CRACKING THE ENIGMA

Conference report: BioAutism 2012

2012-02-07T19:30:00.000-08:00

BioAutism speakers and organisers. Photo by Dee McGrath (QBI).

A couple of weeks ago, I attended the BioAutism 2012 conference at the (very swanky) Queensland Brain Institute in Brisbane. It was a pretty long day for me but, although I was cursing when my alarm went off at 4:30am, it was well worth the trip.

What struck me as I sat waiting for the plane home, digesting the meeting (and a slightly plasticky pizza), is that there are a whole lot of Australian autism researchers doing a whole lot of really interesting work. If there was a theme to the meeting, it was one of people looking at familiar problems in unfamiliar and innovative ways.

Rather than trying to describe all 13 presentations, I thought I'd share three that really illustrate this point.

Broader Autism Phenotype in extended families

The first example came from a presentation by Natasha Brown, looking at the broader autism phenotype - the idea that relatives of people with autism tend to have some traits characteristic of autism, even if they don't actually meet criteria for autism themselves.

The conventional approach is to just look at a group of people who have an autistic relative and compare them to a group of people who don't. However, as Brown pointed out, it's becoming increasingly apparent that there are a wide range of different genetic events that are implicated in causing autism, so lumping relatives of different autistic people together risks losing or diluting a lot of useful information at both the clinical and the genetic level.

The approach that Brown and colleagues are taking is to identify extended families that include multiple autistic individuals, look at how different autistic traits cluster together, and then look for genetic anomalies that predict whether a person within the family will be autistic or show substantial autistic traits. Brown presented data from one family that included nine individuals with autism and 15 with the broader autism phenotype. By looking at the family tree and comparing this to the results of genetic testing, they were able to tentatively link the presence of autism or autistic traits to a small region on chromosome 17.

Gut malfunction in a mouse model of autism

A second example of a slightly leftfield approach was work presented by Elisa Hill, also of Melbourne Uni. Like other research groups across the world, she and her colleagues have been looking at the behaviour of mice with a mutation of the Neuroligin gene and the effects of different drugs on those behaviours.

But they have also been looking at how the genetic mutations affect the intestines of these mice. It turns out that we (as in us vertebrates) have a complete nervous system in our intestines, known as the enteric nervous system; and that genes expressed in the brain are also expressed in the gut. Hill and colleagues dissected out the colons of some of the mice and measured the colonic muscle contractions in response to different drug solutions. The muscle contractions were reduced in the mutant mice, suggesting that the mutation affected the way the gut works.

This is pretty interesting because many people with autism have gastro-intestinal problems, leading to the hypothesis that gut problems somehow cause autism. Hill's preliminary findings point towards an alternative explanation for this link - certain mutations that cause autism might also lead to malfunction of the gut.

Individual differences in responsiveness to intervention

Finally, Giacomo Vivanti from Latrobe University presented some preliminary findings from a study looking at the effectiveness of the Early Start Denver Model intervention. Compared to other interventions, this has a relatively good evidence base, with a randomized control trial suggesting that kids with autism on the program tend to do better than those who don't get the intervention.

However, as Vivanti noted, not all kids derive the same benefit. Some show huge improvements, but others are less responsive. So rather than just seeing whether the intervention overall had a net positive effect, the Latrobe researchers are trying to work out whether there are characteristics of individual children that predict the extent to which they are likely to benefit.

The preliminary results were encouraging and somewhat surprising. The best predictor wasn't a measure of language use or social interaction, as I would have expected, but how much the kids interacted appropriately with objects.

On reflection, this perhaps makes sense, if we assume that kids who don't interact with objects are less likely to engage in the activities that are involved in the intervention, and so are less likely to benefit. It's still very early days with this research, but I'm convinced that this strategy is the way to go for intervention research.

Further reading:

Autism Research Australasia: BioAutism 2011
The Tumultuous Truth: Asia Pacific Autism Conference

The Adventures of DataThief

2012-01-20T15:34:00.000-08:00

DataThief by Jed Pascoe: Reproduced with the artist's permission

Having spent much of the past week struggling to make sense of my data, it’s good to come home, pour a glass of wine, put on some Sharon Jones, and, er… play with somebody else’s data!

Recently, I’ve discovered DataThief - an application that allows you to scan in a graph from a paper and extract the data points. Sometimes, this provides insights that really aren’t obvious from the original paper.

The other week, for example, I came across an intriguing neuroimaging study reported on the SFARI website. In the study, Judith Verhoeven and colleagues used diffusion tensor MRI to examine the superior longitudinal fasciculus, a bundle of nerve fibres that is assumed (although see this paper) to connect two brain regions involved in language production and comprehension - Broca’s area (left front-ish) with Wernicke’s area (left and back a bit).

Verhoeven et al. reported that integrity of the superior longitudinal fasciculus was compromised in kids with specific language impairment (SLI) – that is, kids who have language difficulties for no obvious reason. However, the same was not true of kids with autism, even though they had poorer language skills than those with SLI.

Taken at face value, this is a pretty major blow to the idea that autism and SLI have anything more than a superficial resemblance [pdf].

DataThief, however, suggests otherwise.

The figure below is a scatterplot with each coloured shape representing a single child. On the x-axis is performance on a language test. On the y-axis is fractional anisotropy (FA) – the imaging measure used to assess the integrity of the left superior longitudinal fasciculus.

Figure 3a from Verhoeven et al 2011, showing integrity of the left superior longitudinal fasciculus plotted against the child's language scores (z-scores). Children with SLI in red, autistic kids are the blue squares. Control children are the green and blue circles.

The purpose of the graph was to show the significant correlation between these two measures in the SLI group. But if we can read off the y-coordinates of each shape, we can show the distribution of fractional anisotropy scores for all three groups.

Cue DataThief.

It’s really just a case of clicking on three reference points for which you know the coordinates and then clicking on each of the data points in turn. Then you simply export the coordinates of the data points as a text file. The only thing I had to remember was to do the three groups separately so I knew which point belonged in which group.

Here’s the fractional anisotropy data replotted to show the distribution for each group. What we can now see is that there is a small subgroup of control kids who have really high FAs. There is also one autistic kid and one kid (arguably two) with SLI who have low FAs. Everyone else is pretty much in the middle.

Verhoeven et al.'s data replotted to show the distribution of fractional anisotropy for each group

On average, kids with SLI have lower than ‘normal’ fractional anisotropy [1], but looking at the spread of scores, you’d be hard pressed to conclude that this was a characteristic of SLI. Likewise, the overlap between the distributions of the autism and SLI groups is almost complete. Hardly evidence for fundamentally different neural mechanisms in the two disorders.

At the risk of sounding like a broken record, this once again highlights the importance of looking at individual variation within diagnostic groups such as autism and SLI, rather than (or as well as) looking at group averages.

But it also emphasizes a more general point (and this I have to stress is no criticism of the authors of this particular paper).

The data reported in a journal article are really just a snapshot of the actual data recorded, filtered through the authors’ preconceptions about what questions are interesting to ask and how to go about doing that. There’s an imperative to present the data in a neat, sanitized package, with all the rough edges and anomalies smoothed out; to tell a coherent story that will convince reviewers and editors that it’s worthy of publication in a reputable journal. Years of work and terabytes of data may be compressed into just two or three pages.

DataThief only takes us so far. It allows us to extract the information presented visually in the published article, but no further.

Most of the past week has been spent convincing myself that it doesn’t really matter how I analyse my data because the results come out the same regardless. This is reassuring for me, but it doesn’t mean that somebody else, looking at my data with fresh eyes and a different perspective, would not come to an entirely different set of conclusions.

In an ideal world, when a paper is published, researchers should also be able (and encouraged) to publish the data on which the paper is based, as well as the script showing exactly how those data were analysed.

There are, of course, many obstacles in the way and questions to be answered before this becomes standard practice. Who would host and maintain the data? Just how raw should the raw data be? What if the authors are writing multiple papers based on the same data set? Who gets credit for reanalyses of the data set? What happens if a reanalysis shows up an error in the original paper? If the research involves human participants, how do we reassure them that their anonymity will be maintained?

Undoubtedly, there are many more problems that I haven't thought of. But, as scientists, we need to work through these issues and find ways to set our data free.

Footnotes:

[1] The analyses involved an ANOVA with left and right hemisphere as a within-subjects factor. This showed a main effect of group, but no group by hemisphere interaction.

Update:

Originally, I linked to the wrong SFARI article in the third paragraph. That's now fixed. The one I mistakenly linked to reports a conference presentation that does indicate atypical connectivity between language regions in the brains of nonverbal autistic kids (although not the same pathway as examined by Verhoeven et al.)

Further reading:

Dana Foundation Blog: The Power of Data

Reference:

Verhoeven, J., Rommel, N., Prodi, E., Leemans, A., Zink, I., Vandewalle, E., Noens, I., Wagemans, J., Steyaert, J., Boets, B., Van de Winckel, A., De Cock, P., Lagae, L., & Sunaert, S. (2011). Is There a Common Neuroanatomical Substrate of Language Deficit between Autism Spectrum Disorder and Specific Language Impairment? Cerebral Cortex DOI: 10.1093/cercor/bhr292

Take part in our research on language and auditory processing

2012-01-19T20:52:00.000-08:00

We’re looking for kids with autism as well as typically developing kids to take part in our research.

The study is looking at how kids’ brains respond to different sounds, and how this relates to their language and communication skills.

We are using a technique known as magnetoencephalography or MEG for short. MEG works by measuring the tiny magnetic signals naturally emitted by neurons in the brain. It will tell us which parts of the kids’ brains are responding, how quickly, and how sensitive they are to subtle changes in the sounds they are hearing.

It involves absolutely no physical risks. Kids get to go in a “space rocket”, watch a movie of their choice - and get paid!

If you’d like your child to take part, please ring Shu Yau (02 98504314) or email shu.yau@mq.edu.au

Who can take part in the study?

We are currently recruiting children aged 5-12 years, who live in the Sydney area:

Children on the autism spectrum (i.e., children with a diagnosis of autism, autism spectrum disorder, Asperger syndrome, or PDD-NOS). Our only criterion is that kids need to have at least some spoken language and can complete the different tasks.
Typically developing children (i.e., non-autistic children with no language or communication difficulties or epilepsy). These children are very important because they provide an objective age-matched comparison.

What would happen if my child took part in this research?

Firstly, you and your child would be invited to the KIT-Macquarie Brain Research laboratory to meet the researchers and become familiar with the MEG lab. It is important for us to take time to get to know you and your child before we proceed with the study. We will help the children understand what will be expected of them if they decide to take part. For the younger ones, we also give out prizes and certificates to show that they are qualified MEG astronauts!

If you and your child are happy to proceed, we will start with a short hearing screening test, using headphones, to establish the softest sound your child can hear. Then we will proceed to the MEG, where they will lie on a bed and listen to sounds while watching a DVD of their choice. After the MEG recording, your child will complete some behavioural tasks to give us a record of his/her cognitive, social and communicative skills. These involve playing with toys (for the younger ones), storybooks and computer games.

For some children, a second visit may be scheduled to complete the MEG recording, if they wish, or if the child prefers to finish the behavioural tests on another day.

For parents, we would send you a brief questionnaire concerning your child’s social and communication skills. We’d give you a freepost envelope so you could complete it and post it back to us in your own time, free of charge.

Do we get paid for taking part?

Yes. We pay $40 for the first MEG visit, and $20 for each subsequent visit to complete behavioural testing.

Where and when would the research take place?

The study will take place at a time that suits you, and can be split into two or more sessions if needed. The MEG system is at the KIT-Macquarie Brain Research laboratory at 299 Lane Cove Road, close to Macquarie Park station.

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Are there any risks involved in this research?

There are absolutely no physical risks involved in the study. If your child became tired or anxious, testing would stop immediately. Unlike other brain imaging techniques, MEG is silent, doesn’t involve things being stuck to the child’s head (except for a swimming cap), and you will be able to stay with your child the entire time. The short hearing test is just a screening test, but we will alert you immediately if we suspect hearing loss/impairment in your child.

What happens to the information recorded?

The information we record during this study will be treated in strictest confidence and we certainly wouldn’t pass on any information about your child to anyone outside the research project without your written permission. Your child’s scores on the various tests would be coded and stored on a computer with password protection. They would be given an ID number so that nobody outside the research project knows their real name.

How will I find out about the outcomes of the research?

We will send you a summary of the research project and its outcomes. We will also send you a summary of your child’s scores on the different tests, which you may take to clinicians if you wish.

What happens if I change my mind?

You are free to withdraw your child from the research study at any time. You don't have to give a reason and you'll still get paid.

Who is conducting the research?

The study is being conducted by Shu Yau, as part of her PhD, supervised by Dr Jon Brock at the Macquarie Centre for Cognitive Science. It is part of a larger research program funded by the Australian Research Council and Macquarie University.

Would we be asked to take part in other studies?

If you’d like to get involved in other research projects, we can send you information about future studies. But there is absolutely no obligation for you to take part in these.

I'm still interested. What do I do now?

If having got this far, you're still interested in your child taking part, please phone Shu Yau (PhD student) at 0298504314 or email shu.yau@mq.edu.au

The ethical aspects of this study have been approved by the Macquarie University Human Research Ethics Committee. If you have any complaints or reservations about any ethical aspect of your participation in this research, you may contact the Committee through the Director, Research Ethics (telephone (02) 9850 7854; email ethics@mq.edu.au). Any complaint you make will be treated in confidence and investigated, and you will be informed of the outcome.

Do kids with autism have big brains?

2012-01-13T04:51:00.000-08:00

Brain coral, the Whitsundays, Australia

Like most things in autism research, the idea that people with autism have big brains goes back to an observation in Leo Kanner’s original autism paper, where he noted that some of the kids in his group had larger than normal heads. Over the years, there have been dozens of studies looking directly or indirectly at the issue of brain size in autism. In 2005, Martha Herbert provided a comprehensive review [pdf] of 25 such studies, describing the tendency towards large brains as "the most replicated finding in autism neuroanatomy".

Redcay & Courchesne 2005

Also in 2005, Elizabeth Redcay and Eric Courchesne published a meta-analysis, in which they ingeniously plotted how much bigger or smaller than average the autism brains in different studies were as a function of the mean age of the participants in the study. They concluded that there is an early period of brain ‘overgrowth’, with autistic brains being on average 10% larger than normal. But then growth slows down and typically developing kids eventually catch up.

Redcay & Courchesne's meta analysis. Red circles (my annotation) indicate studies in which brain volume was inferred from head circumference measures.

Redcay and Courchesne's paper has been extremely influential. But their analysis rests on a number of assumptions that are worth highlighting.

First, the data are cross-sectional. Different people are being measured at each of the different ages. This is inevitable because brain imagining technology hasn't been around long enough for a proper longitudinal study be conducted, following individuals over the first decades of their life. But if we think of the curve as being the actual growth trajectory of a person with autism (as Redcay and Courchesne want us to) then we are essentially assuming that a 30-year-old autistic adult in one study is what a 5-year-old in another study will be like a quarter century from now. This is a pretty big assumption.

Second, data for the youngest age groups actually came from measurements of head circumference taken during regular infant check-ups, rather than actual brain scans. Head circumference is correlated with brain size in infants, and realistically it's the only way to study brain size in autism pre-diagnosis. But in order to plot the data on the same graph, Redcay and Courchesne had to make quite a few assumptions about the relationship between head size and brain volume [1].

Courchesne et al 2011

More recently, Courchesne and colleagues published an update, pulling together data from all of their MRI studies. The data were still largely cross-sectional but, this time, they fitted growth curves to the data from autistic and non-autistic individuals.

This gives a clearer sense of the variation within each group, which, even for typically developing children (blue circles), is huge. Having a brain that is 10% bigger than average (as Redcay and Courchesne's analysis suggests) isn't actually all that abnormal. Nonetheless, Courchesne et al.'s curve-fitting led them to again conclude that autism is associated with “early brain overgrowth”.

Individual brain volume data as a function of age (Courchesne et al., 2011). Red squares are boys with autism. Blue circles are typically developing boys.

Comparing the two curves suggests that the difference between autistic and non-autistic brains is largest in the period between around 20 and 32 months (which I've conveniently highlighted). However, if we look at the actual data in this period, ignoring the curves, then we see that none of the autistic kids had brains that were unusually large for their age.

The curve for the typically developing boys is strongly curved because it has to fit the data from the youngest kids (12 to 18 months). The autism data don’t start until around 20 months, so the curve is inevitably less curvy. This gives the impression of a big difference in brain size at around 2 years of age, which I don't think really exists in the data.

That being said, there were quite a few 3- to 4-year-olds who did appear to have relatively large brain volumes.

Nordahl et al 2011

Just before Christmas another MRI study of brain size in autism came out. Christine Nordahl and colleagues focused on a narrow age range, around 3 years, when the "overgrowth" appears most evident.

Before discussing their results, it's worth mentioning their methods: While previous MRI studies have involved sedating the kids with autism in order to keep them still (and get them near the scanner in the first place), Nordahl and colleagues' solution was to scan the kids in the dead of night while they slept. Heroically, they scanned 114 autistic kids and 66 non-autistic control children in this way. I imagine a lot of coffee was drunk.

13 of the 114 autistic children met the criteria for megalencephaly - the technical name for a big brain - defined here as having a brain volume that was more than 2 standard deviations greater than the control group mean. Put another way, 89% of the autistic kids had normal-sized brains. This shouldn't be surprising. Courchesne et al.'s study appears to show something similar, as indeed do most of the previous studies of head and brain size.

Nordahl et al. noted that 11 of the 13 autistic kids with large brains were boys who were reported by their parents as having undergone regression - losing skills that they had previously acquired. In fact, when they looked at all the boys who had regressed, they found significantly larger brains than for typically developing boys. And when they looked back at head circumference measures from the first year of life, the boys who went on to regress had significantly larger heads than the typically developing boys from as early as 6 months [3].

In contrast, increased brain and head size was not found in the autistic boys with no history of regression. Nor was it a characteristic of autistic girls, regardless of whether or not they had regressed.

Distribution of head sizes in Nordahl et al (2011). Green line (added) shows the approximate cut-off for magalencephaly in boys

It's fair to say that Nordahl et al.'s results are still preliminary. As the authors note, they rely on parents' reports of their child's early development, which may not be very accurate. Also, there isn't, as far as I can tell, any precedent for a link between regression and increased brain size [2]. So the results should be treated with more caution than if they had been grounded in previous research findings.

Finally, Nordahl et al. only report total brain volume. They didn't look at what parts of the brain were enlarged or otherwise, or whether different types of brain tissue were affected differentially.

Mechanisms of overgrowth

This brings us to the really interesting question, which is not whether kids with autism have large brains (the answer, if you hadn't gathered by now, is that some do and some don't); but why?

A recent study by Courchesne and colleagues linked increased brain size in autism to an increased number of neurons in prefrontal cortex. But in an earlier MRI study, Courchesne et al (2001) reported that it was the white matter (essentially the axons that connect different brain regions) that was disproportionately enlarged in young autistic children.

In her 2005 review, Martha Herbert speculated that increased brain size might be related to reduced brain connectivity (see also this intriguing paper by Sarah White). It's not entirely clear to me how that would work and I'm not aware of any research showing that larger brains are less well connected. It might be that the link is less direct - perhaps a genetic variation that leads to increased brain size also puts a child at increased risk of autism through a different mechanism.

One thing we can be sure of. Making sense of the association between autism and large brains is going to be far from straightforward. Not only do most people with autism not have large brains, but most people with large brains don't have autism [4]. Large brains have also been reported in relation to other disorders including language impairment and ADHD. And just to add further complication and intrigue, there's evidence that relatives of people with autism tend to have large heads, even if they don't have autism themselves.

Here, I think, we have autism research in microcosm. A finding that dates back to Kanner, that consistently holds up across studies, but doesn't hold up across individuals within those studies; overlap with other developmental disorders and continuity with non-autistic family members; and theories that don't quite stand up to close scrutiny. It's an illustration of how complicated the answers we're looking for are likely to be, and the fact that the answers are likely to be different for different individuals.

Footnotes:

[1] In order to convert head circumference into brain volume, Redcay and Courchesne adopted the following procedure:

They took normative data on brain weight at different ages from a Danish post-mortem study and converted this to brain volume based on an estimate of brain density from one of their own studies.
They then matched up the brainweights with normative data on head circumferences from an American study.
These pairs of values were entered into a linear regression analysis, along with data from MRI scans of older children.
The regression equation was used to convert circumference into volume.

It's difficult to see what else they could have done, but given how influential the study has been, it's important to highlight how many assumptions were involved. It's also a little strange that they assumed (or found) a linear relationship between head circumference and brain volume - when mathematics teaches us to expect a cubic relationship between circumference and volume.

[2] I recently came across a blogpost discussing the fact that none of the kids in Kanner's 1943 study had regressed. I can't track this down (please comment if you know what I'm talking about). But, given that Kanner first noted the children's big heads, it would put him at odds with the authors of this paper.

[3] It's not reported whether the boys with large heads at 6 months were the same boys who had large heads at age 3.

[4] I'm not sure if there is any research on this, but if we define megalencephaly as 2 standard deviations from the mean then roughly 2.5% of the population have megalencephaly (assuming a normal distribution). Even with a generous 1% prevalence for autism, I think it's safe to say that the majority of people with megalencephaly are not autistic.

References:

Courchesne, E., Campbell, K., & Solso, S. (2011). Brain growth across the life span in autism: Age-specific changes in anatomical pathology Brain Research, 1380, 138-145 DOI: 10.1016/j.brainres.2010.09.101

Nordahl, C., Lange, N., Li, D., Barnett, L., Lee, A., Buonocore, M., Simon, T., Rogers, S., Ozonoff, S., & Amaral, D. (2011). Brain enlargement is associated with regression in preschool-age boys with autism spectrum disorders Proceedings of the National Academy of Sciences, 108 (50), 20195-20200 DOI: 10.1073/pnas.1107560108 Download PDF

Redcay, E., & Courchesne, E. (2005). When Is the Brain Enlarged in Autism? A Meta-Analysis of All Brain Size Reports Biological Psychiatry, 58 (1), 1-9 DOI: 10.1016/j.biopsych.2005.03.026 Download PDF

2011 Autism Connections

2011-12-28T06:20:00.000-08:00

Memory cell networks by Vishwanathan, Zeringue, & Bi (via Neuro Images)

A small selection of the many wonderful autism-related blogposts I had the pleasure of reading in 2011:

Diagnosing the DSM: Diagnostic Classification Needs Fundamental Reform

2013 will see the release of DSM 5, the latest version of the official guidelines for diagnosing "mental disorders". The preliminary draft was released in 2010 and includes the radical and controversial proposal to merge autistic disorder, Asperger syndrome, and PDD-NOS into a single category of "Autism Spectrum Disorder".

On the Dana Foundation website, Steven Hyman, a member of the DSM-5 task force, discussed the history and limitations of the DSM approach. Although not specifically about autism, the issues Hyman raises are extremely relevant. He finishes with this:

"Whatever the ultimate approach to the DSM-5, it is critical that the scientific community escape the artificial diagnostic silos that control so much research, ultimately to our detriment."

So far as autism research is concerned, I couldn't agree more.

Freeways, autism and correlation versus causation

As Emily Willingham recently pointed out, it seems that virtually every aspect of modern life has at some time been linked to autism. Indeed, you'd be forgiven for not really caring.

In one of the more highly publicized studies of 2011, Volk and colleagues reported that living within 309 metres of a freeway was associated with an increased risk of autism. While it's tempting to conclude (as some people did) that air pollution from traffic causes autism, interpreting such epidemiological data is fraught with difficulties. David Gorski of Science Based Medicine offered, not only a pointed critique of Volk et al.'s study and several alternative explanations, but also some valuable insights into his "love-hate relationship" with epidemiology.

Split brains, autism, and schizophrenia

Autism is complicated. It's clear that it is in large part genetic. However, the more we learn about autism genetics, the more complex the picture becomes. Genetic variations linked to autism don't always lead to autism and are often linked to other disorders such as schizophrenia, epilepsy, or intellectual disability.

On his Wiring the Brain blog, Kevin Mitchell looked at attempts to piece together what role one such gene, DISC1, actually plays in neurodevelopment and how variations might sometimes lead to a failure to connect the right and left hemispheres of the brain. It's a fascinating read, not least for the "final note".

The obsessive joy of autism

November saw the second official "Autistics Speaking Day" - an opportunity for people with autism to educate everybody else about what it's actually like to be autistic and the challenges of being autistic in a non-autistic world. As Corina Becker, who set the ball rolling in 2010 pointed out,

"If people really want to understand autism, they should be listening to Autistic people".

While it's important to remember that the autistic experience isn't necessarily the same for everyone, reading first-hand accounts certainly lends a different perspective and new insights. The Autism and Empathy blog is a particularly fine example of this, challenging the popular "theory" that people with autism lack empathy.

But for me, the most eye-opening first-hand account from 2011 came from Julia Bascom in Shift Journal, where she spoke of the up-sides of autism:

"Neurotypical people pity autistics. I pity neurotypicals. I pity anyone who cannot feel the way that flapping your hands just so amplifies everything you feel and thrusts it up into the air... I pity anyone who is so restrained by what is considered acceptable happiness that they will never understand when I say that sometimes being autistic in this world means walking through a crowd of silently miserable people and holding your happiness like a secret or a baby, letting it warm you as your mind runs on the familiar tracks of an obsession and lights your way through the day."

I don't pretend to understand autism and I'm not sure whether I (or anyone else for that matter) ever will. But this post brought me a step closer.

The last-placing winner

From Autism and Oughtisms. My favourite post of 2011.

Happy New Year.

Further reading:

Autism Speaks Top 10 Autism Research Achievements of 2011
Simons Foundation Autism Research Initiative: Looking back on 2011
Thinking Person's Guide To Autism: 2011: The TPGA Year in Review
Left Brain Right Brain: Around the blogosphere: January 8 2011

A case of colour-emotion synaesthesia?

2011-11-26T13:01:00.001-08:00

Anger he smiles, towering in shiny metallic purple armour. Queen Jealousy, envy waits behind him, her fiery green gown sneers at the grassy ground. Blue are the life giving waters taken for granted, they quietly understand. Once happy turquoise armies lay opposite ready, but wonder why the fight is on.

My red is so confident he flashes trophies of war and ribbons of euphoria. Orange is young, full of daring, but very unsteady for the first go round. My yellow in this case is not so mellow, in fact I'm trying to say it's frightened like me. And all of these emotions of mine keep holding me from givin’ my life to a rainbow like you.

Hendrix fans amongst you will recognise the above as lyrics from Bold as Love, the title track of Jimi's second album. According to the sleevenotes (from a long-lost cassette, so you'll have to trust my memory on this), the concept for the song was the idea of using emotions to describe colours to a blind person. The more obvious interpretation is that Hendrix was using colours as a metaphorical device to describe his own conflicting emotions.

Earlier this week, I was reminded of Bold as Love when I came across an intriguing study reported in the journal, Neurocase [1]. The authors, VS Ramachandran and colleagues, described the case of TK, a young man with Asperger syndrome who was encouraged to use colours to help him understand emotions:

"Around the age of 10 his mother suggested that he attempt to label the feeling of each emotion (presumably based on context, social situation, and facial expressions) with a specific color, in an attempt to relay the appropriate emotions to his father and her. For example, while experiencing what he considered happiness he would tell his parents that he was feeling ‘green’."

"Further, by comparing the color elicited by another person with the emotion that would be associated with the same color in his own mind, TK was able to ‘read’ the other individuals’ emotions more accurately."

"At about the same time that he began associating colors with emotions, he also began seeing colored halos around individuals. The color of these halos corresponds to TK’s emotional stance toward that particular person, and when a new individual is encountered a blue halo emerges de-nouveau and the color evolves progressively with repeated exposure."

Purple haze

To objectively measure the halo perception, Ramachandran et al asked TK to identify letters that were projected onto a white screen. An unfamiliar person, identified as having a blue halo, stood in front of the screen.

If the letters were blue and projected close to the person (i.e., within the halo) then TK was unable to identify the letters above chance levels - presumably because the letters and background appeared to be in the same colour. When the colour was changed or the letters moved to outside the halo, TK's performance was flawless.

It's a shame that the authors weren't able to test TK with a second person standing in front of the screen, whom he perceived as having a different coloured halo. Nonetheless, these results appear to provide some objective confirmation of TK's unusual subjective reports [2].

Love or confusion

In a second experiment, Ramachandran et al tested TK and 15 control subjects on a Stroop interference test.

Participants were given words printed in colour and had to say the colour of each word, ignoring what the word itself said. In the classic version of the test, the words are all themselves colour names.

In the congruent condition, the word matches the colour in which it's printed:

RED BLUE YELLOW GREEN

In the incongruent condition, the word and its colour are mismatched

RED BLUE YELLOW GREEN

People are generally faster to name the ink colours when the word matches the colour. Even though they're supposed to be ignoring what the word says, they can't help but read it, and this affects their response to the actual colour. As you can see from the graph below, TK was no exception. Like the control group, his reaction times were longer for the incongruent condition than for the congruent condition.

TK showed a similar effect when the words were emotions, being quicker to name the colour if the emotion word matched the colour he associated with that emotion (e.g., PRIDE and AGGRESSION) than when they were incongruent. When the control participants were given the same stimuli, they showed no such effect [3].

Ramachandran et al. interpret these findings as evidence of "emotion-colour synaesthesia" - the implication being that TK actually perceives emotions as colours. This is certainly one possibility, but it's worth noting that similar effects are commonly observed in typical adults using non-emotion words that have associations with colours. For example, it's easier and quicker to name the colours in FIRE GRASS LEMON SKY than it is in FIRE GRASS LEMON SKY.

Seeing the word SKY makes us think of the colour blue, which then affects our ability to name colours; but there's no suggestion that we actually perceive the colour blue every time we read SKY. By the same token, TK associates PRIDE with blue and this affects his colour naming, but the data from the Stroop task don't show that he experiences pride as the colour blue.

Crossbrain traffic

It's undoubtedly a fascinating case study. Ramachandran et al.'s data indicate that TK perceives a blue halo around certain people and it's safe to say that he has strong cognitive associations between colours and emotions. However, we are still relying on TK's subjective reports that the halos vary from person to person and that emotions are actually experienced as colours. This is not to cast doubt on TK's reports, merely to note that the objective evidence is not perhaps as strong as the authors claim.

Ramachandran et al. speculate that TK's experiences derive from increased connectivity between brain regions involve in vision (V4), face processing (FFA), and emotion (insula and amygdala). It would certainly be interesting to know whether this is supported by brain imaging.

I'd also like to know more about TK's Asperger's diagnosis and the extent to which his social and communication difficulties could be attributed to problems more specifically with face processing.

Finally, I'd be interested to know how common TK's reported experiences are, and whether other people on the autism spectrum have been able to use colours to help them understand or convey emotions.

Notes:

[1] Thanks to Michelle Dawson for the heads-up. Follow her on Twitter at @autismcrisis

[2] Ramachandran et al. begin the discussion by noting that the magician James Randi has offered a million dollar prize for anyone who can objectively demonstrate the existence of energy fields emanating from people. They then claim to have provided "the first evidence of the existence of this effect". You don't need me to tell you that Randi's million is safe. At best, the study demonstrates that a person genuinely perceives a halo. It doesn't show that the halo is actually there!

[3] Separate from the congruency effect, TK's responses were much slower for emotion words than for colour words. Control subjects didn't show this effect. Ramachandran et al don't discuss this finding and I'm not really sure what to make of it.

Slight return:

NeuroTribes: Inside the mind of a synaesthete
Wiring the Brain: Synaesthesia and Savantism
Terri Drake-Floyd: Your aura is a bit splotchy: Synesthesia revisited
Inkfish: I'm a synesthete. Is something wrong with me?
Asperger's Diary: An encounter with the salesman smile
Incorrect Pleasures: Famous synaesthetes or possible synaesthetes

Reference:

Ramachandran VS, Miller L, Livingstone MS, & Brang D (2011). Colored halos around faces and emotion-evoked colors: A new form of synesthesia. Neurocase PMID: 22115465

Update [9/12/11]:

Some really great comments below. Thanks to everyone for their insights.

This from Rohan, who's a member of the indie rock band Rudely Interrupted:

"our lead vocalist has Aspergers and was born without eyes. He's obsessed with colour. We wrote a song about it (Green Lights) Rory also has perfect and absolute pitch.

All being well, you should be able to listen to the song by clicking the Play button below:

RGreen Lights Green Lights

The many faces of autism

2011-10-26T07:01:00.000-07:00

Evidence and Artifacts: 1 in 110

A few years ago, before I got into autism research, I worked on a couple of projects looking at Down syndrome and Williams syndrome. Down syndrome, I assume, is familiar to most readers. Williams syndrome is much rarer and less well known, but is of considerable interest to researchers, not least because the extremely sociable personalities of many people with Williams syndrome provide an interesting (although complex) contrast with autism.

What these two syndromes have in common is that both are defined in terms of their genetics. Down syndrome is the result of having an extra copy of chromosome 21. Williams involves a deletion of a small sequence of genes on chromosome 7. But even without genetic testing, people with Down's and Williams are pretty easy to identify because each syndrome has its own characteristic facial structure.

Doing research on these two syndromes wasn't easy, but at least we could be confident that the people in our study all had the same condition - and that our participants were coming from the same population as those in other studies by other research groups.

Girls with Williams syndrome (left) and Down syndrome (right)

The same, unfortunately, can't be said about autism. While it's certainly a genetic disorder, in the sense that it is highly heritable, we're still some way from fully understanding what those genetic mechanisms might be. And so, at least for now, autism is defined in terms of behaviour. Show enough atypical behaviours, tick enough boxes, and you get an autism diagnosis.

What this means in practice is that people with autism are an extremely varied bunch. In a 2007 paper [pdf], Daniel Geschwind and Pat Levitt argued that we should really stop talking about autism as if it were a single entity and instead talk about "the autisms" as a collection of distinct disorders.

While this idea has certainly gained some traction, it's still the case that most autism research focuses on the differences between autistic and non-autistic people, ignoring the variation within the groups. Often, the implication is that the group average is somehow representative of all people with autism. But if, as Geschwind and Levitt argue, there really are many autisms, the average of the autism group may not actually be representative of anyone.

A study out last week in the (oddly titled) journal, Molecular Autism, illustrates this point rather nicely in concrete terms. And it does it by looking at differences in facial characteristics.

Facial characteristics of autistic boys

The study was conducted by Kristina Aldridge and colleagues at the University of Missouri. They took multiple photos of 64 boys with autism aged between 8 and 12 years, and then stitched the photographs together to create a 3D realisation of each boy's face. They then identified 17 different points on each face (as shown below) and measured the distance between them. The faces of the autistic boys were then compared with those of 41 typically developing (i.e., non-autistic) boys.

The 17 points used by Aldridge et al to measure facial structure

The press release from the University of Missouri summarises the results as follows:

Children with autism have a broader upper face, including wider eyes.
Children with autism have a shorter middle region of the face, including the cheeks and nose.
Children with autism have a broader or wider mouth and philtrum -- the divot below the nose, above the top lip.

However, a second analysis lends a very different perspective on these results. Aldridge and colleagues performed a cluster analysis of the 64 autistic boys and identified two subgroups with distinctive facial characteristics.

The first subgroup contained 12 boys, who had wider nose and mouth but a shorter distance between the upper and lower parts of the face (see the left face below for an example).

The second subgroup (right face below) contained just 5 boys, and was characterised by a wide upper face.

The faces of the remaining 47 boys were indistinguishable from those of typically developing boys.

Black lines indicate a reduced distance, white lines indicate an increase

These results rather undermine the claims of a "distinct facial phenotype" in autism. On average, the autistic boys had a shorter middle face region and a broader upper face than controls, but these characteristics, it would appear, were actually owned by different individuals. It's quite possible that no single individual actually possessed the average "autistic face". And most of the boys (almost three quarters of the sample) didn't show any of the "distinct" characteristics.

Embryonic ideas

Aldridge et al.'s data show the problems inherent in relying on the group average, but they also demonstrate how much richer an understanding can be gained by considering individual differences within autism.

Citing evidence that the brain and face both develop from the same embryonic structures, Aldridge and colleagues argue that atypical facial structure in autism is a clue to underlying differences in early prenatal development. If we take this at face value (pun intended), then the data actually suggest that there are multiple different ways in which embryonic development can diverge from the typical trajectory, each associated with different facial profiles.

We don’t know (as yet) about the brain structure or function of the boys in this study. However, Aldridge et al do report that these two different facial subgroups differed in terms of their clinical and cognitive profiles. Boys in the first subgroup tended to have more severe autism symptoms, lower IQ, and a higher incidence of regression (loss of skills).

An obvious next question involves the origin of these facial and behavioural differences. Williams syndrome and Down syndrome provide obvious comparisons and suggest a possible genetic cause. The authors note that boys with Fragile X syndrome, chromosomal disorders (like Down syndrome), or copy number variations (like Williams syndrome) were excluded, but it's not clear (to me at least) how consistently the participants were screened, or how easy it would have been to miss a genetic "abnormality". This screening also wouldn't rule out that possibility that particular combinations of common genetic variations could lead to developmental differences

It's also worth considering possible non-genetic influences. Although not implicated in this study, fetal alcohol syndrome provides another example of a syndrome where cognitive developmental problems are associated with distinctive facial features, but in this case the primary cause is environmental rather than genetic.

Kids with fetal alcohol syndrome

It's important not to get too carried away. This is one study. As Uta Frith commented in response to my previous post, ultimately what matters in science is replication. Only time will tell whether the subgroups identified by Aldridge and colleagues fall out of other datasets with other groups of autistic individuals. Perhaps larger studies with additional measures will be able to pull out other subgroups.

The general point will stand, however. Looking at autism in terms of group differences - autism vs not-autism - only gives a limited and sometimes distorted view. Progress in autism research will depend on the investigation of differences within as well as across diagnostic boundaries.

Reference:

Aldridge K, George ID, Cole KK, Austin JR, Takahashi TN, Duan Y, & Miles JH (2011). Facial phenotypes in subgroups of pre-pubertal boys with autism spectrum disorders are correlated with clinical phenotypes. Molecular autism, 2 (1) PMID: 21999758

The paper can be downloaded here (Open Access)

Further coverage:

Deborah Rudacille on the SFARI blog: Facial features provide clue to autism severity

Peer review: Is it all it's cracked up to be?

2011-10-11T06:25:00.000-07:00

Sometimes, it seems as though every new day brings a new groundbreaking finding in the quest to understand autism. New genes discovered. New bits of brain found to be a different shape or size; to be over-activated, underactivated, or not properly connected. New tasks that people with autism are either exceptionally good or exceptionally bad at. New environmental factors linked to an ever so slightly increased chance of having an autistic kid.

With all this progress, it's a wonder we haven't, well, made more progress.

In truth, advances in scientific understanding are a little more gradual than the blizzard of press releases would have you believe. Science is also a fairly haphazard process. Less the sleek and indomitable machine of popular imagination, more like a drunkard trying to find the light switch. Sometimes, science gets it completely wrong and, like my best friend on a caravan holiday, ends up weeing in the oven. True story.

Keeping things as much as possible on the straight and narrow is the process of peer review. Before they can be published as journal articles, scientific papers must be vetted by other researchers in the field. These reviewers will report back to the editor of the journal who ultimately gives the thumbs up or the thumbs down. However, the fact that a paper has successfully run the peer review gauntlet is no guarantee that it's actually any good, that it's free from errors, or that the conclusions reached are justified.

Some journals, let's be frank, will publish any old rubbish. And even well-respected journals sometimes let things slip through the net.

An example I covered a while back. In 2009, the prestigious journal, Biological Psychiatry, published a paper claiming that people with autism have extraordinary visual acuity. To cut a long story short, it’s now clear that there were major problems with the astudy and, as several subsequent studies have shown, people with autism seem to have visual acuity that is distinctly uneaglelike - no better or worse than your average non-autistic person in the street. The reviewers didn’t spot the technical problem. Neither, I should confess, did I initially. But still a peer review #fail.

A more recent example, also coincidentally from Biological Psychiatry, involved a study trying to use MRI brain scans to diagnose autism. Remarkably, one of the measures derived from this process was able to predict the severity of communication difficulties – information that it hadn't been trained on. However, a quick look at Figure 3 in the paper showed a pretty glaring mistake.

Figure 3, Uddin et al, 2011, Biological Psychiatry

The severity scores for three of the autistic kids had been lost but, instead of excluding them from the analysis, the authors had accidentally included them, giving each person a score of zero, as if they didn’t have any communication difficulties. As it happens, the authors have confirmed that the result just about holds up when the analyses are done correctly, although the effect is somewhat diminished. [Update: A correction has now been published to this effect]. The point, nonetheless, is that the paper made it past the reviewers (and eight authors and an editor) without this problem being noticed.

Mistakes such as these are easy to make – and they’re not always so easy to spot. In the case of the brain scan paper, it was only because the actual data points were plotted in a figure in the paper that the error was even visible. Errors buried deep in the analyses may never be discovered. Peer review can't help.

Even when there are no technical problems and the statistical analysis is flawless, there's still no guarantee that the results mean what the authors think they mean. The conclusions drawn depend on assumptions about what the tests are actually measuring. If those assumptions are wrong then so too might be the conclusions.

A classic example, again from the autism literature. In 1991, Josef Perner and Sue Leekam reported a neat dissociation - kids with autism failed to comprehend that a person could believe something that wasn't true any more, but those same kids were perfectly able to understand that a photograph could show a scene that had since changed.

The false photograph task by Axel Sheffler

The conclusion at the time was that kids with autism must have a very specific problem with understanding other people's mental states, otherwise they would have found both tasks equally difficult.However, this story has gradually unravelled. As Perner and Leekam have latterly argued, the two tasks aren't really equivalent at all. In particular, a photograph isn't a false representation of the present (in the way that a false belief can be), but a true representation of the past. As such, the conclusions of a specific problem with mental states were not warranted.

In hindsight it all seems quite obvious. Indeed, it is really only with hindsight that we can see which ideas, studies, and methods were the ones worth following.

This, in essence, is why scientific progress is slow and haphazard.And while peer review does serve a function, at best it's a crude spam filter for weeding out those papers that are most obviously problematic. It isn't a stamp of scientific truth, because there is no such thing as scientific truth. We shouldn't be shocked or surprised when results don't hold up. Even good science can be wrong - and it frequently is.

What is absolutely critical is that any statement presented as being "science-based" is backed up with a clear report of how the data were collected and analysed. Then the whole world can see how you reached those conclusions; where the problems in your method, your analysis, your conclusions might lie.

Further reading:

Plus Ultratech: Will Google Scholar dominate the world of research?
Tom Hartley: A parable
Brad Voytek: Peer review does not equal publisher-owned journal
Alex Holcombe: Everything's fine with peer review

The post that got me writing this:

Petroc Sumner, Frederic Boy, Chris Chambers: Scientists should be allowed to check stories on their work before publication

And a response:

Emily Willingham: What's wrong with this piece on science and journalism?

The curious case of the reversed pronoun

2011-08-19T04:58:00.000-07:00

"In solving a problem of this sort, the grand thing is to be able to reason backward."

“You made a circle”, exclaimed Ethan, looking up from his drawing.

“You did make a circle”, his mum acknowledged, ignoring the fact that, not for the first time, Ethan had reversed the pronoun, saying “you” when he should have said “I”.

Ethan was one of six children from Providence, Rhode Island taking part in a study of child language development. Every couple of weeks, a researcher from Brown University would visit him and his mum at home, record, and then transcribe their conversations in painstaking detail. The transcriptions would show that Ethan was a prolific reverser of pronouns; frequently saying “you” when he meant “I” and “your” instead of “my” or “mine”. This curious habit began as soon as pronouns entered his vocabulary and he was still reversing pronouns when, just before his third birthday, the study came to an end.

Ethan’s language skills were otherwise exceptionally good. When assessed at 18 months, his scores put him in the top 1% for children his age. However, some years after the study finished, it transpired that Ethan had Asperger syndrome.

Pronoun reversal is common amongst children on the autism spectrum. Leo Kanner noted as much in the first systematic description of autism and, to this day, it is considered an important marker when conferring an autism diagnosis. But the underlying cause of this highly specific problem remains something of a mystery. Ethan’s diagnosis made sense of his pronoun reversal, but it didn’t exactly explain it.

While pronoun reversal is relatively common in autism, it certainly isn’t unique to the disorder. Deaf children in particular are prone to reversal, despite the fact that in many sign languages, pronouns simply involve pointing to the person in question. And while most typically developing children appear to have little difficulty with pronouns, there have also been several case reports of children who go through a prolonged phase of pronoun reversal.

By coincidence, Naima, one of the five other children in the Providence study, was one such child.

Aware of the serendipitous nature of their data, two of the researchers, Karen Evans and Katherine Demuth, returned to their transcriptions. Forensically re-examining the evidence, they tried to work out why the two children had encountered such difficulties with pronouns. The results of their enquiries provide some intriguing insights into the multiple challenges facing both typically and atypically developing linguists.

It is a capital mistake to theorize before you have all the evidence.

The pronoun problem

Personal pronouns represent an unusual problem for the young language learner. Most words they encounter will have a constant reference, at least within the context of the ongoing conversation. “Mummy” will refer to their own mother. “Dog” will refer to the animal that is sat on the carpet right in front of them. But the meanings of “I” and “you” change, depending on who it is that is speaking. My “you” is your “me”.

In Naima’s case, it seems that she simply failed to grasp this concept, thinking that “you” was really just another name for herself. It wasn’t that she sometimes got it right and sometimes got it wrong. Between the ages of 19 and 28 months, virtually every time she used “you” or “your”, she was actually referring to herself, sometimes with amusing results:

Naima: "I think you peed in your diaper."

Mother: "Just now?"

Naima: "I think you did."

Then, all of a sudden, something clicked. In Naima’s final two sessions at 29 and 30 months, every single pronoun was used correctly. But why did she make this mistake in the first place? And what happened for the penny to drop?

One should always look for a possible alternative, and provide against it.

Are you experienced?

Yuriko Oshima-Takane, a psychologist at McGill University in Montreal, has argued that children can only deduce the principles of pronoun use by listening in on other people’s conversations. Pronoun reversers, she suggests, are children who, for one reason or another, have missed out on this vital linguistic experience.

Naima appears to be a perfect illustration of this theory. She was an only child at the time of the study and spent most of her time alone with either her mother or her father. As a result, most of the speech she heard was directed at her. This in turn meant that almost every time she heard the word “you” it referred to her. It would be perfectly understandable if she thought of "you” as simply another name for herself.

Evans and Demuth note that the abrupt end of Naima’s pronoun reversal coincided with a family holiday. They speculate that the time spent with both mum and dad is what gave her the learning experience necessary to finally grasp the concept of “you”.

Oshima-Takane suggests a similar explanation for the high rates of pronoun reversal in deaf and autistic children. For deaf kids, having to rely on visual communication or poor quality auditory input makes it much more difficult to follow other people’s conversations. For autistic kids, the argument goes, the problem is more that they are disinterested in other people and so fail to pay attention to their conversations. Like Naima, both groups of children will only learn from speech that directly engages them and will mistakenly jump to the conclusion that “you” only ever refers to themselves.

So could this explain Ethan’s difficulties? Evans and Demuth suggest not, pointing out that, although he often used “you” to refer to himself, he used it appropriately on enough occasions to demonstrate that he’d grasped the concept.

The trail led elsewhere.

Say it again

Kanner’s explanation for pronoun reversal in autism came from another observation - that children with autism often repeat entire phrases verbatim, inappropriately and out of context. This so-called ‘echolalia’ would lead to reversals as the pronouns are repeated exactly as heard. British child psychiatrist, Michael Rutter gave the example of a hungry child requesting a biscuit by echoing the phrase “Do you want a biscuit?” The pronoun was reversed but the biscuit was obtained.

Consistent with this explanation, Evans and Demuth noted that Ethan was indeed most likely to reverse pronouns when imitating an utterance that somebody else had previously made. “Dad gave me that ring”, for example, was clearly a reversal but was almost certainly something his mum had said previously.

Case closed one might think.

However, even using the most generous criteria, imitations accounted for less than half of Ethan’s recorded reversals. What’s more, in contrast to the child in Rutter’s example, he actually made relatively few reversals during requests. For example, when asking for his bottle, he said “I want bottle”, using “I” correctly (even though the sentence wasn’t fully formed).

We balance probabilities and choose the most likely. It is the scientific use of the imagination.

An alternative perspective

Further analyses revealed two final clues. First, as well as using “you” to refer to himself, Ethan occasionally used “I” to refer to other people (something Naima very rarely did). Second, reversed pronouns were more likely to occur in sentences that contained multiple pronouns. For example, at aged 22 months, Ethan was recorded saying “I got you out” when he should have said “You got me out”.

These observations suggest that his problem lay, not in understanding the principles of which pronoun to use, but in applying those principles during a conversation. His difficulties were pragmatic rather than conceptual. More precisely, Evans and Demuth propose that Ethan’s pronoun reversal reflected difficulty in referential perspective taking - in choosing the right word given who was being referred to at any given moment in the conversation.

This account of Ethan’s pronoun reversal fits nicely with research suggesting that autistic children have difficulty with other linguistic terms that depend on the speaker’s perspective.

In an intriguing study published last year, Peter Hobson and colleagues at University College London (Hobson et al. 2010) found that children with autism were competent at using “here” and “there” to refer to locations near or far from themselves. However, the same children struggled to follow similar instructions given by two other people – a task that required them to consider the speaker’s perspective to work out which locations “here” and “there” referred to.

Wrapping up

It's difficult to be certain whether or not Evans and Demuth really have solved the mystery of why these two particular children reversed pronouns. But either way, their investigations demonstrate that, if you scratch beneath the surface, even a phenomenon as striking and specific as reversal of first- and second-person pronouns can have quite different underlying causes. In Naima’s case, it seems she misunderstood the meaning of “you”. In Ethan’s case, he appears to have grasped the concept but lacked the wherewithal to consistently choose the correct pronoun during a conversation.

Ethan’s pronoun reversal is particularly intriguing in the light of his Asperger syndrome diagnosis. However, it would be unwise to assume that he is representative of all individuals on the autism spectrum. His difficulties do not seem to be explicable in terms of either a lack of relevant linguistic experience or a tendency to echo phrases verbatim, but these may still be contributory factors, and could well explain pronoun reversal in other autistic individuals. Indeed, as noted earlier, Ethan’s error patterns are quite different to some other examples in the autism literature.

Perhaps then the reason pronoun reversal is so common in autism is that there are multiple factors associated with autism that each contribute to difficulties producing and understanding pronouns. Working out why autistic children reverse pronouns may involve looking at the evidence on a case-by-case basis.

Evans KE, & Demuth K (2011). Individual differences in pronoun reversal: Evidence from two longitudinal case studies. Journal of Child Language, 1-30 PMID: 21669013

Notes:

Katherine Demuth is now a colleague and collaborator at Macquarie University. Together with PhD student, Neha Khetrapal, we are planning a number of studies to further investigate pronoun reversal and related phenomena in kids with and without autism. All comments and feedback are gratefully received.

Further reading:

Gareth Cook: The secret language code

On neural correlates and causation

2011-08-14T05:54:00.000-07:00

The advent of neuroimaging techniques such as magnetic resonance imaging (MRI) has revolutionized autism research. We can now look into the brain and see the "neural correlates" of autism. But, as with any form of correlation, identifying a neural correlate doesn't necessarily mean that we have identified a neural cause.

A case in point. Earlier this week I stumbled across a press release doing the rounds of the internet, proclaiming that "Brain imaging research reveals why autistic individuals confuse pronouns". Pronouns are the words like "he", "she", "you" and "I" that can stand in for real names. Kids with autism often struggle with them (there goes another one). In particular, they'll say "you" to refer to themselves and "I" to refer to other people.

Various theories have been put forward over the years to try and explain pronoun "reversal". Leo Kanner thought it happened just because the autistic kids were echoing things other people had said. Bruno Bettelheim (he of 'refrigerator mother' fame) reckoned kids with autism didn't have a sense of self, and so "you" and "I" were indistinguishable to them. An intriguing theory, proposed more recently by Yuriko Oshima-Takane is that kids with autism don't learn how pronouns work because they don't attend to other people's conversations.

So what does brain imaging add to this debate?

The study

The study was conducted by Akiko Mizuno, a graduate student working with Marcel Just at Carnegie Mellon Uni. She tested a group of 15 high-functioning adults with autism on what is known in the trade as a first-order visual-perspective-taking task. On each trial, they saw a series of photographs in which a woman (called Sarah) first showed them a card with different pictures on each side and then asked "What can you see now?" or "What can I see now?" Participants had to press a button on the left or right to give the correct answer.

Interpreting Sarah's questions required the participants to comprehend the pronouns "you" and "I". The adults with autism were slower and less accurate at this task than non-autistic adults. They were also a little slower on control questions that didn't involve pronouns, such as "What can Sarah see?" and "Who can see the carrot?" but the group differences weren't quite as marked. This is crucial because it suggests that the adults with autism had specific problems with the pronoun condition.

These results in themselves are really interesting. They suggest that subtle difficulties with pronouns are apparent, even amongst high functioning adults with autism. It's not clear whether these individuals ever reversed pronouns themselves in their speech, and it's important to remember that the study looked at comprehension of pronouns rather than production. But it's nevertheless striking that there are group differences, even on such a simple task.

The focus, however, was on the brainy stuff.

While the participants were completing the task, their brains were being scanned using fMRI. The headline finding was that, in the autism group, there was reduced "connectivity" between two brain regions, the right anterior insula and the precuneus. Furthermore, within the autism group, there was a significant correlation between brain connectivity and reaction time. People who were slower had weaker connectivity.

Mizuno et al. imply that this is what ultimately causes pronoun reversal:

"The observed lower functional connectivity between those two neural nodes in the autism group, therefore, may result in disturbed perspective-taking processes in shifting a centre of reference between self and other."

Finer grained analyses showed that group differences in "connectivity" were observed only when Sarah asked "what can you see?" and not when she asked "what can I see?". The author's explanation is as follows:

"These findings indicate that the critical disturbance... may be dysfunctional processing when recognizing the self as a referent of ‘you’, and shifting to map self onto the pronoun ‘I’."

In other words, when Sarah says "What can you see?", the participant has to translate that into "What can I see?" and this translation process is reliant on the "connectivity" between the precuneus and anterior insula [1].

Reasons to be cautious:

It's possible that Mizuno and colleagues are correct in their interpretation. In fact, I'd really like them to be right, because I've been waffling on about brain connectivity in autism for ages. But there are a number of reasons to query their conclusions.

1. Everyone uses the term "functional connectivity" in the context of fMRI scans, but it's pretty misleading. fMRI measures brain activity indirectly via changes in blood oxygen levels. Here's an example of the time course of oxygen level changes for a control participant in Just et al.'s original fMRI "connectivity" in autism study.

The two brain regions in this figure are considered to be "functionally connected" because their activation goes up and down at roughly the same time. What isn't obvious from the figure (and is rarely acknowledged) is the fact that the changes are happening really slowly - roughly one cycle of activation and deactivation every trial.

If the two brain regions are 'talking' to each other in order to complete the pronoun task, they're doing it a much faster rate than anything fMRI can hope to measure.

2. Since that first paper, Just and colleagues (as well as several other research groups) have published a large number of studies demonstrating changes (usually reductions) in "functional connectivity" throughout the autistic brain. Their new study adds to this impressive body of evidence. But this in turn raises a second concern.

As mentioned before, Mizuno et al. looked at connectivity between two brain regions - the right anterior insula and the precuneus. Importantly, this was the only pair of regions they considered looked at [2]. Based on their previous findings, there's a fair chance that they could have chosen any number of brain regions and would have found "underconnectivity" between them too. They may be right and this is the only connection that relates to pronoun comprehension difficulties. But we don't know this.

3. The claim is that differences in "connectivity" are responsible for difficulties in comprehending pronouns. But it could just as easily be the other way around. People with autism struggle to comprehend pronouns, so they have to work harder or (as the reaction time data suggests) for longer, so it's no surprise that their brain activity while they're doing the task is different.

Brains vs Minds

Neuroimaging studies have provided many important insights into the workings of autistic brains. But sometimes, it's easy to be seduced by the fancy gadgets, the pretty pictures, and the funny words and think that brain imaging is somehow more scientific than good old-fashioned cognitive psychology (as exemplified by Mizuno et al.'s reaction time data), or that it offers privileged insights into the autistic mind.

Neural correlates are just that - correlations. All the usual caveats apply.

Notes:

[1]. Unfortunately, Mizuno et al. don't report whether the same effect is apparent in the reaction time data. If the people with autism had specific difficulty comprehending the word "you", they should be slower on this condition than control participants.

[2]. As far as I can tell, there is no direct evidence from previous studies that the precuneus and right anterior insula are involved in pronoun comprehension, so effectively Mizuno et al. are relying on a hunch. And in their own analyses, they show that, while the right anterior insula is one of 7 brain regions activated by the task, the precuneus isn't.

Reference:

Mizuno A, Liu Y, Williams DL, Keller TA, Minshew NJ, & Just MA (2011). The neural basis of deictic shifting in linguistic perspective-taking in high-functioning autism. Brain : a journal of neurology PMID: 21733887

Further reading:

BishopBlog: Brain scans show that...
Neuroskeptic: Brain scans prove that the brain does stuff
SFARI: You and I

Baroness Greenfield's contribution to autism science

2011-08-08T08:24:00.000-07:00

Not so very long ago, autism was considered to be a rare condition, affecting perhaps 3 or 4 people in every 10,000. The most recent studies, however, paint a very different picture, suggesting that the rate is closer to 1 in every 110 - almost 1%.

Much of that increase can be put down to the progressive widening of the boundaries of autism. Many people with an autism spectrum diagnosis wouldn’t have received a diagnosis 20 years ago or would have been given a different diagnosis. When we compare autism rates over the past few decades, we’re not comparing apples with apples - we’re comparing historical oranges with present day citrus fruit.

Other factors may also be at play, including increased awareness of autism, decreased stigmatization, and improved access to services. And as methods for collating this kind of data improve, the numbers are only ever going to go up.

None of these mitigating factors rule out the possibility that there has also been a real increase in autism, but any increase is going to be much much smaller than the headline-grabbing statistics suggest.

What matters, however, is the public perception that we are in the throes of an autism epidemic. Riding the wave of hysteria, there’s no shortage of theories trying to explain the “epidemic”.

The argument typically goes as follows:

“Autism is increasing. X has also increased. That can’t just be coincidence”.

Well, of course, it can just be coincidence. Plenty of things have changed over the past few decades and they're not all causally related.

Does US National Debt cause autism?

Latest to make the illogical leap is Baroness Susan Greenfield, neuroscience professor at Oxford University, and former director of the Royal Institution, one of the world's oldest scientific societies. In other words, someone who really should know better.

In an interview in the New Scientist magazine, she was asked for evidence to support her view that digital technology is changing our brains. Number two on the list was:

"There is an increase in people with autistic spectrum disorders."

In case we were in any doubt, she later clarified her position in the Guardian:

"I point to the increase in autism and I point to internet use. That's all. Establishing a causal relationship is very hard but there are trends out there that we must think about."

Of course, one very easy way to investigate causal relationships is to look at timing. Autism is typically diagnosed in the preschool years, but can be diagnosed reliably in the second year of life. If the internet causes autism then kids would have to be using the internet even earlier than this.

Now, my four-year-old is pretty internet savvy. He can turn on a computer, click on the swirly fox and then click on the Boowa and Kwala bookmark. But that's about it. He doesn’t have a facebook account, he doesn't tweet, and his instant messaging is limited to repeatedly typing the word "zoo". Suffice to say, he doesn't get his social interaction from the internet and I think it's fair to say that the same is true of pretty much every kid his age, including autistic kids.

In short, internet use comes after autism. Ergo, it cannot cause autism (at least not in this particular universe).

Greenfield’s comments drew a swift riposte, notably from Professor Dorothy Bishop, who wrote an open letter highlighting the dangers of casually bringing autism into the debate on internet use.

On Twitter, science writer, Carl Zimmer, proposed his own “Greenfieldism”, which made about as much sense.

"I point to the increase in esophageal cancer and I point to The Brady Bunch. That's all. #greenfieldism"

Soon everyone had a #greenfieldism.

However, while I share Bishop and Zimmer’s frustration, I do think that Greenfield might, inadvertently, have made an important contribution to autism science.

Her theory is demonstrably false. You don't need a professorship to realise that autism cannot possibly be caused by the internet. It's easy to understand that, in this case, there may be a correlation between internet usage and autism rates but there's no causal relationship.

Other theories may be less readily disproven, particularly if they refer to events in a child's life that happened before or around the same time as autism symptoms first become apparent. But, as with internet use, the fact that there's now more of whatever-it-is than there used to be is not in itself evidence that it causes autism. Using that logic is what's now officially known as a Greenfieldism.

Further reading:

Morton Ann Gernsbacher: Three reasons not to believe in an autism epidemic [PDF]
Autism and Oughtisms: Does Loss of Empathy make you Autistic? Continuance of the Internet-ASD Debacle.
Martin Robbins: Has Susan Greenfield been misrepresented?
Neuroskeptic: Susan Greenfield causes autism
Risk Science Blog: Is the internet dangerous? Taking a closer look at Baroness Greenfield’s concerns
BishopBlog: Susan Greenfield and autistic spectrum disorder: was she misrepresented?
Andrew Steele: An interview with Susan Greenfield (from 2009)

Autism, temporal binding... and chiropractic

2011-07-08T16:23:00.000-07:00

"There you go sir, that should sort out your social interaction difficulties"

I'm famous. Well, sort of. Earlier this week, one of my colleagues sent me a link to a YouTube video in which chiropractic doctor David Sullivan discusses one of my papers on autism and how it influences his "evidence based practice".

It's a classic of its genre. The video starts off with a spinning brain and funky science-o-mercial music. And Sullivan somehow manages to equate autism with a dodgy dial-up internet connection whilst weaving our hypothesis in with Einstein and the space-time continuum. I'm flattered, but also more than a little baffled.

Our paper was called "The temporal binding deficit hypothesis of autism" and came out in the journal Development and Psychopathology nine years ago (now there's a scary thought). In it we suggested that autism might be caused, at least in part, by a reduced interaction between different brain regions. Based on the idea that communication within the brain involves synchronization (or 'temporal binding') of oscillatory neural activity, we predicted that there would be reduced synchronization of brain oscillations in autism.

I'm always pleased when people read and share my papers, especially when they greet it with this degree of enthusiasm. Sullivan gets a lot of things wrong but, as someone who likewise blogs on papers I find interesting but maybe don't completely understand, I can't be too critical [1].

But there are a number of things that it's important to clarify.

First and most importantly, our paper does not endorse chiropractic as a treatment for autism. We don't even mention it. To be fair, Sullivan doesn't say that we do, but if you were distracted by the spinning brain, the white coat, and the fancy neuro-terminology then you might come away with that impression.

Second, while I'm prepared to admit that I know very little about chiropractic, I really can't see how people with autism might benefit from someone fiddling about with their spines. Last time I checked, autism wasn't considered to be a form of back problem. Sullivan doesn't provide any evidence that chiropractic is a suitable treatment. He doesn't explain how it might be beneficial, even in theory. More to the point, he doesn't elaborate on how the insights gained from our paper are at all relevant to his practice.

Digging around on his website, we do however get this mission statement:

"Therapeutically, the goal is to restore optimal synchronization and inter-communication between all brain areas. As this process evolves, the brain becomes more cohesive in its function, and the child is able to perform at a more age-appropriate and higher functional level."

But there still nothing as to how his chiropractic treatments would actually achieve this goal.

Third, our paper presented a hypothesis. We didn't show anything; there was no evidence, no data; we had an idea and ran with it. As it happens, there have since been a number of studies suggesting that autistic brains on the whole are less well-connected than your average brain. But, it's not nearly as simple or straightforward as we initially hypothesized. Different studies find that different neural pathways are disconnected. Some studies even suggest heightened connectivity. And while there's lots of evidence for abnormal brain oscillations, look more closely and the actual pattern of abnormality isn't very consistent. Another big problem is that evidence for abnormal brain connectivity has been found for umpteen other disorders that are quite different to autism. And there's a fairly compelling counter-argument that anomalous brain connections might be a consequence of autism rather than its cause.

As in so many other fields of autism research, progress is being made, but each new finding generates as many questions as it does answers. We're still a long way from understanding the neurobiological basis of autism in its various manifestations. Changes in brain connectivity and neural oscillations are, I believe, part of the story. But it's going to be a very complicated story.

Sullivan claims to have "a thorough understanding of the science and neurology behind ASD". If he does, he's in a minority of one.

Footnote:

[1] I do make a point of emailing the authors of the paper I'm blogging and giving them the opportunity to comment and make corrections. And if there's something I'm not sure about, I run it past them before posting.

Reference:

Brock J, Brown CC, Boucher J, & Rippon G (2002). The temporal binding deficit hypothesis of autism. Development and psychopathology, 14 (2), 209-24 PMID: 12030688 Download PDF

Update 15/7/11:

Kylie Gray (Monash Uni) has passed me a chapter on autism that she wrote for a chiropractic textbook with a view to educating chiropractic students about autism. She did a comprehensive literature search and found no evidence of efficacy.

Here are the relevant paragraphs:

"There is no evidence [the editor added the words "at this point"] of the efficacy of chiropractic in the treatment of autism. A few cases studies, not published in peer reviewed journals, have claimed that successful outcomes were achieved through the use of chiropractic with children with autism (Gleberzon 2006). Case reports and anecdotal reports do not provide evidence for the efficacy of a treatment; randomized clinical trials are needed to investigate the effects of any treatment.

"It has been noted that primary management of the treatment of a child with autism by a chiropractor is neither in keeping with knowledge of current best practice nor in the best interests of the child (Ferrance 2003, Gleberzon 2006). It is essential that professionals working with the families of children with autism are knowledgeable about the demonstrated efficacy, or lack thereof, of treatments that are available. It is important for professionals to be able to explain these issues to families and provide them with informed advice about their treatment options."

Gray, K.M., Brereton, A.V., & Tonge, B.J. (in press) Autism. In N Davies (Ed.) Chiropractic Paediatrics. Edinburgh: Harcourt Brace & Company.

Update 20/08/11:

A number of commenters have pointed out that Dr (of Chiropractic) Sullivan is employing "Brain Balance" techniques which may or not involve chiropractic treatment of autistic kids after all. I've contacted him to find out but haven't had a response. Anyway, if you've come across Brain Balance and think that it sounds vaguely plausible, I'd urge you to read this and this on the Science Based Medicine website.

Further reading:

Gimpy: The [not] libellous Simon Singh article on chiropractors
Stuff & Nonsense: Chiropractic for autism
The Australian: The chiro kids
Edzard Ernst: Chiropractors have an ethical duty to tell their patients about risks
EBM-First: Chiropractic: Safe for children?
The Autism Blog: Separating the Wheat from the Chaff- How to Decide on Treatments and Therapies for Your Child
Kim Wombles: Before you buy - a woo primer for parents
A Photon in the Darkness: Dr Know-It-All

Why null ain't necessarily dull

2011-06-29T08:29:00.000-07:00

Photo by Flickr user BenFrantzDale

Something slightly unusual happened this week. In a paper in the journal Vision Research, Simon Baron-Cohen and colleagues reported that they had failed to find any statistically significant difference between the visual acuity of individuals with and without autism.

The study was a follow-up to a 2009 paper that claimed to show enhanced (or "eagle-eyed") visual acuity in autism. Following two particularly damning commentaries by experts in vision science, the Baron-Cohen group got together with the critics, fixed up the problems with the study, and tried to replicate their original findings. They failed.

While it's slightly concerning that the original study ever made it to publication, it's heartening that the authors took the criticism seriously, the concerns were addressed, and the scientific record was set straight fairly quickly. This is how science is supposed to work. But it's something that happens all too rarely.

In a brilliant piece in last weekend's New York Times, Carl Zimmer highlighted the difficulty science has in correcting itself. Wrong hypotheses are, in principle, there to be disproven but it's not always that straightforward in reality. In particular, as Zimmer points out, scientists are under various pressures to investigate new hypotheses and report novel findings rather than revisit their own or other people's old studies and replicate (or not) their results. And many journals have a policy of not publishing replication studies, even if the outcomes should lead to a complete reassessment of the original study's conclusions.

There is, however, a deeper problem that Zimmer doesn’t really go into.

Most of the time, at least in the fields of science I'm familiar with, we’re in the business of null hypothesis testing. We're looking for an effect - a difference between two conditions of an experiment or two populations of people, or a correlation between two variables. But we test this effect statistically by seeing how likely it is that we would have made the observations we did if our hypothesis was wrong and there wasn’t an effect at all. If the tests suggest that it’s unlikely that this null hypothesis can account for the data, we conclude that there was an effect.

The criteria are deliberately strict. By convention, there has to be less than a 5% chance that the null hypothesis can explain your data before you can confidently conclude that an effect exists. This is supposed to minimize the occurrence of people making grand claims based on small effects that could easily have come about purely by chance. But the problem is that it doesn’t work in reverse. If you don’t find a statistically significant effect, you can’t be confident that there isn’t one. Reviewers know this. Editors know this. Researchers know that reviewers and editors know this. Rather than being conservative, null hypothesis testing actually biases the whole scientific process towards spurious effects entering the literature and biases against publication of follow-up studies that don't show such an effect. Failure to reject the null hypothesis is seen as just that - a failure.

This is something with which I'm well acquainted. My PhD was essentially a series of failures to replicate. To cut a very long story very short, a bunch of studies in the mid 90s had apparently shown that, during memory tasks, people with Williams syndrome rely less on the meanings of words and more on their sounds. I identified a number of alternative explanations for these results and, like a good little scientist, designed some experiments to rule them out. Lo and behold, all the group differences disappeared.

Perhaps not surprisingly, publishing these studies turned out to be a major challenge. One paper was rejected four times before being finally accepted. By this time, I'd finished my PhD, completed a post-doc on similar issues in Down syndrome, and published two papers arising from that study. In some ways, they were much less interesting than the Williams syndrome studies because they really just confirmed what we already knew about Down syndrome. But they contained significant group differences and were both accepted first time.

So the big question. How do you get a null result published?

One helpful suggestion comes from Chris Aberson in the brilliantly titled Journal of Articles in Support of the Null Hypothesis. He points out that you can never really say that an effect doesn’t exist. What you can do, however, is report confidence intervals on the effect size. In other words, you can say that, if an effect exists, it’s almost certainly going to be very small.

Another possibility is to go Bayesian. Rather than simply telling you that there is not enough evidence to reject the null hypothesis, Bayesian statistics provides information on how likely it is that the null hypothesis versus the experimental hypothesis is correct given the observed data. I haven't attempted this yet myself so I'd be interested to hear from anyone who has.

The strategy I've found really helpful is to look at factors that contribute to the size of the effect you're interested in. For example, in one study on context effects in language comprehension in autism, we were concerned that group differences in previous studies were really down to confounding group differences in language skills. Sure enough, when we selected our control group to have similar language skills to our autism group, we found no difference between the two groups. But more importantly, within each group, we were able to show that an individual's language level predicted the size of their context effect. This gave us a significant result to report and in itself is quite an interesting finding.

This brings me neatly to my final point. At least in research on disorders such as autism or Williams syndrome, a significant group difference is considered to be the holy grail. In terms of getting the study published, it certainly makes life easier. But there is another way of looking at it. If you find a group difference, you’ve failed to control for whatever it is that has caused the group difference in the first place. A significant effect should really only be the beginning of the story.

Reference:

Tavassoli T, Latham K, Bach M, Dakin SC, & Baron-Cohen S (2011). Psychophysical measures of visual acuity in autism spectrum conditions. Vision research PMID: 21704058

Further reading:

Screening for autism in infants and toddlers

2011-06-24T17:13:00.000-07:00

It’s widely believed that early intervention is crucial for long-term prognosis in autism and that the earlier the intervention begins the better. Getting in early, of course, requires that autistic children are identified at a young age. But even for more severe forms of autism, children are rarely diagnosed before three to four years of age. With this in mind, the American Academy of Pediatrics has recommended screening all toddlers for autism.

However, writing in next July’s issue of Pediatrics (the academy’s own journal), Mona Al Qabandi and colleagues argue against routine population-based screening for autism. Chief amongst their objections is that existing screening tools are simply not up to the task. Most of these screens involve a questionnaire given to parents, sometimes augmented with a brief phone interview. But they all have their problems. Some are insensitive, missing a large number of kids who go on to get an ASD diagnosis further down the line. Others are sensitive but not specific, hoovering up all kinds of kids, many of whom don’t have autism, and may not have any kind of developmental problems at all.

Al Qabandi et al. conclude that “none of the autism screening tests currently available has been shown to be able to fulfill the properties of accuracy… in a population-wide screening program”.

Similar conclusions were reached in an earlier review by Josephine Barbaro and Cheryl Dissanayake at the Olga Tennison Autism Research Centre in Melbourne. So they tried a different approach. Rather than relying on parental questionnaires, they set up a 'surveillance program', training community nurses to spot the signs of autism during regular infant health checks.

Each nurse attended a short two-and-a-half-hour workshop in which they were shown how to complete the screen. They were given a checklist with key behaviours to monitor, depending on the child’s age, and were trained how to score each item as either typical, atypical, or absent. For instance, the item for “eye contact” read as follows:

"Has the child spontaneously made eye contact with you during the session? If not, interact with the child to elicit eye contact. Does s/he make eye contact with you?"

From an initial sample of almost 21 thousand children, 216 were identified as “at risk” of ASD by 24 months of age. Of these, 110 completed further assessment, including the ADOS and ADI-R. 89 of these kids received an ASD diagnosis, giving the surveillance program a positive predictive value of 81%. Of the remaining 21 children, all but one had developmental language disorders.

Calculating the ~~screening~~ program’s sensitivity is an inexact process at this stage. But assuming that the rates were similar for the children who did not undergo further assessment, Barbaro and Dissanayake estimated that approximately 175 ASD children would have been picked up. Dividing this by the total number of kids in the program gave an estimated prevalence of 1 in 119. This is reassuringly close to recent estimates of approximately 1 in 100 kids having an ASD, suggesting that the ~~screen~~ researchers managed to pick up the majority of ASD kids in the initial sample.

To get a more accurate indication of sensitivity, however, the researchers will have to wait until the children enter school. Only then will they be able to work out how many children end up with an ASD diagnosis but weren’t picked up by the ~~screening measure~~ surveillance program.

While it’s still early days, the Melbourne study suggests that population-wide screening for autism is possible, at least in areas that already have ~~comprehensive~~ regular child health checks.

References:

Barbaro, J., & Dissanayake, C. (2010). Prospective Identification of Autism Spectrum Disorders in Infancy and Toddlerhood Using Developmental Surveillance: The Social Attention and Communication Study Journal of Developmental & Behavioral Pediatrics, 31 (5), 376-385 DOI: 10.1097/DBP.0b013e3181df7f3c

Al-Qabandi M, Gorter JW, & Rosenbaum P (2011). Early Autism Detection: Are We Ready for Routine Screening? Pediatrics PMID: 21669896

Links:
Olga Tennison Autism Research Centre

Further reading:

Social Communication Disorder - A new category in DSM 5

2011-06-06T06:59:00.000-07:00

A couple of weeks ago, I posted on a paper by Mandy and colleagues, which aimed to better characterise kids meeting current (DSM IV-TR) criteria for PDD-NOS (Pervasive Developmental Disorder Not Otherwise Specified). Their conclusion was that most of these kids had social and communication difficulties but not the repetitive and stereotyped behaviours (RSBs) that would have given them a full 'autistic disorder' diagnosis.

Under proposed revisions to diagnostic criteria (DSM 5), PDD-NOS is supposed to be subsumed by a broader category of "Autism Spectrum Disorder". However, Mandy et al. pointed out that the proposed criteria for Autism Spectrum Disorder require evidence of RSBs, and so would actually exclude most of their PDD-NOS kids.

In a new paper, Prof Francesca Happe, a member of the DSM-5 working group, outlines the rationale for the proposed DSM 5 changes affecting autism spectrum disorders. The paper overlaps to a large extent with her excellent blogpost on the SFARI website. However, she also references the Mandy et al. paper, acknowledging that many individuals with PDD-NOS may miss out on an Autism Spectrum Disorder diagnosis because they don't have repetitive or stereotyped behaviours.

Here's what she has to say:

“Recently, Mandy et al. raised concerns that many children currently receiving [a PDD-NOS] diagnosis will not meet proposed DSM-5 criteria for ASD because of a lack of restricted / repetitive behaviour. For these children, the proposed new neurodevelopmental diagnostic category of social communication disorder will be relevant. This diagnosis, it is hoped, will more clearly and accurately capture the pattern of impaired social and communication abilities seen in the largest subgroup now labeled PDD-NOS”.

On the DSM 5 website, the new disorder is defined more formally:

"Social Communication Disorder (SCD) is an impairment of pragmatics and is diagnosed based on difficulty in the social uses of verbal and nonverbal communication in naturalistic contexts, which affects the development of social relationships and discourse comprehension and cannot be explained by low abilities in the domains of word structure and grammar or general cognitive ability."

Effectively, SCD seems to be official recognition for what researchers and practitioners have previously referred to as "Pragmatic Language Impairment" rather than a replacement for PDD-NOS. The emphasis is very much on the communication side of things, particularly conversation skills, with a suggestion that social difficulties are a secondary consequence of impaired communication. That's my interpretation at least.

As Happé suggests, it seems likely that many people who currently reside in the PDD-NOS pigeon hole would meet the SCD criteria. However, I'm not sure that the criteria necessarily capture the extent of the issues they face. As Will Mandy mentioned in his comment to my post:

"Our clinical experience is that children with PDD-NOS (i.e. mainly individuals with severe autistic social-communication difficulties, but without high levels of repetitive and stereotyped behaviours) are similar to those with a full autism diagnosis in terms of their functional impairment."

How this will all play out in practice in terms of access to services and interventions, I don't pretend to know. I'd certainly welcome comments from people better informed than I.

Reference

Happé F (2011). Criteria, Categories, and Continua: Autism and Related Disorders in DSM-5. Journal of the American Academy of Child and Adolescent Psychiatry, 50 (6), 540-2 PMID: 21621137

Related posts

What is PDD-NOS?

Further reading

Dorothy Bishop: Pragmatic language impairment: A correlate of SLI, a distinct subgroup, or part of the autistic continuum? [PDF]

What is PDD-NOS?

2011-05-22T03:20:00.000-07:00

Some cases of autism are obvious. Anyone who knew anything about autism would agree that the child or adult in question was autistic. Other cases are less clear cut. Indeed, the term “autism spectrum” implies the existence of a continuum that fades gradually into what we think of as the “normal” population.

Somewhere a line has to be drawn and where exactly we choose to draw that line defines what we mean by autism. It determines who is eligible to take part in autism-related research and this in turn influences the development of theories of autism. Eventually, this feeds back to our evolving definitions and cut-offs for autism. Most importantly when it comes to immediate real-world consequences, the diagnostic boundaries specify who is labeled “autistic” and, ultimately, who gains access to interventions and support.

In the absence of reliable biological markers or break points in the continuum, diagnoses are made by checklist. Tick enough boxes and you get a diagnosis of “autistic disorder” or “Asperger’s disorder”. Tick fewer boxes or the ‘wrong’ combination of boxes and you’re not considered autistic. You may, however, qualify for the mysterious diagnosis of PDD-NOS - “Pervasive Developmental Disorder – Not Otherwise Specified”.

Defining PDD-NOS

“Pervasive Developmental Disorder” is an umbrella term covering five diagnoses:

Autistic disorder
Asperger's syndrome
Rett syndrome
Childhood disintegrative disorder
PDD-NOS

As the name suggests, PDD-NOS is generally thought of as a residual category for people who have a pervasive developmental disorder but don't quite fit into the other more specific categories. However, this all gets a bit circular because "pervasive developmental disorder" is defined only in terms of its constituent diagnoses. You've got a pervasive developmental disorder if you have any of the five diagnoses above (including PDD-NOS), and you've got PDD-NOS if you don't have the other four.

In practice, PDD-NOS is defined along the same lines as autism but with less strict cut-offs. Current autism diagnostic criteria require evidence of difficulties in each of three 'domains' - the famous autistic triad of:

social impairments
communication impairments
repetitive and stereotyped behaviours (RSBs for short).

The 1994 version of the diagnostic rules allowed a PDD-NOS diagnosis to be given to anyone with significant impairment in any one of the three domains.

However, the most recent revision, published in 2000, is much more restrictive. PDD-NOS is currently defined as:

“a severe and persistent impairment in the development of reciprocal social interaction associated with impairment in either verbal or nonverbal communication skills or with the presence of stereotyped behavior, interests and activities”

In other words, there has to be evidence of impairment in exactly two domains and one of these has to be the social domain.

Confused? You ought to be.

PDD-NOS and DSM 5

In 2013, the diagnostic rules are set to change yet again. One of the proposals for the new set of rules, codenamed DSM 5, is to do away with the current distinction between autism, Asperger's, and PDD-NOS, replacing them with a single super-category of "Autism Spectrum Disorders".

While there has been heated debate about the abolition of the Asperger's diagnosis, there appears to be little opposition to the demise of PDD-NOS. It's not hard to see why. The term itself is unwieldy, suggesting diagnostic uncertainty. And there's no real sense of a PDD-NOS identity as there is for Asperger syndrome.

An important question, however, is what will happen to people who would currently be diagnosed with PDD-NOS? In a study, published recently in the journal, Autism Research, William Mandy and colleagues at University College London set out to address precisely this question.

Specifying PDD-NOS

The study centred on the Developmental, Dimensional and Diagnostic Interview (known as the 3Di), a semi-structured interview, which provides scales for the three autism domains (social, communication, RSBs) as well as a number of other clinically relevant scales such as auditory sensitivity, motor impairment, and sleep difficulties.

The 3Di was administered to parents of 256 children who had been referred for assessment. Based on the parents' responses, the researchers were able to identify 66 kids who met criteria for PDD-NOS according to the current rules. In other words, these kids were above the diagnostic threshold on the social scale and either the communication or the RSB scale. The remaining kids in their sample were above the threshold on all three scales and so were diagnosed with autistic disorder or Asperger’s disorder (depending on their history of language development).

The graph below shows the scores of the kids in the three diagnostic groups on each of the three main scales. Compared with children meeting criteria for autistic disorder or Asperger's disorder, the kids with PDD-NOS on average had lower scores (less impairment) on all three diagnostic scales. They also scored lower on the scales for auditory sensitivity, visuo-spatial impairment, and feeding difficulties (not shown in the graph).

The PDD-NOS group (on the right) showed much lower levels of Repetitive Stereotyped Behaviours (Grey Bars) than kids with Autistic Disorder or Asperger's.
Thanks to William Mandy for recreating the graph.

As you can see in the far right column, group differences were particularly marked on the RSB scale. Indeed, the authors found that only two of the 66 PDD-NOS kids had clinically significant RSBs and both of these children were very close to also meeting the communication criterion, which would have given them a full autism diagnosis. The remaining 64 PDD-NOS kids fell well short of criteria for RSBs and achieved their PDD-NOS diagnosis by virtue of having both social and communication difficulties.

The authors acknowledge that this isn't a huge sample and that kids weren't selected at random from the community so it might not give a totally accurate picture of the prevalence of the different diagnostic categories. However, their results suggest that what we currently term PDD-NOS should not be thought of as simply a milder form of autism. Nor is it, as the name suggests, merely a rag-bag miscellaneous category for kids whose difficulties can’t quite be pinned down. Rather, the PDD-NOS label appears to broadly correspond to those individuals facing social and communication difficulties in the absence of the RSBs that characterize autism and Asperger’s.

Implications for DSM 5

As Mandy et al. point out, their findings suggest a potential unforeseen consequence of the proposed changes to diagnostic criteria in DSM 5.

To receive a diagnosis of "Autism Spectrum Disorder" (which is supposed to replace autism, Asperger's and PDD-NOS), an individual will have to show evidence of both:

social and communication impairment (these two domains will be merged)
repetitive and stereotyped behaviors (RSBs)

Under these rules, 64 of the 66 children in the PDD-NOS group would not meet the criteria for Autism Spectrum Disorder. To the extent that Mandy et al.'s data are at all representative, this suggests that the overwhelming majority of people who currently meet criteria for PDD-NOS would not be considered autistic under DSM 5 and may not receive any form of diagnosis.

There is certainly a case to be made that children are being over-diagnosed and that the boundaries for autism-related disorders should be brought in. However, there is also a real danger that individuals with severe social and communication difficulties would be excluded from support and interventions designed to improve their social and communication skills. All because they don’t also have RSBs.

What is autism?

Although the study focused on PDD-NOS, it also raises some more philosophical questions about what we actually mean by "autism" or "autism spectrum disorders". In particular, how do we determine what counts as a defining feature of autism?

Up until the early 1970s, language impairment was seen as one of the major defining features of autism. Indeed, researchers such as Michael Rutter argued that autism was essentially a severe form of language impairment. This theory was abandoned, however, when it became clear that there were some individuals who had the social impairments associated with autism, despite having very good language skills. Gradually, the diagnostic criteria were relaxed and today language impairment is no longer considered a necessary criterion.

Mandy et al.'s study seems to present an analogous situation with respect to repetitive and stereotyped behaviours. As with language impairment, RSBs have long been considered a defining feature of autism. And, as with language impairment, it now appears to be the case that a substantial group of individuals exhibit social impairments without exhibiting RSBs. This begs the question of why RSBs should continue to be considered a defining characteristic of autism when language impairment is not.

Thinking outside the diagnostic box

In essence, autism is whatever we say it is. Although we might like to think of it as a natural kind, an objectively discrete entity that falls out of nature, we're essentially just taking a multi-dimensional cookie cutter to the human population. Given our current state of ignorance, there is little alternative to this approach to diagnosis at this time. But for researchers, there's no obligation to be restricted by the prevailing diagnostic boxes in our quest to understand autism's place in the human spectrum.

Update [06/06/11]

In a new paper, Prof Francesca Happé from the DSM 5 working group has addressed the Mandy paper and its implications for PDD-NOS. She suggests that most PDD-NOS individuals who don't meet DSM 5 criteria for ASD will fall under the new category of Social Communication Impairment. For more details, see my new post here.

Reference

Mandy W, Charman T, Gilmour J, & Skuse D (2011). Toward specifying pervasive developmental disorder-not otherwise specified. Autism research : official journal of the International Society for Autism Research, 4 (2), 121-31 PMID: 21298812

Related posts

Exactly how many ways are there to get an autism diagnosis?

Further reading:

Francesca Happe: Why fold Asperger syndrome into autism spectrum disorder in DSM 5?

John Elder Robison: What's the difference between Asperger's, autism, and PDD-NOS?

Dorothy Bishop: What's in a name?

Steven Hyman: Diagnosing the DSM: Diagnostic classification needs fundamental reform

How do siblings influence theory of mind development in children with autism?

2011-03-26T02:27:00.000-07:00

Guess which one is me...

It goes without saying that brothers and sisters play an important role in a child's development, particularly when it comes to their social skills. For young children especially, the family is their social environment and the main opportunity to learn about other people and what makes them tick.

Research conducted in the past 15 years or so has consistently shown that children with siblings of a similar age tend to pass tests of "theory of mind" at a younger age than those without siblings. The implication is that the experience of interacting with siblings helps children to develop the concept that other people have minds and that their thoughts and beliefs are sometimes different from their own.

Children with autism typically struggle on tests of theory of mind. An interesting question, then, is what effect siblings have on theory of mind development in autism. Based on the literature on typically developing kids, we might expect siblings of autistic children to have a beneficial effect. We could even make a case that, because autistic kids may have fewer interactions with non-family members, siblings may be even more important than normal. Counterintuitively, however, a new study published in the Journal of Child Psychology and Psychiatry suggests that having older siblings can have a detrimental effect on autistic children's theory of mind development.

The study was conducted by Karen O'Brien, a PhD student from the University of Queensland and involved 60 kids with autism aged between three and thirteen years. The children each completed a battery of six "theory of mind" tests, that assessed their awareness of the separation between mental states and reality. Tests involved understanding that another person can have a false belief; that an object can look like something else; and that someone can pretend something that isn't true. Each child received a score out of 6 depending on how many tests they passed [1].

Here are the results for the children, divided up according to the siblings in their family. The striking finding is that autistic kids who had older siblings did worse than those with no older siblings. Children with only older siblings (ie those who were the youngest in their family) performed worst of all.

Number of "theory of mind" tests passed

Given the unexpected nature of their results, O'Brien and her co-authors tried to find other differences between the groups that might explain their performance on the theory of mind tasks. They looked at their age, language skills, planning skills, and measures of autism severity, but the four groups were pretty well matched on all of these. So what else might explain the sibling effect?

The authors speculate that well-meaning older siblings may over-compensate for the autistic child's difficulties. By treating them with kid gloves, they may somehow limit their development. Younger siblings might be less likely to do this and so have a more benign influence. However, it's not clear why having older siblings would be worse than having none at all.

As O'Brien et al. also point out, children without older siblings are by definition first born children. As such, they probably benefit from more one-to-one time with their parents. It may be that, for an autistic child, this advantage outweighs the lack of input from siblings.

The authors are refreshingly circumspect in discussing the implications and limitations of their study, noting that the results really need to be replicated in another study before we can have full confidence in them. They also urge caution in generalising beyond the middle-class Western culture to which the families in the study belonged.

To this I would add that performance on these kinds of theory of mind tasks is a fairly narrow measure of social functioning. Even if it's true that siblings can unwittingly hold back the theory of mind development of their younger autistic siblings, they may well have beneficial effects on other aspects of social development. And, as in typical development, the effect of siblings on the development of social skills is going to vary considerably depending on the individuals involved and the family circumstances - factors that aren't captured by the measures used in the current study.

Clearly, these are preliminary findings but they point towards an important new direction for research into theory of mind in autism. If nothing else, this study highlights the relevance of the social environment in the development of autistic children's social skills - something that has been ignored in a research literature that has traditionally viewed theory of mind as a component that is simply missing from the autistic child's brain. Despite the acknowledged limitations of the study, I think it represents an important step in the right direction.

Notes:

[1] To me, the way the tasks were scored was a bit weird. It's common practice to include control questions to check that subjects have a basic understanding of the task requirements. If they fail the control question then their performance on the theory of mind question is pretty much impossible to interpret. However, O'Brien et al. used the control questions to check that the kids weren't just guessing. So whether or not they got the theory of mind question right, they were scored as failing if they got any of the control questions wrong. This means that kids with low scores may have had specific problems with theory of mind questions or with the general demands of the question - we just don't know. That said, it's not clear how this unusual scoring method might explain their pattern results.

Reference:

O'Brien K, Slaughter V, & Peterson CC (2011). Sibling influences on theory of mind development for children with ASD. Journal of child psychology and psychiatry, and allied disciplines PMID: 21418062

Connections: 13/03/11

2011-03-13T04:29:00.000-07:00

Synaptic connections by Bernard Barnes

Recently, the Science of Blogging website carried a post advocating the virtues of a weekly round-up blogpost. While I can't promise to do this every week, I thought I'd have a go at an Autism Research round-up, at least as an experiment.

Mo Cost at Neurophilosophy has a fascinating interview with neuroscientist, VS Ramachandran. This follows on from a pretty spot-on review on the Simon's Foundation blog of Ramachandran's controversial "mirror neuron" theory of autism.

Another busy person I've recently discovered is Emily Willingham. She writes some amazing stuff on the biology of autism. In the last couple of weeks, she's written some great blogposts on possible links between autism and mitochondrial disease and the interaction between genes and sex hormones. They're all way out of my area and pretty technical but I think even I understood them. If that wasn't enough, Emily also provides some brilliant insights into the nature of autism, courtesy of her autistic nine-year-old. If you only follow one link from this post, make it this one!

Steve Silbersman has a really interesting interview with Seth Mnookin, author of The Panic Virus (next on my reading list), which covers the autism-MMR/thimerosol scare. And while we're on the topic of vaccines, Orac has an extremely clear (if provocative) review of a study of vaccinated versus unvaccinated kids in Germany. Bottom line, the only differences they found were in the number of vaccine-preventable diseases.

Left Brain Right Brain provides an update on a story that broke late last year about a Danish study linking episodes of jaundice just after birth to increased risk of autism. The journal published a number of critical commentaries, the authors of the original study went away and did some new analyses, and ended up agreeing with the critics that their own original conclusions were not justified. This, as far as I'm concerned, is exactly how science should work. It's just unfortunate that the change of interpretation almost certainly won't get the coverage that the original story did.

Finally, I have to go back to the consistently excellent Simons Foundation autism research blog. Highlights in the last couple of weeks include a piece on the controversy over new boundaries for diagnosing autism; and a review of a study looking at how the behaviour of mice with Fragile X syndrome is affected by their genetic background. One of the great things about the blog is that the writers often look at research that isn't directly about autism but is potentially important in the longer term. A case in point is this piece by Emily Anthes on gut bacteria and behaviour in mice (although the headline is somewhat misleading).

Links to these and some other pieces can be found in the "Of Interest" links down the side of the blog. I'd be interested to know which format is more popular (I currently have no idea whether anyone actually follows any of those links) so comment away. If people prefer the round-up I might do away with the list and tidy things up a bit. Also, feel free to add more links in the comments section - just so long as they are relevant!

Theories of autism: lessons from Dr House

2011-03-02T13:06:00.000-08:00

So apparently there's an episode called "Lines in the Sand" about an autistic boy

I've just been watching House. I say watching. To be honest, the details of this week's plot passed me by as I was trying to follow it whilst simultaneously eating my dinner and having a conversation-slash-argument about, of all things, carbon taxing.

Anyway, the plot is pretty much the same each week: Patient shows up in the hospital with a weird combination of symptoms; House and team conduct various ethically dubious tests; initial diagnosis is disconfirmed, usually by some new symptom; House finally ends up with the correct diagnosis and a single cause that neatly explains all of the symptoms. The patient this week had some extremely rare syndrome that gave her photographic memory and kidney failure.

So here's the question I found myself asking: What lessons does House's anarchic approach to medicine have for autism research? I'm not talking of course about his dodgy ethics, the lack of informed consent or the disregard for proper procedures. We've had enough of that recently thank you very much.

The crucial point is that for House the cause he ultimately identifies has to explain everything.

In case you missed Autism 101, autism is defined in terms of impaired social and communication skills, co-occurring with repetitive behaviours and/or restricted interests. But it's oh so much more than that. Associated features include intellectual disability, epilepsy, sensory hypersensitivity, motor coordination problems, memory difficulties, face processing impairment. And so on. Autism is also associated with certain strengths, particularly in perceptual processing, and a disproportionate (but still rare) incidence of savant skills including amazing feats of artistry, musicianship, and calculation.

If House could explain autism, it would be the best episode ever.

The genius behind House (and yes I do realise he's a fictional character) is the premise that, although there are many potential explanations for a given individual symptom, start looking at combinations of symptoms and suddenly the plausible underlying causes are reduced drastically.

"But that wouldn't explain the sensory hypersensitivity and motor coordination problems"

I do wonder whether autism researchers may be missing a trick here. Social difficulties on their own could have multiple causes. But social difficulties combined with motor discoordination and epilepsy? Suddenly the possibilities are no longer endless.

But here comes the big "however". House is dealing with a single patient. He knows that all of the symptoms he's trying to account for affect that one patient. With autism, on the other hand, we're dealing with a group of people who, in a very general sense, have some things in common but, as individuals, are all different from one another. We know, for example, that people with an autism diagnosis tend to have issues of social anxiety and also that many are hypersensitive to sound. But we don't know if it's the same individuals in both cases. So should we be thinking in terms of a common mechanism that could neatly account for both features, or would that be trying to explain the co-occurrence of two things that never actually co-occur?

Over the years, a number of grand unifying theories of autism have been proposed that try and link together different symptoms. But they are all theories of autism, assuming that autism is a single homogeneous entity.

I'm not suggesting that we need a completely new theory for every individual. But I do genuinely believe that if we're ever going to make sense of autism, we need to recognise the fact that the 'core' symptoms that define autism can come about by a number of different means. Any given theory probably won't apply to everyone.

The lesson from House is that looking at all the symptoms might help identify these different causal pathways.

As ever, I'd love to hear your thoughts.

Update (28/03/11):

This post has been reposted at the Shift Journal website and has garnered some more really insightful comments there too. I hadn't come across the Shift site before I was contacted by the editor but there's some really nice stuff there on Neurodiversity. Well worth checking out.

Exactly how many ways are there to get an autism diagnosis?

2011-02-11T06:40:00.000-08:00

There’s a saying in autism circles that I really like: “If you’ve met one person with autism, you’ve met one person with autism”. I reckon I’ve met a few hundred in my time, and I can vouch for the fact that people with autism are a pretty mixed bunch.

This has a big influence on the way I think about autism and, increasingly, the way I conduct autism research. Rather than just trying to determine whether or not X (whatever X is) happens to be impaired in autism, my colleagues and I look at our group of participants with autism and try and work out which individuals have problems with X and what makes them different from the individuals with autism that don’t have a problem. This seems an eminently sensible approach to us. One that might actually tell us some useful stuff. But it doesn't always go down very well.

I’ve given a few talks on the issue, which have been really well received. But then again, I’ve mostly been speaking to teachers and paediatricians – people who actually work with lots of different people with autism every day – or to researchers who don’t do autism research and so have a fairly neutral perspective.

But when we try and publish this research, we invariably come up against reviewers conditioned to think in terms of autism as a big box of amorphous abnormality; reviewers who consider that any study is "fatally flawed" and "theoretically irrelevant" if it doesn't finish up with a conclusion that X is impaired / normal / enhanced (delete as applicable) in autism. Not all reviewers, I hasten to add. But enough to make it very difficult for journal editors to accept the papers.

In my talks, I usually start off with a couple of slides that show the current diagnostic criteria for autistic disorder according to the clinical psychologist’s bible, DSM IV. In a nutshell, there are 12 different things that the person making the diagnosis should look for – 12 different boxes that can be ticked or not. To get a diagnosis, you need at least 6 ticks. It’s not quite as simple as that though. The 12 boxes are divided into three categories, headed social interaction; communication impairments; and repetitive behaviours / restricted interests. You need at least two ticks in the first category and at least one tick in the other category. If you don’t, then you don’t have autism.

I know what you’re thinking but them’s the rules.

I then point out the fact that, in principle, this means that you can have two different people with the same diagnosis despite ticking six completely different boxes. And I illustrate this with two imaginary kids who have nothing in common other than their diagnostic label.

Anyway, today I was busily trying to write a paper related to these issues and I got to wondering, just how many different ways are there to get an autism diagnosis?

So this is what I did. I made a spreadsheet in Excel which had 12 columns, corresponding to the 12 different boxes that can be ticked. I then filled each of the rows below with a different combination of ticks and crosses (actually 1s and 0s).

Altogether there were 4096 possible combinations of ticks and crosses, going from all crosses to all ticks with everything in between (mathematically inclined readers will spot that 4096 is 2 to the power 12).

Then I added a 13th column that showed for each row whether the particular combination of ticks and crosses would get you a DSM IV diagnosis of autistic disorder. Finally I added up the number of rows with a positive diagnosis.

The answer… drum roll… is 2027. That’s right. Two thousand and twenty seven different ways of getting an autism diagnosis.

Now, you can argue that some of the combinations might not actually exist in reality. And you might well be right. But that’s not really the point.

The point is that a lot of autism research begins with the premise that even though there are 2027 different ways of getting an autism diagnosis, being in the autism 'gang' makes you (a) fundamentally similar to all the other gang members and (b) fundamentally different to everyone that doesn't make the grade. That’s a big, big assumption. And I for one am not willing to make it.

Notes:

I've posted the Excel sheet here. Feel free to download it, check my sums, and tell me if I've done something stupid!!

Update (31/01/12):

The always excellent Autism and Oughtisms pointed out that in DSM 5, the number of combinations will drop from 2027 to 11. However, that's mainly because the 8 boxes under social and communication are being replaced with a single box called "Deficits in social-emotional reciprocity". Although this is mandatory (you'll need a tick in this box to get a diagnosis), it's incredibly broad. "Deficits" can range “from abnormal social approach and failure of normal back and forth conversation through reduced sharing of interests, emotions, and affect and response to total lack of initiation of social interaction”.

Then Allen Frances in the Huffington Post somehow concludes that the number of combinations will go down from 2688 to 6. I have no idea where he gets these numbers from. He also completely misses the point that the number of combinations is only meaningful if the items themselves are the same.

Finally, writing in Scientific American, Ferris Jabr got some astronomer dude to write a computer program for him to work out the combinations. He gets 2027 and 11 too. And computers are always right. Right? Jabr argues that the 2027 is meaningless because cluster analysis suggests there are far fewer combinations that actually exist. He's right of course. But it doesn't change the fact that, regardless of whether we're looking at DSM IV or DSM 5 criteria, the heterogeneity within autism is massive, and it's a bit bonkers for us all to keep pretending that it isn't there.

PhD scholarship in Person Perception and its Disorders

2011-01-20T17:40:00.000-08:00

My colleague, Prof Gill Rhodes, at University of Western Australia is offering a PhD scholarship in Person Perception and its Disorders (including autism). International students are eligible to apply. See details below:

The Research

We aim to understand the mechanisms (perceptual, cognitive, neural, evolutionary) underlying face recognition and other person perception skills.
A major focus is on how person perception skills emerge during typical development and in children with autism spectrum disorders. A long-term goal is to develop interventions to enhance person perception, and ultimately, social functioning and quality of life in individuals with person perception difficulties.
The research will be conducted in the facelab at UWA’s School of Psychology.

Scholarship Value and Eligibility

The scholarship provides a living allowance, valued $26,360 pa, for a maximum of 4 years.
Candidates must meet eligibility criteria for entry to a postgraduate research degree and have an
outstanding undergraduate record with an Honours degree in Psychology or a related discipline.
Candidates must apply for and be awarded a Scholarship for International Research Fees (SIRF).
Applications open 24 Jan, 2011 and 4 March, 2011.

Application Process

Apply online in conjunction with the SIRF application round for commencement in Semester 1 2011: http://www.scholarships.uwa.edu.au/home/postgrad/international
PRIOR TO APPLYING candidates MUST send a CV and one page statement of research experience and interests to Professor Gill Rhodes
Closing date: March 2011

Of 'autistic' mice and men

2011-01-15T08:43:00.000-08:00

Studies looking at potential environmental and genetic causes of autism are pretty much always correlational. They may identify risk factors, but they can only ever show that people exposed to a particular risk factor are more likely to have autism. They don’t show whether it actually causes autism. Eating ice cream is a risk factor for getting sunburnt, but (unless you get your ice cream and your sunscreen mixed up) there’s no sense in which ice cream causes sunburn. Even if we are confident that there is a genuine causal relationship between a risk factor and autism, it’s difficult to know how the risk factor operates.

Increasingly, animal models of autism are being used to help researchers answer some of these difficult questions. An elegant illustration of the kinds of insights afforded by such an approach (as well as some of its limitations) comes from a study just out in Biological Psychiatry, looking at the effects of prenatal valproic acid (VPA for short) in mice.

Valproic acid - a brief background

VPA is a drug widely prescribed to patients with epilepsy. Various studies have reported that women who take VPA during pregnancy are at considerably higher risk of carrying an autistic child. For instance, Bromley and colleagues recently followed up 64 children born to mothers taking VPA during pregnancy and found that four children (6% of the total) had been diagnosed with autism. This is considerably higher rate than the rate of 0.9% reported for children born to mothers who didn't have epilepsy.

One possible interpretation is that VPA affects fetal brain development, leading to autism. However, it’s difficult to rule out the possibility that whatever causes the mothers to require VPA in the first place might also be a factor that causes autism [1]. Given that many people with autism have epilepsy, this isn’t entirely fanciful. What's more, these epidemiological studies don’t tell us how VPA causes autism.

Autistic mice?

To address some of these questions, Mike Gandal and colleagues at University of Pennsylvania investigated the effects of VPA in mice. Pregnant female mice were divided into two groups and injected with either VPA or saline (salt-water) as a control. The researchers waited until the baby mice were born and then, over the first few weeks of their lives, conducted a battery of tests to determine the effects of VPA exposure.

One of these, the Rotarod test, sounds like a challenge on some weird Japanese gameshow. The mice had to balance on a cylinder spinning faster and faster until they fell off. It's not clear from the methods section what they fell into. But in any case, it turns out that the VPA mice were absolutely fine on this test.

Last mouse standing wins a prize!

The VPA mice did, however, show evidence of socialization deficits (reduced sniffing other mice) and communication impairment (reduced vocalization during mating) as well as increased repetitive behaviours (self grooming). And, if you’re prepared to draw the relevant analogies then you could argue that the mice met all three criteria for autism.

What's more, unlike in the human research, we can be confident in the direction of causation. We know that the experimenter administered the VPA and that this was done randomly, so there’s no way that characteristics of a particular mother mouse caused her to be administered VPA. Somehow, exposure to VPA caused the unusual behaviours in her offspring.

Obviously, the relevance of these particular findings to autism hangs on the validity of the comparison between human and mouse behaviour. Can we really say, for example, that a reduction in vocalization in mice during mating is equivalent to the communication impairments that are seen in autism? If an autistic child was suddenly metamorphosed into a mouse, would he suddenly start repetitively grooming himself? Would he be averse to sniffing other mice? These are rhetorical questions. But we have to be cautious about over-interpreting the mouse behaviour.

So far, these findings are broadly consistent with previous reports of 'autistic' behaviour in rats that were exposed to VPA prenatally. The study gets really interesting when the researchers start to look at brain responses.

Auditory brain responses

At 12 weeks old, the mice had electrodes implanted in their brains near the auditory cortex. Then, after being given a week off testing to recover, each mouse's electrical brain responses were recorded as pure tones (pips) were played into its cage.

The researchers looked at a number of indexes of brain responses, but the most interesting of these was so-called gamma phase-locking factor. Hearing each sound resulted in a short burst of oscillatory electrical activity in the gamma frequency range (40 Hertz or thereabouts). Phase-locking refers to the precise timing of the oscillations relative to the start of the auditory tone. The VPA mice had a lower phase-locking factor, meaning that their gamma oscillations were not as tightly synchronized to the tone [2].

High phase-locking: The peaks and troughs of the oscillations occur at almost exactly the same time relative to the onset of each sound.

Low phase-locking: The precise timing of the oscillations is different for each sound.

But what about the children?

Having established that the VPA mice had abnormal brain responses, Gandal and colleagues then set out to determine whether similar responses were found in autistic kids. Obviously, they couldn’t go implanting electrodes in kids’ brains. So instead they used a technique known as magnetoencephalography - or MEG for short.

MEG - or the world's most advanced hairdryer?

Whenever you have an electrical current, you also get a magnetic field. MEG records the magnetic fields produced by the brain using hundreds of super-sensitive sensors all around the outside of a helmet. By combining the information from all of the sensors placed around the head, it’s possible to estimate what a sensor placed inside the child’s brain would have measured if it had been there.

Remarkably, the autistic kids' brain responses were very similar to those of the VPA mice. In particular, they showed a reduced gamma phase-locking factor: Like the mice, their brain oscillations were less synchronized to the sound.

So what does it all mean?

These findings are pretty intriguing. They show that administering VPA to mice in utero results in mouse behaviour that could be construed as 'autistic'. But more than that, VPA mice have brain responses that are atypical in the same way that autistic children's brain responses are atypical. While we should be cautious about over-interpreting the mouse behaviour, the similarities between the brain responses are extremely compelling.

What's really intriguing, however, is this. As far as I can ascertain, none of the autistic kids were exposed to VPA. In other words, VPA appears to have an effect on brain development that is similar in some respects to the effect of other (currently unknown) causal mechanisms that lead to autism. Further studies of the VPA mouse model may, therefore, have implications for autism in general, particularly if they can show how VPA causes reduced phase-locking.

A twist in the tail

Finally, it's worth mentioning another MEG study conducted by Donald Rojas and colleagues at the University of Colorado. They reported similar results (i.e., reduced gamma phase-locking) in people who don't have autism but are related to someone who does. As always, we have to be cautious about assuming causation, but this suggests that genetic factors may well be at play. An obvious next step, therefore, would be to look at auditory brain responses in genetic mouse models of autism.

Rojas's findings also demonstrate that reduced gamma-phase-locking doesn't necessarily lead to autism. Despite showing this 'biomarker', the relatives did not have autism. It may be that the mechanisms underlying the reduced phase-locking are not causally implicated in autism. It may be that the brains of 'unaffected' relatives are somehow able to compensate for these differences. Or it may be the case that reduced phase-locking only 'leads' to autism in combination with other genetic or environmental factors.

Given this, a further important question is how genetic and environmental factors interact. Remember that, in Bromley's study, discussed earlier, 4 out of 64 children exposed to VPA developed autism. Although this is a relatively high percentage compared with the general population, it's still important to note that the vast majority of VPA-exposed kids (94%) did not meet criteria for autism. Further studies in humans may indicate genetic or environmental factors that mediate the relationship between VPA and autism, helping to determine whether a child ultimately develops autism or not. Mouse models may then come in to play again, allowing researchers to test their causal hypotheses.

Disclaimer:

I am not a medical doctor and until a couple of weeks ago had not even heard of VPA. Please do not take any of the information in this post as a substitute for proper medical advice.

Notes:

[1] Bromley et al.'s study also included 47 children born to women with epilepsy who were not taking medication. None of these children were diagnosed with autism. However, it's not clear why these mothers were not medicated. It's possible, for example, that their epilepsy was less severe than those on VPA, which would represent a confound.

[2] Gandal et al also investigated the effect of MPEP, a drug affecting the glutamate neurotransmitter system, on the two groups of mice. MPEP reduced the group differences in phase-locking factor, although this failed to reach statistical significance.

Links:

In a recent post, Neuroskeptic discussed the 'Intense World' theory of autism, according to which, autism is caused by hyper-reactivity and hyper-plasticity in local local neural circuits. The theory is based in large part on VPA rat models of autism. It's not clear to me at this stage what the implications of Gandal's study are for this theory.

Virginia Hughes has a post on the same study over on the Simons Foundation blog.

Reference:

Gandal MJ, Edgar JC, Ehrlichman RS, Mehta M, Roberts TP, & Siegel SJ (2010). Validating γ oscillations and delayed auditory responses as translational biomarkers of autism. Biological psychiatry, 68 (12), 1100-6 PMID: 21130222

MMR and autism: evidence of scientific fraud

2011-01-11T06:03:00.000-08:00

In 1998, Andrew Wakefield and colleagues published a paper in the medical journal, Lancet, which triggered a major public health scare, linking autism to the MMR (measles mumps rubella) vaccine. Wakefield's research has since been widely criticised on both scientific and ethical grounds. Many of his co-authors have disassociated themselves from the research and last year the paper was retracted, meaning that the editors of the Lancet no longer considered it worthy of publication. But still vaccination rates have fallen, measles cases in particular have skyrocketed, and children have died as a result.

Measles: Not a stroll in the park

Earlier this week, the British Medical Journal published an article by journalist, Brian Deer, who painstakingly cross-checked the descriptions of the 12 children presented in the 1998 paper with the children's health records and correspondences between the research team and other health professionals.

Deer demonstrates that all 12 children were systematically misrepresented by Wakefield et al to give the misleading impression of a close temporal association between administration of the MMR and the onset of regressive autism in previously healthy children.

The article includes a summary, which is pasted below:

The Lancet paper was a case series of 12 child patients; it reported a proposed “new syndrome” of enterocolitis and regressive autism and associated this with MMR as an “apparent precipitating event.” But in fact:

Three of nine children reported with regressive autism did not have autism diagnosed at all. Only one child clearly had regressive autism
Despite the paper claiming that all 12 children were “previously normal,” five had documented pre-existing developmental concerns
Some children were reported to have experienced first behavioural symptoms within days of MMR, but the records documented these as starting some months after vaccination
In nine cases, unremarkable colonic histopathology results—noting no or minimal fluctuations in inflammatory cell populations—were changed after a medical school “research review” to “non-specific colitis
The parents of eight children were reported as blaming MMR, but 11 families made this allegation at the hospital. The exclusion of three allegations—all giving times to onset of problems in months—helped to create the appearance of a 14 day temporal link
Patients were recruited through anti-MMR campaigners, and the study was commissioned and funded for planned litigation

I'm a cognitive scientist. I do research on how kids with autism think and how their brains work. I'm not an immunologist and I'm not an epidemiologist, so I don't really have anything to add to the autism-MMR "debate" that hasn't already been said a million times.

But what I will say is this. If you've stumbled upon this blog looking for information about autism and you have concerns about vaccines, I'd urge you to read the Deer article in the British Medical Journal. I'd also urge you to remember that vaccines save children's lives. The science there is beyond any doubt.

Links:

For comprehensive coverage, I highly recommend the LeftBrainRightBrain website.
Liz Ditz has compiled an exhaustive list of responses to the Deer article.

The fairytale of new year

2011-01-03T14:23:00.000-08:00

They say that Christmas starts earlier each year. But in our household, the Christmas season doesn’t officially begin until Fairytale of New York is first heard. That's our rule. Only then can we dust off the fake plastic tree and decorations. But this year, with Christmas Day fast approaching and our house still resolutely non-festive we still hadn’t heard it.

We own a 7 inch single of the famous duet between Kirsty MacColl (tragically departed) and Shane McGowan (remarkably still with us). But thanks to a certain three-year-old, our record player is currently out of action. So, instead, I downloaded a live recording of "Fairytale", covered by the legendary Irish folk singer, Christy Moore.

He’s singing on his own, so it doesn’t have the back and forth love-hate banter as the MacColl/McGowan version. But it makes up for that with the obvious chemistry between the singer and the audience. The track begins with Christy recounting a (quite possibly fictional) meeting with Shane McGowan:

“Where are you going?” says I. “I don’t know” says he. “Geez, I’m going there too.”

So he took me into Paddy Kennedy’s pub in Puckane into the snug. And he called for a drink. And then I called for a drink. And then he called for another drink and I called for two drinks. And then we sat down and we had a drink.

And old tongues started to loosen up and old thoughts began to flow and he told me a few of his poems and they were marvelous - after a few drinks.

Then I sang a song and he put on the jukebox.

Now, transcribing this little monologue probably doesn’t do it justice. But I thought I'd share it, not just because it's been amusing me these past few weeks, but also because of what it illustrates about the nature of human communication.
Listening to the track for the umpteenth time today, I noticed how much is left unsaid. The words are dots and we somehow manage to connect them up to see the picture. The humour comes from the fact that we are left to make those jumps ourselves, that the implications are quite different to what is explicitly said and that, sometimes, we're led astray by our initial interpretation. The poems were marvelous after a few drinks, implying they weren’t marvelous when heard sober. Shane put on the jukebox because he was unimpressed with Christy’s singing. Christy and Shane were not actually drinking their drinks before ordering the next round, but were lining up four rounds before they even started drinking. The implication being that this was no ordinary drinking session.

What’s more, there’s a crowd of several hundred people at the gig, all laughing together at the same points. They’ve obviously all made the same jumps that I did, listening decades later via my iPod.

So much of communication is like this. It’s not just the words that are actually spoken, or even the combination of lots of words. But the context in which the words are spoken, combined with the listener’s knowledge of the world and their assumptions about the speaker’s knowledge. And that's just in monologue. When there are two people having a conversation it gets even more complicated because the context keeps changing.

It's sometimes easy to forget how remarkable the human capacity for communication actually is. When we think about autism, or indeed any other 'disorder', we often take all this for granted. We ask, for example, why an autistic child fails to produce or understand speech, or why an adult with Asperger syndrome might have difficulty grasping conversational niceties. But every now and then, I find myself stopping and wondering, "Geez, why isn't everyone autistic?"

Of course, these incredible feats of mental agility aren't the sole preserve of the neurotypical. I just happen to be focusing on communication skills. In all its variations, the human mind is a truly remarkable thing. We're all amazing.

So here are my resolutions for 2011: I'm going to make sandwiches for work the night before. I'm going to leave work at a sensible time. I'm going to learn to swim properly so that I can have a go at surfing without the near certainty of death by drowning. And I'm going to do less taking for granted and more marvelling at our beautiful minds.

Happy New Year.

Language comprehension in autism

2010-12-17T16:26:00.000-08:00

Here's a presentation I gave a few years ago at the Autism08 online conference. I'm thinking of writing this up properly as a chapter in a book I'm co-editing on Communication in Autism. So any feedback would be most gratefully received (including any more recent papers that I should include).

Abstract

In this paper, I review studies that have used a number of different methodologies to investigate comprehension of spoken and written language in autism. Difficulties understanding the meaning of spoken and written language are thought to be characteristic of autism. However, language comprehension skills vary widely between individuals and would appear to be closely linked to other core language skills. Moreover, traditional tasks used to assess language comprehension may prove difficult for people with autism for a number of reasons and thus underestimate true levels of comprehension.

Language comprehension in autism

Impaired communication is one of the defining features of autism, but there is enormous variation in the nature and degree of communication difficulties across the autism spectrum. At present, there is a broad consensus that the use of language in social situations (i.e., pragmatics) is affected in all individuals with an autism spectrum disorder (ASD), but there is huge individual variation in the ability to process speech sounds (phonology); to combine words to make grammatical sentences (syntax); and to mark words to indicate the tense of verbs or plurals of nouns (morphology).

The focus of this paper is semantic processing; that is the knowledge and appreciation of word and sentence meaning. It has long been recognised that many people with autism have difficulty in processing semantic information. Indeed, impairments of semantic processing lie at the heart of Uta Frith’s influential ‘weak central coherence’ account of autism (Frith, 1989), which states that autism is characterised by “the inability to draw together information so as to derive coherent and meaningful ideas”. Weak central coherence remains, however, a somewhat nebulous concept and the precise nature of any semantic impairment is still unspecified. Moreover, recent studies have indicated that semantic processing difficulties may be related to an individual’s level of general language ability rather than being a generic feature of autism.

One of the major difficulties in making sense of the wealth of relevant data lies in the fact that a wide range of tasks have been used across studies and performance on these different tasks can be affected by various extraneous factors. The aim of this paper, therefore, is to review the available evidence from studies of semantic processing in autism across a number of different paradigms, considering the conclusions that can be drawn as well as any methodological concerns and confounds. I will also describe a recent study of language comprehension in autism that I conducted with my colleagues, Courtenay Norbury, Shiri Einav, and Kate Nation, in which we used eye-tracking as a means of avoiding some of the concerns affecting earlier studies (Brock et al., 2008). Finally, I will consider the implications for assessment of language in individuals with autism, for theories of autism, and directions for future research.

Semantic memory

The idea that individuals with autism may have some form of semantic impairment was first given serious consideration by Hermelin and O’Connor (1967), who gave an immediate memory test to a group of children with autism and a control group of non-autistic children with severe intellectual delay. They found that children in the control group were considerably better at recalling meaningful sentences such as “The fish swims in the pond” than they were at recalling strings of unrelated word such as “By is go tree stroke lets”. Children with autism, however, failed to show a significant advantage for meaningful material, suggesting that they were not attending to the meanings of the words.

A number of subsequent studies have adopted a similar approach, comparing memory for lists of related words (e.g., animals) with memory for lists of unrelated words. However, results have been somewhat mixed. In some studies, individuals with autism have failed to show any benefit for recalling semantically related words (Bowler et al., 1996; Tager-Flusberg 1991), while others have demonstrated entirely normal semantic facilitation (e.g., Fyffe & Prior, 1978; Lopez & Leekam 2003; Ramondo & Milech 1984). It has also been suggested that, where group differences do exist, they may reflect differences in strategies adopted to aid task completion rather than actual deficits in semantic processing or an insensitivity to semantic associations (see Gaigg et al., 2008; Schwartz, 1981).

Semantic priming

A common means of investigating semantic associations is via a priming task. Semantic priming occurs when processing of a stimulus is made easier or quicker when it preceded by a semantically related stimulus. For example, people react quicker to the word “dog” when it follows “cat” than when it follows “hat”. Priming effects rely on the ability to make associations between words, which in turn depend on first accessing the meaning of those words. If individuals with autism fail to access meaning or fail to make the semantic association then priming effects should be reduced.

Most published studies have in fact reported normal semantic priming effects. Lopez and Leekam (2003) found that, just like typically developing control children, those with autism read words more rapidly if they were preceded by an appropriate context word. For instance, they were quicker to read the word “jug” if it followed the word “kitchen” rather than the word “garden”. Similar results were reported by Kamio & Toichi (2000; Toichi & Kamio, 2001), who used a fragment-completion task. Participants were asked to read aloud a word with some of the characters missing. Individuals with and without autism were more likely to provide the correct response if the word-fragment was preceded by a semantically related prime word. More recently, Kamio et al. (2007) utilised a lexical decision task in which participants had to decide whether written words were real or made-up. Control children were quicker to respond to real words when they were preceded by a semantically related word, but this effect was not significant in the autism group. This contradicts other findings, but it is important to note that there were only eleven participants in the autism group and there was huge individual variation in their reaction times. Moreover, the authors were only able to use a non-parametric statistical test, which has relatively little statistical power to detect a priming effect.

In sum, the balance of evidence suggests that people with autism show normal semantic priming and therefore do access word meanings. Having said that, all of the above-mentioned studies have tested individuals with relatively high verbal IQs and none have looked at individual variation in performance. It remains theoretically possible, therefore, that some people with autism do show reduced semantic priming.

Reading comprehension

Another well-researched theme in early as well as contemporary accounts of autism has been the contrast between relatively good text-decoding skills (i.e., reading aloud) and poor reading comprehension. In his seminal description of autism, Kanner (1943) noted that “reading skill is acquired quickly, but the children read monotonously, and a story… is experienced in unrelated portions rather than its coherent totality”. Subsequent studies have broadly supported these observations. Of particular note are studies using the Neale Analysis of Reading Ability – a standardised test in which participants are scored for the accuracy in reading a short story aloud and then their ability to answer questions about the story. Age equivalent (mental age) scores for children with autism are typically lower for reading comprehension than for reading accuracy (Frith & Snowling, 1983; Lockyer & Rutter, 1969; Nation et al., 2006; Rutter & Bartak, 1973). Indeed, Nation et al (2006) found that comprehension was poorer than accuracy for virtually all their sample of children with autism. Notably, those with the lowest reading comprehension scores also had the poorest receptive vocabulary scores, indicating a link between reading comprehension and more general language abilities.

Jolliffe and Baron-Cohen (1999) investigated the ability to make so-called ‘bridging inferences’ about events that are implied but not explicitly stated in the text. They asked participants to read pairs of sentences such as “George left his bathwater running. George cleared up the mess in the bathroom.” They were then given a multiple choice question in which participants had to choose the sentence that best completed the story (i.e., “The bath had overflowed”). High-functioning adults with autism or Asperger syndrome were less likely to choose the correct answer than non-autistic adults, suggesting that they had difficulty integrating the two components of the story to make the inference.

The concern with all of these reading comprehension tests, however, is that the tasks are each quite demanding in a number of ways. Potentially, an individual with autism could have perfectly good understanding of the text, but have difficulty answering the questions because they don’t understand what they have to do, have difficulty formulating an answer, or have forgotten the correct response by the time they get to the question. These issues are highlighted by a recent study in which Saldaña and Frith (2007) used an indirect measure of the ability to make bridging inferences. Participants were asked to read short stories followed by a question. The critical measure was not the answer to the question but the time it took to read the question. Reading times were shorter when the question was primed by an inference that could be derived from the story. For example, children were quicker to read the question “Can rocks be large?” when it followed the story “The Indians pushed the rocks off the cliff onto the cowboys. The cowboys were badly injured”. The story implies that the rocks were large enough to cause serious injury, thereby providing the answer to the question. Contrary to predictions, children with and without autism showed similar reductions in reading times, indicating that both groups had made the appropriate inferences. Notably, the children with autism still performed poorly on a standardized reading comprehension test, emphasising the point that poor performance on traditional reading comprehension tests may underestimate the true level of comprehension.

Homograph-reading

The weak central coherence account emphasises difficulties in deriving ‘contextualised meaning’. The most widely cited evidence for linguistic weak central coherence comes from studies looking at the use of context to derive the appropriate meanings of homographs. These are words with different meanings that are written the same, so the correct meaning can only be derived by considering the sentence context. Crucially, the homographs used in studies of autism also have different pronunciations associated with their two meanings. For example, the word “tear” is pronounced differently in the sentences “In her eye was a tear” and “In her dress was a tear”. Thus, the extent to which somebody correctly reads the homographs aloud indicates their ability to access the contextually appropriate meaning. Importantly, the reader’s attention is not explicitly drawn to the ambiguity so, as with Saldana and Frith’s inferencing task described above, homograph-reading arguably taps into natural ongoing reading comprehension processes in a way that more conventional tests do not. Frith and Snowling (1983) found that children with autism tended to produce the most common pronunciation of the homographs, regardless of contextual cues. By contrast, typically developing children and children with dyslexia performed much better, indicating that they had made use of the contextual information.

The basic finding that, on average, people with autism make more errors than control participants on the homographs task has been replicated on numerous occasions, both with adults and with children. It is important to note, however, that many people with autism appear to have absolutely no trouble with this task. Three reports (Happé, 1997; Jolliffe & Baron-Cohen 1999; Lopez & Leekam, 2003) with a combined total of 65 participants with autism or Asperger syndrome provide sufficient information to allow individual scores to be derived. The critical condition is when the correct pronunciation of the homograph is the less common one and so the participant has to rely on the preceding sentence context to arrive at the appropriate response (i.e., if they give the most common pronunciation they will be scored incorrect). Across these three studies, 40% of participants with ASD gave the correct response on every single trial and a further 29% made only one error. These are, admittedly, considerably lower proportions than observed for control participants, but the point stands that consistent reports of group differences should not be mistaken for consistent performance at the individual level.

Of further concern is that, while the homographs task avoids some of the pitfalls associated with conventional reading comprehension tests, performance still relies on familiarity with both meanings of the word and the contextual information as well as an understanding that words can have multiple meanings (see Lopez & Leekam, 2003). Snowling and Frith (1986) attempted to address these issues by giving participants training; familiarizing them with both meanings of the homographs, and then re-testing them. In contrast to other studies mentioned above, they found no differences between the performance of children with and without autism. Unfortunately, they only reported the average of performance before and after training, so it is unclear what effect training actually had for each group. Nevertheless, it is interesting to note that children with lower language scores performed relatively poorly, regardless of their autism diagnosis, again highlighting the importance of general language abilities for explaining task performance.

Homophone comprehension

The majority of studies reviewed thus far have, in one way or another, looked at comprehension of written material. However, the assumption is that comprehension difficulties should equally affect spoken material. Two recent studies have, therefore, investigated comprehension of spoken sentences containing homophones – words that sound the same but mean different things. As with homographs, correct interpretation relies on consideration of the context in which they occur, so results should in theory parallel those of homograph-reading studies.

In the first of these studies, Hoy et al. (2004) asked participants to listen to sentences containing a homophone followed by a second sentence that provided disambiguating information. For example “The boy wanted to go to the beech. He wanted to climb in its branches.” They were then asked which of four pictures went with the story – options included pictures related to both meanings of the homophone (e.g., a tree and a seaside picture). Children with autism performed worse than typically developing control children on this task. However, their language scores were also considerably lower, so it is unclear whether their poor performance was a function of their autism diagnosis or their language difficulties.

This issue was addressed in a subsequent study by Norbury (2005) using a similar homophone-comprehension task. Participants heard a single sentence containing a homophone (e.g., “John stole from the bank”). They then saw a single picture corresponding to one of the meanings of the homophone and had to decide whether it matched the sentence. Children with autism performed just as well as non-autistic children with similar language abilities. However, when participants were divided up according to their language ability, it was found that, regardless of their autism diagnosis, those with poorer language skills made more errors when the sentence context was biased towards the less common meaning of the homophone. For example, on hearing “John fished from the bank”, they were less likely to say that it matched a picture of a river and more likely to say that it matched a picture of some money.

These findings suggest that difficulties in processing semantic context are not ubiquitous in autism, as widely argued, but are instead related to an individual’s level of language ability. Having said that, the homophones task faces many of the concerns that were raised against the homographs task. Performance depends not only on the ability to use contextual information provided in the sentence but also knowledge of the different meanings of the homophones and the world-knowledge required to determine whether a particular interpretation of a homophone is sensible. Potentially, any of these factors could contribute to poor performance among children with language difficulties. Moreover, the picture-matching task lacks some of the subtlety of the homographs task, asking participants directly to consider the meaning of the homophones after they have heard the whole sentence. Perhaps an indirect measure of ongoing spoken language comprehension would reveal subtle differences in semantic processing.

Language-mediated eye-movements

This brings us to our eye-tracking study of language comprehension (Brock et al., 2008). Studies have shown that spoken language can have a strong influence on eye-movements. People tend to look at objects that match the words they are hearing; they also look at objects that sound similar to those words or are semantically related. This happens quickly and automatically, so eye-movements can provide important insights into ongoing language comprehension without requiring participants to give answers to direct questions.

In our study, we simply asked participants to listen to spoken sentences while looking at a computer screen on which there were various different objects. All they had to do was press a button if and when they heard a word in the sentence that corresponded to one of the objects on the screen. This task was fairly trivial and most participants scored close to 100% correct. Our real interest was in their patterns of eye-movements as they completed the task. We tested 24 adolescents with autism who had a wide range of language skills. Our control group was made up of 24 typically developing children and non-autistic children with language impairment so the two groups were matched overall for language ability. We could then look at a number of different factors that affected participants’ eye-movements and determine whether they were related to their autism diagnosis or their language score.

First, we investigated whether participants looked at objects that were mentioned in the speech; for example, if they heard “Sam chose the hamster”, did they look at the hamster on the screen more than any other object? Reassuringly, they did, and there was no evidence that adolescents with autism were any different to non-autistic adolescents, indicating that all the participants were processing the meaning of individual words. We also investigated whether participants could anticipate objects that were predicted by the speech but hadn’t actually been heard yet. For example, if they heard “Joe stroked the hamster”, did they wait until after the word “hamster” to look at the hamster or did they look at it immediately after the word “stroked” (because it was the only strokeable object on the screen)? Such anticipatory eye-movements would indicate that participants were making semantic associations between the sentence verbs and the objects to which they were likely to refer and were aware of the semantic properties of the objects (e.g., that hamsters are strokeable items). Again, we found a strong anticipatory effect but failed to find any differences between our two groups or any association between patterns of eye-movements and language ability.

The most interesting results came from our consideration of ‘phonological competitors’. On certain trials, we replaced the target object with a different object that shared the same onset; for example, the hamster was replaced by a hammer. Participants showed a strong ‘competitor effect’. So on hearing “Sam chose the hamster”, they looked briefly at the hammer and then looked away once they had heard sufficient information to realise that the word wasn’t “hammer” after all. Again, we found no differences between adolescents with and without autism and no association with language ability.

Crucially, we then looked at the effect of sentence context on this competitor effect. In a previous study with university undergraduates as participants, we found that the competitor effect was wiped out if the competitor didn’t fit in with the sentence context. Participants would look at the hammer if they heard “Joe chose the hamster” but not if they heard “Joe stroked the hamster”. This effect of context on eye-movements is broadly analogous to the effect of context on the interpretation of ambiguous words (i.e., homographs and homophones). Spoken words unfold over time and halfway through the word “hamster”, it is ambiguous – it could be “hamster”, “hammer”, “hamburger”, or indeed any other word beginning with “ham”. It is this temporary ambiguity that ‘tricks’ people into looking at the competitor object. The results from previous studies using the homographs task predicted that adolescents with autism would be unable to use sentence context to overcome this ambiguity, so would look at the competitor object regardless of context. On the other hand, the results from Norbury’s (2005) homophones study predicted that the effect of context would be related to language ability rather than autism diagnosis. As it happened, the eye-tracking data were entirely consistent with Norbury’s findings. Overall, adolescents with autism did not differ from non-autistic adolescents, but in both groups there was a strong relationship with language ability – those with the poorest language scores tended to look at the competitor even when it was contextually inappropriate.

Having criticized various aspects of the methodology of earlier studies, it is only fair to subject our eye-tracking study to similar scrutiny. Our main concern was that the reduced effect of sentence context on the eye-movements of adolescents with language impairment may have arisen because these participants were simply less familiar with the words used in the sentences, were less motivated, or were paying less attention. However, these factors would have affected eye-movements across all the conditions. We only found an effect of language in the one condition that required participants to use the sentence context to resolve the (temporary) ambiguity. Given this, our results further undermine the weak central coherence account, but suggest that difficulties in processing semantic context on-line are related to language impairment rather than autism.

Discussion

A number of key issues arise from this brief review. The first is that traditional behavioural tests of comprehension may underestimate the true capabilities of individuals with autism. People with autism often struggle when they are asked to answer questions after the event about a complex passage of prose that they have just heard or read. However, when the test demands are stripped back, indirect measures of comprehension such as semantic priming or eye-tracking can reveal a surprising degree of understanding, often in line with expectations based on general verbal abilities. Having said that, it is important to acknowledge that, at this stage, studies using such techniques have been quite limited in scope and future studies may reveal language comprehension difficulties that cannot be easily explained away. It is also important to distinguish between the kinds of ‘extraneous’ difficulties that only compromise experimental task performance and processing difficulties (such as general memory difficulties) that may also impact upon everyday communication.

The review highlights the potential of techniques such as eye-tracking for assessing language comprehension in autism (cf. Edelson et al., 2008). At present, eye-tracking technology is probably too expensive to be used routinely for assessments in most clinical or educational settings, but costs are falling rapidly and this may be a significant avenue for future developments. In the meantime, this review demonstrates the need for careful consideration of confounding factors that could detrimentally affect performance when trying to evaluate the comprehension skills of an individual with autism.

A second overarching theme coming out of this review is the heterogeneity within the autism spectrum. Whenever we look at individual differences rather than just group averages, it becomes clear that some people with ASD have difficulties on semantic processing tasks whereas others do not. Evidence from homophone-processing and eye-tracking tasks suggests that this heterogeneity in semantic processing is related to more general verbal abilities, particularly when considering the use of semantic context. In the same way that some individuals with ASD have perfectly adequate phonological and grammatical skills, so, it appears, some individuals have age-appropriate semantic skills. However, the fact that semantic and other language skills are not universally impaired in autism does not make them any less important. Clearly, many people with autism do have problems understanding the meaning of language and it is imperative to understand why they do and how best to ameliorate their difficulties.

This revised perspective on semantic impairment in autism also has important implications for theoretical accounts of autism. In particular, recent findings are clearly at odds with the weak central coherence account, according to which, difficulties in extracting meaning and processing words in context are characteristic of autism (Frith, 1989). One resolution would be to acknowledge the possible existence of subgroups of ASD with completely different underlying causes. Thus weak central coherence and semantic processing deficits may only be a characteristic of a subgroup of people on the autistic spectrum. An alternative possibility is to abandon the notion of a central cognitive mechanism and instead think in terms of neural or genetic mechanisms that act as risk factors for ‘symptoms’ associated with weak central coherence. To illustrate in more concrete terms, Brock et al. (2002) hypothesized that aspects of autism attributed to weak central coherence may reflect abnormal connections between different regions of the brain. However, genes influencing the development of neural connectivity are likely to act in a probabilistic manner – they may or may not impact upon the functioning of any particular brain system (Geschwind & Levitt, 2007) so would not always lead to impaired semantic processing or indeed any other given symptom.

These considerations also shed some light on the hypothetical relationship between autism and specific language impairment (SLI); a developmental disorder in which language acquisition is severely delayed in the absence of autism or any other obvious cause. Overlaps between SLI and autism are well-documented in relation to phonology, syntax and morphology, leading some researchers to conclude that autistic individuals who also have language difficulties effectively have both autism and SLI (e.g., Roberts et al., 2004), The evidence reviewed here also points to overlap in terms of semantic processing; in both Norbury’s homophones task and our eye-tracking study, a lack of sensitivity to semantic context was demonstrated by individuals with language impairment regardless of their autism diagnosis. That being said, Williams et al. (2008) have recently argued that similarities between autism and SLI are probably more superficial than real, so it remains to be seen whether the overlap in semantic processing holds up to further detailed investigation.

Bearing these arguments in mind, an important avenue for future research is to consider the brain mechanisms involved in semantic processing in autism. There is now a growing body of evidence from studies of autism using magnetic resonance imaging, event-related potentials and, latterly, magnetoencephalography, testifying to atypical brain responses during semantic processing tasks (e.g., Braeutigam et al., 2008; Harris et al., 2006; Ring et al., 2007). A detailed discussion of these studies is beyond the scope of this review, suffice to say that many of the criticisms raised here against behavioural-cognitive studies may also apply to these brain-imaging studies. Typically, studies consider group averages rather than individual variation and groups are often mismatched in terms of language ability, muddying any attempt to interpret group differences. Furthermore, the tasks used in these studies introduce various confounding demands that could lead to differences in brain activity unrelated to actual semantic processing.

Clearly, there is considerable work to be done before we fully understand the nature of semantic processing impairments in autism at either the cognitive or the brain level. Future research addressing the links between cognitive and neural mechanisms is likely to generate important insights into the underlying causes of communication impairment in autism. Crucially, however, the studies reviewed in this paper highlight the need to acknowledge the heterogeneity that exists within autism as well as potential overlaps with other groups of non-autistic individuals who also have communication difficulties.

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Networks in the autistic brain: insights from graph theory

2010-12-03T16:26:00.000-08:00

A couple of weeks ago I travelled from Sydney to a conference taking place in San Diego, California. There isn't a direct flight to San Diego so instead I had to fly via Los Angeles. Colleagues coming from Melbourne had an even more convoluted journey - they had to get a connecting flight to Sydney first before they could fly to LA. The issue here is that airline routes are determined by economic pressures. There simply aren't enough people wanting to travel from Sydney or Melbourne to San Diego on a regular basis for a direct route to be commercially viable. Instead, travellers rely on a small number of long-distance routes with local connecting flights at either end. In this way, it's still possible to get between any two airports with only a couple of flight transfers along the way.

Airline networks

But what has all this to do with autism?

It turns out that the brain operates according to similar network economics. Neurons communicate via action potentials - electric pulses sent along their axons. Ordinarily, these are quite slow, so in order to send messages quickly over long distances in the brain, axons have to be insulated by a fatty sheath known as myelin. However, it's not feasible to have every axon heavily myelinated - for one thing, the myelinated axons would take up too much space in the brain. So, as with the airlines, there are lots of local connections within brain regions and a limited number of long-range super-fast myelinated connections. And as with the airlines, this actually allows messages to be sent across the brain relatively efficiently, with every neuron being only a few synapses (flight transfers) from every other neuron.

This is more than just an extended metaphor. In fact, there is an entire branch of mathematics, known as 'graph theory', that can be applied to pretty much every imaginable kind of network - from airports around the world to co-stars in Hollywood movies, or friendship 'circles' on Facebook.

Researchers have recently begun applying those same graph theory principles to human neuroimaging data. And now, in a new paper, currently in press at Neuropsychologia, Pablo Barttfeld and colleagues from Buenos Aires have applied graph theory to autism.

In graph theory, networks range from completely orderly (left) to completely random (right). "Small world" networks lie between these two extremes.

In Barttfeld et al.'s study, 10 adults with autism and 10 non-autistic adults were simply asked to look at a cross on a computer screen, while the electrical currents generated by their brains were measured via 128 EEG electrodes placed strategically in different locations on their scalps. The researchers then estimated the strength of the connection between each pair of electrodes. If two electrodes recorded similar changes in the EEG response across time, they were deemed to be strongly connected. Connections below a certain threshold were eliminated, leaving a network with only the stronger connections. The researchers then used graph theory to characterise the network of inter-electrode connections.

The main findings were as follows:

The brain networks for autistic adults were less interconnected than those for the control group. On average, each electrode had fewer neighbours to which it was connected. In our air travel analogy, this corresponds to there being fewer routes between different airports.

The path length was also longer. Path length refers to the minimum number of steps it takes to get from A to B. My journey from Sydney to San Diego via LA had a path length of two because there were two separate flights involved. My colleagues from Melbourne had a path length of three.

Finally, the autistic network was more modular - removing the weaker connections very quickly led to a sub-divided network where it was impossible to get from one region to another. The analogy would be a network where it was possible to fly around Australia or America but impossible to get between the two.

While the methods are new, the findings really just confirm much of what we already know about autism. There's plenty of evidence from other studies that autistic brains are less well connected (or the connection patterns are different to typical brains). The exciting aspect of this paper is that it introduce a whole new way of thinking about the autistic brain.

In particular, thinking in terms of networks and graph theory might finally allow us to reconcile connectivity theories of autism with other theories that focus more on localised brain dysfunction. Over the years, it has been variously argued that autism is caused by dysfunction of the hippocampus, the cerebellum, the temporo-parietal junction, the medial prefrontal cortex, and the amygdala, to name just a few brain regions. What these regions have in common is that they are all highly connected with other brain regions - they are the Chicago O'Hares and London Heathrows of the brain. Dysfunction of any of these regions could have huge impacts on the whole of the brain (imagine the knock-on effects of closing Heathrow airport). Alternatively, changes in global connectivity would have greatest impact on the functioning of these hubs.

This approach may also help us get a better handle on genetic causes of autism and the overlap with other disorders. As mentioned in my previous post, some of the genes implicated in autism may be better conceived as genes for neural connectivity that act as risk factors for a range of disorders. Graph theory offers a potential way of quantifying these effects. Indeed, using a similar approach, Stam and colleagues have already shown that the network properties of EEG are highly heritable and are compromised in schizophrenia.

Reference:

Pablo Barttfeld, Bruno Wicker, Sebastián Cukier, Silvana Navarta, Sergio Lew, & Mariano Sigman (2010). A big-world network in ASD: Dynamical connectivity analysis reflects a
deficit in long-range connections and an excess of short-range connections Neuropsychologia arXiv: 1007.5471v1

Genes for autism or genes for connectivity?

2010-11-13T22:10:00.000-08:00

Autism is a genetic disorder. We've known this ever since the 1970s when studies by Susan Folstein and Michael Rutter showed that genetically identical twins are much more likely to both be autistic than non-identical twins. These findings were incredibly important at the time and fundamentally changed the way people think about autism. But they didn't tell us which genes cause autism or, perhaps more importantly, how they do it.

Gratuitous picture of chromosomes

I've just been attending the Autism Brain Research meeting in San Diego. Much of the first day was dedicated to genetic research and animal models of autism. The gist of the talks was that, while there are some genetic variations that carry a high risk for autism, these are probably very rare and only account for a very small proportion of cases. Most 'genes for autism' will actually carry a very low risk of the person actually having autism, so identifying these genes is going to be difficult. However, a recent study, just out in Science Translational Medicine, offers a new perspective.

Ashley Scott-Van Zeeland and colleagues focused on one particular gene - CNTNAP2 - apparently referred to colloquially as the "catnap" gene. Previous studies have linked CNTNAP2 to autism, but also to specific language impairment, ADHD, Tourette syndrome, and schizophrenia. It encodes a protein, Caspr2, which is thought to be involved in the migration of cells during brain development and is expressed in frontal and temporal lobes in humans.

The CNTNAP2 gene is common to many species

In the first part of the study, the authors conducted a genetic test on the saliva of 32 children, half of whom had a diagnosis of autism. Across the whole sample, they identified 9 kids who carried the allele (variant) of the CNTNAP2 gene that has been linked to autism. It's not clear how many of the 9 'at risk' kids were in the autism group, but reading between the lines it seems like a 5:4 split. Then, rather than comparing the autism group to the non-autism group, they compared the 9 children with the 'risk allele' to the remaining 23 children

fMRI was used to record brain activity while participants completed a reward-guided implicit learning task in which they were given a monetary reward for correct responses.

The first main finding was that the 'non-risk' group showed reduced activity in the medial prefrontal cortex (MPFC). This might sound a bit counter-intuitive, but the MPFC is part of what is termed the 'default mode network' - a collection of brain regions that show reduced rather than increased activity during cognitive tasks. So the risk allele was associated with a reduction in normal reduction in MPFC activity. If that makes sense. Previous studies have reported abnormal patterns of MPFC activity in autism during theory of mind tasks, as well as abnormalities of the default mode network. So this finding fits nicely with the autism research, except for the fact that it's looking at the CNTNAP2 gene, irrespective of autism diagnosis.

MPFC = medial prefrontal cortex (i.e, in the middle at the very front)

The authors also conducted connectivity analysis on residual time series. Put simply, this involved subtracting out activity related to actually completing the task and then looking at which brain regions showed a similar pattern of changes in activity over time as the MPFC. Individuals with the risk allele showed greater connectivity between the MPFC and neighbouring right frontal cortex, but reduced connectivity with more distant regions including the medial occipital cortex and the lateral temporal cortices*. This fits in nicely with the idea that "the frontal cortex in autism might be only talking to itself". Except again this a study relating to a risk allele, not to autism per se.

Just to be sure, the authors then analysed the data from a second study, using a completely different task and a completely different group of subjects. This time none of the subjects were autistic. But the connectivity analysis showed a very similar pattern of results. Individuals with the risk allele showed stronger local connectivity and weaker long-range connectivity with the MPFC.

So really, this study isn't about autism. It's showing a link between a gene associated with autism (CNTNAP2) and individual differences in patterns of brain activity that have been associated with autism. Having this gene doesn't mean that you've got autism. It doesn't even mean there's a high risk of autism. But it may have a subtle effect on the way the brain is wired up and this may put you at an ever-so-slightly higher risk of having autism. Or schizophrenia. Or language difficulties. Presumably, all depending on a host of other genetic and environmental risk factors to which you're also exposed.

One thing I'd really like to know is whether non-autistic individuals with the 'risky' variant of the CNTNAP2 gene differ in terms of their behaviour or cognitive processes. Are there subtle differences, for example, in language or perceptual processing, or their social characteristics? Or are they only observable at the brain level? Looking at this might help us work out which particular aspects of autism might be linked to this neural/genetic pathway.

Notes:

* The authors also reported that the non-risk group showed focal patterns of connectivity between the MPFC and regions in the left hemisphere classically associated with language processing, including left inferior frontal gyrus, insula, anterior temporal pole, superior temporal gyrus, and angular gyrus. In contrast, the at-risk group showed much more widespread connectivity across both left and right hemispheres. However, while tantalising, it doesn't appear that these differences were statistically significant when direct comparisons were made between the two groups.

Links:

Virginia Hughes (as per usual) had the scoop on this research last year.
Discover and Time also covered the study
Lindsay at Autist's corner has recently written about the CNTNAP2 gene and has covered some other autism genetics stories here and here

Reference:

Scott-Van Zeeland AA, Abrahams BS, Alvarez-Retuerto AI, Sonnenblick LI, Rudie JD, Ghahremani D, Mumford JA, Poldrack RA, Dapretto M, Geschwind DH, & Bookheimer SY (2010). Altered Functional Connectivity in Frontal Lobe Circuits Is Associated with Variation in the Autism Risk Gene CNTNAP2. Science translational medicine, 2 (56) PMID: 21048216

Autism Brain research Meeting, Day 2

2010-11-13T14:45:00.000-08:00

Day 2 of the Autism Brain Research meeting began far too early for me. Due to a combination of jetlag and blogging Day 1, I only managed a couple of hours sleep. So both my attention and my note-taking followed a U-shaped trajectory: coffee-fuelled and enthusiastic in the morning; present in body but not mind during the middle sessions; and then a second wind at the end, inspired by David Amaral's rousing closing speech. More on that later.

Cognition and development trajectories:

The morning session was home turf - cognition!

Tony Charman kicked off, highlighting again the heterogeneity within autism and pointing out that, even in biological subtypes of autism such as Fragile X, there is huge variability in clinical presentation. So the heterogeneity problem isn't solved by biology alone. He noted that, during the 1990s, many researchers (particularly in the UK) were optimistic that there might be a common cognitive explanation for autism, even if there were multiple genetic and neurobiological pathways leading to the cognitive deficit. It seems fairly clear now that this isn't the case. Nevertheless, cognitive research is still vital, acting as a potential signpost to different etiological mechanisms and potentially explaining the behaviours that characterise autism and suggesting useful intervention strategies. However, cognitive autism research is typically hampered by a combination of small sample sizes, lexclusion of individuals with low IQ, and narrow focus on only one cognitive domain at a time.

Charman then presented data from three recent studies from the SNAP cohort project, which involved a sample of over 70 adolescents with autism who each completed a battery of 58 cognitive tests, allowing potential subgroups to be pulled out (see the Jones et al. paper on auditory discrimination that I blogged about last week). He concluded by suggesting that a combination of approaches to cognition would be needed, akin to the two different approaches to autism genetics (candidate gene versus genome-wide screening) that were discussed yesterday. There wasn't much to disagree with here, although personally I think we can have the best of both worlds if we're thoughtful enough in the design of our studies.

Kasia Chawarska then presented work using eyetracking techniques to investigate face-processing in young children with autism. One such study found that autistic children were quicker to disengage their attention from a picture of a face in order to saccade towards a new object. Another investigated recognition memory by measuring whether the child had a preference for looking at novel versus previously viewed faces. Interestingly the autistic children showing the poorest recognition looked less at the eyes and more at the mouth. Dr Chawarska argued that there may be different subtypes of autism related to face processing skills. This certainly fits with work my PhD student, Ellie Wilson, did with older children, and again highlights the importance of considering individual variation.

To round off the session, Cathy Lord spoke about longitudinal studies using the ADOS repeatedly between 10 and 40 months. Using some fancy statistics (which I didn't quite follow) she was able to split the group up according to their trajectories. What was most noticeable about her data, however, was how incredibly noisy it was, with children's ADOS scores varying wildly from session to session. Because she had multiple data points, this probably wasn't too much of a concern for the study. But the lack of stability worries me a lot given that we are all supposed to be using the ADOS if we want to get our autism research published. Lord also presented similar data from older children, again showing diverging trajectories in different subgroups*.

Behavioural interventions:

The second session focused on behavioural interventions. There was some interesting stuff, although I can only remember one presenter even mentioning anything vaguely brain-related. So it wasn't clear how any of the research linked up with the rest of the meeting.

Fred Frankel reported on a program to enhance children's friendship-making skills, but whilst he was able to show improvements on a number of social measures, there was no control group, so it wasn't clear whether the program was causing the improvement.

Aubyn Stahmer echoed the general theme of heterogeneity in autism and discussed different ways of optimising and adapting interventions programs for different children as they develop.

Judith Reaven presented data from a randomized control trial of "Face Your Fears" - a CBT group therapy treatment for anxieties. This involved gradual exposure to anxiety-provoking stimuli, self-rating of anxiety before and after exposure, and talking through the situation. There was evidence for efficacy in young kids and preliminary support for a modified version for teenagers.

Finally, Sally Rogers provided an overview of four studies published this year looking at various interventions that, in different ways, involved training parents to manage their interactions with their autistic child. There was some evidence for changes in the children's attention to other people, although no improvements on standardised measures of language beyond the (fairly large) improvements also shown in the control groups. In fact, the improvements in language shown by the untreated control children was perhaps the most remarkable finding, highlighting the need for properly controlled studies before claims of treatment efficacy can be made.

Pharmacological interventions:

This session also provided mixed evidence for successful interventions. The general theme seemed to be that non-core symptoms can be treated pharmacologically, but with potentially serious side effects. And there's no evidence at this point in time for interventions targeting the diagnostic features of autism.

By this point in the afternoon, I was really struggling to stay with it, so I need to put a massive disclaimer here: what follows may well not be a fair representation of the three presentations. In any case, this is a research blog, and none of the information here should be taken as clinical advice.

Christopher McDougle reported on the use of antipsychotics as a treatment for 'irritability'. I haven't heard this term used clinically before, but apparently the FDA define it as "symptoms of aggression towards others, deliberate self-injury, tantrums, and quickly changing moods". Traditional antipsychotics such as haloperidol that block dopamine pathways have proven successful at reducing 'irritability' but have severe side-effects in dystonia and dyskinesia. Second generation antipsychotics that affect serotonin pathways are also successful compared with placebo but lead to severe weight gain in most cases. These side effects are obviously a particular concern if the drugs are being given to children.

Bryan King talked about the overlap between autism and ADHD, pointing out that, while an autism / PDD diagnosis precludes a diagnosis of ADHD, the patterns of ADHD symptoms shown by a large subgroup of kids with autism are almost identical to non-autistic ADHD kids. Drug trials of methylphenidate have shown some success, but slightly lower response rates than for ADHD without autism. King also reported a study of citalopram (an SSRI) for repetitive behaviours in autism, which showed no benefits beyond placebo.

Craig Erickson closed the session by highlighting the challenges for developing pharmacological autism interventions: autism presents a moving developmental target; there's little agreement on appropriate outcomes measures; placebo responses can be large; and (again) there is huge heterogeneity in autism. I think the same could be said of all autism interventions. Erickson then gave a run-down of various drug treatments that have either been shown not to work or show promise but lack compelling evidence as yet. In this latter category he included ongoing work on oxytocin; therapies combining pharmacological interventions with social skills training; and drug therapies derived from animal models of Fragile X syndrome.

Future directions:

David Amaral gave the final talk entitled "Autism research: The promise and the pitfalls". The promise part was really a summary of the preceding presentations, and the pitfalls were highlighting some of the themes emerging from the meeting: the inadequate supply of post-mortem tissue; the need to recognise heterogeneity and the developmental nature of autism; and the "plethora of misleading information" available out there in the real world. Amaral also urged researchers to keep an open mind about possible causes of autism, not to take anything off the table, and to be prepared for surprising results.

To illustrate some of these points, Amaral presented two strands of research from his own lab. The first related to MRI studies of the amygdala. The available cross-sectional data suggests early overgrowth, such that the amygdala are at their final adult size by around eight years in autism, compared with 18 years or so in typical development. Looking at much younger kids showed that the amygdala are significantly larger than in controls by 3 years of age. However, there appeared to be three subgroups within the autism cohort: kids with rapid amygdala growth but normal total cerebral volume; kids with the opposite pattern (enlarged total cerebral volume but normal amygdala growth); and kids for whom both amygdala and total cerebral volume were normal.

Amaral also presented some fascinating work on autoimmune function in autism. In one study, his team looked for autoantibodies in the blood samples of kids with autism and then used them to stain monkey brains. They identified some unusual antibodies that targeted Golgi cells in the cerebellum. In another study, his group detected IgG antibodies in the blood of a small subgroup of mothers of autistic children. These were then injected into pregnant rhesus monkeys. The offspring showed no robust changes in social behaviour, but did show evidence of increased hyperactivity and whole body stereotypies.

Conclusions:

It's been a fascinating couple of days, although I was disappointed there wasn't more emphasis on brain imaging, electrophysiology, or links between brain and cognition. Partly because those are the areas I'm most interested in personally, but also because this research may help bridge the huge gulf that currently exists between the genetic / neurotransmitter level research and the intervention side of things. I'm also looking forward to hearing people talk about "ortism" again rather than "artism"!

The main issue that was hammered home again and again is the heterogeneity that exists within autism. It seems that real progress can only be made, both in terms of understanding the causes of autism and designing and optimising intervention strategies, once we address this problem. But things at last seem to be moving in that direction.

NB: Again, please note that this summary is based on the notes I made during the conference. I'm not an expert in most of these areas and there may be some inaccuracies, in which case I'll be happy to correct any that are pointed out to me. You can email me on jon.brock@mq.edu.au or just leave a comment at the bottom of this post. I'll try and get round to adding some links, but need to go souvenir shopping before I catch my plane!

Autism Brain Research Meeting, Day 1

2010-11-12T03:49:00.000-08:00

I’m currently at the Autism brain research meeting in San Diego, having finally, finally made it through immigrational control and customs in Los Angeles. Two people to check a jumbo jet’s worth of passengers. Possibly not enough. That’s all I’m saying.

I think I'm currently in one of those tall buildings. Not sure which.

So far, the meeting has been pretty interesting. Day 1 was focusing mostly on genetics, animal models of autism, and neuropathology with a little bit on brain imaging. Not really stuff that I’m over familiar with but a fascinating learning experience nonetheless. Here's a brief(ish) summary:

Genetics

The main theme of the early sessions was genetics. Recent research seems to suggest that we need to think about genetic causes of autism as a combination of (a) rare genetic variations that have large effects (i.e., if you’ve got the allele or mutation then you’re at high risk of autism) and (b) more common variations that each carry a low risk.

Consistent with this, Bernie Devlin pointed out that the search for common genetic factors has been largely unsuccessful. He highlighted three recent high-profile studies that have each identified genetic loci associated with autism in their sample. However, there was no overlap between any of the studies, so none of the loci have been validated. The problem, he suggested, is that these studies only had the power to detect genetic variation that was both common and carried a high risk of autism. And so much larger studies would be needed to identify genes that carried a lower risk.

Indeed, in the previous talk, Steve Scherer noted that evolution would be expected to select against common high risk genetic factors that, by causing autism, would reduce an individual’s likelihood of reproducing. So perhaps it’s not too surprising that none have been found. However, Scherer suggested that various rare genetic events might all have common effects by acting upon the same neurodevelopmental pathways and that looking at these functional groups of genes is the way forward.

Joseph Buxbaum added a further caveat – that different genetic variations in the same loci could have positive, negative, and neutral effects. The solution, he argued, was to look at the distribution of outcomes rather than just the overall relative risk.

The highlight of the session, for me, was a presentation by Catalina Betancur. She reported a study of 180 families in France with at least one autistic child. Via a combination of clinical evaluations, metabolic tests, and genetic screening, her team were able to identify a specific genetic disorder in 32 (18%) of the families. These included Fragile X, Angelmann, Di George, Timothy, Smith-Magenis, and Jacobsen syndromes. Many of these disorders are linked to intellectual disability and epilepsy, but none of them necessarily lead to autism. She concluded that autism is not a single disorder but the behavioural manifestation of many different genetic disorders – only some of which we are currently able to easily identify. However, as Dr Betancur pointed out, in those cases where a genetic etiology can be determined, this may have implications for the specific treatments and therapies offered.

Animal models:

Session 2 focused on animal models of autism. First up was Jacqueline Crawley, who talked about her group’s research investigating behavioural analogues of autistic impairments in genetically engineered mice. Her focus was more on the methods rather than specific genes. However, in each case, she provided evidence that mice with mutations linked to autism showed evidence of abnormal behaviour. Social impairments were measured by seeing whether a mouse would choose to approach a cage containing another mouse or an empty cage, or by recording social behaviour such as sniffing and climbing over and under another mouse. Communication was indexed by scent marking behaviour and by recording ultrasonic vocalizations in different social contexts (e.g., when an intruder mouse was added to the cage). Although, as one questioner pointed out, some of these associations may reflect the influence of genetic mutations on sexual behaviour rather than social behaviour. Most convincing, perhaps, were the measures of sterotyped behaviour, particularly the ability to learn and then re-learn a simple maze, which seems to correspond more directly to the cognitive flexibility impairments in autistic humans.

Presentations then followed from Tom Jongens (models of Fragile X syndrome in fruit flies) and Joseph Buxbaum (mouse models of the SHANK3 deletion, linked to autism). Finally, Alcino Silva talked about genes related to tuberous sclerosis, neurofibromatosis, and schizophrenia in mice. The common theme across the three presentations was that knowledge of the neurodevelopmental pathways affected by these genetic manipulations led to biological treatments that could ameliorate at least some of their behavioural consequences. These studies offer the prospect of pharmacological treatments for the corresponding disorders in humans, although they are still some way off. And, as the genetic studies presented earlier showed (and Dr Silva acknowledged), each treatment is only likely to be relevant to at best a small proportion of the autistic population.

I must admit to having had some skepticism about the relevance of animal models. Does it make sense to think of autistic mice? Or even fruit flies? Some of the speakers stressed that we mustn’t anthropomorphise animal behaviour. But then they kind of all did anyway. The problem for me is trying to define what is an equivalent behaviour in humans and non-humans. In fact, the most interesting animal research I heard about was a poster presented later on, by Mike Gandal and colleagues. Their approach is to develop biomarkers for autism that can be used with little alteration in both humans and animal models. The poster focused on brain responses to auditory stimuli, particularly the synchronization of gamma oscillations. They showed reduced gamma synchronization, both in autistic children (measured using MEG) and in mice (measured via intra-cortical electrodes) that were administered valproic acid prenatally. The connection here is that mothers who are forced to take valproic acid during pregnancy to counteract their epilepsy are at much higher risk of having a child with autism.

Neuropathology:

The afternoon session began with Eric Courchesne, who has previously reported cross-sectional data showing an increase in brain size early in post-natal development in autism. This increase is particularly noticeable in the dorsolateral prefrontal cortex (DLPFC). Here, he presented results from detailed studies of neural architecture in the DLPFC in the brains of seven autistic children who had died between the ages of two and fifteen years. Compared with control brains (N=6), the autistic brains had an estimated 68% increase in the number of neurons in DLPFC, as well as abnormal clustering, irregular spacing, and disorganization of the cortical layers. There was also much more patchy expression of various genes in the different cortical layers of the autistic brains. Inevitably (and thankfully), the sample size was small. The age range was also large and it wasn’t clear what had caused these tragic deaths or whether that might have been related to the neuropathology rather than it being autism-related. So we have to be cautious about these (nevertheless intriguing) results.

Later in the day, Cyndi Schumann presented a further series of neuropathological studies, this time focusing on the amygdala. Again, there is cross-sectional data suggesting initial amygdala overgrowth in young children with autism. Her sample was somewhat older (10-44 years) and she took care to exclude people with a history of seizure disorder that might have confounded results. Although there were no differences between autism and control brains in terms of overall volume, there were significant reductions in the number of neurons in various nuclei of the amygdala. She and her colleagues hypothesized that there may be degenerative processes at work, leading to loss of cells. Consistent with this, they found on average an increased number and size of microglia, indicating some form of neuroinflammation. However, there was considerable individual variability and the predicted inverse correlation between microglial number and neuron number wasn’t found.

Following on from that, Patrick Hof presented work on von Economo neurons – these are large neurons that have so far only been found in large-brained social mammals, including humpback whales, elephants, gorillas, and hippos (as well as humans). In most of these species, they are only found in the anterior cingulate and frontal insular cortex. Von Economo neurons are depleted in fronto-temporal dementia (a degenerative disorder related to inappropriate social behaviour), and have an abnormal distribution in Riley-Day syndrome (a disorder of the autonomic system). Somewhat surprisingly, the neuropathological study conducted by Dr Hof showed an increase in number in autism and a broader distribution. What this means wasn’t entirely clear to me.

Brain imaging:

Surprisingly, there were only two talks on brain imaging (and none tomorrow). Karen Pierce talked about fMRI studies of children as young as one year old, identified by paediatricians as possible cases of autism, language disorder, or developmental delay. The only way this kind of study is possible is to test the children while they are sleeping. Remarkably, playing them speech still leads to sensible responses in language-related regions. In the first study of its kind, Redcay and Courchesne found that children with autism had reduced activation in left temporal lobe but increased right hemisphere activation. And in fact the autistic children with greatest right hemisphere activity had the best language skills, suggesting perhaps that their right hemisphere is recruited to compensate for left hemisphere problems. A more recent study by Pierce and colleagues found that in non-autistic children, playing speech samples including the child’s name increased activation in the superior temporal sulcus. However, this was not true in autistic children. As Dr Pierce noted, failure to respond to their own name is a common sign of autism in young children. While still in its early days, this research has the potential to tell us a lot about early brain development in autism. My only slight concern is that, given the prevalence of sleep abnormalities in autism (e.g., reduction in REM sleep), it may be important to somehow monitor what stage of sleep the kids are in when the brain scan is being conducted.

The second brain imaging talk was presented by Declan Murphy, who gave a whistlestop tour of a number of recent and ongoing MRI studies with autistic adults. Using traditional structural MRI, his research group have shown differences in temporal, occipital, and frontal lobe grey matter volume. Using magnetic resonance spectroscopy, they’ve shown reductions in glutamate concentrations in the basal ganglia. Using diffusion MRI, they’ve found differences in the arcuate fasciculus - the white matter pathway linking language regions of the left hemisphere. There was more, but I wasn’t writing fast enough to get it all down. Murphy’s aim is to be able to use some of these measures to assist in diagnosis. I’ve previously blogged about a study this group conducted using MRI to diagnose autism and, as various other people did at the time, suggested that there are many hurdles to overcome before that becomes a reality. Prof Murphy was careful to emphasise that they are still very much at the proof of concept stage, although he was confident that objective brain-based diagnoses are ultimately achievable.

There were a couple more studies at the end of the day by Drs Blatt and Pardo, but sadly I can't make much sense of my notes. Will try and do a better job tomorrow!

PS: If there's anything here that you notice is wrong (and there almost certainly will be), please comment and I'll make the corrections. As I say, this is all pretty much new to me!

Update (18/03/11):

Many (if not all) of the presenters at the meeting contributed to a special issue of the journal, Brain Research dedicated to The Emerging Neuroscience of Autism.

In case it wasn't obvious, I blogged Day 2 here.

Pitch discrimination in autism - links to language delay?

2010-11-03T06:48:00.000-07:00

Until recently, research on perception in autism has focused primarily on the visual modality. However, there is now a growing body of research on auditory processing. Of particular note are two recent studies, both published in the journal Neuropsychologia, which report enhanced auditory discrimination abilities in a subgroup of individuals on the autism spectrum.

"Beep"

The first of these studies was conducted by Catherine Jones and colleagues from the Institute of Education in London, who tested 72 adolescents with autism and a control group matched on age and IQ. Participants played a computer game in which they saw two dinosaurs, each of which produced a pure tone (beep) sound. They simply had to decide which dinosaur had made the higher sound. If they got two in a row correct, then the task got slightly more difficult (the two dinosaur sounds were made more similar in pitch). If they were incorrect then the task was made slightly easier. In this way, the researchers could work out each participant's threshold for detecting a pitch difference between two tones. Participants also completed similar tasks that involved discriminating between tones of different amplitude (loudness) and duration.

The performance of adolescents with autism on the tests of duration and amplitude discrimination was fairly unremarkable. But while the group differences in pitch discrimination threshold also failed to reach statistical significance, Jones et al noted that a disproportionate number of the adolescents with autism performed exceptionally well on the task. To be precise, 20% of the autism group (14/72) had thresholds that would have put them in the top 9% of the control group*. Interestingly, these exceptional performers were themselves disproportionately made up of adolescents with a history of language delay (based on parental interview)

Broadly comparable results were reported in a second study, this time from a Canadian group headed by Anna Bonnel from McGill University. Adults with autism performed better than control adults at discriminating between pure tones based on pitch. However, adults with Asperger syndrome failed to show this advantage. Given that participants were allocated to the autism or Asperger group based on parental reports of early language development, this again suggests a link between early language delay and exceptional pitch perception. Notably, differences were again found only for discrimination of pure tones. On other tasks involving complex tones or speech stimuli, performance was comparable across the groups.

Some caution is justified here. In both studies, the key results are hovering around the borders of statistical significance, so it's not clear how robust they are. Nevertheless, the apparent link between enhanced pitch discrimination and delayed language is as intriguing as it is counterintuitive. Not least because studies using the same tasks with non-autistic children with language difficulties have found the opposite pattern or results - a subgroup of these children have very poor pitch discrimination.

Jones and colleagues float the possibility that enhanced pitch perception may actually disrupt language processing. Bonnel et al, on the other hand, suggest that diminished interest in linguistic stimuli might lead to enhanced discrimination skills for non-linguistic stimuli. Both hypotheses are fairly speculative at this point, particularly as they assume that participants' current auditory thresholds, measured in adolescence or adulthood, are a fair reflection of their auditory skills in early childhood.

Looking at the bigger picture, what these two studies highlight is the importance of looking at differences between individuals with autism rather than focusing only on differences between autistic and non-autistic participants. It seems that there are some autistic people with very good pitch discrimination skills. But this isn't true of everyone, and there's no real reason to suppose that it should be. As is often pointed out, autism is a heterogeneous disorder - if you've met one person with autism, you've met one person with autism. So asking whether a particular faculty is impaired / unimpaired / enhanced (delete as applicable) is probably not the best research strategy. Investigating the nature of this variation, whether at the cognitive or neurobiological level, should ultimately lead to a better understanding of the mechanisms that cause different forms of autism

* The cut-off for 'exceptional performance' was 1.65 standard deviations away from the control group mean. 4 of the 48 kids in the control group also met this criterion.

References:

Bonnel A, McAdams S, Smith B, Berthiaume C, Bertone A, Ciocca V, Burack JA, & Mottron L (2010). Enhanced pure-tone pitch discrimination among persons with autism but not Asperger syndrome. Neuropsychologia, 48 (9), 2465-75 PMID: 20433857

Jones CR, Happé F, Baird G, Simonoff E, Marsden AJ, Tregay J, Phillips RJ, Goswami U, Thomson JM, & Charman T (2009). Auditory discrimination and auditory sensory behaviours in autism spectrum disorders. Neuropsychologia, 47 (13), 2850-8 PMID: 19545576

Can a magician trick people with autism?

2010-10-12T06:08:00.000-07:00

Are people with autism susceptible to magical illusions? There are a number of reasons to suspect that they might not be.

Firstly, magicians rely on misdirection. They'll use eye gaze and gesture to make sure the audience is looking one way, while they're secretly switching the cards or sneaking an elephant into a hat (or whatever it is they do). People with autism, it's argued, are less sensitive to these kinds of social cues, so perhaps they're not as easily misdirected.

Second, as mentioned in a previous post, there are a number of studies suggesting that people with autism are less susceptible to visual illusions. They see what's there in front of them rather than what they're supposed to see. Another reason to think that the magician might not be able to trick them as easily as a non-autistic person.

Gustav Kuhn and colleagues set off to test this prediction by getting participants to watch a short video clip of the vanishing ball illusion. In the clip, a magician threw a ball up in the air twice. He then pretended to throw the ball a third time but actually kept hold of it. Non-autistic people tend to report that they have actually seen the ball thrown a third time before disappearing into thin air. The illusion is particularly strong if the magician looks to where the ball is expected to be.

Keep your eye on the ball...

Surprisingly, Kuhn et al. found that adults with autism were, if anything, more susceptible to the illusion than non-autistic adults. They would report having last seen the ball at a much higher location. And when asked what had happened to the ball, they were more likely to give an explanation that involved the ball leaving the hand.

Kuhn et al also report some eyetracking data, which provides some clues. It turns out that the participants with autism spent less time fixating on the ball. They also tended not to follow the ball to the top of its trajectory, which fits in well with other studies showing problems on smooth pursuit tasks, in which participants have to follow the trajectory of a moving object.

The authors conclude that the adults with autism were misdirected by the magician's social cues, challenging the idea that they have social attention difficulties. This is quite a bold conclusion to reach based on a single 6-second video clip, particularly as there was no comparison between clips with and without social cues. And the eye-tracking data seems to suggest an alternative explanation - that the autistic adults were tricked because they simply were not following the ball closely enough.

Nevertheless, the study highlights the potential of using magic tricks as a means of investigating the social and non-social attention skills of people with autism. It would certainly be interesting to see how they fare on other magical illusions. At this stage, I'm not making any predictions.

Reference:

Kuhn G, Kourkoulou A, & Leekam SR (2010). How Magic Changes Our Expectations About Autism. Psychological science : a journal of the American Psychological Society / APS PMID: 20855904

Do children with autism understand the link between seeing and knowing?

2010-09-22T16:36:00.000-07:00

Autism researchers are control freaks. A large part of what we do is concerned with ruling out alternative explanations for our results, which involves designing carefully controlled experiments. Autism is a pervasive developmental disorder, meaning that it affects just about every aspect of cognition (and apparently most parts of the brain). So there are always plenty of alternative explanations to worry about. And attempting to publish your research involves running the gauntlet of reviewers, each primed with their own alternative explanations, which you hadn’t even considered let alone controlled for. Some of these may even be plausible.

In a new paper in Journal of Autism and Developmental Disorders, Sophie Lind and Dermot Bowler report a study looking at autistic children’s understanding of the concept that seeing something leads to knowing about it. This is an interesting topic because understanding the link between a person’s perception of the world and their consequent mental states is an important milestone in the development of theory of mind. And, of course, impaired theory of mind is widely argued to be the root cause of the social difficulties in autism. However, the study also highlights some important methodological issues relating to experimental control in autism research.
As Lind and Bowler point out, previous studies looking at the performance of autistic kids on "see-know" tests have had one major methodological problem or another. Either there have been floor effects (even the control group struggled on the task), or group differences have been confounded with differences in language ability. In one case, the statistical analyses and conclusions didn’t actually match up with the data reported. On top of this, it isn't really clear that failure on "see-know" tests is indicative of specific problems with comprehension of seeing and knowing. It could just be that kids with autism find these kinds of questions difficult in general.
To address these issues, the authors took a number of steps. They ensured that the tasks were age-appropriate to avoid floor effects and they compared the performance of children with autism to a control group matched on age and verbal ability, allowing them to rule out language difficulties as a potential explanation. Most importantly, they added control questions to ensure that the kids could actually do the task. These questions were similar in structure and format to the "see-know" questions. The idea being that, if kids with autism can pass the control questions but still fail the "see-know" questions, then we can rule out any alternative explanation that predicts that they should also fail the control questions.

Lind and Bowler’s "see-know" test was similar to those used in previous autism studies. It involved two Playmobil characters, John and Fiona, and a load of boxes. On each trial, one of the characters opened a box, the other looked inside, and the child was asked “Who knows what is in the box?” The control task involved scenarios that didn’t involve seeing and knowing but were similar in their structure and memory demands. For example, the child was told that Fiona cut her knee while John got muddy knees; they were then asked who had sore knees.

Are you thinking what I'm thinking?

90% of the control children passed the see-know test, getting it right on at least 4 of the 5 trials. In comparison, only 60% of autistic children passed. However, children with autism were also much more likely to fail the control task.

The authors therefore excluded all the children who failed the control task, reasoning that their problems on the see-know task could be explained away in terms of “extraneous” task demands such as recalling the action sequences or making inferences in general. They then reanalysed the data, looking only at the children who passed the control task. There was still a statistically significant difference between the pass rates of the two groups, and so Lind and Bowler concluded that “children with ASD have a specific deficit in understanding that seeing leads to knowing”.

In many ways, this is a really neat study. Methodologically, it is certainly a cut above previous work in this area, for all the reasons mentioned earlier. The results seem pretty compelling - even controlling for all the extraneous task demands, there are still significant group differences in the pass rates. Case closed one might think. But, there is just one more thing…

Typically, researchers just exclude the participants who fail the control task and we hear no more about them. We’re left to assume that they would have failed the theory of mind task too. Helpfully, Lind and Bowler include the full cross-tabulated data showing the number of children in each group who passed and failed each task.

Table 2 from Lind & Bowler (2010)

The kids who either pass both questions or fail both questions don't really tell us much. What we’re really interested in is the performance of kids in the off-diagonal cells of the tables – the ones who pass one task but fail the other. If autism is associated with specific difficulties understanding seeing and knowing, then we would expect to see lots of kids failing the see-know task despite passing the control task. In fact, only 8 out of the 40 kids with autism show this pattern (highlighted in the table). Three kids with autism actually show the opposite pattern. However, these kids were excluded in the final analysis. In the control group, the numbers are smaller but the ratio (2:1) is similar.

So, at the risk of sounding like one of those annoying reviewers I'm not entirely convinced that children with autism really do have a specific deficit in understanding that seeing leads to knowing. If anything, this reaffirms the importance of Lind and Bowler's novel control tasks. Further proof that, in autism research, control is everything.

Reference:

Lind, S., & Bowler, D. (2010). Impaired Performance on See-Know Tasks Amongst Children with Autism: Evidence of Specific Difficulties with Theory of Mind or Domain-General Task Factors? Journal of Autism and Developmental Disorders, 40 (4), 479-484 DOI: 10.1007/s10803-009-0889-y