Links to recent writing from my second home on the web

This past year, I've largely switched to using Medium, and have gotten behind in cross-posting here. Medium is cognitively accessible, with its clean, easy-to-read formatting. It's linked to Twitter, making it more active these days than Blogspot. I've always had more Twitter followers than regular blog readers, making Medium a better platform for me.

However, I can't bring myself to completely make the switch. Medium doesn't distinguish between real posts and comments on others' posts, calling them both "stories" and displaying them on the same page. That means real posts intended for a wide audience can be hidden from view behind comments that may not be. Plus, this blog has about ten years' worth of posts (!), too many to conveniently transfer to Medium.

While I decide how best to resolve the issue, here are the links to my recent Medium posts.

Maps in the Brain [Neuroscience for Dummies]
"The cortex has a surprisingly simple organizing principle...a 'topographic principle.'"

"Innovative methods and surprising findings from a new study of autistic youth with minimal speech."

"The history of curb cuts teaches us two important principles. 1. Technology designed for disabled people can help everyone... 2. When assistive technology becomes sufficiently ubiquitous and widely used, it is no longer considered assistive technology."

Two Steps Forward, One Step Back [Research Review, Advocacy]
"Researchers are starting to realize that 'regressive autism' is a myth based on poor methodology. The story tells us about the failings of autism research--and the complexity of human development."

"To improve one's physical abilities, one must find the middle ground between ease and pain. That's where yoga comes in...Perhaps flow is an evolutionary adaptation to make us seek out the 'sweet spot.'"

"Adults with disabilities often find it difficult to know how to push themselves because they have rarely been allowed to experience the sweet spot [of effort]."

Rumors of fMRI's Demise Have Been Greatly Exaggerated [Neuroscience for Dummies, Research Review, Opinions]
"Software bugs and statistical problems still plague fMRI research, but don't spell doom for the field." 

Why Does Ableism Cause Harm? and Continuation [Advocacy, Opinions]
"Even with the best intentions, you can't help someone you view as less."

I have a number of posts planned for the new year, plus an update on some major life and career changes.

Happy holidays and new year to all!


All the #NeurodiverseSTEM Chats in One Place, At Last!

In 2015, Elizabeth Bartmess, Diana Crow, and I co-ran the #NeurodiverseSTEM Twitter chats, a biweekly forum for discussing the circumstances of neurodivergent people in STEM fields. Elizabeth Storified each session, but there was no landing page for all, and only, #NeurodiverseSTEM chats. Until now!

Chat #1, 02/20/2015
Chat #2, 3/13/2015: How Our Neurodivergence Affects Our STEM Perspectives, and Vice Versa
Chat #3, 3/27/2015: Barriers to Advancement in STEM
Chat #4, 4/17/2015: Communication
Chat #5, 5/1/2015: ND and STEM as Dual Identities
Chat #6, 5/15/2015: Science communication
Chat #7, 5/29/2015: Including neurodivergent perspectives in research
Chat #8, 6/12/2015: Technical and scientific writing
Chat #9, 6/26/2015: Executive Function and Workflow
Chat #10, 7/17/2015: Mentoring
Chat #11, 7/31/2015: Networking


ADHD Tipping Points: Why people with ADHD suddenly seem to fall apart, and what you can do about it

In a recent webinar, ADHD coach and mother of an ADHD son Laurie Dupar introduced the concept of a "tipping point.

In her coaching practice, Laurie met many people diagnosed as adults as late as middle age. Often, they had functioned well in school, at work, and in their relationships, until their lives suddenly seemed to fall apart--at which point they were finally diagnosed. Laurie developed the concept of a "tipping point" (similar to what I call "hitting the wall") to describe this phenomenon. She then looked for patterns in her clients' lives to explain why these bright, successful adults were able to function so well for so long, and then suddenly could no longer do so.

Image result for dominoes falling
Like a domino, a tipping point can cause many areas of life to fall apart at once.

Tipping points occur because undiagnosed people have always had an ADHD brain with ADHD strengths and weaknesses. However, these traits may have never disabled them before because they found ways to compensate, and their physical and social environments allowed them to do so. 

To the person with ADHD, a tipping point may feel like one is falling apart. It might also feel like confirmation that one wasn't good enough and was just pretending all along--"now it's finally caught up with me, and everyone can finally see I'm just faking being good enough." In reality, a tipping point does not reflect a person's intelligence, hard work, or competence. It simply reflects that new life circumstances make it impossible to compensate for, manage, and hide one's ADHD traits. When capable adults can no longer cope, and their strategies either no longer work or actually become counterproductive, their ADHD may suddenly become obvious.

Laurie argued that the best way to deal with tipping points is to predict them in advance and head them off before they begin. Tipping points involve so much pain and confusion that it can be easier to prevent them than to cope with them.

Laurie most often sees tipping points when:
  • A child moves from elementary school to middle school, middle school to high school, or high school to college.
  • An adult gets promoted at work.
  • An adult marries, or has a new baby.
  • An adult woman goes through menopause.

Changes in physical environment. Moving to a new home or a new workplace can trigger a tipping point. We often overlook the importance of the light, sound, crowding, traffic flow, and other factors of the physical environment, but they can impact us both directly (in terms of comfort and distraction) and indirectly (in terms of making productivity routines easier or harder to implement).

New life roles. When a child transitions from one level of schooling to another, they face new expectations for organization, social, and academic functioning. For example, a new middle school student must move between classes with different teachers and track assignments in a planner, while navigating increasingly cliquey peer groups. An adult promoted at work may be expected to spend less time on the tasks where she previously excelled, and more time on managing others doing those same tasks. These role changes involve changes in identity and can stress anyone, but may be even harder for those with ADHD, especially if they involve less time or greater need for executive functions.

Changes in family dynamics. Sometimes happy changes, such as marriage or a new baby, can trigger an ADHD tipping point. These events involve new demands from others that may push one's executive functioning to the limit--such as when a new partner expects an ADHD person to keep a spotless, organized home. Or, as with a new baby, they might reduce the time one has to implement strategies that used to help them. (As Laurie points out, adults with ADHD often "use time to make up for things we've been missing." New family members also means more stuff and clutter.

Changes in physical health. Many adult women are diagnosed at menopause because hormonal changes drastically alter their functioning. Laurie Dupar claims that estrogen helps dopamine bind to neural receptors, and thus dopamine becomes less effective when estrogen levels drop. (Note: smaller drops in estrogen levels also occur during menstrual periods, which may explain some women's claims that they have more difficulty managing their ADHD during their period). Hormonal changes during adolescence could also intensify ADHD symptoms or make them harder to manage, but they might be overlooked because teenagers are expected to be "moody" and impulsive.

Changes in activity level. High school athletes may have difficulty transitioning to college if they do not pursue college sports, both because they lose a great deal of structure to their time and because of the reduced physical activity itself. Physical injuries that cause a sudden drop in activity level can also cause adults to struggle in seemingly unrelated areas of work and school.

Changes in sleep. Prolonged sleep deprivation can cause people without ADHD to exhibit ADHD symptoms like distractibility. It will only intensify ADHD symptoms in those who actually have ADHD. ADHD traits often mean that it takes more energy to complete everyday tasks than it does for other people, thus sleep becomes more necessary, and lack of sleep more impairing than for the average person.

Changes in technology usage. While many people with ADHD swear by using mobile phones to set alarms, access their calendar from anywhere, and stay organized, new technology implemented thoughtlessly can disrupt analog organizational strategies without providing a replacement. For example, Laurie has worked with doctors who reached a tipping point during a transition from paper medical records to electronic ones. Doctors could no longer, for example, use the size of the stack of medical records on their desk as a clue to how much time was left to spend on them. Electronic records can also prevent use of tactile strategies. People with ADHD need to ensure that the technology they use offloads working memory demands rather than increasing them (e.g., by requiring one to hold information in working memory from one screen to the next).

Usually, a combination of these factors triggers the tipping point, because life changes typically affect several of them. For this reason, the transition to college can challenge even the most talented people with ADHD. Many college students are academically prepared for college, but relied on structure from home. They may not know how to structure their own time and tasks, they may not get enough sleep, may engage in less physical activity, and may have less control over their physical environment due to roommates with different preferences. Meanwhile, they face very different (and less clearly-communicated) academic and social expectations. Pretty much every factor listed (with the possible exception of physical health) plays into the transition to college. Incoming college students with ADHD may not realize that the self care and social demands of college may prove challenging even if the academics do not, and the typical disability services office, focused on academic access, may not offer much help.

This analysis underscores the fluidity of ADHD, and the continuity between those who can be diagnosed and those who cannot. The Diagnostic and Statistic Manual of Disorders (DSM), which provides the basis for diagnosis, emphasizes that ADHD should be diagnosed not based on whether a person displays frequent inattention, hyperactivity, and impulsivity, but based on whether these disable a person and causes them distress. A person may have an ADHD neurotype (for example, dysregulated dopamine systems in their brains, delayed prefrontal cortex development, and reduced prefrontal cortex activity during executive function), but they may only have the disability ADHD when they can no longer compensate for these traits or their environment makes these traits a sufficient liability to cause disability and distress. Thus, a person could theoretically go back and forth over their lives between having ADHD and not having ADHD!

Laurie lays out a simple but powerful approach for dealing with tipping points:
  1. Try to predict whether a tipping point is coming. Are you or a loved one with ADHD about to transition to a new school or work environment? Are there upcoming changes in family dynamics? Are you about to move?
  2. If a tipping point has already happened, ask yourself what changed. Physical health (including activity level and sleep)? Physical environment? Social environment? Consider all possible variables.
  3. What were you doing before the tipping point that helped you in the same situation? Or, if the tipping point hasn't happened yet, what strategies are working for you now? (Not all of these may have been consciously developed. For example, a woman stopped coming to meetings on time after her promotion, only to realize that she had been relying on a neighboring coworker to see when to get up from her desk). 
  4. Create a structure that will work in a similar way. 
  5. Laurie Dupar didn't mention this step, but it's extremely important: Test your strategy to see if it works! Maybe you guessed wrong about what aspect of your old environment to replicate. Or, maybe you guessed right, but your strategy was too complicated or too hard to use. If it doesn't work, you may have to start over and develop a new one.
  6. Consider working with an ADHD coach. This coach does not have to be local, because coaches are trained to work with clients remotely. However, because coaching is a new profession with still-developing credentials, Laurie recommends asking coaches where they trained, how long they have worked, and how many clients they have helped. In particular, one should ask how much experience the coach has with people in your situation (e.g., college students, middle-aged women).
Laurie's stories also highlight the importance of listening to people with ADHD and paying attention to seemingly unimportant details. Sometimes, a life transition can cause a tipping point for different reasons than one might expect. For example, she worked with a young man, formerly a good student, whose grades dropped after moving to a new school. He was happy with the new school, his motivation was high, and he was not discouraged by his poor grades. The change in school did not appear to cause his problems, so Laurie moved on to understanding the changes associated with moving house. It turned out that before he moved, this young man used to set aside a specific amount of time to relax by shooting hoops in the backyard. This left him mentally prepared to focus on studying. At his new house, there were snakes in the backyard and he was afraid to go outside. Thus, he could no longer use this routine, and his concentration (and studying) suffered. Disruptions to one's functioning can often be like this--small, prosaic, and hard to identify without asking the right questions.

In short, I gleaned the following from Laurie's talk:
  1. Tipping points are common among people with ADHD, and nothing to be ashamed of. If you are going through a tipping point, do not blame yourself or judge yourself to be inadequate. "Remember, you've always had ADHD...you have the ability to compensate somewhere." The longer you've gone before the tipping point, the more you've used your talents, creativity, and hard work to succeed.
  2. ADHD traits (inattention, hyperactivity, impulsivity) and the neurodevelopment that creates them are lifelong. However, ADHD, the diagnosable disability, may not be, and a person can move into or out of ADHD status over a lifetime. Thus, clinicians and researchers must develop a sensitivity both to ADHD traits and to the subtle changes in the physical and social environment and in physical and mental health that determine disability status.
  3. Certain common life changes can make ADHD traits disabling and can cause people to get diagnosed. These include changes in environment and in role. The interactions between such life changes and ADHD traits needs more attention and research.
  4. ADHD tipping points can be managed, with awareness. You need to figure out what was working for you and how to implement something similar in your new environment or role.
  5. Understanding and treating ADHD requires both an understanding of ADHD traits (which can be approached scientifically by external experts, like researchers and clinicians) and an understanding of the subtle ways ADHD traits manifest in an individual's life (which can be best understood by the person with ADHD). Thus, people with ADHD should be at the center of research and treatment.
Have you, a family member, a friend, or a student gone through a tipping point? What helped? Do you know of any research that takes the interactions between physical and social environment and ADHD traits into account? Please share your thoughts!


New edition: How do developmental psychologists think?

[This is the new and improved version of an old post, cross-posted from Medium].

Courtesy of Shutterstock.

A developmental psychologist researches how people’s minds change over their lifetime. Most study babies or children, but some focus on adolescence or old age. They could also investigate other life transitions, like parenthood, middle age, or emerging adulthood. Developmental psychologists care about life stages: How do we change as we move from one to the next? How we change within a life stage? Conversely, what about us stays the same as we move from one stage to another?

Developmental psychologists care about processes of continuity and change, not 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). 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 know something about personality and social development.

Like people in other fields, developmental psychologists are guided by a set of assumptions, which may or may not be discussed explicitly.

Assumptions Developmental Psychologists Make

1)Gene-environment interactions
While developmental psychologists debate nature vs. nurture just as intensely as other people, 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. Genes and the environment interact like vinegar and baking soda. Alone, these chemicals are each inert, but they come together to make an explosive reaction. Similarly, genes and the 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. 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. In other words, some people react a lot to their environments, while others react much less. More reactive people will be the most successful in a good environment, but least successful in a bad environment. 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 iswidely accepted. Some children who have suffered abuse and neglect will have worse life outcomes than others, and one contributing factor is differences in specific genes. This is a well-known gene-environment interaction.

2) Developmental trajectories
You don’t have to be a developmental psychologist to notice that different individuals develop at slightly different rates. Some children learn to talk and read early and remain skilled speakers and readers throughout their lives, while others develop language and reading skills more slowly and never achieve the same levels. Some children are taller than their peers from an early age, and remain so over time, while others start out short and stay that way.

More interesting, though, are children who start behind their peers in a skill and come out ahead, or vice versa. For example, Einstein, though a late talker, developed fine 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 often recommend getting one’s children IQ tested at 6 or 7 years old).

Children’s rate of development of a skill can change — not only relative to peers the same age, but also relative to themselves at earlier ages. 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.
In this example of developmental trajectories, each line represents an autistic preschool child's vocabulary. Parents were given a survey four times, which asked how many words their child could both say and understand.

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

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”). On the other hand, autistic people may continue developing language skills longer than neurotypical peers, sometimes improving into adulthood. And of course, since autism embraces people with a wide range of characteristics, you can find autistic people with every imaginable trajectory of language development. Many recent studies have attempted to find subgroups of autistic children with different trajectories, to predict 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, early experiences profoundly shape our abilities and choices later on. The influence of earlier upon later development is called a “developmental cascade,” but I like to think of it as a “developmental avalanche.”

For example, let’s say you’re studying children’s 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.

Initial vocabulary has both direct and indirect influences, 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 in life can lead to big differences.

4) Two-way interaction between child and environment
Children aren’t just shaped by their environment. Their behavior also shapes the input they get from their environment. For example, a child who is shy from infancy will be treated differently than a more outgoing child. The shy child might be reproached, shamed, pushed hard, or gently encouraged to interact, depending on the parents’ parenting style and values. These actions in turn will shape how the child behaves around other people, and whether he becomes a painfully shy or quietly confident adult. A child who has been told she is smart from an early age will probably think of herself differently, and take different levels of risk in the classroom, than one who has been told that she is average, or even dumb. I’m sure you can think of many more examples.

While the role of children in shaping their environment seems obvious when pointed out, it looks different than the description of children in many parenting books*. Too often, the paradigm seems to be “push the right button, receive the desired behavior,” with little focus on children’s reasons for their behavior (good or bad), or on how the children might be triggering parents’own insecurities about parenting. Not surprisingly, many of these books aren’t written by developmental psychologists.

These four assumptions lead developmental psychologists to ask a special set of questions.

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 newborn’s world would seem like a “blooming, buzzing confusion.” I think most developmental psychologists accept that at the least, babies are born with some basic learning abilities, and an inclination to observe and learn about the world. But psychologists differ on how much “software” babies come with. Some people think we’re born with implicit knowledge of all the grammatical rules of human language; a basic understanding of how objects move (e.g., that they fall), and concepts about other people (e.g., that they have minds and intentions). Others think we develop these concepts early in life, but aren’t born with them. This debate has inspired interesting research on what babies understand about people, things, numbers, and more. The debate will likely continue for decades.

2) Are there developmental stages, and if so, how do people transition between them?
Does development have discrete steps, like a staircase, or is it continuous, like a ramp?

Piaget thought at certain ages, children transition from one way of thinking to a qualitatively different one. Everyone progresses through the same stages in the same order at a similar age. Also, if children have reached a developmental stage in, say, math, then they must have reached it in all other areas of knowledge. (That is, 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). Piaget had an extreme stage theory.

His successors, the Neo-Piagetians, were a little more flexible, particularly about different areas of knowledge and individual differences. However, they still thought that development has steps.

Whether development looks continuous or stage-like depends on how closely you zoom in. If you observe a child two times a month apart, you will observe more abrupt changes than if you observed the child every day for a month.
Courtesy of Getty Images. Grandma is much more likely to say "My, how you've grown!" than Mom, because Mom has seen all the gradual changes in between.

If you ask parents to rate the child’s behavior using a continuous scale, it will look less stage-like than if they use a Likert scale, with discrete numbers on it. It’s hard to tell how much our findings merely reflect our measurement tools, and how much they reflect how children really develop.

3) How do individuals differ in their development?

I think this is pretty self-explanatory.

4) How do changes in the brain contribute to development?
This question is easy to understand, but hard to answer. It’s even harder to study the brain in children than adults.

5) What develops, and how does change occur?
Last year, Anna didn’t understand the principle of “conservation of matter,” but this year she does, and she passed Piaget’s 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 had this year? This difficult, abstract question is the central question of developmental psychology, and probably the hardest to answer.

6) How does the social world contribute to development?
We are constantly observing, imitating, and being taught by other people. We grow up in cultures that provide us with tools for thinking, such as language, writing, the abacus, or the internet. Our cultures also determine how we spend our time, and who we spend it with, at different ages (for example, do children spend more time with age peers, or adults?)

People 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 in our category should and should not behave. We also generally have innate desires to learn from and connect emotionally with other people, and make them 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 new 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.

*This generalization is based on parenting books read between 1995 to 2008, so it may not apply to books published since then, or to books I might have missed. There are also some brilliant exceptions, such as The Heart of Parenting, which explains how to help children recognize and verbalize their emotions.

[This post was inspired by a developmental psychology seminar I took with Dr. Bennett Bertenthal at Indiana University].

Can we diagnose autism using a brain scan?

[Crossposted from Medium].

It seems like every day, a news story breathlessly claims that neuroscientists have found a way to reliably diagnose autism using neuroimaging (usually, fMRI). So, could you go to a hospital, ask for an MRI scan, and be told within a few days whether you or your child are autistic?
Not right now, and probably not any time soon.
Why not?
Above: Neuroscientist Russell Poldrack in an MRI scanner.
Limitations of neuroimaging
Structural neuroimaging won’t tell us anything about autism, because autistic gross anatomy is usually normal. You won’t find any missing parts, tumors, or swollen, inflamed areas. Sometimes, very young children have unusually large heads, but it’s uncommon, and rarely lasts long.
Many of the studies in the news use functional neuroimaging, or fMRI. Participants perform a task while the scanner measures the changes in blood flow that follow neural activity (see this post by Neurologism for more information on what exactly fMRI measures and how it relates to brain activity). A statistical analysis then determines whether an autistic brain’s activity during the task differs from a non-autistic brain’s more than you would expect by chance.

Currently, functional neuroimaging can tell us a lot about groups, but not so much about individuals. In other words, an entire group of autistic brains looks reliably different from a group of neurotypical brains. But we might not be able to look at an individual participant’s brain and determine whether it belongs to an autistic or neurotypical person. Why?

In order to get statistically significant changes during a task, you need to collect many trials from many people. The changes in brain activity you’re looking for are very small, and embedded in noise, so you need large numbers to reach statistical significance. Furthermore, each time any given person performs the task, her brain activity is a little different. One time, she might be thinking about the task; another time, what she’s going to have for dinner; another time, the scanner noise. You need a lot of trials from a lot of participants to make up for that variability.
In order to determine where group differences in brain activity are located, you have to map everybody’s brain onto a 3D coordinate system. But everybody’s brain is different — even neurotypicals of the same age. So, a little distortion necessarily occurs.
[TANGENT FOR PEOPLE WITH MORE OF A NEUROSCIENCE BACKGROUND: One could also use resting state fMRI, where participants lie in the scanner doing nothing instead of performing a task. The participant’s experience is similar to an anatomical scan, but the data resembles a functional scan — you’re still looking at changes in blood flow that reflect brain activity. Resting state scans look at patterns in functional connectivity — which parts of the brain activate (or deactivate) together. It takes a long time to collect data in these studies, because the variability over time is even greater (since participants aren’t even performing a consistent task). Interpreting resting state fMRI can be controversial, and right now, autism studies using this technique are plagued by conflicting results and confounds. We’re not ready to diagnose autism yet using resting state fMRI, either.]
Autism is too heterogeneous.
Autism is heterogeneous. As they say, “if you’ve met one person with autism, you’ve met one person with autism.” It probably isn’t a single type of brain at all. More likely, it’s a bunch of different disabilities with different causes that all happen to lead to the same sorts of behavior. If the autisms have different causes, then the brain signatures are likely to be different, too.
The difference between the brains of any two autistic people might be at least as big as the difference between an autistic and a non-autistic brain. And if so, it will be impossible to find a test that can cleanly separate the two groups.
Autism overlaps with other conditions.
Most of the studies in the news compare autistic to neurotypical brains. That’s the easy comparison. In practice, people would only be scanned if they had some sort of developmental problem that caused concern. So autistic children would be compared to those with various developmental delays, or those with overlapping disabilities, such as ADHD, sensory processing disorder, or specific language impairment. Adults seeking a diagnosis, if not autistic, are also likely to have another disability that affects them enough to make them seek help. Not only does autism resemble other developmental delays and disabilities, but can co-occur with them, and share genetic causes. If a scan can’t reliably distinguish an autistic brain from these other, similar sorts of brains, it’s not ready for real-world use.
Autism occurs in a tiny percentage of the population.
So far, all these problems seem like they could be fixed with better methods and better technology. But a statistical issue — the rarity of autism in the population — places a hard limit on the accuracy of diagnostic tests in principle.
Despite the media hysteria about rising autism rates, autism still affects only about 1–2% of the population. Even the best tests will give you a lot of false positives: most of the people diagnosed with autism will not have it. Even with a 90% accurate test, only 8% of people with “autistic” brains would actually be autistic, as shown in the graph below. This post by autism researcher Jon Brock explains the problem (and the graph) in more detail.
The likelihood of false positives remains high until a test has well over 90% accuracy. It may not be realistic to develop a test that accurate. Source: Jon Brock.
Importantly, the same argument applies no matter what sort of screening test one uses. It doesn’t matter if it’s based on neuroimaging, genetics, a parent survey or the child’s behavior. The same signal detection problem applies.
Whether a high rate of false positives is acceptable is a moral issue, not a scientific one. But autistic children are subjected to stigma, described as burdens who are “missing” from their own lives (perhaps a reason why people fear labels, saying things like “labels are for soup cans”). The hours of therapy they endure involve an opportunity cost — denying them the opportunity to relax, play, and interact with their families. Children with an autism diagnosis are often denied an equal education with their peers, put in isolation rooms or physical restraints, and are physically manhandled and denied the right to say no to such treatment, which some autistic people and parents fear set them up for later abuse. No child should be treated this way, autistic or not. But certainly, nobody would want to risk this sort of treatment for a child who society does not even deem to “need” it.
Since we are unwilling to risk false positives, an autism screening test will probably not exist any time soon.
Does that mean we must give up on recognizing autism altogether? Not necessarily. Although, as we’ve seen, a perfect screening test isn’t possible, clinicians do a pretty good job of recognizing autism in children, based on their observed behavior and parent reports, and they can do so as early as two years old. Furthermore, diagnoses are pretty stable. That is, a child diagnosed with autism often meets criteria for the diagnosis a few years later. So, we can diagnose autism reasonably well — and we don’t even need an expensive MRI scan to do it.
Take Home Message: We cannot diagnose a person with autism using brain scans for several reasons. These include the limits of the technology, the variability within autism, the overlap between autism and other conditions, and the statistical problems with diagnosing any rare condition.


Neurotypical babies' social behavior takes off as their attention to social input plummets: Why we should be wary of autism theories based on attention to people vs. objects

During the second half of the first year, usually around nine months, most babies learn to share attention with others by alternating their gaze between another person and an object. Their repertoire of social gestures expands enormously, too. With such a rapid spurt of social development, typically developing babies must be paying more attention to people and less attention to other things in their environment, right?

As it turns out, when you measure what babies are actually looking at, the opposite is true.

Babies' visual environments
There are lots of theories about what babies learn from their environment, how much they can learn from the environment, and how much must be present innately. For example, is the language babies hear complex and varied enough to allow them to figure out the grammatical rules of language? Or, is an innate grammar-understanding part of the brain necessary to explain it (a "poverty of the stimulus" argument)?  Do babies need lots of exposure to faces to learn to recognize them, or are they just born with a specific part of the brain that processes faces in a unique way that supports recognition? These issues are easy to speculate about, but hard to actually test: you need a way to measure what babies see and hear in their homes and communities. And until recently, this was very hard to do.

One particularly important aspect of babies' environments is the other people they see, particularly their faces. Faces are a particularly important part of the visual environment because they are vital for recognizing others, contain emotional and social information, and convey cues that are helpful for language perception (e.g., mouth movements). So, Swapnaa Jayaraman, Caitlin Fausey, and Linda Smith [1] wanted to measure the faces babies saw during their first year, at home and in the community. How often did they see faces? Whose faces did they see? How close up were they, and what parts were visible? Did these variables change as babies grew?

They measured the faces babies saw using small head cameras mounted on top of a hat, which babies wore1. The cameras showed a broad view of whatever was directly in front of the child's head. Parents were shown how to use the camera and asked to try to capture 4-6 hours of video during a variety of daily activities while the baby was awake and alert. They were given up to two weeks to make the recordings.

Left: A baby sits in a toy-covered baby seat at home, wearing a blue soft hat with a head camera on top. Right: Examples of three 5-second frames recorded by the head camera, showing a woman spooning out food and bringing it towards the baby. Her head takes up a large percentage of the frame.
Above: a) A baby at home, wearing the head camera mounted on a hat. b) Example frames coded during data analysis.
From Jayaraman, Fausey & Smith (2015).

Families of 22 babies ranging from 1 to 11 months old participated, providing over 100 hours. Most of the recordings were in the child's home (84%), but some took place outdoors or in group settings (11%), in the car (4%), or other locations (2%), such as during errands. From this data, one still frame per five seconds of video was coded (a total of 72,150 frames).  Coders looked for the following:

  1. Is there a face, or part of a face, in the frame?
  2. Whose face is in the image?
  3. Estimated distance of the face from the head camera.  This estimate was made by comparing the face or face parts in the frame with templates created by filming a female face at increments of 1 foot (1 foot, 2 feet, etc.) from the camera.
  4. Are both eyes visible?

Smith's team wanted to know how many faces babies saw, to determine how much experience they actually had looking at faces. They also wanted to know how close-up and clear the faces would be, because quality might matter as well as quantity. Further, they wanted to know how many people's faces babies saw. If babies only saw a few faces, such as those of family members, they might get very good at recognizing their family's and similar-looking faces, but might be less skilled at recognizing very different-looking faces. Lastly, the researchers wondered how these variables changed as babies learned to crawl and walk, and their visual acuity improved.

Smith's team found that babies saw an average of 8 unique people during the videos--but the number ranged from 2 to 20. The number of different faces babies saw wasn't related to age.  However, the most frequently-viewed faces (generally parents) appeared proportionally less often for older babies. (This was true for the most frequent, two most frequent, and three most frequent faces).

Babies are born with very poor eyesight, which gradually gets more acute. So, not surprisingly, faces were under two feet from the youngest babies, and higher distance correlated with greater age.

Regardless of age, babies typically saw faces from the front, with both eyes visible. Thus, they usually get fairly high-quality views of faces.

There was one surprising finding: The proportion of frames containing faces dropped dramatically with age. The youngest babies saw faces nearly 15 minutes out of every recorded hour, while the oldest saw them only about 5 minutes per hour. So as babies are becoming more competent at social interaction behaviors, they are actually getting less exposure to social stimuli.
Above: The proportion of frames containing faces drops by about half between 1 and 11 months.
From Jayaraman, Fausey & Smith (2015).

A brave new world of objects
So, if older babies are seeing fewer faces, what are they looking at instead? Another head camera study by the same research team [2] suggests an answer.

Smith and colleagues compared head camera views from six 1-3 month old babies, who could neither sit independently nor hold objects, with five 7-9 month olds, who could crawl and manipulate objects.  Forty-four hours of video were sampled every 5 seconds. Younger babies saw mostly faces, ceiling, and walls, with very few objects. By contrast, older babies typically saw hands, objects within close reach, and floors. In order to see objects, younger babies have to have these objects placed within their view by others, or the objects must be coincidentally present near where the babies are lying or being held. But when babies learn to crawl (typically around six months), they spend a great deal of time on the floor and can maneuver themselves within reach of many objects.

Objects, not faces, dominate the visual worlds of babies at the very age they are developing joint attention and social gestures.

Researchers in my department are highly aware of this dynamic, and argue that a central problem for babies in the second half of the first year is to balance the competing demands of attending to others with attending to objects. Because attention control is still limited at this age, this is a big challenge.

This increased focus on objects and decreased focus on faces should not be assumed to reflect a lack of social motivation by these typically developing babies (as would be assumed if they were autistic). Rather, developing motor skills are changing what babies see, and therefore what they can attend to.

How do typically developing babies solve the problem of maintaining social engagement in a world of fascinating objects? They use cues produced by others interacting with objects to share attention. Parents' hand movements are coordinated with their eye gaze, and babies can use these movements to determine what parents are attending to. In so doing, babies consistently look at the same object at the same time as parents, an experience that may allow them to appreciate shared attention before they start using eye gaze or facial expressions as a cue.

Implications for social attention theories of autism
Some researchers speculate that autistic children are biased to look at "nonsocial" stimuli, such as objects or interesting geometrical patterns, more than faces early in life. This in turn limits their exposure to faces and the information they convey, potentially delaying their social development.

Ami Klin's team--well-known proponents of this explanation of autism--even argued that whether male "high-risk siblings" were later diagnosed autistic themselves could be predicted based on how much they looked at the eyes while watching short video clips of a female caregiver.  Although this study was widely reported in the media, Jon Brock points out a number of fatal flaws with this study--including that the trajectories of the later-diagnosed-autistic and low-risk control groups did not actually differ until the final test session at 24 months. When the analyses are carefully restricted to 2-6 month olds only, boys who developed autism showed declining eye gaze while low-risk controls showed increasing eye gaze--but this can be explained simply by the fact that the high risk babies had higher eye gaze than the controls to begin with. 

So, there is plenty of reason to be skeptical about this account of autism even on its own terms.

But it's the research with typically developing babies that truly suggests we should take social attention theories of autism with a large dose of salt. Typically developing babies are reducing their attention to faces and increasing their attention to objects, so if the autism theorists are right, their social development should decline. In fact, it soars. Moreover, rather than distracting babies from social engagement, objects and the hands that manipulate them offer new ways to share attention with others. If attention to objects over faces doesn't necessarily impair social development in neurotypical children, there is no reason to assume that it does in autism, either.

Too often, researchers assume a specific trait, such as social disability in autism, and then reach backwards looking for something to explain it. Or, they might see two traits--social disability and avoidance of eye contact--and link them together, because intuitively, eye contact seems related to social functioning. This is not good science, and the flaws of this approach become especially obvious when it is done without reference to how the trait typically develops, as happened here.

To determine the real explanation, we need to use head camera measures like these, along with eye tracking, to better understand what autistic babies are seeing and doing during this crucial developmental stage. How does this compare with typically developing babies? Are they seeing the same amount and type of faces? Do they see fewer faces and more objects during the second half of the first year, too--or might delays in motor development affect this pattern? Do autistic babies also use others' manipulations of objects to share attention and maintain social engagement? If there are differences here, whatever they are, they are likely to be more subtle and interesting than any social attention theories that have so far been proposed.

[1] Swapnaa Jayaraman, Caitlin M. Fausey, and Linda B. Smith (2015). The faces in infant-perspective scences change over the first year of life. PLoS ONE vol. 10 iss. 5, e0123780. Open access PDF.

[2] Swapnaa Jayaraman, Caitlin M. Fausey, and Linda B. Smith (2013). Visual statistics of infants' ordered experiences. Meeting abstract presented at Vision Science Society 2013.

1 A limitation of head cameras is that the head and eyes are not always perfectly aligned, although they usually are--especially for babies. Another limitation is that they miss peripheral information; however, babies' central vision is much more acute and probably more used anyway.


Does language develop differently in autism? [Summary of book chapter]

Image courtesy of ShutterStock.

When autism first appeared in the "diagnostic bible," the 1980 Diagnostic and Statistical Manual, one of the few criteria for diagnosis was "gross deficits in language development" (APA, 1980).  Autism was once associated with:
"marked abnormalities in the production of speech, including volume, pitch, stress, rate, rhythm, and intonation" (1987)
"marked abnormalities in the form or content of speech, including stereotyped and repetitive use of speech" (1987)
"delay in, or total lack of, the development of spoken language." (1994, 2000).
Today, in the most recent version, language disabilities are not even referenced (2013).

So, as the definition of autism expanded, abnormal language development started out as a defining characteristic, then became an optional trait, and now is no longer part of the diagnosis.

This change might seem strange to most people exposed to autism in the media, and even many who know autistic people personally. After all, many autistic children still do not produce spoken language, and some people who speak fluently sound "odd" in their volume, pitch, or even choice of words. So, what is autistic language like? Has it really changed in the past forty-odd years, or have researchers and clinicians just deemed it less essential?

Morton Ann Gernsbacher, Elizabeth Grace, and I tried to find out. We read hundreds of papers on the topic that came out since 2000. These studies examined every imaginable language skill, in every imaginable age group, with every imaginable method. What we learned might surprise you. Details can be found in our book chapter here, but since it will likely be hard to access, I'm summarizing the important points here.

Autistic Language is Often Delayed.
Studies often find that autistic children develop language more slowly than typically-developing peers, especially when it comes to spoken language. They may be delayed in speaking their first words, first combinations of words (e.g., "blue-car") and first grammatical sentences1-7.

Parents report that young autistic children say fewer words than age peers1,8-14. In fact, their concern about late talking often leads them to seek out a diagnosis15.

Parents also often report autistic children understand fewer words1,8,10,11,16-20. However, parents can easily either underestimate or overestimate what a young autistic child knows. If an autistic child responds with atypical words or body language, or does not respond at all, a parent may mistakenly assume the child does not understand. Alternatively, a parent may think a child understands language associated with a routine (e.g., "let's go outside") when the child really only understands the behavior that accompanies it (e.g., taking the child's coat and shoes out of the closet).

Fortunately, there are more objective ways to measure children's language understanding, which involve testing them directly. These include standardized tests such as the Peabody Picture Vocabulary Test (PPVT) and its equivalent, the British Picture Vocabulary Scale (BPVS); the Preschool Language Scale; or the Clinical Evaluations of Language Fundamentals (CELF). Many studies using such tests indicate delays in understanding language, not just speaking8,9,10,17,20-29.

Autistic Language is Variable.
Some studies do not find any difference between autistic people and age peers30-34. These studies range from toddlers to adults, and evaluate skills as various as spoken vocabulary, understood vocabulary, and quality and quantity of writing.

Typically, studies find a wide range of performance in autistic groups. The majority are often unimpaired, while a minority may have significant delays35,36. Some examples:

  • One group surveyed parents of a large sample of autistic toddlers with a wide range of IQ scores. Over three quarters of this group said their first words before 18 months, which is within the range of typical development. However, a little over 5%  had still not spoken their first words by six years of age--a huge delay.37
  • In a group of autistic children and teenagers, half had average receptive vocabulary scores (on the BPVS). One quarter performed one to two standard deviations below average, and another quarter scored over two standard deviations above average.38

Standard scores often range from as low as 4 standard deviations below average to two standard deviations above28,39-41. Thus, autistic people can rank among the most language impaired--or the most verbally gifted.

When researchers measure the rate of language development--instead of ability level at a given moment in time--autistic people are similarly variable.

Sometimes, despite lower initial performance, autistic people develop language skills faster, and for longer, than age peers6,42. Vocabulary may even improve into adulthood43.

However, different individuals have very different rates of language development. The graph below shows the growth in spoken vocabulary development for 35 autistic preschoolers44. Parents reported these children's vocabulary (using the MacArthur-Bates Communicative Development Inventory) four times over two years.

All the children started with a spoken vocabulary of fewer than 60 words, but they ended up with very different vocabulary sizes two years later. Those with the steepest growth could say nearly 700 words at the end of the study; another group showed little change at all. All these children were the same age, with similar levels of autistic traits, and similar measured IQ. Interestingly, they were also all undergoing the same interventions--which included speech and language therapy.

Overall, it seems that language development can be slower than normal during the first few years of life45, but more rapid later on. However, individuals differ so greatly that it would be hard to identify a "typical rate" of autistic language development.

Autistic Language is Similar to that of People with Similar Language Skills.
Psychologists often draw a distinction between "delay" and "deviance." Delay is when a person develops in the same way as others, but does so more slowly. For example, someone with delayed spoken vocabulary might have the vocabulary of the typical two year old at the age of six. Deviance is when a person develops in a qualitatively different way. They might develop a different pattern of skills, or they might develop the same skills in a different order. For example, some people have claimed that autistic people have a unique difficulty understanding nonliteral language, such as metaphors. A person with a disability could, in theory, be delayed, deviant, or both. So, do autistic people have "deviant" language, or are they just more likely to be delayed?

In order to answer this question, we have to compare autistic people to those with similar levels of language development, but who are not autistic. Such comparison groups might include younger typically-developing children, late talkers, or children with specific language impairment. If autistic people are simply delayed, they will learn the same language skills in the same order as these "language-matched" peers.

And in fact, they do.

Autistic children do not have a unique difficulty with learning social or emotional words, or an advantage in learning words associated with special interests. They learn the same words in the same proportion and in the same order as younger typically developing children. For example, they are no less likely to learn words for people or social routines, and no more likely to learn words for vehicles.1 They also are no less likely to say emotion words46.

Autistic people also do not have any reliable difficulty with understanding and using nonliteral language, once their general language delays are taken into account. Autistic children in grade school learn to understand metaphors, draw inferences from stories, and structure their own narratives at the same time as language-matched peers47-52. Their level of language impairment, not their degree of autistic traits, predicts how much difficulty they have with nonliteral language47-51.

Autistic children sometimes develop language for a time, then seem to abruptly lose it--this is called "regression." Some people have argued that regression is characteristic of, and unique to, autism.

Regression is hard to define and measure. However, it seems that only a subgroup of autistic children lose language this way. Interestingly, those who lose language were previously experiencing little or no delay53,54.  Language loss also occurs in a seizure disorder called Landau-Kleffner syndrome.

Some people have claimed that autistic children use language in unique ways--for example, echolalia (repeating what they or others say), or pronoun reversal (e.g., switching "you" for "me" and vice versa). These characteristics appear to occur in only a small minority of autistic children, and are reported less and less frequently now that they are no longer included in the diagnostic manual. They also occur in other disabled groups.

Pronoun reversals do not occur in all autistic children, and they also occur in other populations (see my earlier post here, and Dr. Jon Brock's here). Young typically developing children sometimes confuse first- and second-person pronouns for a short time while learning them55. Children with other developmental disabilities, such as Down Syndrome, also reverse pronouns56.  Like these other groups, autistic children are more likely to have difficulty producing the correct pronouns when using more complex sentences, or complex types of pronouns57-60. Thus, pronoun reversals may be a normal part of early language development; it simply lasts longer in autistic children and those with Down Syndrome because their language develops more slowly.

Echolalia was once viewed as unique to autism. However, very young typically developing children also produced echolalia--that is, they imitate all or part of the preceding utterance without any change. As they get older, they produce less echolalia61,62. Similarly, autistic children also may produce less echolalia as their language improves. The majority of children who were reported to have "lost" their autism diagnosis by age nine had once exhibited echolalia, but no longer did so63. A longitudinal study followed autistic and non-autistic children with language delay and measured their increase in language comprehension. During this time period, both groups made fewer immediate, exact repetitions, and increased their use of mitigated echolalia (e.g., making small changes to the repeated sentence to better express the desired meaning)64. Echolalia appears to be a stepping stone to full self-generated language, and it may last longer in autistic children when their language develops more slowly.

Some people, after observing young autistic children progress from repeating whole phrases unchanged to self-generated speech, have concluded that autistic children must learn language in an entirely different way than typically developing ones. That is, whereas typically developing children first learn what words mean and then how to put them together, autistic children first learn whole phrases, and only later learn what the words mean and what grammatical rules link them together. As far as I know, this hypothesis has yet to be directly tested with a large group of young autistic children. However, there is also nothing more than anecdotal evidence for it. If every known population learns language in one way, the burden of proof must be very high to show that one group learns it in the opposite way.

What can we conclude about language in autism?
In short:

  • Autistic people's language is heterogeneous. Their language ability at any given time ranges from the most delayed to the most advanced possible. Their rate of development ranges from virtually nil44 to nearly ten times that of typically developing peers42
  • Language delays are common in autism.
  • Autistic language is "delayed, not deviant." Researchers have yet to identify any characteristics of autistic language that are universal in autism or cannot be found in other groups. Autistic language is not unique, but continuous with typical development and language disabilities.

1. Charman, T., Drew, A., Baird, C., & Baird, G. (2003). Measuring early language development in preschool children with autism spectrum disorder using the MacArthur Communicative Development Inventory (Infant Form). Journal of Child Language, 30, 213 -236.
2. Matson, J. L., Mahan, S., Kozlowski, A. M., & Shoemaker, M. (2010). Developmental milestones in toddlers with autistic disorder, pervasive developmental disorder-not otherwise specified, and atypical development. Developmental Neurorehabilitation, 13, 239 -247.
3. Grandgeorge, M., Hausberger, M., Tordjman, S., Deleau, M., Lazartigues, A., & Lemonnier, E. (2009). Environmental factors influence language development in children with autism spectrum disorders. PLoS ONE, 4.
4. Kenworthy, L., Wallace, G. L., Powell, K., Anselmo, C., Martin, A., & Black, D. O. (2012). Early language milestones predict later language, but not autism symptoms in higher functioning children with autism spectrum disorders. Research in Autism Spectrum Disorders, 6, 1194 -1202.
5. Pry, R., Peterson, A. F., & Baghdadli, A. M. (2011). On general and specific markers of lexical development in children with autism from 5 to 8 years of age. Research in Autism Spectrum Disorders, 5, 1243- 1252.
6. Anderson, K., Lord, C., Risi, S., DiLavore, P. S., Shulman, C., Thurm, A., et al. (2007). Patterns of growth in verbal abilities among children with autism spectrum disorder. Journal of Counseling and Clinical Psychology, 75, 594- 604
7. Wodka, E. L., Mathy, P., & Kalb, L. (2013). Predictors of phrase and fluent speech in children with autism and severe language delay. Pediatrics, 131, e1128- e1134.
8. Fulton, M. L., & D’Entremont, B. (2013). Utility of the psychoeducational profile-3 for assessing cognitive and language skills of children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 43, 2460- 2471.
9. Kover, S. T., McDuffie, A. S., Hagerman, R. J., & Abbeduto, L. (2013). Receptive vocabulary in boys with autism spectrum disorder: Cross-sectional developmental trajectories. Journal of Autism and Developmental Disorders, 43, 2696- 2709.
10. Luyster, R. J., Kadlec, M. B., Carter, A., & Tager-Flusberg, H. (2008). Language assessment and development in toddlers with autism spectrum disorders. Journal of Autism and Developmental Disorders, 38, 1426- 1438.
11. Luyster, R., Lopez, K., & Lord, C. (2007). Characterizing communicative development in children referred for autism spectrum disorder using the Mac-Arthur Bates Communicative Development Inventory (CDI). Journal of Child Language, 34, 623- 654.
12.Miniscalco, C., Fra¨nberg, J., Schachinger-Lorentzon, U., & Gillberg, C. (2012). Meaning what you say? Comprehension and word production in young children with autism. Research in Autism Spectrum Disorders, 6, 204- 211.
13. Sandercock, R. K. (2013). Gesture as a predictor of language development in infants at high risk for autism spectrum disorders (unpublished doctoral dissertation). Pittsburgh, PA: University of Pittsburgh.
14. Stone, W. L., & Yoder, P. J. (2001). Predicting spoken language level in children with autism spectrum disorders. Autism, 5, 341 -361.
15. Agin, M. C. (2004). The “late talker”—When silence isn’t golden. Contemporary Pediatrics, 21, 22 -32.
16. Maljaars, J., Noens, I., Scholte, E., & Van Berckelaer-Onnes, I. (2012). Language in low-functioning children with autistic disorder: Differences between receptive and expressive skills and concurrent predictors of language. Journal of Autism and Developmental Disorders, 42, 2181- 2191.
17. Miniscalco et al., 2012
18. Paul, R., Chawarska, K., Cicchetti, D., & Volkmar, F. (2008). Language outcomes of toddlers with autism spectrum disorders: A two year follow-up. Autism Research, 1, 97 -107.
19. Paul, R., Chawarska, K., Fowler, C., Cicchetti, D., & Volkmar, F. (2007). “Listen my children and you shall hear”: Auditory preferences in toddlers with autism spectrum disorders. Journal of Speech, Language, and Hearing Research, 50, 1350- 1364.
20. Vanvuchelen, M., Roeyers, R., & DeWeerdt, W. (2011). Imitation assessment and its utility to the diagnosis of autism: Evidence from consecutive clinical preschool referrals for suspected autism. Journal of Autism and Developmental Disorders, 41, 484- 496.
21. Grigorenko, E. L., Klin, A., Pauls, D. L., Senft, R., Hooper, C., & Volkmar, F. (2002). A descriptive study of hyperlexia in a clinically referred sample of children with developmental delays. Journal of Autism and Developmental Disorders, 32, 3 12.
22. Howlin, P. (2003). Outcome in high-functioning adults with autism with and without early language delays: Implications for the differentiation between autism and asperger syndrome. Journal of Autism and Developmental Disorders, 33, 3 13.
23.  Sigman, M., & McGovern, C. W. (2005). Improvement in cognitive and language skills from preschool to adolescence in autism. Journal of Autism and Developmental Disorders, 35, 15 23
24. Wisdom, S. N., Dyck, M. J., Piek, J. P., Hay, D., & Hallmayer, J. (2007). Can autism, language, and coordination disorders be differentiated based on ability profiles? European Child and Adolescent Psychiatry, 16, 178 186.
25. Sutera, S., Pandey, J., Esser, E. L., Rosenthal, M. A., Wilson, L. B., Barton, M., et al. (2007). Predictors of optimal outcome in toddlers diagnosed with autism spectrum disorders. Journal of Autism and Developmental Disorders, 37, 98- 107.
26. Swensen, L. D., Kelley, E., Fein, D., & Naigles, L. R. (2007). Processes of language acquisition in children with autism: Evidence from preferential looking. Child Development, 78, 542 557.
27. Hudry, K., Leadbitter, K., Temple, K., Slonims, V., McConachie, H., Aldred, C., et al. (2010). Preschoolers with autism show greater impairment in receptive compared with expressive language abilities. International Journal of Communication Disorders, 45, 681- 690.
28. Jasmin, E., Couture, M., McKinely, P., Reid, G., Fombonne, E., & Gisel, E. (2009). Sensori-motor and daily living skills of preschool children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 39, 231- 241.
29. Walton, K. M., & Ingersoll, B. R. (2013). Expressive and receptive fast-mapping in children with autism spectrum disorders and typical development: The influence of orienting cues. Research in Autism Spectrum Disorders, 7, 687 -698.
30. Goodwin, A., Fein, D., & Naigles, L. R. (2012). Comprehension of wh-questions precedes their production in typical development and autism spectrum disorders. Autism Research, 5, 109- 123.
31. A°sberg, J. (2010). Patterns of language and discourse comprehension skills in school-aged children with autism spectrum disorders. Scandinavian Journal of Psychology, 51, 534 -539
32. Henderson, L. M., Clarke, P. J., & Snowling, M. J. (2011). Accessing and selecting word meaning in autism spectrum disorder. Journal of Child Psychology and Psychiatry, 52, 964-973.
33. Paul, R., Augustyn, A., Klin, A., & Volkmar, F. R. (2005). Perception and production of prosody by speakers with autism spectrum disorders. Journal of Autism and Developmental Disabilities, 35, 205- 220.
34. Troyb, E. (2011). Academic abilities in children and adolescents with a history of autism spectrum disorders who have achieved optimal outcomes (unpublished master’s thesis, paper 189). Storrs, CT: University of Connecticut.
35. Jones, C. D., & Schwartz, I. S. (2009). When asking questions is not enough: An observational study of social communication differences in high functioning children with autism. Journal of Autism and Developmental Disorders, 39, 432 -443.
36. A°sberg, J., & Dahlgren Sandberg, A. (2012). Dyslexic, delayed, precocious, or just normal? Word reading skills of children with autism spectrum disorders. Journal of Research in Reading, 35, 20 -31.
37. Wilson, S., Djukic, A., Shinnar, S., Dharmani, C., & Rapin, I. (2003). Clinical characteristics of language regression in children. Developmental Medicine & Child Neurology, 45(8), 508 -514.
38. McCann, J., Peppe´, S., Gibbon, F. E., O’Hare, A., & Rutherford, M. (2005). Prosody and its relationship to language in school-aged children with high-functioning autism (working paper WP-3). Queen Margaret University College Speech Science Research Center.
39. Nation, K., Clarke, P., Wright, B., & Williams, C. (2006). Patterns of reading ability in children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 36, 911- 919.
40. Joseph, R. M., McGrath, L. M., & Tager-Flusberg, H. (2005). Executive dysfunction and its relation to language ability in verbal school-age children with autism. Developmental Neuropsychology, 27, 361 378
41. Ricketts, J., Jones, C. R. G., Happe´, F., & Charman, T. (2013). Reading comprehension in autism spectrum disorders: The role of oral language and social functioning. Journal of Autism and Developmental Disorders, 43, 807- 816.
42. Cariello, A., Bigler, E. D., Tolley, S. E., Prigge, M. D., Neeley, E. S., Lange, N, et al. (2011, May). A longitudinal look at expressive, receptive, and total language development in individuals with autism spectrum disorders. Paper presented at the International Meeting for Autism Research, San Sebastian, Spain.
43. Mawhood, L., Howlin, P., & Rutter, M. (2000). Autism and developmental receptive language disorder—A comparative follow-up in early adult life. I: Cognitive and language outcomes. Journal of Child Psychology and Psychiatry, 41, 547- 559.
44. Smith, V., Mirenda, P., & Zaidman-Zait, A. (2007). Predictors of expressive vocabulary growth in children with autism. Journal of Speech, Language, and Hearing Research, 50, 149- 160.
45. Landa, R., & Garrett-Mayer, E. (2006). Development in infants with autism spectrum disorders: A prospective study. Journal of Child Psychology and Psychiatry, 47, 629 -638.
46. Ellis Weismer, S., Gernsbacher, M. A., Stronach, S., Karasinski, K., Eernisse, E. R., Venker, C. E., et al. (2011). Lexical and grammatical skills in toddlers on the autism spectrum compared to late talking toddlers. Journal of Autism and Developmental Disorders, 41, 1065- 1075.
47. Norbury, C. F. (2004). Factors supporting idiom comprehension in children with communication disorders. Journal of Speech, Language, and Hearing Research, 47, 1179- 1193.
48. Norbury, C. F. (2005a). Barking up the wrong tree? Lexical ambiguity resolution in children with language impairments and autistic spectrum disorders. Journal of Experimental Child Psychology, 90, 142- 171.
49. Norbury, C. F. (2005b). The relationship between theory of mind and metaphor: Evidence from children with language impairment and autistic spectrum disorder. British Journal of Developmental Psychology, 23, 383- 399.
50. Norbury, C. F., & Bishop, D. V. M. (2002). Inferential processing and story recall in children with communication problems: A comparison of specific language impairment, pragmatic language impairment and high-functioning autism. International Journal of Language Communication Disorders, 37, 227- 251.
51. Norbury, C. F., & Bishop, D. V. M. (2003). Narrative skills of children with communication impairments. International Journal of Language Communication Disorders, 38, 287- 313.
52. Young, E. C., Diehl, J. J., Morris, D., Hyman, S. L., & Bennetto, L. (2005). The use of two language tests to identify pragmatic language problems in children with autism spectrum disorders. Language, Speech, and Hearing Services in Schools, 36, 62 -72.
53. Baird, G., Charman, T., Pickles, A., Chandler, S., Loucas, T., Meldrum, D., et al. (2008). Regression, developmental trajectory and associated problems in disorders in the autism spectrum: The SNAP study. Journal of Autism and Developmental Disorders, 38, 1827- 1836.
54. Pickles, A., Simonoff, E., Conti-Ramsden, G., Falcaro, M., Simkin, Z., Charman, T., et al. (2009). Loss of language in early development of autism and specific language impairment. Journal of Child Psychology and Psychiatry, 50, 843 -852.
55. Evans, K. E., & Demuth, K. (2012). Individual differences in pronoun reversal: Evidence from two longitudinal case studies. Journal of Child Language, 39, 162-191.
56. Warner, G., Moss, J., Smith, P., & Howlin, P. (2014). Autism characteristics and behavioral disturbances in ~500 children with Down’s syndrome in England and Wales. Autism Research, 7, 433-41
57. Arnold, J. E., Bennetto, L., & Diehl, J. J. (2009). Reference production in young speakers with and without autism: Effects of discourse status and processing constraints. Cognition, 110, 131-146.
58. Fortunato-Tavares, T., Andrade, C. R., Befi-Lopes, D,. Limongi, S. O., Fernandes, F. D., & Schwartz, R. G. (2015). Syntactic comprehension and working memory in children with specific language impairment, autism or Down syndrome. Clinical Linguistics & Phonetics, 29, 499-522
59. Perovic, A., Modyanova, N., & Wexler, K. (2013). Comprehension of reflexive and personal pronouns in children with autism: A syntactic or pragmatic deficit? Applied Psycholinguistics, 34, 813-835.
60. Terzi, A., Marinis, T., Katsopoulou, A., & Francis, K. (2014). Grammatical abilities of Greek-speaking children with autism. Language Acquisition, 21, 4-44.
61. Bloom, L., Rocissano, L., & Hood, L. (1976). Adult-child discourse: Developmental interaction between information processing and linguistic knowledge. Cognitive Psychology, 8, 521-552
62. van Santen, J. P. H., Sproat, R. W., & Hill, A. P. (2013). Quantifying repetitive speech in autism spectrum disorders and language impairment. Autism Research, 6, 372-383.
63. Kelley, E., Paul, J. J., Fein, D., & Naigles, L. R. (2006). Residual language deficits in optimal outcome children with a history of autism. Journal of Autism and Developmental Disorders, 36, 897-828.
64. Roberts, J. M. A. (2014). Echolalia and language development in children with autism. In J. Arciuli & J. Brock (Eds.), Communication in autism (pp. 55-73). Amsterdam: John Benjamins.