final tip -- you'll need to use a font that has uniform spacing. Courier will work. Times will not.

Finally, here's another stereogram that uses a completely different principle. If you can fuse these images, you should see an illusory white box floating in front of a background of Xs. In a future post, I'll explain how to make these.

Sure faces are special, but why?

Faces are special. There appears to be a dedicated area of the brain for processing faces. Neonates just a day or two old prefer looking at pictures of faces to looking at non-faces.

This has led many researchers to claim humans are born with innate knowledge about faces. Others, however, have claimed that these data are not the result of nature so much as nurture. Pawan Sinha at MIT attached a video camera to his infant child and let the tape roll for a few hours. He found that faces were frequently the most salient objects in the baby's visual field, and (I'm working from memory of a talk here) also found that a computational algorithm could fairly easily learn to recognize faces. Similarly, a number of researchers have claimed that the brain area thought to be specialized for face detection is in fact simply involved in detecting any object for which one has expertise, and all humans are simply face experts.

Things have seemed to be at an impass, but today, Yoichi Sugita from AIST spoke at both Harvard and MIT. The abstract itself was enough to catch everybody's attention:

Infant monkeys were reared with no exposure to any faces for 12 months. Before being allowed to see a face, the monkeys showed preference for human- and monkey faces in photographs. They still preferred faces even when presented in reversed contrast. But, they did not show preference for faces presented in upside-down. After the deprivation period, the monkeys were exposed first to human faces for a week. Soon after, their preference changed drastically. They preferred upright human faces but lost preference for monkey faces. Furthermore, they lost preference for human faces presented in reversed contrast. These results indicate that the interrelated features of the face can be detected without experience, and that a face prototype develops abruptly when flesh faces are shown.

Just to parse this: the monkeys were raised individually without contact with other monkeys. They did have contact with a human caregiver who wore a mask that obstructed view of the face. The point about not preferring upside down faces is important, as this is a basic feature of face processing.

This seems pretty decisive evidence for an innate face module in the brain, though one that requires some tuning (the monkeys' face preferences evolved with experience). However, Sugita apparently noted during the talk -- I heard this second-hand -- that perhaps the monkeys in question did in fact have some experience with faces prior to the face preference test; they could have learned by touching their own faces. This strikes me as a stretch, since that doesn't explain why they would become face experts.

Music on the Brain (on TV)

A few weeks ago, our building had a fire alarm. A friend who works on another floor speculated that maybe it was all the heat from the lights and cameras in her PI's office that day.

"Who was interviewing him?" I asked.

"I don't know," she replied. "There's always somebody interviewing him."

Our 11th floor has fewer media stars, but last week it was crawling with reporters. A magazine reporter was there most of the week interviewing people (I still don't know what magazine). Even more exciting, though, was the NBC camera crew.

Click here for the clip.

As far as science reporting goes, I'm afraid I have to admit it's uninspiring. But it was fun to see my friends and colleagues on the nightly news, and it couldn't have happened to nicer people.

You like video games, but does your brain?

According to CBC in Canada:

Men are more rewarded by video games than women on a neural level, which explains why they're more likely to become addicted to them.

In other words, men like video games more because their brains like them more. Since only one's brain can like or dislike something, this could be rewritten: Men like video games more because they like video games more.

It's hard to blame CBC entirely for this one. I haven't tracked down the article itself, but the abstract remarks:

Males showed greater activation and functional connectivity compared to females in the mesocorticolimbic system... These gender differences may help explain why males are more attracted to, and more likely to become "hooked" on video games than females.

This is hard to parse, and given the authors work at Stanford Medical School, I'm inclined to give them the benefit of the doubt. However, the way this is phrased seems to have the natural order of investigation backwards. Men are more likely to be addicted to video games than are women. Given they show these particular brain differences during video game playing, we can make some intelligent guesses as to what those parts of the brain do.

Once we understand those parts of the brain much, much better than we do today, we may actually have a good structural model that explains this gender difference. That may be what the authors of the study meant, and they may spell this out in the full article. However, CBC's statement that men are more likely to get addicted to video games because they are "more rewarded on the neural level," is both repetitious and obvious.

See the original CBC article here.