The Autistic Brain: Thinking Across the Spectrum (16 page)

“We are searching for actionable diagnosis,” he says. “Not just that we say, ‘Yeah, you’re different,’ but, ‘You are different and because of this particular form of difference, we think this is the most likely path for getting you to as much of the outcome as we want you to get.’ We want to go in and in on that individual brain—not a group study but an individual brain—so we can say to a parent, ‘This is what the situation is, this is what we expect the effect to be, and this is how we plan to get around it as efficiently as possible to give you effective communication with your child in the next two years.’”

You can hear the same argument beginning to surface in genetics as well. Yale neurogeneticist Matthew W. State likes to invoke the medical phrase
from the bench to the bedside
—meaning from experiments on groups to treatments for individuals. In a 2012 article in
Science,
he and collaborator Nenad Šestan suggested that researchers look for inspiration from other areas of medicine that have made this transition. “For example, heart disease and stroke prevention both rely in part on the management of hypertension,” they wrote. “It may well be that ASD and schizophrenia will increasingly be thought of in a similar light”—different behaviors arising from the same genetic source. As a result, Šestan and State anticipated that treatment trials would be organized around “shared mechanisms” rather than “psychiatric diagnostic categories.” They didn’t doubt that this rethinking of the autistic brain would be challenging. But like Schneider, they foresaw the development of therapies that were not only more effective but “more personalized.”

Twenty years from now, I think we’re going to look back on a lot of this diagnostic stuff and say, “That was garbage.” So as I see it, we have a choice. We can wait twenty years and several more editions of the
DSM
before we start to clean up this mess. Or we can take advantage of the technological resources that are beginning to become available and start phase three right now.

As you will soon see, I choose phase three.

6

A
FEW YEARS AGO
Michelle Dawson, an autism researcher at the Rivière-des-Prairies hospital at the University of Montreal, asked herself an important question. Her research on the autistic brain, like the other autism research at the clinic, like autism research everywhere, focused on cognitive impairment—on what was wrong. And she realized that when an autistic person exhibited characteristics that we would call strengths if they belonged to a normal person, we still saw those strengths as merely the fortunate byproducts of bad wiring.
But what if they’re not?
she asked herself. What if they’re not the
byproducts
of anything? What if, instead, they’re simply the
products
of wiring—wiring that’s neither good nor bad?

She and her colleagues began digging in the literature. Sure enough, they found that studies routinely emphasized only the negative aspects of autism, even when some of the results were positive. According to Laurent Mottron,
Dawson’s frequent collaborator and the director of the autism program at Rivière-des-Prairies hospital, “Researchers performing fMRI scans systematically report changes in the activation of some brain regions as deficits in the autistic group—rather than evidence simply of their alternative, yet sometimes successful, brain organization.” When researchers look at cortical volumes, for example, they automatically throw variations into the deficit bin, regardless of whether the cortex is thinner or thicker than expected. And even when a study does recognize a strength in autistic subjects, the authors often regard it as the brain’s way of compensating for a deficit—but a 2009 report
in the
Philosophical Transactions of the Royal Society
that reviewed papers based on this assumption concluded “that this inverse hypothesis rarely holds true.”

Dawson and her colleagues began conducting their own experiments to determine the intelligence level of people with autism. In 2007 they designed a study
that used two common tests of intelligence, the Wechsler Intelligence Scale for Children and the Raven’s Progressive Matrices. The Wechsler test consists of twelve subtests, some verbal and some nonverbal (arranging blocks into designs, for instance). The Raven’s is totally nonverbal. It consists of sixty questions that show a series of geometric designs and then a choice of six or eight alternative designs, only one of which completes the series. These tests were administered by independent neuropsychologists who were unaware of the purpose of the study, and the test subjects included fifty-one children and adults with autism and forty-three children and adult controls.

The results were striking. Dawson found that the measure of intelligence in the autistic population depended on the type of test. On the Wechsler, one-third of the test subjects with autism qualified as “low functioning.” On the Raven’s, however, only 5 percent did so—and one-third qualified as having “high intelligence.” On the Wechsler, the autistic subjects on the whole scored far below the population average, while on the Raven’s they scored in the normal range. I myself have scored really well on the Raven’s Coloured Progressive Matrices.

Why such a wide disparity in responses to the two tests? Perhaps because answering many of the Wechsler questions correctly depends on the social ability to acquire skills and information from others, whereas the Raven’s is purely visual.

“We conclude,” the Montreal group wrote in their groundbreaking study published in
Psychological Science
in 2007, “that intelligence has been underestimated in autistics.”

“Scientists working in autism always reported abilities as anecdotes, but they were rarely the focus of research,” one of the authors of the paper, Isabelle Soulières, later said.
“Now they’re beginning to develop interest in those strengths to help us understand autism.”

This new attitude toward autism is consistent with the phase-three thinking that I described in the previous chapter. Just as we can now begin to look at autistic-like behavior on a trait-by-trait basis, we can also reconceive autistic-like traits on a brain-by-brain basis.

Don’t get me wrong. I’m not saying that autism is a great thing and all people with autism should just sit down and celebrate our strengths. Instead, I’m suggesting that if we can recognize, realistically and on a case-by-case basis, what an individual’s strengths are, we can better determine the future of the individual.
I need you to fix me,
Carly Fleischmann, the nonverbal we met in chapter 4, once typed.
Fix my brain.
By contrast, when a journalist
asked Tito Rajarshi Mukhopadhyay, the other nonverbal we met in chapter 4, “Would you like to be normal?” Tito answered, “Why should I be Dick and not Tito?” For Tito, the “acting self” might have been weird, but it was no less a part of him than his “thinking self.”

I also want to be clear that when I say
strengths,
I’m not talking about savant skills like those of Stephen Wiltshire, who needs only one helicopter tour of a portion of a city, like London or Rome, in order to draw the entire landscape down to the last window ledge, or Leslie Lemke, who needs to hear a piece of music only once—any style, including complex classical compositions—in order to re-create it on the piano. Only about 10 percent of autistics belong in the savant category (though most savants are autistic).

So what strengths
can
we look for? While autism researchers traditionally haven’t seen this trait as a strength, they’ve nonetheless noted over the years that people with autism often pay greater attention to details than neurotypicals. Let’s start there and see where it takes us.

Bottom-Up Thinking

People with autism are really good at seeing details. “When a person with autism walks into a room,” one researcher said,
“the first thing they see is a stain on the coffee table and 17 floor boards.” That seems an exaggeration and an overgeneralization to me, but the idea is on the right track.

Traditionally researchers have characterized this trait as “weak central coherence”—a deficit. Weak central coherence is at the heart of the impairments in social communication and social interactions that have long been part of the official diagnosis of autism. More informally, you can say that autistic people have trouble putting together the big picture, or that they can’t see the forest for the trees.

Think about Tito and his encounter with the door. He saw the door as a series of properties—its physical features (hinges), its shape (rectangular), its function (allowing him to enter the room). Only when he’d collected enough details did he know what he was seeing. When I met him at a medical library, I asked him to describe the room. Rather than discussing the objects in the room or the size of the room, he talked about fragments of color.

My experience is nowhere near as extreme, but the tendency to see details before I see the big picture has always been a central feature in how I relate to the world. When I was a child, my favorite repetitive behavior was dribbling sand through my hands over and over. I was fascinated with the shapes; each grain looked like a tiny rock. I felt like a scientist working with a microscope.

A landmark study
in 1978, “Recognition of Faces: An Approach to the Study of Autism,” brought the social implications of this trait to the forefront of research. Subjects were shown only the lower parts of a series of faces of people they knew and asked to identify the people. The autistic population performed better than the controls. The same was true when both groups were shown inverted images. The people with autism were better at figuring out what the image was when it was upside down. The researcher who performed the study, Tim Langdell, posited that people with autism were better at seeing “pure pattern” rather than “social pattern.”

This interpretation would be consistent with results from biological motion tests. You know motion-capture technology in filmmaking, where an actor wears a bunch of white dots that map his movements in a computer? That’s biological motion. On a computer screen, biological motion is nothing more than dots moving, but the dots are arrayed in such a way that they suggest an action a living person or animal would perform, like running. Studies
have repeatedly shown that people with autism can identify biological motion, but they don’t do so with the same ease as neurotypicals. Nor do they attach emotions and feelings to the motions. What’s more, they use different parts of the brain than neurotypicals do. Neurotypicals show a lot of activation in both hemispheres, while autistics show less activation overall. The way the autistic brain engages with biological motion is reminiscent of Tito’s description of focusing on a door at the expense of seeing the room, or a description by Donna Williams I once read, of her being entranced by individual motes of dust.

The interpretation of this tendency as a deficit in social pattern recognition was adopted by R. Peter Hobson in an influential series of studies
he spearheaded in the 1980s at the Institute of Psychiatry in London. Did children with autism prefer to sort photographs according to facial expressions exhibited (happy or sad) or the type of hat worn (floppy or woolen)? The hats won. Did children with autism have trouble putting the pieces of a face together into an interpretation of facial emotions? Yes.
⁹

These are important findings. But there can be a flip side to a deficit in social pattern recognition: a strength in pure pattern recognition—being really good at seeing the trees. Studies have repeatedly shown that people with autism perform better than neurotypicals on embedded-figure tests—a variation on the old something’s-hidden-in-the-picture game. Several years ago I took a test where I had to look at large letters that were composed of smaller, different letters—for instance, a giant letter
H
that was built out of tiny
F
s. I then had to identify either the big letter or the little letter. I was faster at identifying the little letters, a result that’s far more common among autistics than neurotypicals. Research has also shown
that when performing language tasks, the autistic subject relies on the visual and spatial areas of the brain more heavily than the neurotypical subject does, perhaps to compensate for a lack of the kind of semantic knowledge that comes with social interaction. An fMRI study
in 2008 showed that when the neurotypical brain conducted a visual search, most of the activity was confined to one region of the brain (the occipitotemporal, which is associated with visual processing), while what lit up in the autistic brain was just about everything. Perhaps this is why I can immediately spot the paper cup or hanging chain that’s going to spook the cattle, while the neurotypicals all around me don’t even notice it. Researchers have a lovely term for that tendency to see the trees before recognizing the forest:
local bias.

Consider Michelle Dawson, the researcher who thought to look for references to autistic strengths that are buried in the literature. She’s autistic. I can’t say she made her conceptual leap
because
she’s autistic, but I think she was more likely to make it because she herself possessed a fine attention to details. “Dawson’s keen viewpoint keeps the lab focused on the most important aspect of science: data,” Mottron wrote in a 2011 article
in
Nature.
“She has a bottom-up heuristic, in which ideas come from the available facts,
and from them only.
”

Dawson had always approached her research with the same received wisdom, making the same unthinking assumption, as her mentors and peers—that studying autism means studying deficits. But that assumption was the result of what Mottron identified in himself as a “top-down approach: I grasp and manipulate general ideas from fewer sources.” Only when he’s come up with a hypothesis does he “go back to facts.” Dawson found it easier to free herself of the preconceptions inherent in top-down thinking because she was able to see the details dispassionately and in isolation. When other researchers look at her data about autistic strengths and say, “It’s so good to see something positive!” she answers that she doesn’t see it as positive or negative: “I see it as accurate.”