Why languages can't be learned

One of the most basic, essentially undisputed scientific facts about language -- and the one that tends to get the most interest from laypeople -- is that while learning a foreign language as an adult is very difficult, children learn their native languages with as much ease and proficiency as they learn to walk. This has led researchers such as Steven Pinker to call language learning an "instinct." In fact, this "instinct" is more than remarkable -- it's miraculous. On careful reflection it seems impossible to learn just a single word in any language, much less an entire vocabulary (and thus figuring out how we nonetheless all learned a language is a major area of research).

The paradox goes back to W. V. O. Quine (who, I'm proud to say, is a fellow Obie), who suggested this thought experiment: Suppose you are an anthropologist trying to learn the language of a new, previously undiscovered tribe. You are out in the field with a member of the tribe. Suddenly, a rabbit runs by. The tribesperson points and says, "Gavagai!"

What do you make of this? Most of us assume that "gavagai" means "rabbit," but consider the possibilities: "white," "moving whiteness," "Lo, food", "Let's go hunting", or even "there will be a storm tonight" (suppose this tribesperson is very superstitious). Of course, there are even more exotic possibilities: "Lo, a momentary rabbit-stage" or "Lo, undetached rabbit parts." Upon reflection, there are an infinite number of possibilities. Upon further reflection (trust me on this), you could never winnow away the possibilites and arrive at the meaning of "gavagai" ... that is, never unless you are making some assumptions about what the tribesman could mean (that is, if you assume definitions involving undetached rabbit parts are too unlikely to even consider).

Quine offered this thought experiment in a discussion about translation, but it clearly applies to the problems faced by any infant. To make matters worse, people rarely name objects in isolation -- parents don't say "bunny," they say "Look, see the bunny?" or "Look at that bunny go!"

Generally, it should be very clear that infants could not learn a language if they didn't make certain assumptions about which words meant what. One of the major areas of modern psycholinguistics is figuring out what those assumptions are and where do they come from (that is, are they innate or are they learned?).

Long-time readers know that the major focus of my research is on how people resolve ambiguity in language. My first web-based experiment on this topic has been running for a while. Last week I posted a new experiment. Participants hear sentences like "Show me the dax" and try to guess which of several new objects might be the "dax." As usual, I can't say much about the purpose of the experiment while it's still running, but participants who finish the experiment will get an explanation of the experiment and also will get to see their own results. You can try it by clicking here.

How does the brain read?

Reading is an important skill, so it's not surprising it gets a lot of attention from researchers. Reading is an ancient skill -- at least in some parts of the world -- but not so old that we don't know when it was invented (as opposed to, for instance, basic arithmetic). And, unlike language, it appeared recently enough in most of the world that it's unlikely that evolution has had time to select for reading skill...which would explain the high prevalence of dyslexia.

Some decades ago, there was a considerable amount of debate over whether reading was phonologically based -- that is, "sounding out" is crucial (CAT -> /k/ + /{/ + /t/ -> /k{t/) -- or visual-recognition based -- that is, you simply recognize each words as a whole form (CAT -> /k{t/). People who favored the former theory emphasized phonics-based reading instruction, while the latter theory resulted in "whole language" training.

At least from where I sit, this debate has been largely resolved in favor of phonics. This isn't to say that skilled readers don't recognize some high-frequency words as whole, but it does mean that sounding out words it crucial at least in learning to read. One important piece of evidence is that "phonological awareness" -- the ability to figure out that CAT has 3 sounds by COLON has 5 or that DOG and BOG rhyme -- is just about the best predictor of reading success. That is, preschoolers who are at the bottom of the pack in terms of phonological awareness tend to in the future be at the bottom of the pack in learning to read.

At least, that is the story for writing systems like English that are alphabetic. There has been some question as to the role of phonology in learning to read character-based systems like Chinese. Two years ago, a group including Li Hai Tan of Hong Kong University presented evidence that in fact phonological awareness may not be particularly important in learning to read Chinese.

I have been trying to test one aspect of their theory for some time. Not having collaborators in China or Taiwan, I have to recruit my Chinese-speakers here in Cambridge, which is harder than you might think. The first experiment I ran took nearly six months, most of which was spent trying to recruit participants, and it was ultimately inconclusive. Last spring I piloted a Web-based version of the experiment, thinking that I might have more luck finding Chinese participants through the Internet. However, that experiment failed. I think it was too complicated and participants didn't understand what to do.

I have spent the last few months thinking the problem through, and now I have a new Web-based study. I am trying it in English first, and if it works well enough, I will write a Chinese version of the experiment. If you are interested, please try it out here.

Knowing the meanings of words

In “On the evolution of human motivation: the role of social prosthetic systems,” Stephen Kosslyn makes a very interesting conjecture about social interactions. He argues that, for a given person, “other people serve as prosthetic devices, filling in for lacks in an individual’s cognitive or emotional abilities.” This part seems hard to argue with. Intuitively, we all rely on other people to do certain things for us (mow our grass, edit our papers, provide us with love). His crucial insight is that “the ‘self’ becomes distributed over other people who function as long-term social prosthetic systems.”

You may or may not agree with that stronger claim. I haven't made up my own mind yet. I recommend reading the paper itself, which unfortunately is not available on his website but should be available in a decent college library.

There is one interesting application of his idea to an old problem in linguistics and philosophy.
What is the problem? Intuitively, we would like to believe that our words pick out things in the world (although words and concepts are not interchangeable, for the purposes of this discussion, they have the same problems). When I say “cows produce milk,” I like to believe that this sentence is either true or false in the world. For this to even be plausible, we have to assume that the words “cow” and “milk” refer to sets of real, physical objects.

This is problematic in myriads of ways. It is so full of paradoxes that Chomsky has tried to define away the problem by denying that words refer to anything in the world. I will focus on one particular problem that is relevant to the Kosslyn conjecture.

If you are like me, you know nothing about rare plants such as the three-seeded mercury or the Nova Scotia false-foxglove. Yet, we are able to have conversations about them. I can tell you that the both are endangered in the state of Maine, for instance. If I tell you that they both survive on pure Boron, you would probably be skeptical. Thus, we can talk about these plants and make empirical claims about them and learn new things about them without having any idea what these words actually pick out in the world. This is true of a large number of things we talk about on a daily basis. We talk about people we have never met and places we have never been.

What distinguishes these words from words that truly have no reference? To you, likely neither the words “Thistlewart” nor the word “Moonwart” mean anything. Now, suppose I tell you the first is a made-up plant, while the second is a real plant. To you, these are still both essentially empty words, except one refers to something in the world (though you don’t know what) and the other doesn’t.

Intuitively, what makes “Thistlewart” an empty concept and “Moonwart” not is that you believe there is some expert who really does know what a Moonwart is and could pick one out of a lineup. This “Expert Principle” has seemed unsatisfying to many philosophers, but within the context of the “social prosthetic system” theory, it seems quite at home. Certainly, it seems like it might at least inform some of these classic problems of reference and meaning.

Wait -- are you suggesting your brain affects your behavior?

One of my office-mates burst out laughing on Monday after receiving an email. The email was a forward, but it wasn't intended to be funny. It was a brief news blurb about a recent study looking at teenage impulsiveness, entitled "Teens' brains hold key to their impulsiveness."

What's funny about that? Well, where did the journalist think the key to impulsiveness was hidden -- in teens' kidneys? Many scientists puzzle over the fact that 150 years of biology have not driven out Creationism, but 150 years of psychology and neuroscience have been even less successful. Many people -- probably most -- still believe in mind/brain duality.

Philosophers began suggesting that all human behavior is caused by the physical body at least as early as Thomas Hobbes in the 1600s. A century and a half of psychology and neuroscience has found no evidence of an immaterial mind, and now the assumption that all behavior and thought is caused by the physical body underlies essentially all modern research. It's true that nobody has proved that immaterial minds do not exist, but similarly nobody has ever proved the nonexistence of anything. It just seems very unlikely.

This leads to an interesting dichotomy between cognitive scientists and the general public. While journalists get very excited about studies that prove some particular behavior is related to some particular part of the brain, many cognitive scientists find such studies to be colossal wastes of time and money. It would be like a physicist publishing a study entitled "Silicon falls when dropped." Maybe nobody ever tested to see whether silicon falls when dropped, but the outcome was never really in doubt. 

This isn't to say that the study I mentioned above wasn't a useful study. I have no doubt that it is a very useful study. Determining mechanistically what changes in what parts of the brain during development affect impulsiveness is very informative. The mere fact that the brain changes during development, and that this affects our behavior, is not.

Scientists arguing about the scientific method

The scientific method should be at least passingly familiar to most people who took a high school science class. Generate a hypothesis, then design an experiment that will either support or contradict your hypothesis. A more nuanced version is to find two competing hypotheses, then design an experiment that will unambiguously support at most one of those two hypotheses.

But is this what scientists actually do? Is it what scientists should do?

This question was put to us by Ken Nakayama in our first-year graduate psych seminar last week. Though it may surprise some of you, his answer was "no." In contrast to theory-driven research (the proposal above), Nakayama prefers data-driven research.

Although there are some good descriptions and defenses of theory-driven research, I don't know of one for data-driven research. Here's my best effort at describing the two.

Suppose you are a tinkerer who wants to know how a car works. If you are a theory-driven tinkerer, you would start with competing hypotheses (that tube over there connects the gas tank to the engine VS that tube over there is part of an air circulation system) and conduct experiments to tease those hypotheses apart. The theory-driven tinkerer will focus her energies on experiments that will best tease apart the most important theories, ignoring phenomena that aren't theoretically important. 

A data-driven tinkerer would say, "I wonder what happens if I do this," do it, and see what happened. That is, she may run experiments without having any hypotheses about the outcome, just to see what happens. If the data-driven tinkerer's attention is caught by some odd phenomenon (the car seems to run better in the afternoon than in the morning), she may pursue that phenomenon regardless of whether it seems theoretically interesting or helps distinguish between competing hypotheses. 

One potential reason to favor data-driven research is that while theory-driven research is constrained by our theories (which, at this stage in psychology and cognitive neuroscience, frankly aren't very good), while data-driven research is constrained only by your imagination and skill as an experimentalist. Data-driven exploration, one might argue, is more likely to lead to surprising discoveries, while theory-driven research is may only show you what you expected to see.

I suspect that most psychologists use some combination of the two strategies, though  when it comes time to write a paper, it seems to be easier to publish data that is relevant to theory (whether it was theory that led you to do the experiment in the first place is another question).

Thoughts?

How do children learn to count? Part 3

Two posts ago, I presented some rather odd data about the developmental trajectory of counting. It turns out children learn the meanings of number words in a rather odd fashion. In my last post, I described the "number" systems that are in place in animals and in infants before they learn to count. Today, I'll try to piece all this together to explain how children come to learn to be able to count.

Children first learn to map number words onto a more basic numerical system. They learn that "one" maps on to keeping track of a single object. After a while, they learn "two" maps onto keeping track of one object plus another object. Then they learn that "three" maps onto keeping track of one object plus another object plus another object. All this follows from the Wynn experiments I discussed two posts ago.

Up to this point, they've been learning the meanings of these words independently, but around this time they notice a pattern. They know a list of words ("one, two, three, four") and that this list always goes in the same order. They also notice that "two" means one more object than "one," and that "three" means one more object than "two." They put two and two together and figure out that "four" must mean one more object than "three," even though their memory systems at that age don't necessarily allow them to pay attention to four objects simultaneously. Having made this connection, figuring out "five," "six," etc., comes naturally.

So what is that more basic number system? One possibility is that children to learn to map the early number words onto the analog number system I also described in the last post (the system adults use to estimate number when we don't have time to count)?

Something like this claim has been made by a number of well-known researchers (Dehaene, Gallistel, Gelman and Wynn, to name a few). There are a number of a priori reasons Susan Carey of Harvard thinks this won't work, but even more important is the data.

As I described two posts ago, very young children can hand you one marble when asked, but hand you random numbers of marbles if asked for "two," "three" or any larger number. They always give you more than one, but they can't distinguish between the other numbers. Following Wynn, these are called "one-knowers." Slightly older children are "two-knowers," who can give you one or two marbles, but give you random amounts greater than 2 if asked for another other number. At the next stage, the child becomes a "three-knower." Usually, the next stage is being able to succeed on any number. I'll call those "counters."

Recently, LeCorre and Carey replicated this trajectory using cards with circles on them. They presented the children a card with some number of circles (1 to 8) and asked the kid, "How many?" One-knowers tended to reply "one" to a card with one circle, and then guessed incorrectly for just about everything else. Two-knowers could count one or two circles, but guessed incorrectly for all the other cards. Three-knowers could count up to three, but just guessed beyond that. Counters answered correctly on essentially all cards.

So far this doesn't tell us whether children learn to count by bootstrapping off of analog magnitudes or some other system. Carey and Mathieu LeCorre published a paper this year that seems to settle the question. The setup was exactly the same as in the last paper (now with cards with anywhere from 1 to 10 circles), except that this time the children were only briefly shown the card. They didn't have enough time to actually count "one, two, three..." The data for one-, two- and three-knowers didn't change, which isn't surprising. Both the "3-object" and the analog magnitude systems are very fast and shouldn't require explicit counting.

However, counters fell into two groups. One group, about 4.5 years old on average, answered just as adults. When they saw six circles, their answers averaged around "six." When they saw ten circles, their answers averaged around "ten." This is what you'd expect if they have mapped number words onto the analog magnitude system.

However, the other group, which was slightly younger (average age of 4 years, 1 month), guessed randomly for cards with 5 or more circles, just as if they didn't know how to count. However, these kids can count. If given time to look at the cards, they would have said the right number. So despite the fact that they can count, they do not seem to have their analog magnitude system mapped onto number words.

This means that the analog magnitude system isn't fundamental in learning how to count, and it actually takes some time for children to learn that mapping even after they've learned to count. Carey takes this as meaning that the analog magnitude system doesn't play a fundamental role in learning to count, either, and there are other reasons as well that this is probably the case.

One remaining possibility is that children use the "3-object system" to understanding the meanings of 1, 2 and 3. This seems to work nicely, given that the limits of the system (3 objects in children, 4 in adults) seem to explain why children can learn "one," "two," and "three" without really learning to count. Carey actually has a somewhat more nuanced explanation where children learn the meanings of "one," "two," and "three" the same may that quantifiers (like "a" in English) are learned. However, to the best of my knowledge, she doesn't have an account of how such quantifiers are learned, and if she had an account, I suspect it would itself hinge off of the 3-object system, anyway.

That's it for how children learn to count, unless I get enough comments asking for more details on any point. For those who want to read more, there are many papers on this subject at Carey's web page.

How do children learn to count? Part 2

In my last post, I showed that children learn the meaning of number words in a peculiar but systematic fashion. Today, I'll continue trying to explain this odd behavior.

Important to this story is that children (and non-human primates) are born with several primitive but useful numerical systems that are quite different from the natural number system (1, 2, 3, ...). They can't use these systems to count, but they may be useful in learning to count. In this post, I'll try to give a quick summary of how they work.

One is a basic system that can track about 3-4 objects at a time. This isn't a number system per se, just an ability to pay attention to a limited and discrete number of things, and it may or may not be related to similar limits in visual short-term memory.

You can see this in action by playing the following game with a baby under the age of 2. Show the baby two small boxes. Put a single graham cracker into one of the boxes. Then put, one at a time, two graham crackers into the other box. Assuming your baby likes graham crackers, she'll crawl to the box with two graham crackers. Interestingly, this won't work if you put two graham crackers in one box and four in the other. Then, the baby chooses between the boxes randomly. This is understood to happen because the need to represent 6 different objects all in memory simultaneously overloads the poor baby's brain, and she just loses track. (If you want to experience something similar, try to find a "multiple object tracking" demo with 5 or more objects. I wasn't able to find one, but you can try this series of demos to get a similar experience.)

On the other hand, there is the analog magnitude system. Infants and non-human animals have an ability to tell when there are "more" objects. This isn't exact. They can't tell 11 objects from 12. But they can handle ratios like 1:2. (The exact ratio depends on the animal and also where it is in maturity. We can distinguish smaller ratios than infants can.)

You can see this by using something similar to the graham cracker experiment. Infants like novelty. If you show them 2 balls, then 2 balls again, then 2 balls again, they will get bored. Then show them 4 balls. They suddenly get more interested and look longer. However, this won't happen if you show them 4 balls over and over, then show them 5. That ratio is too similar. (I'm not sure if you get this effect in the graham cracker experiment. I suspect you do, but I couldn't find a reference off-hand. The graham cracker experiment is more challenging for infants, so it's possible the results might be somewhat different.)

You can also try this with adults. Show them a picture with 20 balls, and ask them how many there are. Don't give them time to count. The answer will average around 20, but with a good deal of variation. They may say 18, 19, 21, 22, etc. If you give the adult enough time to count, they will almost certainly say "20."

Those are the two important prelinguistic "number" systems. In my next post, I'll try to piece all this information together.

How do children learn to count? Part 1

How do children learn to count? You could imagine that numbers are words, and children learn them like any other word. (Actually, this wouldn't help much, since we still don't really understand how children learn words, but it would neatly deflect the question.) However, it turns out that children learn to count in a bizarre fashion quite unlike how they learn about other words.

If you have a baby and a few years to spend, you can try this experiment at home. Every day, show you baby a bowl of marbles and ask her to give you one. Wait until your baby can do this. This actually takes some time, during which you'll either get nothing or maybe a handful of marbles.

Then, one day, between 24 and 30 months of age, your toddler will hand you a single marble. But ask for 2 marbles or 3 marbles, etc., your toddler will give you a handful. The number of marbles won't be systematically larger if you ask for 10 than if you ask for 2. This is particularly odd, because because by this age the child typically can recite the count list ("one, two, three, four...").

Keep trying this, and within 6-9 months, the child will start giving you 2 marbles when asked for, but still give a random handful when asked for 3 or 4 or 5, etc. Wait a bit longer, and the child will manage to give you 1, 2 or 3 when asked, but still fail for numbers greater than 3.

This doesn't continue forever, though. At around 3 years old, children suddenly are able to succeed when asked for any set of numbers. They can truly count. (This is work done by Karen Wynn some years ago, who is now a professor of psychology at Yale University.)


Of course, this is just a description of what children do. What causes this strange pattern of behavior? We seem to be, as a field, homing in on the answer, and in my next post I'll describe some new research that sheds light onto the question.

SNPs and genes for language

Modern genetic analyses have told us a great deal about many aspects of the human body and mind. However, genetics has been relatively slow in breaking into the study of language. As I have mentioned before, a few years ago resarchers reported that a damaged version of the gene FOXP2 was responsible for the language impairments in the KE family. This sounds more helpful than it really was, since it turns out that even some reptiles have versions of the FOXP2 gene. In humans, FOXP2 isn't just expressed in the brain -- it's expressed in the gut as well. This means that there is a lot more going on than just having FOXP2 or not.

Over the weekend, researchers presented new data at the Boston University Conference on Language Development that hones in on what, just exactly, FOXP2 does.

It turns out that there is a certain amount of variation in genes. One type of variation is a Single Nucleotide Polymorphism (SNP), which is a single base pair in a string of DNA that varies from animal to animal within a species. Some SNPs may have little or no effect. Others can have disastrous effects. Others are intermediate. The Human Genome Project simply cataloged genes. Scientists are still working on cataloging these variations. (This is the extent of my knowledge. If any geneticists are reading this and want to add more, please do.)

The paper at BUCLD, written by J. Bruce Tomblin and Jonathan Bjork of the University of Iowa and Morten H. Christiansen of Cornell University, looked at SNPs in FOXP2. They selected 6 for study in a population of normally developing adolescents and a population of language-impaired adolescents.

Two of the six SNPs under study correlated well with a test of procedural memory (strictly speaking, one correlation was only marginally statistically significant). One of these SNPs predicted better procedural memory function and was more common in language-normal adolescents; the other predicted worse procedural memory function and was more common in language-impaired adolescents.

At a mechanistic level, the next step will be understanding how the proteins created by these different versions of FOXP2 do. From my perspective, I'm excited to have further confirmation of the theory that procedural memory is important in language. More importantly, though, I think this study heralds a new, exciting line of research in the study of human language.

(You can read the abstract of the study here.)

Finding guinea pigs

One problem that confronts nearly every cognitive science researcher is attracting participants. This is less true perhaps for vision researchers, who can sometimes get away with testing only themselves and their coauthors, but it is definitely a problem for people who conduct Web-based research, which often needs hundreds or even thousands of participants.

Many researchers when they start conducting experiments on the Internet are tempted to offer rewards for participation. It's too difficult to pay everybody, so this is often done in the context of a lottery (1 person will win $100). This seems like an intuitive strategy, since we usually attract participants to our labs by offering money or making it a requirement for passing an introductory psychology course.

If you've been reading the Scienceblog.com top stories lately, you might have noticed a recent study by University of Florida researchers, which suggested that people -- well, UF undergrads -- are less likely to give accurate information to websites which offered rewards.

Although these data are in largely in the context of marketing, this suggests that using lotteries to attract research participants on the Web may actually be backfiring.

Are babies prejudiced?

In 1994, in discussing how children come to learn about inheritance, Susan Carey and Elizabeth Spelke wrote: "There are many ways children may come to resemble their parents: Curly-haired parents may have curly-haired children because they give them permanents; prejudiced parents may have prejudiced children because they taught them to be so. Such mechanisms are not part of a biological process of inheritance..."

It's not clear that Carey & Spelke thought prejudice is taught to children rather than inherited through genes, but it's interesting that in picking only two examples of non-biological inheritance, Carey & Spelke chose prejudice as one. What makes this quotation remarkable is how unremarkable it is. It seems quite natural to assume that prejudice is learned. Recently, however, a number of researchers -- including Spelke -- have been suggesting that although the specifics of a prejudice may come through experience, being prejudiced is innate.

(Just to be clear, nobody I know is saying that prejudice is natural, good, or something that cannot be overcome. The specific claim is that it isn't something you have to learn.)

It's actually been known for a few years that infants prefer to look at familiar-race faces. Very recently, Katherine Kinzler in the Spelke lab at Harvard has started looking at language prejudice. People can get very fired up about language. Think about the fights over bilingualism or ebonics in the US. Governments have actively pursued the extinction of various non-favored, minority languages.

In a long series of studies, Kinzler has found evidence that this prejudice against other languages and against speakers of other languages is innate. Young infants prefer to look at a person who previously spoke their language than somebody who spoke a foreign language. Infants show the same preference to somebody who speaks with their accent rather than with a foreign accent. Older infants (who can crawl), will crawl towards a toy offered by someone who speaks their language rather than towards a toy offered by a foreign-language speaker. Keep in mind that these infants probably do not understand what is being said. Also, the speakers are bilingual (the infants don't know this), which allows the experimenters to control for things like what the speakers look like. For instance, for some babies, one speaker speaks English and the other French, and for the other babies, they reverse. Also, French babies prefer French-speakers to English-speakers, while English babies prefer English-speakers to French-speakers.

Preschool children would rather be friends with somebody who speaks their own language, which is not surprising. They also prefer to be friends with somebody who uses their own accent rather than a foreign accent, even when they are able to understand what the foreign-accented child says.

Of course, none of this says that babies are born knowing which languages and accents to prefer. However, they seem to quickly work out which languages and accents are "in-group" and which are "out-group." This also doesn't say that linguistic prejudice cannot be overcome. For one thing, simply exposing children to many accents and language would presumably do much all by itself. Although it's not possible yet to rule out alternative explanations, what it does suggest is that prejudice -- at least, linguistic prejudice -- can't be overcome by simply not teaching it to children. They must be actively taught not to be prejudiced.

The paper, which is pretty easy to understand, is not available on the authors' website, but if you have a decent library:

Kinzler, Dupoux, Spelke. (2007). The native language of social cognition. Proceedings of the National Academy of Sciences, 104(30), 12577-12580.

Quantum Vision

Can quantum physics explain consciousness? The fact that the mind is instantiated in the physical brain has made it difficult for people to imagine how a physical object like the brain leads to conscious experience in similar ways that it becomes difficult to believe in free will. A number of people have hoped to find the solution in the indeterminacy of quantum physics.

There is a new hypothesis out from Efstratios Manousakis of Florida State University. The phenomenon that he is interested in understanding is binocular rivalry. In binocular rivalry, a different image is displayed to each of your eyes. Instead of seeing a mishmash of the two images, you tend to see one, then the other, then the first one again, ad infinitum. It's not possible to do a demonstration over the internet, but the experience is similar to looking at a Necker Cube, where you first see it popping out of the page, then receding from the page, then popping out, and so on. Notice that what your "eye" sees doesn't change. But your conscious experience does.

Manousakis has found that quantum waveform formulas describe this reasonably well. The question is whether they describe it well because the phenomenon is a quantum phenomenon or because there are two different phenomena for which the same formulas work. Keep in mind that binocular rivalry is something that can actually be seen with neuroimaging. That is, you can see the patterns in the brain change as the person first sees one image, then the other, etc. So if this is really a quantum effect, it is operating at a macro scale. New Scientist has an interesting article on this story this last week. It's not clear from the article if this is a problem Manousakis has thought about or not, and unfortunately his actual journal article isn't available on his website.

The neuroscience of theory of mind

The study of social cognition ("people thinking about people") and social neuroscience has exploded in the last few years. Much of energy -- but by no means all of it -- has focused on Theory of Mind.

"Theory of Mind" is something we are all assumed to have -- that is, we all have a theory that other people's actions are best explained by the fact that they have minds which contain wants, beliefs and desires. (One good reason for calling this a "theory" is that while we have evidence that other people have minds and that this governs their behavior, none of us actually has proof. And, in fact, some researchers have been claiming that, although we all have minds, those minds do not necessarily govern our behavior.)

Non-human animals and children under the age of 4 do not appear to have theory of mind, except in perhaps a very limited sense. This leads to the obvious question: what is different about human brains over the age of 4 that allows us to think about other people's thoughts, beliefs and desires?

It might seem like Theory of Mind is such a complex concept that it would be represented diffusely throughout the brain. However, in the last half-decade or so, neuroimaging studies have locked in on two different areas of the brain. One, explored by Jason Mitchell of Harvard, among others, is the medial prefrontal cortex (the prefrontal cortex is, essentially, in the front of your brain. "medial" means it is on the interior surface, where the two hemispheres face each other, rather than on the exterior surface, facing your skull). The other is the temporoparietal junction (where your parietal and temporal lobes meet), described first in neuroimaging by Rebecca Saxe of MIT and colleagues.

Not surprisingly, there is some debate about which of these brain areas is more important (this breaks down in the rather obvious way) and also what the two areas do. Mitchell and colleagues tend to favor some version of "simulation theory" -- the idea that people (at least in some situations) guess what somebody else might be thinking by implicitly putting themselves in the other person's shoes. Saxe does not.

Modulo that controversy, theory of mind has been tied to a couple fairly small and distinct brain regions. These results have been replicated a number of times now and seem to be robust. This opens up the possibility, among other things, of studying the cross-species variation in theory of mind, as well as the development of theory of mind as children reach their fourth birthdays.

Having solved the question of monkeys & humans, I move on to children and adults

Newborns are incredibly smart. They appear to either be born into the world knowing many different things (the difference between Dutch and Japanese, for instance), or they learn them in a blink of an eye. On the other hand, toddlers are blindingly stupid. Unlike infants, toddlers don't know that a ball can't roll through a solid wall. What is going on?

First, the evidence. Construct a ramp. Let a ball roll down the ramp until it hits a barrier (like a small wall). The ball will probably bounce a little and rest in front of the wall. Now let an infant watch this demonstration, but with a screen blocking the infant's view of the area around the barrier. That is, the infant sees the ball roll down a ramp and go behind a screen but not come out the other side. The infant can also see that there is barrier behind the screen. If you then lift the screen and show the ball resting beyond the barrier -- implying that the ball went through the solid barrier, the infant acts startled (specifically, the infant will look longer than if the ball was resting in front of the barrier as it should be).

Now, do a similar experiment with a toddler. The main difference is there are doors in the screen, one before the barrier and one after. The toddler watches the ball roll down the ramp, and their task is to open the correct door to pull out the ball. Toddlers cannot do this. They seem to guess randomly.

Here is another odd example. It's been known for many decades that three-year-olds do not understand false beliefs. One version of the task looks something like this. There are two boxes, one red and one green. They watch Elmo hide some candy in the red box and then leave. Cookie Monster comes by and takes the candy and moves it from the red box to the green box. Then Elmo returns. "Where," you ask the child, "is Elmo going to look for his candy?"

"In the green box," the child will reply. This has been taken as evidence that young children don't yet understand that other people have beliefs that can contradict reality. (Here's a related, more recent finding.)

However, Kristine Onishi and Renee Baillargeon showed in 2005 that 15-month-old infants can predict where Elmo will look, but instead of a verbal or pointing task, they just measured infant surprise (again, in terms of looking time). (Strictly speaking, they did not use "Elmo," but this isn't a major point.)

So why do infants succeed at these tasks -- and many others -- when you measure where they look, while toddlers are unable to perform verbal and pointing tasks that rely on the very same information?

One possibility is that toddlers lose an ability that they had as infants, though this seems bizarre and unlikely.

Another possibility I've heard is that the verbal and pointing tasks put greater demands on memory, executive functioning and other "difficult" processes that aren't required in the infant tasks. One piece of evidence is that the toddlers fail on the ball task described above even if you let them watch the ball go down the ramp, hit the wall and stop and then lower the curtain with two doors and make them "guess" which door the ball is behind.

A third possibility is something very similar to Marc Hauser's proposal for non-human primate thought. Children are born with many different cognitive systems, but only during development do they begin to link up, allowing the child to use information from one system in another system. This makes some intuitive sense, since we all know that even as adults, we can't always use all the information we have available. For instance, you may know perfectly well that if you don't put your keys in the same place every day, you won't be able to find them, put you still lose your keys anyway. Or you may know how to act at that fancy reception, but still goof up and make a fool of yourself.

Of course, as you can see from my examples, this last hypothesis may be hard to distinguish from the memory hypothesis. Thoughts?

How are monkeys and humans different (I mean, besides the tail)

Marc Hauser, one of a handful of professors to be tenured by Harvard University (most senior faculty come from other universities), has spent much of his career showing that non-human primates are smart. It is very dangerous to say "Only humans can do X," because Hauser will come along and prove that the cotton-top tamarin can do X as well. Newborn babies can tell Dutch from Japanese? Well, so can the tamarins.

For this reason, I have wondered what Hauser thinks really separates human cognition from that of other animals. He is well-known for a hypothesis that recursion is the crucial adaptation for language, but I'm never sure how wedded he is to that hypothesis, and certainly he can't think the ability to think recursively is all that separates human thought from tamarin thought.

Luckily for me, he gave a speech on just that topic at one of the weekly departmental lunches. Hopefully, he'll write a theory paper on this subject in the near future, if he hasn't already. In the meantime, I'll try to sketch the main point as best I understood it.

Hauser is interested in a paradox. In many ways, non-human primates look quite smart -- even the lowly tamarin. Cotton-top tamarins have been able to recognize fairly complex grammatical structures, yet they do not seem to use those abilities in the same ways we do -- for instance, they certainly don't use grammar.

In some situations, non-human primates seem to have a theory of mind (an understanding of the contents of another's mind). For instance, if a low-ranking primate (I forget the species, but I think this was with Chimpanzeees) sees two pieces of good food hidden and also sees that a high-ranking member of the troop can see where one piece was hidden but not the other, the low-ranking primate will high-tail it to the piece of food only he can see. That might seem reasonable. But contrast it with this situation: these primates also know how to beg for food from the researchers. What if primate is confronted with two researchers, one who has a cloth over her eyes and one who has a cloth over her ears. Does the primate know to beg only from the one who can see? No.

Similarly, certain birds can use deception to lure a predator away from their nest, but they never use that deceptive behavior in other contexts where it might seem very useful.

These are just three examples where various primates seem to be able to perform certain tasks, but only in certain contexts or modalities. Hauser proposes that part of what makes humans so smart are the interfaces between different parts of our brains. We can not only recognize statistical and rule-based regularities in our environment -- just like tamarins -- but we can also use that information to produce behavior with these same statistical and rule-based regularities. That is, we can learn and produce grammatical language. We can take something we learn in one context and use it in another. To use an analogy he didn't, our brains are an office full of computers after they have been efficiently networked. Monkey computer networks barely even have modems.

This same theory may also explain great deal of strange human infant behavior. More about that in the future.