How expertise changes the way you see

When you know a lot about something, it doesn't just change how you think--it also changes how you see.

Stock image courtesy of RGBStock.

A long tradition in psychology, education, and business involves comparing people with little experience in an area to others with some amount of expertise (e.g., novice chess players vs. grandmasters, medical students vs. doctors).  Despite this two-group approach to studying it, expertise is actually a continuum, with "experts" in studies ranging from typical competent members of a profession (e.g., doctors) to world-class performers (e.g., chess grandmasters). When "experts" are trained in the lab to recognize artificial creatures1, the level of expertise is lower still--as few would volunteer to spend the famous "10,000 hours of practice"2 in a lab learning to categorize such items. Yet, even this sort of "expert" both thinks about and sees artificial creatures differently than people who have never seen them before. They haven't just memorized a set of images, either: this change in perception extends to members of the category that they have never seen before.

This shift in perception that comes with expert knowledge is called perceptual expertise. It is highly category-specific. For example, a car expert might display perceptual expertise when viewing modern cars but not antique ones, or vice versa3. Perceptual expertise is not limited to vision, but it has been studied less in other senses, so I will only talk about vision here.

Perceptual expertise affects many aspects of vision, including...

1) Memory for Visual Patterns
Many areas of expertise involve learning to recognize complex visual patterns. Chess is a great example. A chess grandmaster can look at an arrangement of pieces on the board and tell you who is attacking and who defending, what each player's likely next move will be, and perhaps even what famous games involved this arrangement. (Some arrangements, called "positions," are named). They are seeing not just the placement of each piece, but a meaningful whole defined by the relationship between them.

A series of classic studies by Chase, Simon, and Gobet demonstrated this elegantly by asking chess masters and ordinary players to remember the positions of a large number of pieces. These positions were either taken from actual master-level chess games, or were completely random (and often would never occur in an actual game). This experiment is shown in part B of the image below:
The image comes from this description of Chase, Simon, and Gobet's chess studies.

If chess experts are learning the meanings of configurations of pieces, then they should have an advantage over the novice players for real game positions, but not for random positions. And that's exactly what the studies found.

The research team also tested the working memory spans of both groups, and these were similar. So chess masters don't remember arrangements of chess pieces better than novices because they're better at keeping in mind large amounts of arbitrary information in general. Instead, they are able to group pieces with particular configurations into a meaningful "chunk" which can then be recalled as a unit, instead of 15 separate pieces.

2) Focus on the Whole Over the Parts
In chess, experts learn to recognize configurations across a set of objects. However, some domains of expertise lead experts to recognize configurations of parts within one object. This phenomenon was first studied in face perception (in which most people can be considered experts). However, it has since been noted in several other areas of expertise, such as cars. It should be found for any objects where the arrangement of parts is important for recognizing an object, but not for objects where specific features, like color or texture, are the defining ones4.

How do we know people are focusing on the relationship between an object's parts rather than the parts themselves? One way is to turn the object upside down. This disrupts the spatial relationship between the parts more than it disrupts the look of the parts themselves. As a result, experts are slower to recognize a specific object upside-down than they are when the same object is right-side-up. This disruption is called the "inversion effect."

Rossion and Curran4 examined the "inversion effect" in car experts, by showing them pictures of faces and cars that were either upright or inverted. Car expertise was determined not only by self-report, but by the ability to match 112 images of cars based on model. The faces served as a comparison condition. We know that inversion affects faces; the question was whether for car experts, inversion would also affect cars, and to a similar extent.

Above: face and car stimuli from Rossion & Curran (2010).

Interestingly, for novices, who have extensive familiarity with faces but less with cars, inversion reduced accuracy for both faces and cars. This is different than you might expect if expertise alone is responsible for inversion effects. However, it makes sense when you consider that even novices have often viewed cars right-side-up, but never upside-down.

For novices, inversion affected faces more than cars, both in terms of accuracy and reaction time. For experts, inversion reduced reaction time for both faces and cars similarly, and in fact, it non-significantly hurt performance for cars a bit more. Furthermore, the degree of expertise (ability to accurately match car models) correlated with the degree to which inversion slowed car identification.

This correlation is important. It makes it less likely that some random factor is responsible for the differences between experts and novices in car perception.  Given that expertise is a continuous phenomenon, it's also much more convincing to find that the amount of expertise correlates with the size of the inversion effect.

In short, just as most people learn to recognize upright faces by their configuration of features, so car experts had learned to recognize upright cars by theirs.

Other studies have found similar inversion effects with various objects of expertise, including artificial objects5, fingerprints6, chess boards7, and words8 . As in all areas of research, some studies have not found any significant effects9, perhaps because the categories of stimuli used were broader than the categories of objects participants were actually expert in. While these studies were part of a debate about whether faces are objects of extreme expertise or innately "special", that's not what makes them interesting. Whatever you think about faces, what matters is that developing expertise with recognizing other specific kinds of objects leads you to view them as a whole, not just as the sum of their parts.

3) Detecting and Recognizing Objects
We all know that people are good at recognizing objects that are important to them. Objects of expertise are important to experts, so it won't surprise you that they notice them better. For example, bird experts notice birds that to anyone else, might seem to blend into the background. (For a beautifully-written meditation on how expertise transforms the look of an ordinary city block, see On Looking: Eleven Walks with Expert Eyes by Alexandra Horowitz).

In the lab, you can show people a large number of objects, including objects of expertise and other common objects.  On some trials, you ask people to identify their object of expertise and on others, to pick out some other sort of object. Experts are faster and more accurate at finding objects of expertise than other sorts of objects. Novices find all sorts of objects equally well (all other things being equal).

Below is an example of this task from a study by Hershler and Hochstein10. Experts were car or bird experts, and control images were either faces or "other objects" (miscellaneous).

Unfortunately, I don't know of studies that investigate visual search in a naturalistic context, like a living room scene or a beach scene. The problem with arrays of objects like this one is that it's difficult to control variables like color, texture, and brightness for all objects or all arrays. But such variables can make some objects easier to find than others, regardless of what type of object they are. It gets even more complicated when you include some experts in living objects (like birds) and others in nonliving objects (like cars), since these likely differ in their low-level visual properties.  For this reason, I don't use (and don't plan to use) this sort of visual search task in my own research.

Other Perceptual Changes?
In the interests of completeness, I should note that a further, controversial set of studies on video games has suggested that some types of expertise may improve people's ability to quickly spread attention across large areas of space or multiple objects. Because these studies are less well-accepted, though, I will save discussion of them for a future post. However, I can safely conclude that the perceptual changes I've discussed in this post are the best established but not the only ones. We will likely discover more as we investigate further areas of expertise.

What we know...and what we still need to figure out
From birdwatching to chess, developing expertise seems to change how you see.

This basic principle seems to hold true across areas of expertise. However, different areas of expertise seem to impose different perceptual demands. For example, chess appears to improve perception of relationships between objects, leading to better pattern recognition, while car expertise improves perception of relationships between features within an object, leading to better object recognition.

Research groups tend to focus on one area of expertise in isolation, and then draw conclusions from their group of experts about expertise in general.  For expert knowledge, this works fine. The conclusions about problem-solving Michelene Chi drew about physics experts11 and young dinosaur experts12 seem to be accepted in domains as diverse as medical diagnosis and business leadership, as even a cursory Google search will indicate. However, perceptual expertise seems to be more domain-specific. Yet I know of no systematic examination of which areas of expertise will change perception in what ways. This is something I might work on during my PhD, so rather than speculate further, I'll simply note that this is an important problem to solve. Ideally, it would be possible to determine how any area of expertise changes how people see.


  1. Isabel Gauthier, Pepper Williams,  Michael J. Tarr, and James Tanaka (1998). Training "greeble" experts: A framework for studying expert object recognition processes. Vision Research 38:15-16, 2401-2428.
  2. K. Anders Ericsson, Ralf T. Krampe, and Clemens Tesch-Romer (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review vol. 100 iss. 3, 363-406. http://psycnet.apa.org/index.cfm?fa=search.displayRecord&uid=1993-40718-001 
  3. Cindy M. Bukach, W. Stewart Phillips, and Isabel Gauthier (2010). Limits of generalization between categories and implications for theories of category specificity. Attention, Perception, & Psychophysics vol. 72, iss. 7, 1865-1874.
  4. Bruno Rossion and Tim Curran (2010). Visual expertise with pictures of cars correlates with RT magnitude of the car inversion effect. Perception vol. 39, pp. 173-183.
  5. Isabel Gauthier and Michael J. Tarr (1997). Becoming a "Greeble" expert: Exploring mechanisms for face recognition. Vision Research vol. 37, iss. 12, 1673-1682. Open access! http://www.sciencedirect.com/science/article/pii/S0042698996002866
  6. Thomas A. Busey & John R. Vanderkolk (2005). Behavioral and electrophysiological evidence for configural processing in fingerprint experts. Vision Research vol. 45 iss. 4, 431-448. Open access paper: http://www.sciencedirect.com/science/article/pii/S0042698904004365  
  7. Merim Bilalic, Robert Langner, Rolf Ulrich, and Wolfgang Grodd (2011). Many faces of expertise: Fusiform face area in chess experts and nonvices. Journal of Neuroscience vol. 31 iss. 28, 10206-10214.
  8. Chien-Hui Kao, Der-Yow Chen, and Chien-Chung Chen (2010). The inversion effect in visual word form processing.  Cortex vol. 46 iss. 2, 217-230. http://www.sciencedirect.com/science/article/pii/S0010945209001427
  9. Rachel Robbins & Elinor McKone (2007). No face-like processing for objects-of-expertise in three behavioral tasks. Cognition vol. 103, 34-79. https://www.msu.edu/course/psy/802/altmann/802/Ch2-3-RobbinsMcKone07.pdf 
  10. Orit Hershler and Shaul Hochstein (2009). The importance of being expert: Top-down attentional control in visual search with photographs. Attention, Perception, & Psychophysics vol. 71 issue 7, pp. 1478-1486.
  11. Michelene T.H. Chi, Paul J. Feltovich, and Robert Glaser (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science vol. 5 iss. 2 121-152. http://onlinelibrary.wiley.com/doi/10.1207/s15516709cog0502_2/pdf 
  12. Camilla Gobbo and Michelene Chi (1986). How knowledge is structured and used by expert and novice children. Cognitive Development vol. 1 iss. 3, 221-237. http://www.sciencedirect.com/science/article/pii/S0885201486800028


Why we reason badly about people with DSM diagnoses, but why we should use these labels anyway

One extremely powerful aspect of human reasoning is our ability to draw inferences about members of a category. For example, let's say you've just learned that there is such a thing as an okapi, and it's a mammal. You will conclude that the okapi probably has fur or hair, has a heart, a brain, and a spinal cord, gives birth to live young, and feeds its babies with milk.With even greater biological knowledge, you can make inferences about the size and structure of its brain. Both kids and adults do this, and it's an incredibly powerful way of gaining at least tentative knowledge about something without ever having to see it.

Above: A mother and baby okapi, from here

Like most human abilities, though, it leads us astray in certain situations we create, just as most people's understanding of perspective, relative size, and color constancy leaves them prey to illusions, and neurotypicals' normally helpful tendency to perceive certain movements as intentional leads them to incorrectly ascribe intentional acts like "chasing" to animated shapes [link goes to a free full text paper, Castelli et al. 2002]. Here, the problem is a little more complicated, and it happens when we attempt to make inferences about people based on their diagnostic categories.

Let's say, for example, that a teacher is told a new student, Alex, has ADHD. The teacher may assume that Alex is male, hyperactive, will disrupt the class, will have difficulty with reading or math, will have a short attention span whether interested or not, will excel at multitasking but not focusing on a single thing, will think and talk too fast, and will benefit from stimulant medication. All these characteristics are true of some people with ADHD. However, Alex might turn out to be a girl with inattentive type ADHD who zones out instead of disrupting the class, excels academically (when interested), can focus for hours when interested, can focus on a single thing but not multitask, thinks, moves and talks slowly, and can't use stimulant medication because it gives her migraines and lessens her appetite to an unhealthy degree.  

Now, one might object that some of these incorrect inferences come from the teacher only knowing public stereotypes of ADHD, not the actual DSM definition. The equivalent in autism might be someone whose mental image of autism is a mix of Rain Man, Temple Grandin, and an Autism Speaks ad. 

But the problem persists even among people who focus strictly on DSM categories. For example, if a few years ago a clinician was told that a child has "autistic disorder" or "classic autism" rather than "PDD-NOS" or "Aspergers," they might assume the child lacked spoken language and communicative gestures, did not attempt to interact with others, did not engage in pretend play, walked on their toes and flapped their hands, made poor eye contact, had below average IQ, melted down frequently, and so on. But as there are 2361 combinations of characteristics that could lead to this diagnosis in DSM-IV, the child could just as easily speak fluently but reverse pronouns and have difficulty making requests, attempt to interact with others but be ignored, act out elaborate superhero stories on their own, make frequent eye contact, have average IQ but poor self-care skills, shut down rather than melt down, or spin in circles and twist their hair rather than toe walk and flap their hands. Similarly, a person with "high functioning autism" or "Aspergers" might not be a male "little professor" with better verbal than spatial skills, a love of facts over stories, good academic skills, and a muted affect. They could be a female, have better spatial than verbal skills, love creating imaginary worlds and telling stories, perform poorly in school, or appear overly emotional rather than unemotional. Even if the traits being assumed really are diagnostic traits and true of many people in the category, we will often be wrong if we assume them of any individual.

Below: From Jon Brock's blog, an example of 2 children with a DSM-IV autism diagnosis despite having no diagnostic characteristics in common.

This is one reason why we insidiously assume the same behavior must have different motivations in people with different diagnostic labels. For example, we assume inattention stems from boredom in a child labeled "gifted" and poor executive function in a child labeled "ADHD" when the former could also have poor executive function, and the latter could also be bored, or both could be inattentive for another, less stereotypical reason (e.g., the class is boring). We ascribe specific sorts of motivations to each diagnostic category and so when we see a behavior, like inattention, we reason from the category and forget to consider other possibilities.

Why are we led astray when we make assumptions about people based on diagnostic category, but not when we reason about the biological features of an unfamiliar animal? One reason might be that biological categories, like "mammals," are "natural kinds" where certain characteristics consistently cluster together for real reasons, whereas diagnostic categories are human-created, and the co-occurring characteristics selected developed historically from clinical observation of a set of people who happened to have those characteristics in common (e.g., Leo Kanner's and Hans Aspergers' cases for autism). However, we do not know why these people have these characteristics in common--are there common causes, as with mammals, is it pure coincidence, or are there cultural and historical reasons? As a result, human diagnostic categories are what I call "cluster concepts," while biological categories probably aren't, or are less so.

So what does all this imply for the debate over whether diagnosis is a good thing?

First, the obvious. Both ignorant and more knowledgeable people will make inaccurate inferences about someone with a diagnosis, and diagnosed people and their parents will continually have to combat these assumptions. 

Furthermore, the diagnosed person could start to make these sorts of assumptions about themselves. Or they might wonder if there's something wrong with them because they don't do something other people with the label often do. I've seen internet posts by people diagnosed with ASD wondering if there's something wrong with them because they don't, say, stim in certain ways. Or, people ask if knowing they're autistic led them to behave "more autistically." That's certainly possible, if one doesn't try to avoid stereotyping oneself.

So, does that mean it's better not to diagnose someone at all? I still think not, because whether a person is diagnosed or not, they are behaving in the same way, and looking just as different from the norm. Their differences will not be read as "normal," they will simply be assigned to a different set of "diagnostic" categories. Instead of a disability category, they might be assigned to categories like "lazy," "spoiled and badly parented," "doesn't care about other people," "stupid," "on drugs," and so on. I have yet to meet someone who would rather have their difficulties explained this way. To be honest, I think it's more psychologically damaging to view one's character as fundamentally flawed for things one can't help doing, despite one's best efforts, than it is to view oneself as having to cope with having difficulty doing things other people don't, or being naturally inclined to behave in ways most people don't like. Surprisingly, there's actually more room for agency with a disability label, because instead of being an irredeemably lousy human being, you have some weaknesses other people don't have that you can choose how to manage.

Rather than avoid diagnostic labels entirely, we should use them while understanding their limits and taking care to avoid making the same inferences from them that we would with biological categories.


Heterogeneous and sometimes opposite connectivity patterns in autistic brains

There's a method of looking at the brain, called "resting-state connectivity," a form of fMRI. fMRI indirectly estimates where areas of higher and lower brain activity are occurring. (Areas that are more active consume more glucose, and require more blood flow in order to supply them with that glucose. fMRI measures these changes in blood flow). "Connectivity" measures the co-occurrence of brain activity--which regions are active at the same time, and therefore might be working together. "Resting state" means that connectivity is being measured while a person sits still in the MRI machine, not doing any particular task. This is different from fMRI studies that look at "functional connectivity," which is the co-occurrence of activity while performing a specific task.

Resting-state activity can be hard to interpret and is still somewhat controversial. That's because people aren't doing anything in particular, they're just mind-wandering, or worrying about problems, or thinking how bored they are and wondering when the experiment will be over, or finding patterns in the scanner noise--or any number of other things. The experimenter has no control over what you're thinking or perceiving during a resting state experiment. What's amazing is that researchers can still find consistent brain networks during experiments like this. This might be because we habitually use our brains in certain ways while thinking, and these relationships exist even when we're not performing any particular task. It may also occur for mind-wandering in particular because mind-wandering is a task with its own brain network(s), just like other (better-defined) tasks.

Not surprisingly, a research group decided to compare resting-state connectivity in autistic and neurotypical adults. You can find an abstract here and a summary for non-scientists here. (The research team was Marlene Behrmann's group at Carnegie Mellon, which does a lot of autism research and is especially interested in perception). The group was trying to address conflicting results about whether autistic brains are "underconnected" or "overconnected." Some studies find less connectivity in autistic than neurotypical brains, others find greater connectivity. It's not clear whether the conflicting results come from different study methods, artifacts (i.e., autistic people move more in the scanner), heterogeneity in the autistic population, or some other factor. My personal theory was that in addition to heterogeneity, the explanation comes from connectivity in autism being atypically high in some brain areas or networks, and atypically low in others, and that furthermore the pattern varies based on what task a person is doing. So, whether you find overconnected or underconnected autistic brains depends on what you're having people do, and what parts of the brain you're looking at.

Behrmann's group specifically recruited autistic adults with IQ in the normal range, perhaps because this made it easier to explain the task and ensure participants stayed still in the scanner. They looked at connectivity both between the brain's left and right hemisphere, and within each of these hemispheres.

As I would have predicted, they found that some areas were more highly connected in the autistic group and other areas were less connected. 

But here's where it gets interesting: 

"Connectivity patterns were pretty similar between neurotypical participants. Their brains all looked roughly the same. By contrast, there was a LOT of variability in the ASD group. Connectivity patterns were 'idiosyncratic.'"

The boring part of this finding is that participants who were rated as having stronger "behavioral symptoms of ASD" also differed more from the normal "template." Well, of course, autism is by definition different than the norm, so we shouldn't be surprised when autistic brains differ from "average" brains, or even that more autistic people should have more divergent brains. The interesting result is that autistic brains were different from each other.

This image shows two brain scans which compare the extent of the voxel deviation in people with autism.

Above: Image from the described paper, accessed via the Neuroscience News writeup, which describes it as follows: "This image shows a comparison in the extent of the vowel deviation from the typical profile of two individuals with autism [a voxel is a 3d pixel that is the unit of measurement in an fMRI study]. The individual with the more severe autism symptoms (right) showed greater deviations, both positive (more red) and negative (lighter blue) from the typical inter-hemispheric connectivity pattern compared to the individual with the less severe autism symptoms (left)."

While in some cases the pattern is qualitatively similar in the two brains (e.g., increased connectivity in frontal areas and in ventral temporal areas), other regions show opposite patterns. For example, the area where the occipital lobe (back of the brain) meets the parietal lobe (top/back of the brain) has atypically low connectivity in the "less severe" brain on the left and atypically high connectivity in the "more severe" brain on the right. The same is true for the medial temporal region (just below the dark indentation in the middle of the brain).

This result seems like the neural flip side of a point Mel Baggs (Ballastexistenz/Withasmoothroundstone) often makes about behavior: for any trait you can think of, autistic people are often found at both extremes while neurotypical people are usually in the middle. You can find autistic people with extremely high and extremely low pain sensitivity, language ability, spatial ability, empathy, tendency to introspect, and so on. Not only are their abilities extreme and often opposite of each other, but so, it turns out, are their patterns of brain connectivity. We need to remember "heterogeneity" can mean not just "variable" but sometimes "opposite," both for behavior and brains.


What is joint attention, and are we defining it wrong?

Most humans have an important skill: the ability to share attention.  That is, they can pay attention to the same thing, knowing that the other person is also attending to and thinking about it.  The ability to share attention with another person enables all sorts of other activities, such as having a coherent conversation, or working together to put together a puzzle or construct a house.  It may even help babies learn language. When parents name an object in the environment, babies are more likely to understand the referent if they are paying attention to the same object as the parent.  Researchers call the act of sharing attention "joint attention." Not surprisingly, they find it to be an integral part of social and language development in neurotypical people.  They also find it to be delayed or absent in young autistic children, and theorize that this may cause all sorts of social and language delays.

When you define an important concept in psychology, you must decide how to measure it.  Psychologists who study social and language development have generally settled on one, highly specific definition. A person has joint attention if they can look back and forth between another person and an object, and lacks it if they cannot.  Notice that this definition focuses on only one sense (vision), and on a highly demanding motor skill: the ability to rapidly move one's eyes between two things.  

Above: A boy engages in joint attention with his mother under this definition. He looks at her, sees she's looking at the toy, looks at the toy, and understands that he and his mother are looking at the toy together.

The advantage of this definition is that it is a common way that people share attention (in the U.S., at least), and it's easily measured when you bring people into the lab.  The disadvantage is that when researchers start to identify this operationalization of joint attention with joint attention itself, they ignore the myriad other ways people can share attention.  This may not matter much when considering typical development, but it definitely matters when trying to explain why autistic people have trouble sharing attention.

Two researchers, Morton Ann Gernsbacher and Chen Yu, have written two very different critiques of why joint attention should not be considered synonymous with alternating eye gaze between another person and an object.  Morton Ann Gernsbacher's theoretical paper1 explains that such a theory of joint attention cannot explain how people share attention in many of the world's cultures.  Chen Yu's experimental study2 indicates even the typical research subjects, middle-class U.S. toddlers, rarely coordinate joint attention through alternating eye gaze, and instead do so through other means. 

Vision isn't the only way to share attention
Akhtar and Gernsbacher (2007) lay out a variety of other ways that children and parents in other cultures share attention.

In some cultures (e.g. Kaluli people in New Guinea, Palestinian families in Israel), babies are not only constantly held but are held facing outward, rather than face to face.  This can occur when babies are carried in the mother's arms, on her shoulders, on her back, or in her lap.  As a result, these babies get very little face-to-face experience with their caregivers compared to U.S. babies.

However, in such non-Western cultures, mothers interact with their babies less through eye contact and talking and more through touching and holding.  These babies' early social engagement occurs through other sensory modalities more than through vision.  Thus, one would expect shared attention to develop out of the other senses more than, or earlier then, it would develop out of vision.

When babies are held, they adjust to the movements of the person holding them, and they're sensitive to changes in posture very early in life.  Changes in the caregiver's posture can convey similar information to changes in their gaze direction--a caregiver is likely to lean towards something they are focused on or interested in.  Thus, babies in these low-eye-gaze cultures have access to the same information that U.S. babies get from eye gaze, but they get it from a different sensory modality.

In addition to postural changes, other tactile cues may be important for establishing shared attention.  If a child sits in his mother's lap while they both handle a toy, he can tell from her posture, touch, and hand movements that she is attending the same toy.

Blind children do not utterly lack the ability to share social engagement and attention with others, as would follow if joint attention were truly nothing but the alternation of visual attention.  Instead, they do so through nonvisual modalities instead.  Caregivers also provide tactile cues that direct the child's attention and cue them to engage in intentional communication.  They use touch to get the child's attention, either before signing in the child's visual field, or simply to maintain contact when one partner has looked away. 

In short:
"Although it is possible that gaze is the primary sense for typically developing, sighted infants in Western middle-class contexts, we cannot assume that gaze is primary without exploring other senses and other populations. By examining variations across cultures and across typical and atypical development, researchers may uncover multiple pathways to achieving social engagement and intentional understanding of others' behaviors."
Alternating gaze may not be the best measure of shared reference
Both Gernsbacher and Yu argue that even for sighted U.S. babies, gaze alternation may not be the best measure of shared attention.

To display joint attention, it's not enough to be looking at the same object as a parent.  A child must also gaze into the caregiver's face.  We've already seen one problem with this--that babies raised in other cultures with less eye contact will be unlikely to do so.  Another problem is that the child might look up at the caregiver for reasons other than trying to share attention.  They might be looking for comfort, if anxious in the unfamiliar laboratory setting.  Or, they might be looking for information, when confronted with odd and ambiguous laboratory toys.  

Furthermore, even U.S. babies who appear to be following eye gaze may not actually be doing so. Changes in gaze direction are usually accompanied by changes in head orientation, body posture, and voice direction, all of which come together to indicate the person's direction of attention.  Studies of joint attention that define joint attention as alternating eye gaze do not necessarily attempt to separate gaze cues from these other visual and auditory cues--which may be the truly informative ones for babies. 

Enter Chen Yu's study, which uses sophisticated real-time measures to determine how U.S. toddlers playing with their mothers really do share attention. These researchers have an innovative procedure: in addition to using overhead camera to provide a third-person view of their behavior, they have mothers and babies each wear head cameras with built-in eye-tracking equipment so that researchers can literally see the world from each participant's point of view.

Here's what the setup looked like:

They brought in seventeen 11-15 month olds and their parents for a play session in the laboratory. There were six toy objects at the table, displayed in sets of three, with which the pair could play freely. As seen above, the room was white and minimally distracting, which could be a strength or weakness of the study depending on your point of view.

Researchers measured frame by frame where the babies looked, where the parents looked, and when both shifted to look at a new object, which partner led and which one followed.  They suspected that social coordination would involve babies and parents looking at the same object at the same time. If one partner looks at a new object, to maintain coordination, the other will soon follow, but they might do so without making eye contact.

That was, in fact, what they found.  Babies and their parents frequently looked at the same object (about 33-42% of the time, depending on the measure), sharing over 23 bouts of joint attention per minute by one measure.  Yet babies rarely looked at their parent's face (about 5 times per minute), certainly not often enough to coordinate their looking behavior with parents.  Indeed, babies did not consistently look at a parent's face when following their gaze to an object. (It's important to note that babies and parents did look at each other's faces at times, just that this was rare and did not seem to relate to their coordinated looking at objects. Also, parents did frequently look at the child's face and used this cue to follow their child's attention. Children just didn't do the same with the parent).

So what cues were babies using to share attention with their parents?  Parents or babies were holding an object almost all the time, and hand cues overlap well with eye gaze cues.  Babies tended to look at the hands of whomever was acting on the object, whether that was themselves or their parent.
Above: Gaze and joint attention data from Yu & Smith (2013). a,b) Comparison of where child and parent were gazing, showing that both were often looking at the same thing; that parents looked at the face more than children did; and that children maintained gaze fixation longer than parents, overall (perhaps related to slower attention shifting in this age group). c) and d) are two different ways of measuring the synchrony between child and parent gaze. e) isn't important for the purposes of this post, but it compares the cross-recurrance of parent-child gaze to a random baseline, where the x axis represents time.
Why does it matter how we measure shared attention?
Since Simon Baron-Cohen proposed3 that autistic children's language delays stem from their inability to alternate joint attention between another person and an object, a line of autism research investigating the relationship has arisen, based on this assumption. But if joint attention is not identical with triangulated eye movements even in typical development, then our explanations for disabilities in autism rest on a faulty foundation.  If this misinformed research informs interventions, then much effort may be spent trying to teach triadic eye movements that may be painful, or even impossible for young autistic children (given their difficulties with rapid eye movements in general). Efforts would be better spent developing ways to teach language skills and desired social behavior using more accessible cues.

Stigma also arises when we assume that a person who cannot triangulate eye movements between a person and an object also cannot share attention with another person. From here, people often make the leap to claiming that autistic children cannot be emotionally engaged with others or realize that other people have mental states, too, which leads to viewing them as alien at best and sociopathic at worst. These conclusions do not follow, of course, but given the difficulty even researchers have with recognizing that, it may be best to emphasize the distinction between the ability to perform a particular pattern of eye movements and the ability to share attention.

Nameera Akhtar & Morton Ann Gernsbacher (2007). On privileging the role of gaze in infant social cognition. Child Development Perspectives 2, pp. 59-65.
Chen Yu & Linda Smith (2013). Joint attention without gaze following: Human infants and their parents coordinate visual attention to objects through eye-hand coordination. PLoS ONE 3, e79659.
Simon Baron-Cohen, Dare A. Baldwin, & Mary Crowson (1997). Do children with autism use the speaker's direction of gaze strategy to crack the code of language? Child Development 68, pp. 48-57.


What should a blogger do with their old posts when they change their mind?

I recently reread some old entries from 2009 and winced.  I still stand behind the main ideas of these posts, but would now express them very differently.

For one, my attitude towards autism and other disabilities has changed immensely since beginning this blog.  When I began, I was just starting to read both autism research and blogs by autistic people and their parents.  Although in the abstract, I thought of disabilities as traits that could be positive, negative, or neutral depending on the situation, I viewed autism in particular as entirely negative, as a source of disability only.  This perspective came from watching my brother struggle with the disabilities themselves, the way others treated him as a result, and the anxiety produced by both.  I saw his positive traits--his brilliant, independent mind, his sardonic humor, his sense of justice and compassion for others--as completely unrelated to autism.  They were just part of who he was.  But I didn't see autism that way.  As Zoe Gross would put it, I was still partially seeing autism as a sort of add-on, like the detachable cape on a Magneto action figure.  Granted, I was seeing it as an add-on that affected the way people perceive, move, think, and feel in various ways, but I still saw it as a basically negative add-on.  When I first started reading autism research (the first papers I read were from the Yale group), a lot of it rang false, and the coldly clinical writing style made me wonder if the writers knew and loved anyone autistic.  But the deficit-focus and deficit-language used didn't bother me yet--I just thought that they were focused on the wrong disabilities and were too far removed from the people they studied.

Then I learned more about the up-sides of autistic ways of perceiving and learning.  Autistic people can quickly hone in on details within a complex visual display.  They have reduced attentional blindness.  They can better perceive and appreciate pitch in music than most.  They can learn challenging skills like reading without being taught, often at a young age.  They're immune to various illusions, including the one where moving triangles appear to carry out intentional actions like "chasing." And it's not like these are anomalies unrelated to the disabling aspects of autism, either.  These positive traits are likely related to the traits that are disabilities.  A bias towards focusing on sensory details can be positive or negative depending on whether the situation demands perceiving the details (e.g., when drawing) or the configuration (e.g., when perceiving faces).  The ability to learn rapidly through self-teaching is the flip side of a difficulty learning from being taught by typical educational methods.  Lacking the neurotypical mind "bug" of perceiving everything as intentional could contribute to missing social cues.  And you can flip it the other way, too--disabling traits come with up-sides in the right situations and with the right support.  Thus, parents, teachers, clinicians, and researchers have an ethical imperative to seek out and build on the positive. 

So now, I would talk about autism very differently.  This poses a problem: should I edit the posts to bring them in line with my current understanding, or leave them unchanged as a testament to the process of change itself?  Perhaps I should edit them, as the technically-savvy can find old versions of most webpages anyway?  What do you think?  What would you do--or, if you've had a similar change in perspective while blogging, what have you done?


If "X Changes the Brain!!!", When Should We Care?

In a post catchily titled "Warning: This Post Will Change Your Brain," Neuroskeptic describes media coverage that breathlessly reports that a single dose of an antidepressant changes the brain.

As Neuroskeptic points out, evidence from brain damage supports the idea that everything the mind does involves corresponding brain activity.  Therefore, we should expect, at some level, that everything we think about, do, or perceive will change the brain in some way.  There are a lot of philosophical positions you could take that are compatible with this notion--that "the mind is what the brain does," that "the mind is the brain," that "the brain causes the mind to do stuff," that "the mind and the brain just happen to perfectly parallel each other," and so on. Regardless, if something is happening in the mind, then something must be happening in the brain, too. Therefore, the mere existence of a change in the brain isn't necessarily headline news. Neuroskeptic has a great example of trivial brain changes we experience every day:

"Every time you open your eyes, for example, widespread changes in your brain activity result. But every time you close your eyes, these changes are reversed."
Above: "Sleep changes the brain?!  I'd better not sleep any more, then!"

Given all the headlines with titles like "New brain study explains why people do/like/think X," journalists do seem to believe that the brain either is or causes what happens in the mind.  So if they really believe this, they should also recognize that mind changes necessarily involve brain changes, so not every brain change is likely to be exciting or important.

So if some brain changes are trivial, how are we supposed to evaluate whether a change reported in a news story should matter to us?

It may not always be possible to tell, given either the limitations of the study or the article reporting on it.  But here are some questions one can ask:

1) At what time scale does the brain change?
Brain plasticity acts at two major time scales.  One, on the order of milliseconds, involves changes in the pattern of neural firing, and the biochemical processes that affect it--neurotransmitter release and the like.  Different neurons in your visual cortex fire when you look at a perfectly vertical line versus when you look at a perfectly horizontal line, for example.  Different assemblies of neurons will fire when you look at (or think about) a cat and when you look at (or think about) a dog; or when you smell Lysol vs. your grandmother's cookies.  And each time you think about something new, the pattern of neurons that fires changes again.  These changes are so fast that fMRI is too slow to catch them.  On the other hand, over years, memories form and solidify through changes in the strength and structure of synapses.

2) How long does the change last?
Brain plasticity at the millisecond scale lasts as long as the thought or behavior it signifies. Long term potentiation--the brain changes that enable memory formation--can potentially last as long as an individual lives.

3) What sort of change is it?  How big is it?
The birth of new neurons and the creation of new synapses is a big deal. For example, a major factor in developmental changes is a proliferation of synapses in a particular brain region, followed by a pruning of the synapses that turn out not to be useful.  Some regions, such as primary visual cortex at the very back of the brain, both proliferate and prune earlier than others, such as the frontal lobe, and this has real behavioral consequences.  Long-term changes in the pattern of short-range and long-range white matter connections in the brain also seem important, as do changes in the functional communication between brain regions that they enable. Look for evidence of large, long-lasting, long-time-scale changes of this sort.    

4) How and why does the change happen?
This is really a question about the mechanisms of the brain change, which, for a neuroscientist, means understanding its effects at all levels, from the molecular up to the whole brain level.  But a layperson can approach the question in a less technical way.  Suppose the brain change is caused by a drug or therapy.  Do these changes simply reflect the transient action of the drug or therapy, and end once the patient is no longer in treatment?  Or does the drug or therapy change the brain in some sort of meaningful way that persists even when the patient is no longer receiving treatment?  For example, people helped by cognitive-behavioral therapy for anxiety may develop habits of examining and correcting their thinking that become so effective that they no longer needs the therapy, because they have been trained to provide their own.  One might expect to see a long-lasting, long-time scale brain change of one of the sorts described in Question 3.

5) What is the real-world, behavioral consequence of this brain change?  Is there one at all?
As Dorothy Bishop points out, teachers don't really care if a dyslexia intervention changes the structure or function of the brain in some way; they care if it teaches dyslexic children to read faster and more accurately, and if this improvement lasts.  A depressed person evaluating possible therapies wants to know if changes in the brain reflect an actual reduction in depression symptoms.  In cases like this, brain changes are interesting because they may inform us about how the behavioral change occurs, but the real measure of interest is behavioral, not neurological.
Next time you read a headline about how something changes the brain, keep these questions in mind and ask yourself what sort of brain changes are actually involved.  The reality may be less exciting, or terrifying, than it first appears.


An Open Letter to Issy Stapleton

Dear Issy,
I don't know if you have free access to the internet, or if you'll ever see this.  But I wanted to tell you something.

I can't even imagine what it's like to live knowing that your mom tried to kill you.  That would traumatize anybody.  Worse, to have to listen to her tell the world that it was your fault, that you didn't deserve to live, and having famous people like Dr. Phil agreeing with her.  Well, I know it hurts, and it's probably infuriating, but I want you to know, it's not your fault.  You don't deserve this. No one does.

Please know that there are a lot of people who support you, who want the best for you, who wish we could protect you.  A lot of people are trying to make the world see that what your mom did to you was wrong.  We couldn't help you, but maybe we can stop it from happening to another child.

And Issy, you're not alone.  There is a whole community of people affected by autism who are very different from your mother.  There are autistic adults* who talk to each other online and meet in person.  An incredibly diverse group of people, many of whom were called "difficult" and treated horribly when they were children, but who now are friends and support each other.  There are parents of autistic kids who treat them kindly and want to understand them, who don't see their children as a burden.  There are siblings, like myself, who know their lives are infinitely better because of their autistic sibling.  There are professionals who actually care about the happiness of the people they work with, not just about making them look "normal."  We're all here waiting to welcome you.

With love,
Emily "Mosaicofminds"

*I don't know if you prefer "autistic" or "with autism" or if you care one way or the other.  This is the term I use, but please fill in whatever you prefer.


Want to learn how something works in psychology? Make it up!

(No, I don't mean that you should invent numbers and call them experimental data, although some people have done that).

There are a lot of theories psychologists have been unable to prove, either because they lack the control over the world necessary to test them, or because it would be unethical to do so.  For example, the nature/nurture problem would be a lot easier to solve if one could separate twins at birth and assign them, say, to a "learn a spoken language" and a "learn a sign language" condition, or an "authoritarian parent" and a "laissez faire parent" condition.  But, since they can't do such things, psychologists have come up with a creative alternative.

They create artificial versions of the things they want to study.

Want to know how people learn a language?  Make up an artificial language, change the parameters of its grammar and other qualities in specific ways, and watch how people learn it.  There are a number of studies that have used invented artificial languages to study language learning in kids and adults.  On a smaller scale, studies routinely examine toddlers' word learning by asking them to learn the names of toys or unfamiliar household objects--names like "blicket" or "dax."

Want to understand how we learn to recognize specific types of objects, such as faces?  One research group invented little creatures called Greebles (see IO9's layperson-friendly description of the study). The researchers trained people to recognize individual Greebles and categorize them into families.  They varied what methods were used to train people to recognize the Greebles, how participants were tested, and various other parameters in order to find out more about the learning processes involved.  They also observed (using fMRI) how learning to recognize these artificial objects changed activation in a specific area of the brain important for object recognition.

Above: Greebles, from Isabel Gauthier's paper in Nature Neuroscience.

Want To Understand How Facial Recognition Works? You'll Need A Greeble
Above: Greebles arranged by family and gender, from the same paper via IO9.

My own lab even used 3D printers to create Greeble-like creatures for children to play with while learning (Sorry, no pictures available at present).  Doing so allows them test whether the experience of touching and looking at the Greebles from different angles helps children learn them.  They also investigate whether it matters exactly how children explore the objects.  There are families of Greebles living on my desk and they are adorable. (And these are just the most appealing of a wide variety of artificial objects my lab has used to study how young children learn).

Other than writers and video game designers, how many people in other fields can say they made up a language or a new type of creature?  How many can say they did it for science?


How do developmental psychologists think?

[The basic structure and ideas for this post come from a developmental seminar I'm taking with Dr. Bennett Bertenthal at Indiana University.  I'm sharing these concepts more broadly because not everyone has access to a class like this, but anyone interested in child development can benefit from understanding the thinking style and assumptions of the people who research it.] 

A developmental psychologist is someone who researches how people's minds change over their lifetime.  Most study babies, children, or adolescents, but some focus on old age, and they could also investigate parenthood, middle age, or emerging adulthood.  Developmental psychologists care about life stages, how we change as we transition from one to the next, how we change within a life stage, and conversely, what about us stays the same as we move from one stage to another.

Above: A developmental psychologist playing with a child.

Developmental psychologists are concerned with processes of continuity and change rather than in particular things the human mind does.  In this respect, they are different from some other sorts of psychologists, who are defined by the functions of the human mind they choose to research.  (I.e., cognitive psychologists study thought and perception, personality psychologists study personality, and social psychologists study group behavior and influences).  Developmental psychology, as a field, is concerned with all these areas of the human mind. Even a developmental psychologist who focuses on cognitive psychology topics--as I do--will have some familiarity with personality and social development.

First, I'm going to lay out some assumptions developmental psychologists make. Then I'll list some big questions they like to ask.

1) Gene Environment Interactions
While the nature-nurture debate is at least as intense among developmental psychologists as elsewhere, they have a unique perspective on it.  They argue that you cannot explain human behavior with only genes or only experiences.  Instead, they come together in a complex way, with different results than you would get from genes or environment alone.  They claim that the interaction between genes and environment resembles that between vinegar and baking soda.  Vinegar and baking soda are each inert, but come together to make an explosive reaction.  Similarly, genes and environment come together to create an outcome--like personality traits or intelligence--that neither would have produced alone.

The least controversial interaction is probably height.  A large amount of variation in people's heights is genetically determined; tall people tend to have tall children, short people tend to have short children, and siblings tend to have similar heights.  However, nutrition determines whether people will grow as tall as their genes permit them to be.  For this reason, my grandparents were taller than my great-grandparents, and my parents were taller than my grandparents (and the same will likely be true for you, as well). However, improvements in nutrition seem to have plateaued, and so has height; my generation (millenials) is the first in some time not to exceed their own parents' height. Notice that the genetic relationships here (parent to child) are constant across the generations from your great-grandparents to yourself, but differences in environment (nutrition) produce large differences in height.

More complicated and controversial are theories like the Orchid Hypothesis, which posits that different people are differentially reactive to their environments (whether these are good or bad). As far as I know, this theory is still new and not completely accepted, but it's based on research on stress and resilience that is widely accepted.  It's pretty well known that some children who have suffered abuse and neglect will have worse life outcomes than others, and that one factor affecting this is differences in specific genes.

2) Developmental Trajectory
You don't have to be a developmental psychologist to notice that different individuals develop at slightly different rates.  For example, some kids are early talkers and readers and remain ahead of their peers in language skills; other children are slower than their peers in developing language and reading skills. Some kids are taller than their peers from an early age, and maintain this status over time, while others start out short and remain that way.  More interesting than that, though, are children who start out behind their peers in a skill and come out ahead, or vice versa.  For example, Einstein, though a late talker, developed perfectly adequate speaking, reading, and writing skills by adulthood, and some late-talking children today follow a similar pattern.  Meanwhile, some children with precocious academic skills and high IQ scores in preschool, kindergarten, or first grade, may perform more like their peers by third grade (for this reason, experts on gifted children tend to recommend getting one's children IQ-tested at 6 or 7 years old). Children's rate of development of a skill can change, both relative to themselves at earlier ages, and relative to peers of the same age.  Basically, when developmental psychologists think about growth, they imagine a line graph, where the steepness of the slope of the line represents the speed of development, and changes in the slope represent changes in the rate of development over time.

Developmental trajectory is especially interesting in two cases: when comparing typical with atypical development, and when comparing outcomes for different individual children.

For example, language development often follows a different trajectory in autism than in typical development.  Speech is often delayed.  Also, the rate of growth may seem to slow down for a while, stop entirely (what developmental psychologists call a "plateau"), or even reverse ("regression" or loss of language).  On the other hand, language development may continue longer in autistic people than in neurotypical peers, with language skills sometimes improving into adulthood.  And of course, since autism embraces people with a wide range of characteristics, you will find autistic people with pretty much every imaginable trajectory of language development.  There have been lots of recent studies that attempt to find subgroups of autistic children with different trajectories, in the hopes of predicting who will have the best language outcomes, and why.

Developmental trajectory is also important when comparing different individuals from the same population.  For example, some late talkers eventually catch up with their peers in spoken vocabulary, while others do not.  Some developmental psychologists spend a lot of time trying to figure out why these children differ, and what can be done to help the persistently-delayed group catch up.

3) Developmental Cascades
While people can and do grow and change throughout their lives, earlier experiences profoundly shape our abilities and choices later on.  The influence of earlier upon later development is called a "developmental cascade."  A better term would probably be "developmental avalanche."

For example, let's say you're looking at vocabulary size from age 3 to age 5.

Age 3 vocabulary size has an effect on age 4 vocabulary size.
Age 4 vocabulary size has an effect on age 5 vocabulary size.
Age 3 vocabulary has an additional effect on age 5 vocabulary size.

So you have a sort of snowball where initial vocabulary has both direct influences and indirect ones, via vocabulary at intermediate ages. It's like a small snowball that hits more snow and becomes a bigger snowball, which hits more snow and becomes an even bigger snowball, and so on.  Eventually, small differences between people early on can lead to big differences later on.

4) 2-Way Interaction between child and environment
Children aren't just shaped by their environment. They can act in different ways, and their behavior in turn shapes the input they get from their environment.  For example, a child who is shy from infancy will be treated differently than a child who is outgoing from infancy.  They may be reproached, or gently encouraged to interact, or pushed hard to interact, or shamed into interacting, depending on their parents' parenting style and values.  This in turn will shape how the child behaves around other people, and whether they become painfully shy and retiring or quietly confident adults.  A child who has been told from an early age that they're smart will probably think of themselves differently, and take different levels of risk in the classroom, than a child who has been told that they're just average, or even dumb.  I'm sure you can think of many more everyday examples.

While the role of children in shaping their environment seems obvious when pointed out, it's very different from how your average parenting book describes children1.  Too often, the paradigm seems to be "push the right button, receive the desired behavior;" there is little focus on the children's reasons for their behavior (good or bad), or on how the children might be pushing the parents' buttons and triggering their own insecurities about parenting or other issues.  Not surprisingly, many of these books aren't written by developmental psychologists.

The four assumptions listed here lead cognitive psychologists to ask a certain set of questions.

Questions Developmental Psychologists Ask:
1) Are some capabilities innate? If so, which ones?
William James pointed out that at any given moment, there are so many shapes, colors, sounds, textures, smells, temperatures, and more that without any inborn means to sort them out, a baby's world would seem like a "blooming, buzzing confusion."  I think most developmental psychologists accept that at the very least, babies are born with some basic learning mechanisms and an inclination to observe and learn about the world.  But they differ on how much "software" babies come with.  Some people think we're born with (tacit) knowledge of all the grammatical rules of human language, a basic understanding of how objects move (e.g., that objects fall), and/or a set of basic concepts about other people (e.g., that they have minds and intentions).  Others think that we develop these concepts early in life, but aren't born with them.  This debate has led to a lot of interesting research on what babies understand about people, things, quantities, and more, and is far from being resolved.

2) Are there developmental stages, and if so, how do people transition between them?
Piaget thought there were certain qualitatively different ways of thinking that everyone progressed through in a certain order at roughly the same age, and that was consistent across domains of knowledge.  (I.e., if you are at the concrete operational stage in thinking about the movement of objects, then you must also be at the concrete operational stage in thinking about other people's behavior).  This is a fairly extreme stage theory.  His successors, the Neo-Piagetians, were a little more flexible, particularly regarding different domains of knowledge and individual differences.  However, they still thought that development has discrete steps, like a staircase, rather than continuity throughout, like a wheelchair ramp.  Whether a particular study seems to provide support for stage-like or continuous development seems to depend whether it uses continuous or discontinuous measures of the behavior in question, so this question is also far from being resolved.

3) How do individuals differ in their development?
I think this is fairly self-explanatory.

4) How do changes in the brain contribute to development?
This question is similarly easy to understand--but it's even harder to answer in kids than it is in adults.

5) What develops, and how does change occur?
Let's say that last year, Anna didn't understand conservation of matter, but this year she does, and can pass a Piagetian conservation of matter task.  How exactly is she thinking differently now than she did last year?  How did she get from the understanding she had last year to the one she has this year?  This is a very difficult and abstract question, is probably the most central question in developmental psychology, and is also probably the hardest to resolve.

6) How does the social world contribute to development?
We are constantly observing, imitating, and listening to explicit teaching from other people.  We grow up in cultures that provide us with tools for thinking like language, writing, the abacus, or the internet. Our cultures also determine how we spend our time at different ages, and whether we spend our time more with age peers or with people of all ages.  We interact with various institutions either directly or indirectly, including schools, churches, and governments.  We are assigned to categories of age, gender, ethnicity, religion, and more, all of which come with messages about how a person within our category "should" and "should not" behave.  We also (in general) have innate desires to learn from and connect emotionally with other people, and get them to like us.  All these things shape both what we experience and how we choose to behave.

So next time you talk to a developmental psychologist or read about a developmental study, know that development is all about change--and change is a complicated mass of factors that changes over time and differs between individuals. Their goal is to sort out that complex system.

1 I read parenting books from about 1995, when my brother was a fetus, to about 2008, when I got too busy with college to read them.  So it's quite possible I've missed books from before or after these dates that take a better approach. (And for that matter, I'm glossing over a few exceptional parenting books that appeared during this time, like The Heart of Parenting, which is based on the concept of emotional intelligence, and involves helping kids recognize and verbalize their emotions).


Eye movements in ADHD: Not a "foolproof" diagnostic method, but interesting and important

Above: Eye movements. Are they really a foolproof clue to ADHD?

Science Daily claims that measuring "Involuntary movement [is] a foolproof indication for ADHD diagnosis." Specifically, they believe it will reduce the rate of misdiagnosis in children:

Attention deficit hyperactivity disorder (ADHD) is the most commonly diagnosed -- and misdiagnosed -- behavioral disorder in American children. Now a new study can provide the objective tool medical professionals need to accurately diagnose ADHD. The study indicates that involuntary eye movements accurately reflect the presence of ADHD.

Unfortunately, the actual study, by Fried and colleagues1, indicates nothing of the sort.2

The study did, in fact, measure involuntary eye movements--specifically, blinking and "microsaccades," small jerky eye movements.

22 adults with ADHD took the TOVA twice, the first time unmedicated and the second time while taking methylphenidate (Ritalin).2  The TOVA, which stands for Test of Variables of Attention, is a common, computerized diagnostic test for ADHD.  While participants took the test, their involuntary eye movements were measured.  The unmedicated ADHD adults made more microsaccades and blinks than neurotypical adults immediately before the onset of the stimulus.  When they took the test a second time on methylphenidate, they did not differ from the control group. The researchers argued that measuring involuntary eye movements is more precise, quantitative, and harder to "game" than many current diagnostic methods, such as questionnaires and self-report.

Unfortunately, this study cannot possibly generalize enough to a wider population to imply anything about diagnosing ADHD in the real world.  First of all, although the Science Daily press release focused on children, and parents' concern about their taking stimulants unnecessarily, Fried's study only examined adults.  Furthermore, the study measured eye movements only during a single specific task, the TOVA.  It's not clear whether the same finding would occur during other tasks, or even at rest.  And of course, a sample of 22 participants may not generalize well to the millions of people with ADHD.

And even if the findings generalize to other ages and tasks, further conditions would need to be met to ensure the method worked in practice.  It would have to be tested in a real-world school or clinical setting, with a large population of people referred for possible ADHD (on the order of hundreds or even thousands).  It would have to successfully distinguish ADHD not only from typical development but from other forms of atypical development--which is much harder.  While most of the hysteria about ADHD misdiagnosis assumes that the misdiagnosed children are "normal" children treated as if they have a developmental disorder, it's probably more common for children to be misdiagnosed as having ADHD because of real symptoms caused by mental illness (such as depression), physical illness (such as sleep problems) or another developmental disability. Furthermore, the method would have to be shown to be cheap, fast, and practical in real-world contexts.  For example, the TOVA is a common diagnostic test among neuropsychologists and other specialists, but to the best of my knowledge, it is less so among pediatricians who may also be called on to diagnose ADHD. If the TOVA is essential to obtaining this pattern of eye movements, the method may not generalize well to all diagnostic settings.

This is not even the first study to identify increased anticipatory saccades as a marker of ADHD.  In a review, Rommelse and colleagues report five others (Castellanos et al., 2000; Mostofsky et al. 2001a & 2001b; Rommelse et al., 2008, & Ross et al., 1994; see reference list).  Bittencourt and colleagues' review described a study by Feifel and colleagues, who tested ADHD adults who went unmedicated at least 48 hours. These participants generated more anticipatory saccades when a task required them to shift their attention from central fixation to a target appearing randomly onscreen.

Furthermore, Richard N. Blazey, David L. Patton, and Peter A. Parks have a U.S. patent for a method of detecting ADHD through saccades, or what they call "angular movements of the eyeball."  Their patent differs from Fried's method in one crucial respect.  Eye movements are measured while the person sits staring at a blank screen, wearing noise-canceling headphones, rather than while doing a demanding test like the TOVA.

So Fried's study doesn't offer a foolproof way to diagnose ADHD, and measuring unconscious eye movements isn't a new way to diagnose ADHD in the first place.  But the paper still offers an important insight, one left unexplored by the Science Daily article.  ADHD adults make more anticipatory saccades than neurotypical adults, and it turns out that anticipatory saccades play an important role in perception and tell us something about the strengths and weaknesses of vision in ADHD.

In order to understand why the finding matters, let's briefly go over the research on what anticipatory saccades do and why they matter.

First of all, a saccade is a rapid, jerky eye movement that brings something new into focus on the fovea, the most sensitive part of the eye.  It is not the only sort of eye movement (there are also smooth pursuit eye movements that smoothly track a moving object already in focus).  However, it is extremely common and essential to vision.  As Michael F. Land explains:

“Throughout the animal kingdom, in animals with as diverse evolutionary backgrounds as men, fish, crabs, flies, and cuttlefish, one finds a consistent pattern of eye movements which can be referred to as a ‘saccade and fixate’ strategy. Saccades are the fast movements that redirect the eye to a new part of the surroundings and fixations are the intervals between saccades in which gaze is held almost stationary. As Dodge showed in 1900, it is during fixations that information is taken in: during saccades we are effectively blind.” 
Saccades can take in varying amounts of the visual field (measured in degrees).  Microsaccades, like the ones in the Fried ADHD study, are generally defined as extending to less than 15 minutes of arc in the visual field.

Even a cursory Google search reveals that anticipatory eye movements play an important role in a variety of tasks at all ages.  Anticipatory eye movements have been used to study expertise in soccer goalkeepers, object perception and expectations for "dynamic visual events" by babies, discourse comprehension in typical adults, sentence processing in adult readers, and the influences of language and knowledge about the world on adults' real-time visual attention.  These lines of research reflect an understanding that anticipatory eye movements are overt indicators of otherwise hidden attention shifts.  It's worth noting that not all anticipatory eye movements are microsaccades like the ones in Fried's ADHD study.  Some are smooth pursuit eye movements (the smooth, rapid eye movements used to track moving objects over a longer period of time).  However, saccades are often used for anticipatory eye movements, and the two overlap in neural areas, task demands, and the cognitive processes believed to be involved.

As Ellen Kowler put it:

"Work over the last 25 years has also converged on the notion that the saccadic system is inherently predictive, using pre-saccadic shifts of attention and signals representing planned saccades to encode the location we are about to fixate, and to prepare visual neurons, in advance, for the post-saccadic image. These predictions may be instrumental in processes ranging from the control of saccadic accuracy (by means of adaptive saccadic adjustments) to the weaving together of discrete glances in a way that gives us the impression of a clear and stable perceptual world despite the continual displacements of the retinal image produced by saccades."
Anticipatory or "look ahead" saccades occur during a variety of real world tasks, including text and sheet music reading, typing, looking at pictures of scenes, drawing, walking over difficult terrain, driving, sports, and cooking. In reading, saccades select a span of 7-9 letters or 1-3 notes for processing.  Typists keep their eyes about 1 second ahead of the currently typed letter.  Sketching involves rapid cycles of gaze shifts between the person being drawn and the drawing.  People instructed to walk in specific, effortful ways will look ahead by 1 to 2 steps.  When steering around a turn, driving instructors look at points their car will not reach for another 2-3 seconds, whereas their students, who have not yet learned to anticipate this way, look straight ahead instead.  Tennis players' saccades anticipated the bounce of a tennis ball by about 0.2 seconds, while cricket players can anticipate the ball by about 0.1 seconds.  When making tea or a sandwich, at the end of each action, the eyes move on to the next object about half a second before beginning the next action.  When there are two objects involved (e.g., a kettle and lid), multiple saccades and fixations must be made between the two objects.  In general, saccades followed by fixations proceed a step ahead of action.  This avoids reliance on visual memory.

All this anticipation is believed to help people do things better.  For example, they help people aim their reaching and grasping movements accurately.  Crucially, these saccades may improve performance on visual tasks and arm movements even when attention is directed elsewhere.

In general, we see, hear, act on, and think about things better when we are attending them.  Therefore, the visual system needs to predict what objects or locations in the visual field will be important and start attending to them before they do anything important.  Anticipatory eye movements are the mechanism for doing this.  As such, extra anticipatory eye movements should be an advantage.  They should increase the likelihood of attending the right thing and perceiving it accurately.  Or, at least, that is the picture presented by research on vision in the general population.

ADHD research describes anticipatory eye movements quite differently.  It describes them as "premature," "impulsive," and a sign of inhibitory difficulties--even when the tasks being studied do not involve inhibition of any kind.

So, is there any real difference between "premature saccades" and "anticipatory" ones, or are they just a negative and a positive label for the same behavior? I asked Sue Fletcher-Watson about this, and it appears that there is a difference, which is only apparent in studies designed specifically to test learning visual patterns. In studies like this, anticipatory saccades reflect an accurate prediction of where a stimulus will appear, based on learning; premature saccades are the eyes' tendency to flick around randomly looking for stimuli when a person gets bored.  Unless a person making premature saccades is lucky, their saccades will have no tendency to land where a new stimulus will appear, so the "success rate" should be measurably lower for premature saccades than truly anticipatory ones.

However, many of the ADHD studies under discussion do not appear to use this sort of learning task. Instead, they measure individuals' control over their eye movements during an experiment that is static and does not encourage or require learning. I suppose individuals could learn in such studies, and their learning could be measured and analyzed, but that's not what these researchers were doing. They might need to reanalyze their data to measure and compare learning in typically developing and ADHD groups. (And perhaps someone should).

Furthermore, I don't think that the ADHD researchers were even asking that question, trying to determine whether ADHD behavior was anticipatory or just premature.  Instead, they seem to be simply assuming "ADHD is a disorder of inhibition, so group differences must be due to an inhibition deficit."  This is an example of biased research, as explained by Morton Ann Gernsbacher--if you take away the labels of the group members, the interpretation no longer makes sense.  It also fails to take into account the more positive picture of anticipatory eye movements painted by the general vision literature.

Researchers on atypical development often say we should take typical development as a starting point, so let's do just that and see what it actually implies for vision in ADHD.

Let's say for the sake of argument we reanalyze the data or do new studies to make sure the eye movements actually are anticipatory--and they are.

Increased anticipatory eye movements in ADHD could have positive effects, which could be viewed either as a simple advantage or as compensation.  The trait may also carry a disadvantage.

When viewed as an advantage, it implies that people with ADHD may be better at noticing and directing their attention to changing and salient things in their environment.3  This ties in well with the theory (described to me by Jeff Gilger's research team) that ADHD vision is well-adapted to dealing with rapidly-changing, highly-salient stimuli, but ill-suited to maintaining attention on static and less motivating stimuli.

When viewed as compensation, extra anticipatory saccades could be seen as a way of increasing the likelihood of focusing on the right things when attention is hard to control by other means.  Anticipatory eye movements could also compensate for lack of visual working memory.  In the general population, people who have to copy drawings or models make lots of saccades to the thing being copied, instead of looking back at the object less and relying mostly on visual memory.  Since children and adults with ADHD may have less visual working memory than neurotypical people, they may need to make even more saccades.

However, there may be a disadvantage to the ADHD pattern.  Remember that we are effectively blind while making saccades or blinking.  The more saccades and blinks a person makes, therefore, the less time they spend taking in visual information from their environment.  This can be a disadvantage when performing a task that requires taking in lots of visual information over a long period of time (e.g., certain sustained attention tasks).

These interpretations of Fried's study are merely my speculations, based on putting aside assumptions about ADHD and instead looking at what we know about how vision works, in general.  So please don't quote them as if they were established research.  Rather, these represent a possible blind spot in ADHD research--and a set of hypotheses we can test.  Even if they turn out to be wrong, we will learn something about the strengths and weaknesses that come with ADHD.

Many thanks to Sue Fletcher-Watson for helping me figure out how to tell the difference between anticipatory and premature saccades and offering encouragement.

1 Interestingly, Moshe Fried himself has ADHD.
2  At least, so far as I can tell from the abstract and media descriptions from the study. This post will be updated when I get access to the full text.
2 Notice the obvious confound: improved performance on the second testing could have been due to practice taking the test rather than the stimulant medication.
3 Note that having an advantageous pattern of anticipatory saccades, which are unconscious and not deliberately controlled, does not preclude difficulty with more controlled eye movements.  In fact, a line of research indicates that ADHD people have difficulty controlling and inhibiting eye movements, just as they do with other behavior.  ADHD could simply involve deficits in controlled, but not necessarily uncontrolled, perception and behavior4.
4 Whether or not uncontrolled ("reflexive") saccades are also impaired in ADHD is still under debate.  Some studies seem to find slower, more variable responses, while others observe no difference from neurotypical peers.

Note:  The basic point about the strengths and weaknesses of anticipatory eye movements in normal development can be found in James Enns' The Thinking Eye, The Seeing Brain (one of the few readable, layperson-friendly textbooks I have ever seen).

Other citations reflect a limited amount of time to survey the role of anticipatory eye movements in ADHD and typical development, so they are mostly reviews and are necessarily incomplete.

  • American Friends of Tel Aviv University (2014). Involuntary eye movement a foolproof indication for ADHD diagnosis. Science Daily, 13 August 2014. www.sciencedaily.com/releases/2014/08/140813131055.htm 
  • Moshe Fried, Eteri Tsitsiashvili, Yoram S. Bonneh, Anna Sterkin, Tamara Wygnanski-Jaffe, Tamir Epstein, & Uri Polat (2014). ADHD subjects fail to suppress eye blinks and microsaccades when anticipating visual stimuli but recover with medication. Vision Research 101, pp. 62-72. http://www.sciencedirect.com/science/article/pii/S0042698914001187
  • Juliana Bittencourt, Bruna Velasques, Silmar Teixeira, Luis F. Basile, Jose Inacio Sailes, Antonio Egidio Nardi, Henning Budde, Mauricio Cagy, Roberto Piedade, & Pedro Ribeiro (2013). Saccadic eye movement applications for psychiatric disorders.  Neuropsychiatric Disease and Treatment, 9, pp. 1393-1409. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3783508/
  • F.X. Castellanos, F. F. Marvasti, J. L. Ducharme, J. M. Walter, M. E. Israel, A. Krain, et al. (2000). Executive function oculomotor tasks in girls with ADHD. Journal of the American Academy of Child & Adolescent Psychiatry, 39, pp. 644-650.
  • D. Fiefel, R.H. Farber, B. A. Clementz, W. Perry, & L. Anilo-Vento (2004). Inhibitory deficits in ocular motor behavior in adults with attention-deficit/hyperactivity disorder.  Biological Psychiatry, 56:5, pp. 333-339. http://www.ncbi.nlm.nih.gov/pubmed/15336515/
  • Eileen Kowler (2011). Eye movements: The past 25 years. Vision Research 51:13, pp. 1457-1483 http://www.sciencedirect.com/science/article/pii/S0042698910005924 
  • Michael F. Land (2006). Eye movements and the control of actions in everyday life. Progress in Retinal & Eye Research, 25, pp. 296-324. http://www.cis.rit.edu/pelz/scanpaths/papers/eye-movements-every-day-life-land-2006.pdf
  • Neil Mennie, Mary Hayhoe, & Brian Sullivan (2006). Look-ahead fixations: Anticipatory eye movements in natural tasks. Experimental Brain Research http://www.ski.org/Renninger_Lab/BSullivan/MennieEtAl_LookAheadFixations2006.pdf
  • S. H. Mostofsky, A. G. Lasker, L. E. Cutting, M. B. Denckla, & D. S. Zee (2001a). Oculomotor abnormalities in attention deficit hyperactivity disorder: A preliminary study. Neurology, 57, pp. 423-430.
  • S. H. Mostofsky, A. G. Lasker, H. S. Singer, M. B. Denckla, & D. S. Zee (2001b). Oculomotor abnormalities in boys with Tourette syndrome with and without ADHD. Journal of the American Academy of Child & Adolescent Psychiatry, 40, pp. 1464-1472.
  • Nadia N. J. Rommelse, Stefan Van der Stigchel, & Joseph A. Sergeant (2008). A review on eye movement studies in childhood and adolescent psychiatry. Brain & Cognition, 68, pp. 391-414 http://www.fss.uu.nl/psn/web/people/personal/stigchel/rommelsereview.pdf 
  • N. N. J. Rommelse, S. Van der Stigchel, J. Witlox, C. J. A. Geldof, J. B. Deijen, J. Theeuwes, et al (2008). Deficits in visual spatial working memory, inhibition, and oculomotor control in boys with ADHD and their non-affected brothers. Journal of Neural Transmission, 115, pp. 249-260.
  • R.G. Ross, D. Hommer, D. Breiger, C. Varley, & A. Radant (1994). Eye movement task related to frontal lobe functioning in children with attention deficit disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 33, 869-874.
  • Alexander C. Schutz, Doris I. Braun, & Karl R. Gegenfurtner (2011). Eye movements and perception: A selective review. Journal of Vision 11:5,