The Prodigy's Cousin

by Joanne Ruthsatz

  In the midst of this first run of art shows—a six-month period that eventually included a trip to Malibu and a return to Boulder City—Doug decided they needed help. Autumn’s artwork was selling. She sold Paradise, a pastel with two birds, for over $1,000; someone paid more than $1,000 for a work Autumn had donated for a charity auction; a middle-aged man offered $10,000 for Sunrise, though Autumn had refused to part with it. Doug researched art agents, came across a man who specialized in child artists, and contacted him. The two met at an art auction the October Autumn turned eight, and after seeing a sampling of Autumn’s work, the agency took her on as a client.

  At the time, Autumn’s work was evolving. The images from her art books had been percolating, and she was shifting away from abstract art in favor of injecting her personality—adding a shot of joyful, mischievous pixie dust—into other artists’ iconic pieces. Dripping Ideas, the portrayal of her creative process, was inspired by Dalí’s melting clocks. When she received a Barbie from her grandmother, she decided to put her own spin on Andy Warhol’s Marilyn Monroe paintings. Not wanting to dirty her new toy, she popped the head off her doll and used it as the model for Barbie Marilyn and Gold Barbie Marilyn. She followed these up with Heart Target, replacing Jasper Johns’s bull’s-eye targets with nesting hearts, and American Graphic, in which she substituted a pink crayon for the pitchfork in Grant Wood’s iconic American Gothic.

  When Autumn was eight, her work was sold as part of an art auction in California. Her paintings generated more than $100,000 in sales; one piece sold for $25,000. “We were definitely overcome, and we were definitely just on cloud nine, and it was unbelievable,” Doug said. “Had she sold nothing, it still would’ve been an incredible victory—an incredible victory. So, it wasn’t about the sales. The sales were just gravy, but, wow, that’s a lot of gravy. It was proof of concept in a wonderful way.” She had her first solo gallery exhibition in Stone Harbor, New Jersey, when she was ten years old.

  The media caught wind of Autumn, whose mix of spunk and innocence can make her seem like a real-life American Girl character. Everyone wanted a few minutes with the “pint-sized Picasso” (Inside Edition), the “pocket-sized genius” (the Daily Mail), the “mini-Pollock” (The Huffington Post). She was an interviewer’s dream; articulate and composed, she seemed more self-assured adult than pre-tween: “an old lady in a young person’s body.” She was also spunky (“a pistol,” as Matt Lauer put it), charming (when asked about earnings, she quips that she’s not the money girl), and so clearly young (hair in braided pigtails and sparkling pink headbands).

  There was, of course, the usual din from the doubters: those who criticized Autumn’s artwork or, attacking from the opposite perspective, those who doubted that she did it herself. The de Forests occasionally responded, and Doug posted videos online of Autumn at work.

  But Autumn kept painting, and the opportunities kept rolling in. She created a series of Disney princess paintings to promote the uDraw GameTablet, signed autographs at the National Art Education Association convention, and produced the artwork used on the inside of the cover booklet for Let Us In: Americana, a Paul McCartney tribute album.

  She had other hobbies. She loved reading, old movies, horseback riding, and animals. But painting was her unrivaled passion. She painted every day—three or four hours on school days and more on weekends. She described herself as itching to paint, compared painting to breathing, and said that she needed to create art to be happy and live. In one interview, she described the dreams she has about what the world would be like without art: it’s beige, white, and boring, and it breaks her heart.

  Joanne flew to Las Vegas in October 2012 to meet Autumn, who was just about to embark on a series of gallery exhibitions and auctions. She gave Autumn the same IQ test she had administered to the other prodigies. She again found that linchpin of prodigy—an exceptional working memory. But there was an interesting wrinkle: Autumn’s score on the visual-spatial subtest of the Stanford-Binet was lower than her scores on the other parts of the test.

  The same thing had happened once before. Lauren Voiers—the only other art prodigy Joanne had tested up to that point—had a similar dip on this part of the test. At the time, Joanne had assumed that Lauren had just run out of energy. After all, Lauren was an artist. How could she not have excellent visual-spatial skills? But once Joanne tested Autumn, there were two prodigies, both artists, with relatively low visual-spatial scores. None of the other prodigies—not the musicians, not the scientists—showed the same pattern.

  Joanne was intrigued. She had long focused on the similarities between the prodigies. After all, they shared something stunningly unique—a flash of talent so bright it created a personal spotlight. Could there really be important underlying differences between them?

  Joanne contacted and tested more art prodigies; she worked with more music and math prodigies along the way. By early 2013, she had broadened her sample of IQ-tested prodigies to eighteen: eight music prodigies, five math prodigies, and five art prodigies.

  The prodigies’ average overall IQ score was 126, well above 100, the average score for the test. Working memory remained the stalwart of prodigiousness: the group of eighteen had an average score of 140—a score more than two standard deviations above the mean. There was only one real working memory outlier, a child with an interest in engineering who scored a 109.

  But it was the differences in the prodigies’ scores that were most intriguing. Whether you looked at the prodigies’ overall IQ scores or sliced them up by subtest, there were variations in the art, music, and math prodigies’ results. Even with a sample size of just eighteen (again, small for most studies, large by prodigy standards), many of those differences reached statistical significance—the academic equivalent of screaming for attention.

  The math prodigies had an average overall IQ score of 140, well above the music prodigies’ and art prodigies’ group averages. Even the lowest-scoring math prodigy pocketed an overall score of 134—placing him more than two standard deviations above the general population average. The math prodigies built their way to the top of the IQ pyramid by outscoring their prodigy peers on several of the subtests. They had the highest fluid reasoning (the ability to reason through unfamiliar problems) and knowledge scores of the bunch. Same story with quantitative reasoning; the math prodigies outscored both the music and the art prodigies. The math prodigies’ results were perhaps not entirely surprising. David Feldman and Martha Morelock had previously predicted that prodigious skill in science or math might require high IQ scores. This study provided the first concrete evidence that this was so.

  In a group chock-full of kids with astounding working memories, the musicians out-recalled them all. They had an average score of 148 for this subtest—more than three standard deviations above the mean for the general population.

  But it was the visual-spatial breakdown—the subtest that had launched Joanne’s interest in the differences in the prodigies by specialty in the first place—that raised the most questions. The artists’ dip in visual-spatial scores held. As a group, the art prodigies had an average visual-spatial score of 88, their lowest mark on any part of the test. Not only did they score significantly lower than the math and music prodigies, but the artists tended to score below the average for the general population on this subtest. It almost seemed like a deficit in visual-spatial abilities was necessary for artistic talent.

  It was counterintuitive: Shouldn’t artistic composition require excellent visual-spatial skills? The answer is yes—sort of. Artists do rely on visualization, the process of “seeing with the mind’s eye” or conjuring an internal representation of an object, landscape, or event. The nitty-gritty of it comes down to the type of visualization upon which they rely: object visualization versus spatial visualization. An object visualizer’s mental imagery is detailed and focused on physical attributes—an item’s color, shape, brightness, and size. A spatial visuali
zer’s mental imagery is more three-dimensional; it’s focused on an object’s position relative to its surroundings, its movement through space, and its physical transformation.

  A 1985 study involving two brain-damaged patients illustrates the difference: Following a car accident, Patient 1’s object imagery declined (he struggled to recognize people either in person or in photographs). His spatial imagery, though, remained intact (he could give detailed directions and locate major cities and states on a map). Patient 2’s object imagery survived a brain hemorrhage (he could still identify objects, animals, and people). His spatial imagery didn’t fare so well (he often collided with objects in his path and couldn’t distinguish left from right).

  So which type of visualization was the IQ test measuring—object or spatial?

  The Stanford-Binet, like many intelligence tests, is rooted in the Cattell-Horn-Carroll (C-H-C) theory of cognitive abilities. The visual-spatial subtest is intended to measure the C-H-C’s visual processing ability—an individual’s ability to recognize an object, understand its location, and predict its motion or transformation. Its “core” is the “ability to perceive complex patterns and mentally simulate how they might look when transformed (e.g., rotated, changed in size, partially obscured).”

  In other words, the visual-spatial subtest measures spatial visualization. This type of visualization is often linked to math and science talent. Consider, for example, that numbers appear to the math prodigy Jacob Barnett as shapes that he can manipulate to solve problems. Galileo similarly visualized motion through space to develop the idea that objects in a vacuum fall at the same rate, regardless of weight. Both of these problem-solving techniques rely on spatial visualization.

  Not surprisingly, then, the math prodigies walloped the visual-spatial subtest. They had the highest average score, by far, of the three groups: 142 compared with 117 for the musicians and 88 for the artists. Even the lowest-scoring math prodigy snared a 132 on the visual-spatial subtest—a score more than two standard deviations above the average for the general population.

  In theory, this left object visualization, a skill tied to artistic ability, unmeasured. But were the artists’ object visualization abilities a complete unknown? Perhaps not.

  The psychologist Maria Kozhevnikov and her colleagues, the team behind some of the most interesting research on distinguishing object visualization from spatial visualization, have hit on an intriguing find that may provide a clue as to the artists’ object visualization abilities. It turns out that not everyone is a visualizer. Some people—verbalizers—approach problems wielding words and logic instead of the visualizers’ mental imagery. But Kozhevnikov and her colleagues have found that people who are visualizers experience a trade-off between object and spatial visualization—the price of excelling at one is a deficit in the other. Scientists’ above-average spatial visualization generally comes hand in hand with below-average object visualization. Visual artists’ below-average spatial visualization is generally accompanied by above-average object visualization.

  Viewed from this perspective, for an artist, a low visual-spatial score isn’t a deficit. It’s a badge of honor. It marks a different type of talent, one not directly measured by the Stanford-Binet; it hints at a reservoir of vivid, detailed object imagery—a critical attribute of an artist.

  Most of Joanne’s work had been geared toward unearthing the inner workings of the prodigy mind. She had long assumed that she would find core similarities in the group. After all, the flash of childhood achievement they shared was extraordinary; surely that rare explosion of talent, when it occurred, had to be caused by the same underlying mechanism.

  To some extent, that assumption was borne out by the prodigies’ extraordinary memories and excellent attention to detail. But the prodigies’ seemingly irresistible attraction to their fields of interest suggests differences between them. Autumn de Forest’s road to painting, for example, feels like destiny, like something she was meant to find. No one pushed it on her. Her parents introduced her to drums; they provided piano lessons. Autumn was a willing-enough student. She had fun experimenting with music. But there was no spark. Music didn’t speak to her. As Autumn put it, “I hadn’t really found it yet; I hadn’t really discovered it yet.” It’s almost as though art were waiting for her. Once she found it, the connection was electric. Autumn latched onto painting as if it were a drug, a tonic, and a path to survival.

  Most prodigies tell the same story. They didn’t waffle over which activity to pursue or weigh the pros and cons of different endeavors. They felt called to something specific. They discovered that something early and clung to it with both fists. Around the time he was two, the music prodigy Jay Greenberg began drawing cellos even though, as far as his parents could remember, he had never seen one. He requested one of his own. Music sprouted from his mind involuntarily. “I just hear it as if it were a, a smooth performance of a work already written, when it isn’t,” he said during a 60 Minutes interview. Jacob Barnett, the science prodigy who took a college astronomy course at eight years old, was obsessed with light and shadows as a baby and, at three, grew so engrossed with an astronomy book—a book so large he had to drag it around on the floor—that his dad had to duct tape its spine to hold it together. The music prodigy Jonathan Russell began saying the word “violin” at eighteen months and repeated the word every time he saw one. Soon thereafter, he could pick the sound of the violin out of audio recordings.

  The prodigies’ IQ-test results suggest that the reasons each chose a particular specialty had to do with deep-rooted differences between them. A quick glance at their visual-spatial scores reveals that something is going on in the prodigies’ brains that sharply divides the math from the art specialists—a critical cognitive difference that led some prodigies to excel at art and others at math.

  The object and spatial visualization abilities of the art and math prodigies, moreover, aren’t only distinct in practice; they rely on separate neural pathways: the ventral pathway (the “what” pathway) processes object imagery, while the dorsal pathway (the “where” pathway) processes spatial imagery. The art prodigies seem to have an express pass to the ventral pathway, while the math prodigies have the same sort of access to the dorsal pathway.

  Autumn then isn’t just a kid with a souped-up memory, a turbocharged engine that would have driven her to blindly latch onto trombone, paintbrush, or equation with equal fervor. She’s a precision instrument. She always had the horsepower for prodigiousness, but she had to find the right lock-and-key fit to unleash it. She needed a task that called upon her very specific mental profile to reveal her extraordinary abilities. She isn’t just a prodigy; she’s an art prodigy.

  But if there are important distinctions among the prodigies, does it make sense to think of them as belonging to the same group? Once you dig into the children’s cognitive profiles and come up with important differences, is there really even such a thing as a “prodigy”?

  There’s another field of research in which researchers face the same question, another field of research in which a focus on behaviors has obscured underlying differences: autism. Is it really one distinct condition? Over several decades, researchers gritted their teeth and tried to find a reliable way to distinguish autism from other disorders. They ransacked autists’ behaviors, cognitive tendencies, and, eventually, genes. But despite the mighty efforts of a slew of scientists, those diagnosed with autism defy neat packaging. If a unifying factor that cleanly separates autists from non-autists exists, it’s an elusive beast in a field brimming with hunters.

  The difficulty of isolating autism-specific symptoms begins at the behavioral level. Kanner’s original 1943 paper described a number of behavioral traits that he had observed among his autistic patients, and he specified that the condition’s defining characteristic was “the children’s inability to relate themselves in the ordinary way to people and situations from the beginning of life.”
But in the early years of autism research, scientists attempting to investigate this new condition used varying criteria. By the early 1970s, one researcher had already observed that there was no symptom that definitively indicated autism; the symptoms associated with autism were also characteristic of a number of other disorders. In a classic 1979 paper aimed at clarifying the clinical picture of autism, the British researchers Lorna Wing and Judith Gould concluded that their results called “into question the usefulness of regarding childhood autism as a specific condition.” Recently, a team of researchers proposed that the behavioral symptoms used to diagnose autism are largely independent of one another. Even autistic siblings often have significant differences in their social and communication abilities. This variety in behavioral symptoms is well captured by the oft-repeated quotation that “if you’ve met one person with autism, you’ve met one person with autism.”

  Digging a level deeper didn’t help. Researchers struggled mightily to identify a core cognitive characteristic of autism—an underlying trait that would explain all of autism’s symptoms. One by one, the first generation of cognitive theories—theory of mind, weak central coherence, and executive dysfunction—were revised or abandoned. Their modern counterparts and new cognitive theories seem to be a better fit, but no one has yet identified a cognitive trait or traits possessed by all autists and not possessed by any non-autists.

  It’s the same story with genetics. Initial optimism that scientists would isolate common genetic risk factors for autism quickly faded. Researchers found not one but dozens of genes—some studies predict that the ultimate count will be in the hundreds—implicated in at least some cases of autism. Even the most prevalent of these genetic variants are tied to less than 1 percent of autism cases. In 2009, one team of researchers observed that “the genetic architecture of autism is as exquisitely complex as is its clinical phenotype” (basically, there are as many autism-related genes as there are variations in individual autists—many). It turns out that even autistic siblings often have different genetic risk factors for autism. Instead of a single genetic pathway to autism, it appears there are many.