The Flynn Effect's Unseen Hand

[Edit 02/11/2017: The final version of this essay can be found here.]

The Flynn Effect's Unseen Hand

An Environmental Description of Human Intelligence

Abstract. The Flynn effect is a well known but inadequately explained phenomenon. Many different causes have been suggested for the population-wide generational increases in raw intelligence scores—including heterosis, better nutrition, more abundant education, environmental complexity and various combinations of the above—but none of these explanations have proven to be scientifically or logically compelling. This lack of progress could be pointing to a misunderstanding of human intelligence itself, which is depicted these days almost entirely in terms of brain-based functioning alone. This brain-based focus, however, has been precisely the bedevilment in the many explanations of the Flynn effect, for it has been difficult to reconcile neuronal mechanisms producing individual intelligence differences with neuronal mechanisms producing widespread intelligence gains. Accordingly, this paper proposes an alternative model of human intelligence, one not centered on the human brain. This model will highlight two complementary aspects of human intelligence: 1. environmental intelligence, defined as the total amount of non-biological pattern, structure and form contained within the human environment, and 2. individual intelligence, defined as an individual’s capacity to absorb and respond to environmental intelligence. It can be shown that it is environmental intelligence that serves as the sole driver of the Flynn effect, independently of individual intelligence, and along the way it will be demonstrated how environmental intelligence is similar to but far more comprehensive than the concept known as environmental complexity. It will also be demonstrated that this dual-aspect model of human intelligence effectively answers several of the Flynn effect paradoxes enumerated by James Flynn himself.

Introduction. Generational gains in raw intelligence scores were first noticed by several individuals—including Reed Tuddenham and Richard Lynn—but it was James Flynn in the 1980s who most clearly demonstrated the ubiquitous nature of what has come to be known as the Flynn effect. In the quarter century since, the Flynn effect has attracted a good deal of study and ink—in part because the phenomenon has been regarded as surprising, and in part because the phenomenon has continued to defy adequate explanation.

This situation stands in contrast to many other areas of intelligence research, including investigations into the source and impact of individual and group intelligence differences. Using factor analysis, identical twin studies and many other tools of modern cognitive science, researchers have been able to demonstrate consistently that individual intelligence differences produce significant impact in such areas as academics and career, and that these individual differences are driven mostly by genetics and are almost certainly neuronally based. These discoveries and achievements have led to a nearly unanimous consensus that intelligence is to be regarded exclusively as a brain-produced activity—in short, greater intelligence is spawned by a more effective brain.

The Flynn effect, however, throws something of a monkey wrench into this widely accepted view. To accept the conclusion that intelligence is exclusively a brain-produced activity—an activity determined primarily by genetics—one also has to anticipate that overall human intelligence will remain relatively stable across time, in accordance with standard biological and evolutionary principles. That is why the Flynn effect has been regarded as so surprising. The sizable raw intelligence gains recorded across the entire twentieth century far outstrip any plausible, brain-based advancement that might be anticipated under a biological, neuronal, or evolutionary framework.

One response to this dilemma would be to search for an orthogonal influence underlying the Flynn effect, and James Flynn himself (1999) has uttered that very reaction in almost those exact same terms (“it is as if some unseen hand is propelling scores upward”). In addition, Richard Lewontin’s (1976) parable of the seed corn provides a nearly precise description of how such an orthogonal influence would actually work. And yet no one has managed to follow this line of reasoning to its ultimate conclusion. What prevents further advancement is the widespread certainty that intelligence is strictly a brain-produced event. All the offered explanations for the Flynn effect—be they heterosis, better nutrition, advancing education, environmental complexity, or any combination or alternative to the above—all explanations are brought back eventually to human neurology, all are ultimately depicted as inducing material impact upon the human brain. This depiction is of course made mandatory by the dogma that intelligence arises exclusively out of human neurons. Vigor, nutrients, schooling, video games—all must somehow change the human brain, must make it more effective, make it more intelligent. Unfortunately, this circling back to neurology serves only to re-create the original tension: now there are neural mechanisms explaining individual intelligence differences and there are other neural mechanisms explaining population-wide intelligence gains, and yet somehow these mechanisms are supposed to co-exist within the same human brain and not interfere with the intelligence-producing impact of the other. Plausibility once again rears its ugly head.

A more decisive alternative would be to drop the dogma altogether. Nothing actually compels acceptance of the idea that intelligence is strictly a brain-produced phenomenon. Despite the consensus, no one has yet to demonstrate an actual neural mechanism producing an actual intelligence effect. Neural activity certainly accompanies intelligence behavior—there is plenty of evidence for that—but as scientists are wont to caution, correlation is not the same thing as causation. Furthermore, with the Flynn effect still a puzzle and a mystery, bumping against many of the fundamental assumptions regarding intelligence, it would seem there is adequate motivation for casting the cognitive net a little wider.

This paper will describe a model of human intelligence that removes the center of intelligence away from the human brain and places it more firmly within the human environment, a concept dubbed as environmental intelligence. Thus freed from the constraints of biology, neurology and evolution, human intelligence can be seen as able to change and accumulate at a significant rate, which indeed it must if it is going to produce the phenomenon known as the Flynn effect. The human brain still gets to play a role within this new model—under a concept dubbed as individual intelligence—but this role will be described as secondary. Instead of producing human intelligence, the human brain will be depicted as responding to the intelligence contained within the surrounding environment—responsiveness after all being the activity traditionally reserved for neural systems.

Environmental Intelligence and Individual Intelligence. A fresh perspective can be gained on human intelligence by considering two orthogonal aspects—environmental intelligence and individual intelligence.

Environmental intelligence is defined as the total amount of non-biological pattern, structure and form tangibly contained within the human environment. This definition immediately ties human intelligence to the advancement of the human species. Prior to the human great leap forward, there would have been essentially no environmental intelligence to be found within the human surroundings, only natural settings, similar to all the other animals. But beginning with ostrich shell beads, bone awls, rudimentary clothing and cave paintings, and proceeding straight through to domesticated crops, mud-plastered abodes and towering pyramids, and crescendoing today in highways, skyscrapers, televisions and rockets to the moon, the one indisputable observation that can be made throughout that entire course of human progress is that no matter where man has found himself, he has found himself among an accumulating amount of non-biological pattern, structure, symmetry, repetition and form. Over the past fifty thousand years, man has been increasingly surrounded with environmental intelligence.

To actually measure environmental intelligence would be admittedly a pragmatic nightmare—the sheer enormity of pattern and structure contained within the modern world would alone overwhelm any genuine effort to size it, and furthermore, there could be no easy agreement on how to quantify structure contained within, for instance, an automobile or a library book. But these practical difficulties do not nullify the material certainty of measurement—environmental intelligence tangibly exists, one can touch it, hear it, talk about it, it exists right before one’s very eyes. Plus there is no need to actually measure environmental intelligence in order to attest to its ever increasing presence. Think of the North American continent alone. Only a few hundred years ago, man dwelled in but a handful of places there and the amount of non-biological environmental complexity would have been quite modest. But by one hundred years ago, man had taken up residence from nearly coast to coast and had augmented an entire patchwork of fields, houses and roads. Today one glance at the skylines of such cities as Chicago and Toronto would be more than sufficient to convince even the most dire skeptic that by almost any reasonable means of measurement, it would have to be calculated that the total amount of human environmental intelligence has been consistently on the rise.

The second, more familiar aspect of human intelligence, individual intelligence, is in many respects nothing at all like the first. Individual intelligence is defined as an individual’s capacity to absorb and respond to environmental intelligence, making it clear that individual intelligence is a secondary (a responding) construct. Nonetheless, the great value in this definition of individual intelligence is that it corresponds exactly to what gets measured on a modern intelligence test—IQ is an ideal quantification of individual intelligence. To see this, consider that the questions, the content, of an intelligence exam—language, arithmetic, geometrical patterns, and so on—these are constructed as proxies for environmental intelligence, and a person demonstrates his comparative capacity for mastering environmental intelligence by answering the questions correctly. Intelligence exams do not assess an individual’s abilities to scavenge food, ward off predators or procreate; instead everything that appears on an intelligence test emanates from the non-biological material artifacts that have been introduced into the human world over just the last several thousand years (and in some cases, over just the last tens of years). Therefore it is in no way surprising, just as psychometric analysis confirms, that those who are more successful in answering the proxies for environmental intelligence on an IQ exam are by and large the same individuals who are more successful at navigating a constructive path through the day-to-day surroundings of the modern world.

It is important to emphasize the orthogonal relationship of environmental intelligence and individual intelligence. Individual intelligence is a biological capacity, a human behavioral ability, and thus there is no objection to associating individual intelligence with neural and genetic causes. But environmental intelligence is not biological at all, it is instead a physical artifact, quantifiable within the material world, and it remains independent of any neurological or evolutionary constraint. Environmental intelligence and individual intelligence are each a crucial aspect upon human intelligence, but each delivers its influence in an entirely separate domain.

The Model. Armed with these definitions and descriptions of environmental intelligence and individual intelligence, it is a straightforward task to develop an illustrative example showing how these two aspects dynamically relate. All that is required from the reader is agreement that the practical difficulties in measuring environmental intelligence can be theoretically overcome, and consistent with observations from human history, environmental intelligence can be assumed to increase over any significant interval of time.

In the example to be developed, EIU (environmental intelligence unit) will be called upon as the arbitrary unit of measure, and the amount of non-biological pattern, structure and form in the hypothesized environment will be assumed to double from 200 EIU at time 1 to 400 EIU at time 2 (time 2 occurring several generations after time 1). All that then remains is to assess the intelligence scores of individuals at time 1 and compare these with the intelligence scores of individuals at time 2.

At time 1, the cognitive characteristics of three individuals—call them A1, B1 and C1—are assessed by means of a standard battery of intelligence tests. Since the content of these tests can be regarded as proxies for the environmental intelligence that exists at time 1, it is reasonable (although not strictly necessary) to state the results of these tests as percentages of environmental intelligence successfully mastered. For instance, when it is discovered that A1 can correctly answer 80% of the test questions, the result can be stated as follows: A1 has demonstrated the capacity to master roughly 80% of the environmental intelligence to be found around him. In a similar vein, when B1 and C1 respectively answer 70% and 60% of the test questions correctly, it can be said they are demonstrating the capacity to master corresponding percentages of environmental intelligence.

As is done with real world intelligence exams, the raw test scores of A1, B1 and C1 are normed and compared to the remainder of the test-taking population. From this procedure, it is determined that A1 falls within the comparative range of high intelligence for the general population, B1 falls within the range of average intelligence, and C1 falls within the range of low intelligence. The results are summarized in the following chart:

Time 1 (Environmental Intelligence: 200 EIU)

	Test Scores	Population Rank
A1	80%	High Intelligence
B1	70%	Medium Intelligence
C1	60%	Low Intelligence

At this point, all the standard types of analysis regarding individual intelligence differences can be performed quite adequately. Using relative intelligence rankings, and employing factor analysis and incorporating an assortment of statistical and biological information gathered from the population at large, scientists would be able to show with considerable confidence that, all other things being equal, A1 can expect greater success than his B1 and C1 peers in academics and career, and that the individual intelligence differences between A1, B1 and C1 can be attributed in large part to biological and genetic forces. The relative intelligence scores at time 1 (or at any given time) provide a wealth of information into the characteristics of individual intelligence.

An absolute measure of intelligence for A1, B1 and C1 has not yet been determined, but it is a simple matter to do so. With a measure of 200 EIU having been assigned to time 1’s environmental intelligence, and test results having been stated as a percentage of environmental intelligence effectively mastered, a quick multiplication reveals that A1’s absolute level of intelligence is 160 EIU (200 EIU x 80%), B1’s is 140 EIU, and C1’s is 120 EIU. The comparative chart can be updated to reflect these figures:

Time 1 (Environmental Intelligence: 200 EIU)

	Test Scores	Population Rank	Absolute Intelligence
A1	80%	High Intelligence	160 EIU
B1	70%	Medium Intelligence	140 EIU
C1	60%	Low Intelligence	120 EIU

This additional calculation of absolute intelligence scores does not aid at all in the understanding of individual intelligence; as far as intelligence differences are concerned, the inclusion of absolute scores is nothing but a superfluous addendum. The information, however, will prove to be invaluable. It will be essential in the comparison of intelligence characteristics between time 1 and time 2.

Time 2 occurs several generations after time 1, and so A1, B1 and C1 no longer exist. Nonetheless, it is a simple matter to summon their descendants—call them A2, B2 and C2—all of whom can be essentially regarded as biological and genetic equivalents to their ancestors. Indeed, when A2, B2 and C2 take the standard tests offered at time 2, they score in a familiar pattern. A2 answers 80% of the questions correctly, which is said to reflect an 80% mastery of time 2’s environmental intelligence, and B2 and C2, as to be expected, score 70% and 60% respectively. Once again these raw scores are normed and compared against the general population, and as with their ancestors, A2 falls within the range of high intelligence, B2 falls within the range of average intelligence, and C2 falls within the range of low intelligence:

Time 2 (Environmental Intelligence: 400 EIU)

	Test Scores	Population Rank
A2	80%	High Intelligence
B2	70%	Medium Intelligence
C2	60%	Low Intelligence

Factor analysis and population statistics reveal the same pattern of individual intelligence differences as were seen at time 1, and this is consistent with real world experience. Science has repeatedly shown that patterns of individual and group intelligence differences remain relatively stable across time—just as to be expected of individual intelligence, a characteristic determined in large measure by biological and genetic causes.

Nonetheless, at time 2, there has been a significant anomaly.

The first intelligence tests offered to A2, B2 and C2 were the very same tests offered to their ancestors at time 1, but as it turns out, A2, B2 and C2 have found those tests to be laughably easy. So easy in fact that they are no longer useful for the purpose of distinguishing individual intelligence abilities. In order to make the tests suitable again for comparative purposes, the test producers have had to beef them up, make the questions more difficult, and it is only after these modifications have been made that the tests can be effectively administered, with the resulting scores as shown.

In one sense, the reason that the tests have to be re-set is clear from the parameters of the illustrative example: since the content of an intelligence exam stands as a proxy for environmental intelligence, and since environmental intelligence has dramatically changed from time 1 to time 2—doubled in fact—the tests must be reconstituted in order to reflect this fact. But in another sense, the reason that tests have to be re-set is made clear from an entirely different source, namely that this is precisely what has been taking place in the real world throughout the previous century. Each successive generation has been scoring progressively better on older intelligence exams, to the point that test makers find they must modify the exams in order to keep them useful. These modifications generally take the form of more difficult questions, questions reflecting a greater amount of pattern, structure and form. In both the illustrative example and in the real world, intelligence tests have to be regularly strengthened in order to counteract the creeping influence of the Flynn effect.

And it is not just the tests that need to be reconsidered. Despite demonstrating equivalent levels of individual intelligence to their ancestors, indicating an equal capacity to absorb and respond to environmental intelligence, A2, B2 and C2 have nonetheless seen their absolute levels of intelligence take a quantum leap. With the time 2 environmental intelligence assessed at 400 EIU, A2’s test results reflect an absolute level of intelligence of 320 EIU (400 EIU x 80%). B2 weighs in at 280 EIU, and C2 scores at 240 EIU—in each case a doubling over A1, B1 and C1:

Time 2 (Environmental Intelligence: 400 EIU)

	Test Scores	Population Rank	Absolute Intelligence
A2	80%	High Intelligence	320 EIU
B2	70%	Medium Intelligence	280 EIU
C2	60%	Low Intelligence	240 EIU

It takes barely a moment’s reflection to recognize the sole cause for this quantum leap. It has nothing to do with individual intelligence. It has nothing to do with neurology or genetics. The sole driver of raw intelligence gains is the increasing amount of environmental intelligence, the increasing amount of pattern, structure and form tangibly contained within the human environment. Individual intelligence, the biological capacity to absorb and respond to environmental intelligence, that capacity remains constant over time, but that capacity encounters an ever expanding target.

Flynn's Paradoxes. In his book What is Intelligence?, Flynn (2007) describes four paradoxes he associates with the Flynn effect. The first paradox deals with g factor analysis, which is only tangentially related to the present discussion, but the remaining paradoxes can be resolved directly using this paper’s dual-aspect model of human intelligence.

Two of the paradoxes, labeled as the intelligence paradox and the mental retardation paradox, state the apparent incongruity that if the Flynn effect were literally true, then humans from one generation would be too implausibly dumb or too implausibly smart compared to humans from a different generation. In Flynn’s words:

If huge IQ gains are intelligence gains, why are we not struck by the extraordinary subtlety of our children’s conversation? Why do we not have to make allowances for the limitations of our parents? A difference of some 18 points in Full Scale IQ over two generations ought to be highly visible.

If we project IQ gains back to 1900, the average IQ scored against current norms was somewhere between 50 and 70. If IQ gains are in any sense real, we are driven to the absurd conclusion that a majority of our ancestors were mentally retarded. (p. 9–10)

The resolution to these two paradoxes is to recognize that Flynn is confusing the two different aspects of intelligence; he is confusing environmental intelligence with individual intelligence. In particular, he is using the changed levels in one aspect (environmental intelligence) to infer a corresponding change in the other aspect (individual intelligence). That inference is unwarranted.

In the illustrative example, consider the individual named A1. At time 1, A1 is assessed to be highly intelligent. He demonstrates his above-average ability to absorb and respond to environmental intelligence by correctly answering 80% of the test questions presented to him, and as A1 navigates through his time 1 world, it can be anticipated he will experience relatively greater achievement, compared for instance to his B1 and C1 peers.

But when A1’s absolute (raw) intelligence score of 160 EIU is compared to the population of time 2, A1 suddenly appears much less smart. 160 EIU scores far below the 240 EIU of C2, a person assessed to be of low intelligence at time 2. If 240 EIU is considered to be of low intelligence at time 2, then A1’s score of 160 EIU seems to mark him as a borderline imbecile.

So which is it? Is A1 highly intelligent or an imbecile? This paradox is resolved by recognizing that A1’s individual intelligence is not subject to change. A1’s absolute intelligence score of 160 EIU has as much to do with the time period during which it was registered as it has to do with A1’s biological capacity. If A1 could be magically transported forward in time and raised in the time 2 world, he would absorb and respond to about 80% of the time 2 environmental intelligence and would score correspondingly on a time 2 intelligence exam, making it clear once again that he is a highly intelligent individual. A1’s apparently low score of 160 EIU has nothing to do with A1’s intelligence abilities; it has everything to do with the change in environmental intelligence from time 1 to time 2.

This works exactly the same way going backwards in time. Consider C2, who is assessed at time 2 to be of low intelligence. But when C2’s absolute (raw) intelligence score of 240 EIU is compared to the time 1 population, where a score of 160 EIU is considered to be highly intelligent, C2 suddenly comes across as a Mensa candidate, and one wonders if C2 simply had the misfortune of being born too late.

So which is it? Is C2 of low intelligence or a Mensa candidate? Once again, the resolution is to recognize that C2’s individual intelligence is not subject to change. If C2 could be magically transported back in time and raised in the time 1 world, he would absorb only about 60% of the time 1 environmental intelligence and would score relatively poorly on the time 1 intelligence exam. The timing of one’s birth does not alter one’s personal intellectual ability.

In addition to these illustrative examples, Flynn provides a real world scenario that brings out the principle quite nicely. After noting that the average raw intelligence score from about 1900 would translate to an IQ of about 50 to 70 on today’s scale, Flynn raises the specter of the following tableau:

Jensen relates an interview with a young man with a Wechsler IQ of 75. Despite the fact that he attended baseball games frequently, he was vague about the rules, did not know how many players were on a team, could not name the teams his home team played, and could not name any of the most famous players.

When Americans attended baseball games a century ago, were almost half of them too dull to follow the game or use a scorecard? My father who was born in 1885 taught me to keep score and spoke as if this was something virtually everyone did when he was a boy. How did Englishmen play cricket in 1900? Taking their mean IQ at face value, most of them would need a minder to position them in the field, tell them when to bat, and tell them when the innings was over. (p. 23–24)

This is a quintessential example of mistaking a change in raw intelligence scores as evidence for a change in individual intelligence, when in fact it is evidence for a change in environmental intelligence.

Think about putting questions dealing with baseball rules on an intelligence test. If such questions had appeared on an intelligence exam in say 1800, no one at all, including the smartest people who then lived, would have been able to answer the questions correctly (other than by random luck). By contrast, if such questions were to appear on today’s intelligence exams, many individuals, including those of average intelligence, would be able to answer the questions correctly—baseball and its rules have become an established part of the human environment. As Flynn indicates, it would be only those with an IQ around 75 or under who would have limited potential to answer such questions correctly.

So does this mean that the smartest people from 1800 had the same intellectual capacity as Jensen’s young man? It does not mean that at all.

The crucial moment in time would have been around 1900. If intelligence questions regarding baseball rules had appeared on intelligence exams at that time, the results would have been mixed. Some people would have been able to answer the questions correctly, but others would not, including those of otherwise average-to-high intelligence, and this because baseball had not yet become widely entrenched within the human environment (it was just then catching on). But after the exam, if one of those baseball-ignorant persons of average-to-high intelligence had been taken to the ballpark, bought a ticket, sat with in the grandstands, explained the rules, given a scorecard and a pencil, a perfectly capable behavior would have swiftly emerged. After all, this is a person of average-to-high intelligence, he can absorb and respond to baseball rules just fine, they will give him not the slightest bit of trouble. And around 1900, this scene would have actually taken place—again and again and again.

The increase in raw intelligence scores from 1900 to 2000 has everything to do with the increasing amount of environmental intelligence (including the addition of baseball rules). It has nothing to do with individual intellectual abilities.

Flynn names his final paradox the identical twins paradox. Flynn’s words again:

There is no doubt that twins separated at birth, and raised apart, have very similar IQs, presumably because of their identical genes. Indeed a wide range of studies show that genes dominate individual differences in IQ and that environment is feeble. And yet, IQ gains are so great as to signal the existence of environmental factors of enormous potency. How can environment be both so feeble and so potent? (p. 10)

In considering Lewontin’s attempt to resolve this paradox, Flynn (p. 37) sorts through a list of candidates for an environmental Factor X—nutrition, education, liberal parenting, the scientific ethos—and dismisses each as not being widespread or potent enough to produce the requisite intelligence gains, concluding finally that one must “shut the door” on any further discussions of an environmental Factor X. But Flynn’s search is not nearly wide enough and is being hampered by a presumed environmental influence on human intellectual capacity—like nearly everyone else, Flynn does not countenance human intelligence freed of human neurology.

Environmental intelligence—the total amount of non-biological pattern, structure and form tangibly contained within the human environment, the countless structural, patterned artifacts humans live among and navigate day by day—that serves as the ideal Factor X. Environmental intelligence is ubiquitous. Environmental intelligence is constantly increasing. Environmental intelligence remains unfettered by the constraints of human biology, remains independent of the workings of individual intelligence.

An analogy to describe the relationship between environmental intelligence and individual intelligence would be to think of ships in a harbor, including lightweight ships such as pleasure craft and heavy duty ships such as battle cruisers. Were a measurement to be taken of the bottommost part of each ship (relative to a fixed vertical point on land), it would be discovered there are significant differences. Some ships will sit higher, some will sit lower. Further analysis of characteristics such as geometric structure and material density (equivalent to psychometric analysis) would reveal ship-based factors that determine relative vertical positions, exactly as scientists determine genetic and neurological factors that drive individual intelligence differences.

At a later point in time, measurements might reveal all the same relative differences in bottommost positions of the ships (with the same factors determining those differences), and yet it is also discovered that the absolute position of each ship (relative to the fixed vertical point on land) has risen by a significant amount. If the mistake is made of trying to explain this increase by appealing to the ships’ characteristics or by insisting that the ships’ environment must be somehow changing the ships’ characteristics, confusion will reign. The ships’ characteristics can explain relative vertical positions, but do nothing to explain absolute changes in position. For that, the context—the environment—of these ships must be taken fully and independently into account, leading eventually to the aphoristic conclusion that it is a rising tide that raises all ships.

In the orthogonal relationship between environmental intelligence and individual intelligence, environment is both feeble and potent, as is genetics—it all depends on the domain. Individual intelligence works through the auspices of human neurology, driven primarily by genetics. Environmental intelligence grows within the context of the physical, non-biological world, free of neurological constraint. Their influences seem paradoxical only when they become mistakenly intertwined (for instance, within the human brain), but when their impacts are kept properly separate, Flynn’s identical twins paradox swiftly disappears.

Environmental Complexity. Of the many offered explanations for the Flynn effect, the one most similar to the model proposed here is the notion of environmental complexity. Schooler (1998) and Greenfield (1998) offer perhaps the most comprehensive introductions to environmental complexity, and Wai & Putallaz (2011) provide a recent instance of the idea being invoked. But it can be seen in these and other discussions highlighting environmental complexity, that in several crucial respects, the explanation falls short.

The first problem with environmental complexity is that its proponents appeal to certain things within the human environment, instead of grasping the environment as a whole. Two commonly cited instances of environmental complexity are the increased use of video games and the complex and multivariate nature of television shows and movie plots; others note the expanded presence of visual puzzles and games. But no matter what thing or set of things is being considered, it becomes immediately clear that by itself it cannot account for the ubiquitous, relentless nature of the Flynn effect. The Flynn effect was working its magic long before there even were video games and television sets, and the Flynn effect remains prominent in locations where video games and sophisticated dramas have yet to take much hold. Any alternative candidate would fall victim to the same dilemma.

It is only by appealing to complete environmental complexity that traction can be gained. One way to envision complete environmental complexity would be to imagine the Earth’s surface as it stood nearly fifty thousand years ago and contrast that with how differently the Earth’s surface stands today. Every material artifact that has been introduced—every house, every road, every sign, every book, the whole entire lot—all of it forms the complete and expanding sum of environmental complexity. The types and examples of environmental complexity will differ from time to time and from place to place, but the one reliable constant is that the total amount of environmental complexity will be nearly always on the rise.

The second problem is that the proponents of environmental complexity—like nearly everyone else—attempt to tie their explanation back to human neurology. Playing video games, for instance, is seen as expanding the capacity of working memory. Modern movie plots perhaps form a larger number of connections within the logical neural circuitry. It would seem that environmental complexity by itself is deemed to be useless; its only purpose is to prompt a major restructuring within the neurons, a massive rewiring between the ears—a proposal that lacks both parsimoniousness and plausibility. The human brain does not need to be changed by environmental complexity, the human brain needs merely to absorb and respond—the simple and common basis of neurological behavior.

The Flynn effect is independent of individual intelligence differences, and thus an explanation for the Flynn effect should be independent of the human brain. If the proponents of environmental complexity are to hit the mark, they must come to accept environmental complexity as the material form of human intelligence itself; they must stop looking for expanding intelligence inside the human skull.

Conclusion. One immediate consequence of this paper’s dual-aspect model of human intelligence is that the Flynn effect cannot be regarded as a twentieth-century anomaly. Tracking the increase in environmental intelligence, the Flynn effect would have begun at the time of the human great leap forward and has been shadowing human existence ever since, and there is no reason to expect it will end anytime soon.

Environmental intelligence, the increasing amount of pattern, structure and form tangibly contained within the human environment—that is the unseen hand propelling intelligence scores ever upward. That it has remained unseen for so long should not be that surprising; it is a frequent human experience that the thing most difficult to perceive is the thing that exists right before one’s very eyes.

References

Flynn, J. R. (1999). Searching for justice: The discovery of IQ gains over time. American Psychologist, 54, 5–20.

Flynn, J. R. (2007). What is intelligence? Beyond the Flynn effect. New York: Cambridge University Press.

Greenfield, P. (1998). The cultural evolution of IQ. In U. Neisser (Ed.), The rising curve. Washington, DC: American Psychological Association.

Lewontin, R. C. (1976). Further remarks on race and the genetics of intelligence; Race and intelligence. In N. J. Block & G. Dworkin (eds.), The IQ controversy. New York: Pantheon Books.

Schooler, C. (1998). Environmental complexity and the Flynn effect. In U. Neisser (Ed.), The rising curve. Washington, DC: American Psychological Association.

Wai, J., & Putallaz, M. (2011). The Flynn effect puzzle: A 30-year examination from the right tail of the ability distribution provides some missing pieces. Intelligence, 39, 443–455.

Introduction to a Paper

Tomorrow I'm going to post a paper here, and I think it might need a little explanation.

The paper's content will be familiar. Last fall, I scrambled together a quick series of posts on the Flynn effect (Flynn Effect 101, Flynn Effect 102, Flynn Effect 103, and Flynn Effect 104) and I've had a hankering ever since to reorganize that material into a single, more cohesive essay. Last month I finally got the opportunity to do so and tomorrow's post is the result.

For me, this paper is extremely formal. The reason for the formality is that I felt I should submit the paper at least once for publication, which I did, to the journal Intelligence. (No surprise, the paper was deemed “not suitable for a scientific journal.”) I didn't struggle with the rigidity of the format as much as I thought I would (although admittedly I bent a few of the rules), but the experience left me wondering why so many people would voluntarily submit to such confinement—the academic community never ceases to amaze me.

At any rate, for the few who might be interested in a different approach to describing human intelligence, tomorrow's essay is my semi-formal attempt to fit the bill.

More Neanderthal Data

One of the better sources for up-to-date information regarding Neanderthal admixture has been John Hawks' weblog. Hawks is a paleoanthropologist at the University of Wisconsin, and in addition to providing links to and commentary upon some of the latest research, Hawks and his students have been working at replicating and extending some of the more interesting findings regarding the Neanderthal genome and its presence in modern humans.

An excellent overview of the process is contained in this post from last week, and in it you will find a thorough but easily accessible explanation for how scientists arrive at the 1-4% admixture estimate of Neanderthal genetic material into non-African humans. In the original paper describing Neanderthal admixture (Green 2010), only five modern human genomes—two African and three non-African—were compared to the Neanderthal draft sequence. Hawks and his students have been making much the same comparison against a much larger database of modern genomes, with some clarifying results. Their work is of course still preliminary and not reviewed (and thus should be taken with a grain of salt), but if it proves to be accurate, it leads to some interesting conclusions:

• The admixture finding from (Green 2010) is being convincingly replicated and confirmed as the genomes from more and more present-day humans are being compared to the draft sequence of the Neanderthal genome. Either the draft sequence has some very bad data, or the assumptions behind the genome comparison techniques are totally without merit, or Neanderthal admixture into non-African humans is a confirmed reality—there doesn't seem to be any other way around it.
• The mean amount of Neanderthal admixture into non-African populations (over and above any admixture into African populations) looks to be around 3%.
• Although 3% is the mean, the variability remains significantly wide: any given non-African individual might easily fall within the range of 2-4% admixture, and there are indications some individuals will fall well outside that range. Even within families, there might be significant variability.
• All indications are that the Neanderthal admixture is shuffled throughout much of the modern human genome. That is, person A might have 3% admixture and person B might have 3% admixture, but the two may share relatively little admixture in common. It's not specific parts of the modern genome that are Neanderthal derived; instead, it appears that much of the modern non-African genome has been impacted in a shuffled-up sort of way.
• The mean Neanderthal admixture difference between Europeans and Asians is extremely small. This result goes against the idea that an out-of-Africa migrating population interbred primarily with Western European Neanderthals around 35 to 40 thousand years ago. Instead, this result points more plausibly to the idea that admixture happened earlier in time and/or at another locale (such as the Middle East).
• All these findings are based solely upon SNP analysis. The other sources of genetic differentiation—such as duplication, deletion, insertion, inversion—still await less costly and more accurate analysis. But in these areas too, Neanderthal admixture might be expected to have significant impact.

None of these findings provide any direct evidence for my idea that autism is a species-differentiation event (in particular, a species dis-recognition event), but neither do any of these findings contradict the idea. As I've said elsewhere, what we can look for now are studies comparing the Neanderthal draft sequence to modern humans diagnosed with such things as autism, schizophrenia and bipolar. If my idea is going to have any legs, then what we might expect to find are Neanderthal-distinguishing genetic signatures among these diagnosed populations, either admixture amounts outside the norm (most likely higher than the typical range) or a specific pattern of relationship against the Neanderthal genome unique to the diagnosed population. Given the rapid rate of technology advancement in this area, we might not have to wait all that much longer.

One other thing: as I read through these Neanderthal admixture findings, I can't help but be reminded of the genetic research conducted so far in the areas of autism, schizophrenia and bipolar. In each instance, researchers have been uncovering extremely lengthy lists of candidate genetic markers for the condition, markers that show up in only a tiny percentage of the affected population and markers that are scattered almost at random throughout the genome. This of course also does not provide any direct evidence that Neanderthal admixture is playing a role in such conditions, but the genetic similarities are difficult not to notice. And contrast this with the dubious conclusion being drawn by the autism research community, a community that insists on casting all these genetic variations as genetic defects, each leading (by miraculous coincidence, it would seem) to the same neurological and phenotypic outcome. There is a difference between the words “speculative” and “implausible,” and I see that difference on display here.

(Green 2010): Green, Richard E. and others. 2010. “A Draft Sequence of the Neandertal Genome.” Science 328:710–22

Ami Klin's Good Science

Can someone explain to me how Ami Klin's research team in (Shultz 2011) could have possibly overlooked the idea of running a second version of their experiment, one employing a visual scene more naturally appealing to autistic perception? It would have been so easy: remove the humans from the scene and through automated means have the toy wagon's door open and shut on a regular basis. Bring in another group of controls and autistic children, and make the same measurements as were made for the first scenario. The comparisons across populations and across scenarios might have provided a wealth of information for both autistic and non-autistic perception, probably far more than was provided by the study as conducted.

Any decent research team might have recognized the potential in that second scenario, but it was criminally stupid for the Klin research team not to have recognized it, because the team had already been through that experience!

The whole beauty of (Klin 2009) was that instead of the nothing-new experiment the authors had originally designed, and prompted by the “serendipitous” observations of a fifteen-month-old autistic girl, the study team was able to re-configure the experiment to test for both non-autistic appealing and autistic appealing scenarios, thereby setting up a wealth of cross-population, cross-scenario information for comparison and contrast. That serendipitous enhancement literally made the study.

So you would think the Klin team would know by now the value of taking that broader approach with every experiment going forward. You would think. But apparently the fifteen-month-old autistic girl didn't hit them upside the head hard enough.

I can't describe how dumbfounded I am by the scientific blindness I see on display almost everywhere in the autism research community. People go on and on to me about the need to weed out bad science and to expose all the charlatans and to have better standards, and on and on and on they go. For what, I ask? For this? For more of Ami Klin's inability to see beyond the end of his own nose? Is this the good science everyone's striving for? Hell, I'd rather have the charlatans. At least the charlatans know what they're doing.

(Shultz 2011): Shultz, Sarah; Klin, Ami; Jones, Warren. 2011. “Inhibition of eye blinking reveals subjective perceptions of stimulus salience.” PNAS (in press).

(Klin 2009): Klin, Ami; Lin, David J.; Gorrindo, Phillip; Ramsay, Gordon; Jones, Warren. 2009. “Two-year-olds with Autism Orient to Non-Social Contingencies Rather than Biological Motion.” Nature 459: 257–61.

Competing Speculative Hypotheses

About a year ago, I wrote a rather lengthy essay (Griswold 2011) inspired by the paleoanthropologist Richard Klein and his ideas regarding the behavioral and cultural changes known as the human great leap forward. Here (http://www.youtube.com/watch?v=qUp_6n8x3D0) you can watch a recent 45-minute lecture by Dr. Klein on the topic, and although I think his written works (for instance, (Klein 2002) and (Klein 2008)) provide better detail, the video lecture does give a reasonable introduction and overview to Klein's approach and is well worth the short investment of time.

Near the very end of the lecture, after having outlined arguments and evidence for the notion that the human great leap forward was a sudden event—occurring around fifty thousand years ago—Klein states his hypothesis that the sudden event must have been launched by a genetic mutation, one producing significant cognitive effect. Klein then briefly mentions the recent and preliminary work on the mapping of the Neanderthal genome (Green 2010), work that has led to two major (and still preliminary) results: 1. there is now a list (a fairly short list) of modern human/non-Neanderthal gene sequences that would serve as obvious candidates for recent genetic mutation; and 2. nearly all non-African modern humans carry a small influence (estimated in the neighborhood of 2.5%) of Neanderthal-originated genetic material.

As Klein mentions in his lecture, the first result opens the door to a means for testing his genetic mutation hypothesis. The idea would be to obtain a list of modern human genetic sequences that differ significantly from those of ancient humans (including Neanderthals) and see if a subset of these produce the kind of neurological impact consistent with human behavioral and cognitive change. There are of course some technical challenges that stand in the way of this approach: for one, the genome mappings are still in need of greater clarification and accuracy, and furthermore, scientists have not yet been all that successful in connecting genetic material to phenotypic effect, be it cognitive or otherwise. Nonetheless, these are challenges that might be expected to be overcome through technological advances, and so indeed, Klein's hypothesis might one day soon be put to a thorough scientific test.

As I outlined in (Griswold 2011), I'm fairly convinced Klein is going to be disappointed in the results of that test. Although I concur with Klein's assertion that the human great leap forward was a sudden anthropological event, I see an incongruity undermining Klein's explanation for that event. Although most scientists, Klein included, would take for granted that human cognitive advancement must have been driven by a genetic/neurological/evolutionary change, nearly everything scientists can actually demonstrate about genetics, neurology and evolution runs counter to the type of sudden, population-wide, large-scale event Klein is describing. It's as though the animal world had gone sightless for billions of years and then overnight one of the species popped up a pair of excellent eyes and immediately conquered the rest of the planet through this new-found vision. It makes for a dramatic story, but biology doesn't seem to work that way.

Genetically-driven evolutionary change does of course happen, but not on the time or impact scale Klein is proposing (and not even on the time or impact scale that cultural evolutionists would propose). On the one hand, Klein's description of sudden human behavioral and cognitive change looks accurate enough based upon the archaeological evidence, but on the other hand, his explanation for that sudden change looks utterly implausible based upon the logic of biology.

That said, it would still be prudent to wait for the science.

Also in the video lecture, almost as an aside, Klein dismisses the other major finding from Neanderthal genome mapping—the admixture of Neanderthal genetic material into modern humans—suggesting that as details of the respective genomes become more complete and accurate, this finding will prove to be false. Logically speaking, however, Klein doesn't need to make that dismissal: it's perfectly possible that Neanderthal admixture will continue to hold upon further analysis, and yet its impact on human behavioral and cognitive change will prove nonetheless to be benign. I think what's driving Klein's desire to dismiss the admixture finding is that he wants to emphasize how modern Homo sapiens—post genetic mutation—were so cognitively and behaviorally advanced over their Neanderthal contemporaries that all they could do was swamp the Neanderthals into extinction, not interact with or incorporate them. That's a reasonable conclusion to draw given what we already know about European replacement of Neanderthals (evidence for which Klein has intimate working knowledge), but in point of fact there's nothing about the Neanderthal admixture finding that implies it had to be a post out-of-Africa event—the evidence for the timing of that admixture remains inconclusive, and it's quite possible any such admixture could have taken place near the beginning or even prior to the out-of-Africa migration.

Here too, it would be prudent to wait for the science.

My own interest in the Neanderthal admixture finding is that it serves as possible evidence for an alternative explanation to the human great leap forward, an explanation I find logically more plausible—albeit perhaps just as speculative—as Richard Klein's. In (Griswold 2011) I outline how the introduction of autism into the human population—autistic perception in particular—could have served as the catalyst driving human cognitive and behavioral change. I won't repeat the details here, but the concepts at work are a description of autism as a lack of species recognition; autistic perception as a compensatory foregrounding of non-biological pattern, structure, symmetry and form; human cognitive and behavioral advancement as the environmental accumulation of these very same elements of non-biological pattern, structure, symmetry and form; and Neanderthal admixture as the conceivable biological cause for autism-related species dis-recognition. Under my scenario, all these concepts would have come together in a kind of circumstantial stew that began cooking around fifty thousand years ago.

With the ongoing advancements in human genome sequencing, parts of my autism hypothesis might become just as amenable to scientific testing as Klein's genetic mutation hypothesis. The key evidence to look for is whether large or distinctive presences of Neanderthal-derived genetic material within individuals correlates significantly to diagnoses of autism (and perhaps to similar conditions of schizophrenia and bipolar). A high and distinctive correlation would be supportive for describing autism as a condition of species dis-recognition, and thereby indirectly supportive of an autism-related explanation for mankind's great leap forward.

Of course it's also possible that neither speculation—mine nor Richard Klein's—will prove to be helpful, and it will be some other explanation, perhaps one not yet thought of, that manages to untangle the mysteries from fifty thousand years ago. But one thing is for certain: these recent advancements in human genome mapping are opening an intriguing window onto our anthropological past. It's an excellent time to be alive if one is prone to asking such questions as, what caused human beings to become so distinctively human?

(Green 2010): Green, Richard E. and others. 2010. “A Draft Sequence of the Neandertal Genome.” Science 328:710–22

(Griswold 2011): Griswold, Alan. 2011. Autistic Songs. Bloomington, IN: iUniverse.

(Klein 2002): Klein, Richard G. 2002. The Dawn of Human Culture. New York: Wiley.

(Klein 2008): Klein, Richard G. 2008. "Out of Africa and the Evolution of Human Behavior." Evolutionary Anthropology 17:267–81.

The Joy of Meta

Here is an abstract from the very latest in autism research:

Recent studies have implicated physiological and metabolic abnormalities in autism spectrum disorders (ASD) and other psychiatric disorders, particularly immune dysregulation or inflammation, oxidative stress, mitochondrial dysfunction and environmental toxicant exposures (‘four major areas’). The aim of this study was to determine trends in the literature on these topics with respect to ASD. A comprehensive literature search from 1971 to 2010 was performed in these four major areas in ASD with three objectives. First, publications were divided by several criteria, including whether or not they implicated an association between the physiological abnormality and ASD. A large percentage of publications implicated an association between ASD and immune dysregulation/inflammation (416 out of 437 publications, 95%), oxidative stress (all 115), mitochondrial dysfunction (145 of 153, 95%) and toxicant exposures (170 of 190, 89%). Second, the strength of evidence for publications in each area was computed using a validated scale. The strongest evidence was for immune dysregulation/inflammation and oxidative stress, followed by toxicant exposures and mitochondrial dysfunction. In all areas, at least 45% of the publications were rated as providing strong evidence for an association between the physiological abnormalities and ASD. Third, the time trends in the four major areas were compared with trends in neuroimaging, neuropathology, theory of mind and genetics (‘four comparison areas’). The number of publications per 5-year block in all eight areas was calculated in order to identify significant changes in trends. Prior to 1986, only 12 publications were identified in the four major areas and 51 in the four comparison areas (42 for genetics). For each 5-year period, the total number of publications in the eight combined areas increased progressively. Most publications (552 of 895, 62%) in the four major areas were published in the last 5 years (2006–2010). Evaluation of trends between the four major areas and the four comparison areas demonstrated that the largest relative growth was in immune dysregulation/inflammation, oxidative stress, toxicant exposures, genetics and neuroimaging. Research on mitochondrial dysfunction started growing in the last 5 years. Theory of mind and neuropathology research has declined in recent years. Although most publications implicated an association between the four major areas and ASD, publication bias may have led to an overestimation of this association. Further research into these physiological areas may provide insight into general or subset-specific processes that could contribute to the development of ASD and other psychiatric disorders.

I'm not sure how badly you'll want to delve into all that verbiage, but in short it's an assessment of various "abnormalities" associated with autism through the means of looking at research publication trends. For instance, the association of mitochondrial dysfunction with autism is assessed by looking at the rising number of mitochondria-autism research articles published over the calendar years from 1971 to 2010. It's the type of work that can be done with a good search engine and a spreadsheet program (3D color graphics would be a bonus).

In other words, it's a shitty piece of meta-analysis.

Of course, there have been better examples of meta-analysis applied to autism research, but this raises an intriguing question. How does one differentiate good meta-analysis from bad meta-analysis (think of how important this will be to Ben Goldacre as he's writing his next book, Bad Meta Science)? Well obviously, what we need to do is institute some standards, protocols and ethics for the general practice of meta-analysis, and once these are in place we can begin performing meta-analyses of all the meta-analyses. And if there happen to be any lingering problems, we can just ask Janet Stemwedel to remind the tribe of meta scientists of all their meta social duties.

No really. I think this would be a fruitful line of endeavor. As far as I can tell, the possibilities for employment are unlimited.

Autism Etiology

Genetics, neurology, environment—permutations and combinations aplenty, plausible mechanisms afew.

Dispelling the Fog

Why try to deny the Flynn effect or pass it off as a short-term anomaly? If we embrace the Flynn effect for exactly what it says, the faulty explanations disappear.

Read All About It

From Rose Eveleth comes an absolutely gorgeous article on autistic potential, spurred by the work of Mottron, Soulières, Dawson and colleagues. The article makes a nice blend of realism and affirmation, and might be the best bit of autism-related journalism I've yet to see.

On the Prowl

Scientists are perfectly free to keep looking for the source of intelligence inside the human brain. But they might as well keep looking for the luminiferous ether while they're at it.

A Balanced Approach

I will say this much in defense of Ami Klin. His description of autistic perceptual characteristics comes with a corresponding (and fairly accurate) description of non-autistic perceptual characteristics, along with an appreciation for the merit and deeply ingrained nature of those characteristics (see for instance the answer to the next-to-last question here). This is an approach I wish the Mottron research team would seriously consider. Indeed, if we could combine the best of Ami Klin's observations and Laurent Mottron's research and ideas, we might arrive at an informative and mutually clarifying description for these two fundamental forms of human perception. But alas, blind spots continue to be the norm within autism research.

Calibrating the Eye-Tracker

Ami Klin is making a fundamental mistake in emphasizing early autistic attention towards objects. When autistic toddlers line up toys, they're not intrigued by the toys—they're intrigued by the line.

Hobgoblin

The one consistent finding throughout autism research is that whatever autistics do, it's wrong.

Liars and Hypocrites

If I'd known that curing autism would be so easy, I might not have raised such a big objection. But according to recent reports, all we need to do is train autistic individuals to be better liars and hypocrites, and they'll become virtually indistinguishable from their neurotypical peers.

Blindside

Many people attack science because they don't want to think. I attack science because scientists don't want to think.

How Do I List Thee? Let Me Count the Ways

Oh, I just relish authorship discussions like this one. They always leave me wondering how Darwin or Tolstoy would have handled such dilemmas.

Applause

It's nice to see the media attention being given to Laurent Mottron, Michelle Dawson, and their immediate colleagues in conjunction with the appearance of Dr. Mottron's commentary Changing perceptions: The power of autism (which sadly is behind a paywall). I've never been one to be hesitant about expressing my dissent from some of these researchers' positions and views, but this has always been done in the context of great admiration and respect for their overall effort. These are scientists who have consistently led the way in providing autism research that is affirmative, encouraging, accurate and productive for autistic individuals, a stance which has demonstrated both courage and insight. Any positive attention they get is well deserved and well earned.

[Update: It appears that the paywall restriction has been removed. More applause.]

Kierkegaard's Lemma

When being a Christian was unpopular, unrewarding, even dangerous, then we had true Christianity. Science is no different.

Lab Rats

The best science is descriptive. If you need an experiment to make your point, you've already missed the point.

Lateral Glance

What makes a brain non-autistic? That would be an important question too.

Optional

You know, to be a scientist these days is to engage in a form of “mandatory hierarchies of processing.” I wonder why people can't choose to be an independent thinker instead.

A Novel Approach to Ad Nauseam

Here is the abstract from the latest autism-genetics breakthrough paper (Casey 2011):

Autism spectrum disorder (ASD) is a highly heritable disorder of complex and heterogeneous aetiology. It is primarily characterized by altered cognitive ability including impaired language and communication skills and fundamental deficits in social reciprocity. Despite some notable successes in neuropsychiatric genetics, overall, the high heritability of ASD (~90%) remains poorly explained by common genetic risk variants. However, recent studies suggest that rare genomic variation, in particular copy number variation, may account for a significant proportion of the genetic basis of ASD. We present a large scale analysis to identify candidate genes which may contain low-frequency recessive variation contributing to ASD while taking into account the potential contribution of population differences to the genetic heterogeneity of ASD. Our strategy, homozygous haplotype (HH) mapping, aims to detect homozygous segments of identical haplotype structure that are shared at a higher frequency amongst ASD patients compared to parental controls. The analysis was performed on 1,402 Autism Genome Project trios genotyped for 1 million single nucleotide polymorphisms (SNPs). We identified 25 known and 1,218 novel ASD candidate genes in the discovery analysis including CADM2, ABHD14A, CHRFAM7A, GRIK2, GRM3, EPHA3, FGF10, KCND2, PDZK1, IMMP2L and FOXP2. Furthermore, 10 of the previously reported ASD genes and 300 of the novel candidates identified in the discovery analysis were replicated in an independent sample of 1,182 trios. Our results demonstrate that regions of HH are significantly enriched for previously reported ASD candidate genes and the observed association is independent of gene size (odds ratio 2.10). Our findings highlight the applicability of HH mapping in complex disorders such as ASD and offer an alternative approach to the analysis of genome-wide association data.

Allow me to interpret that abstract without the spin: Here are a hundred-some authors admitting that all their previous data-mining techniques have failed to find what they were looking for, but fear not, because they've discovered yet another data-mining technique that alas, also fails to find what they're looking for. But there are some secondary benefits—namely getting one's name attached to yet another massive-author publication—and from that perspective, all autism-related data-mining techniques seem to be equally effective.

(Casey 2011): Casey JP, Magalhaes T, Conroy JM, Regan R, Shah N, Anney R, Shields DC, Abrahams BS, Almeida J, Bacchelli E, Bailey AJ, Baird G, Battaglia A, Berney T, Bolshakova N, Bolton PF, Bourgeron T, Brennan S, Cali P, Correia C, Corsello C, Coutanche M, Dawson G, de Jonge M, Delorme R, Duketis E, Duque F, Estes A, Farrar P, Fernandez BA, Folstein SE, Foley S, Fombonne E, Freitag CM, Gilbert J, Gillberg C, Glessner JT, Green J, Guter SJ, Hakonarson H, Holt R, Hughes G, Hus V, Igliozzi R, Kim C, Klauck SM, Kolevzon A, Lamb JA, Leboyer M, Le Couteur A, Leventhal BL, Lord C, Lund SC, Maestrini E, Mantoulan C, Marshall CR, McConachie H, McDougle CJ, McGrath J, McMahon WM, Merikangas A, Miller J, Minopoli F, Mirza GK, Munson J, Nelson SF, Nygren G, Oliveira G, Pagnamenta AT, Papanikolaou K, Parr JR, Parrini B, Pickles A, Pinto D, Piven J, Posey DJ, Poustka A, Poustka F, Ragoussis J, Roge B, Rutter ML, Sequeira AF, Soorya L, Sousa I, Sykes N, Stoppioni V, Tancredi R, Tauber M, Thompson AP, Thomson S, Tsiantis J, Van Engeland H, Vincent JB, Volkmar F, Vorstman JA, Wallace S, Wang K, Wassink TH, White K, Wing K, Wittemeyer K, Yaspan BL, Zwaigenbaum L, Betancur C, Buxbaum JD, Cantor RM, Cook EH, Coon H, Cuccaro ML, Geschwind DH, Haines JL, Hallmayer J, Monaco AP, Nurnberger JI Jr, Pericak-Vance MA, Schellenberg GD, Scherer SW, Sutcliffe JS, Szatmari P, Vieland VJ, Wijsman EM, Green A, Gill M, Gallagher L, Vicente A, Ennis S. 2011. “A novel approach of homozygous haplotype sharing identifies candidate genes in autism spectrum disorder.” Human Genetics (in press).

Evidence Christ Was Autistic?

Here is the abstract from a recently published paper (Izuma 2011):

People act more prosocially when they know they are watched by others, an everyday observation borne out by studies from behavioral economics, social psychology, and cognitive neuroscience. This effect is thought to be mediated by the incentive to improve one's social reputation, a specific and possibly uniquely human motivation that depends on our ability to represent what other people think of us. Here we tested the hypothesis that social reputation effects are selectively impaired in autism, a developmental disorder characterized in part by impairments in reciprocal social interactions but whose underlying cognitive causes remain elusive. When asked to make real charitable donations in the presence or absence of an observer, matched healthy controls donated significantly more in the observer's presence than absence, replicating prior work. By contrast, people with high-functioning autism were not influenced by the presence of an observer at all in this task. However, both groups performed significantly better on a continuous performance task in the presence of an observer, suggesting intact general social facilitation in autism. The results argue that people with autism lack the ability to take into consideration what others think of them and provide further support for specialized neural systems mediating the effects of social reputation.

It's difficult to read that passage without being reminded of Matthew 6:1–4, from the Sermon on the Mount:

Take heed that ye do not your alms before men, to be seen of them: otherwise ye have no reward of your Father which is in heaven. Therefore when thou doest thine alms, do not sound a trumpet before thee, as the hypocrites do in the synagogues and in the streets, that they may have glory of men. Verily I say unto you, They have their reward. But when thou doest alms, let not thy left hand know what thy right hand doeth: That thine alms may be in secret: and thy Father which seeth in secret Himself shall reward thee openly.

What would Jesus do? Apparently not what non-autistics would do.

(Izuma 2011): Keise Izuma, Kenji Matsumoto, Colin F. Camerer, and Ralph Adolphs. 2011. “Insensitivity to social reputation in autism.” PNAS 2011: 1107038108v1-201107038.

Autistics Think Differently, Part 3

[Edit 02/11/2017: The final version of this essay can be found here.]

In “The Level and Nature of Autistic Intelligence II: What about Asperger Syndrome?” (Soulières 2011), the following sentence appears:

“Autistics can maintain more veridical representations (e.g. representations closer to the actual information present in the environment) when performing high level, complex tasks.”

That's an intriguing statement, and I think I have a rough idea of what the authors are driving at (and I would generally agree with that rough idea). But the sentence as stated strikes me as slightly off key and a bit misleading. Let me see if I can explain.

I'm going to lay out a hypothetical visual scene (something similar could be done in the auditory domain if so desired), and once I've described the scene, I'm going to have three different entities survey it, including one that represents autistic perception and another that represents non-autistic perception. But when it comes to veridical representation, it's going to be the third entity that emerges as the clear winner in “capturing the actual information present in the environment.”

Here's the scene: It's a fairly open and sparse field, maybe in a large park or reserve. Near the front section of the field is a bench, where a woman and a girl are seated and talking. Rising behind them are four tall light poles, evenly spaced and situated so that they form a diagonal across the visual plane. The sky is mostly blue with a few nondescript clouds, and there is nothing else worthy of note.

Here are three entities viewing this scene from the same perspective, along with a rough description of what each perceives:

• Entity 1 surveys this scene entirely as light and color stimulus. You can think of it as a pixelated view, where the perception of this scene is best described as a series of points, each point determined by its relative position and its light qualities, such as brightness and hue.
• Entity 2 surveys this scene and is immediately drawn to the woman and girl on the bench. If asked about this perception, Entity 2 might say something like, “Yes, I can see the mother and daughter on the bench over there. See, the daughter is extremely upset—she's crying.” If asked about the light poles, Entity 2 might offer the observation that it's a good thing to have them here, because people can come at night without being afraid.
• Entity 3 surveys this scene and is struck by the particular arrangement of the light poles. Entity 3 might note that there are four of them, or might point out that they are evenly spaced, or might remark on the angle they form in the visual plane. If asked about the people on the bench, Entity 3 might say they were noticed and there were two of them and they looked small beneath the light poles towering above them.

Although these descriptions are meant to highlight only general tendencies, I think most people would agree that the perceptions of Entity 1 closely match those of a camera, the perceptions of Entity 2 are fairly typical of a non-autistic person, and the perceptions of Entity 3 are more indicative of someone who might be on the autism spectrum. Each entity sees the exact same visual stimulus, but each extracts from that stimulus an entirely different set of information. That is the essence of what we mean when we talk about the concept perception.

In my way of thinking, Entity 1 has by far the most veridical representation here—it comes the closest to perceiving this visual scene as it truly is. The key to a camera creating an accurate visual representation is, ironically enough, not to do much of anything at all with it; in particular, not to impose any form upon the visual scene. No foregrounding. No backgrounding. No extracting of signal from noise. Just reproduce the visual scene as it visually is—that's all a camera is required to do.

By contrast, both Entity 2 and Entity 3 come to their particular perceptions by imposing some kind of structure on the raw visual stimulus, which is to say some elements in the visual scene form perceptual foreground while other elements fade mostly unnoticed into the background. The perceptual process is quite similar for both Entity 2 and Entity 3 (and quite different from the perceptual process of Entity 1). What distinguishes the perceptions of Entity 2 and Entity 3 is the material of the signal itself; that is, there is a categorical difference in what tends to foreground within the perceptions of Entity 2 and Entity 3.

It's not obvious yet that Entity 3's representations are more veridical than those of Entity 2, but let's keep exploring all these perceptions in more detail.

It's actually quite fortunate that Entity 1 is not a biological or responsive agent. If it were, having the most veridical representation of the visual scene would manifest as a huge liability. To be responsive to an environmental stimulus requires that information be extracted from it, exactly what Entity 1 cannot do. This has actually been a problem in the world of robotics, where despite having extremely accurate cameras, it has been nonetheless difficult to get machines to respond flexibly and constructively to various visual stimuli, precisely because it is difficult to get machines to recognize what constitutes the necessary foreground and what needs to be dismissed as inconsequential background.

Possessing a perfectly veridical representation of an environmental stimulus is tantamount to experiencing sensory chaos. Everything comes across as noise, nothing appears as signal. And with no signal, there is no information. And with no information, there is no ability to respond with purpose. We must keep in mind these thoughts about perfectly veridical representations and their corresponding sensory chaos, because when we later consider the perceptions of Entity 3 (autistic perception), we'll discover this very same concept comes into play.

First, however, let's talk in more detail about the perceptions of Entity 2 (non-autistic perception). It's my contention that what signifies and distinguishes non-autistic perception is its strong tendency to focus upon human-related events in the sensory environment; that is, it is the human-specific features that most commonly foreground within non-autistic perception, and it is this human-specific focus that provides the necessary structure for extracting signal from the sensory noise. You can see this at work in my depiction of Entity 2's perceptions, where the attention is drawn primarily to the people in the scene—and in a very detailed way—and even the elements which are not so apparently human-related are often tied back to humanity by some indirect means (the light poles, for instance, are comprehended as helping people see at night and not be afraid).

I wouldn't use the terms “global processing” or “hierarchies of processing” to describe this phenomenon, but I would consider such a term as “common thread” to suggest how these people-specific perceptions tie non-autistic cognition together into a cohesive package. And this works at more than just the individual level. Since nearly all humans share the characteristic of these people-specific perceptions, these perceptions serve to coalesce not just individual thoughts and behaviors but also the conventions and actions of the species as a whole. Humans formulate their shared species-specific perceptions into a series of cohesive thoughts, behaviors, conventions and environments, exactly as we might expect from a species-driven, biologically essential phenomenon.

Indeed, it is important to note that it's not just in humans that we observe this common form of species-specific perception. All across the animal kingdom, we can observe abundant evidence that creatures attend most strongly to the other members of their own species and to the species-related elements in their surroundings while most everything else in the sensory environment is ignored as inconsequential background. It is in this sense that I think the word “mandatory” comes into play. The common thread of a species-specific focus is extremely powerful, it has been forged through the long-burning furnace of evolutionary time. I think most organisms inherently rely upon this common thread, and would find it extremely difficult to step outside it.

In my previous post (Autistics Think Differently, Part 2) I complained that the authors of (Soulières 2011) have not provided an affirmative, distinguishing description for non-autistic perception and cognition. If it were up to me to provide that description, I would do it in much the same way I have here, highlighting the species-specific perceptions non-autistics share and that help cement the common cognitions and behaviors across that particular class of the population. I am of course open to criticisms of this idea and am willing to consider alternative suggestions, but so far I've not see much of anything forthcoming, anything beyond that is just a settling for describing non-autistic individuals as constituting the norm.

It is also my contention that what most fundamentally distinguishes autistic perception is that it lacks the species-specific focus that is characteristic of non-autistic perception. For reasons not yet clearly identified, autistic individuals do not tend to naturally foreground human-related elements within the sensory environment, and as a baseline, this would leave autistic individuals in much the same situation as that of Entity 1: autistics would perceive the raw environmental stimulus almost exactly as it is and would have no natural means of obtaining signal from the various aspects of that stimulus.

It's primarily in this sense that I think it's fair to say autistic individuals experience more veridical representations—representations that don't come with as many pre-imposed filters, such as the human-focused filters that get routinely and naturally applied within non-autistic perception. But this also means that the natural (beginning) state of autistic perception is one that comes dangerously close to sensory chaos, and I believe this goes a long ways towards explaining why autistic individuals tend to experience sensory difficulties, difficulties that vary in domain and range and seem to have no discernible physical cause. It also goes a long ways towards explaining the developmental difficulties autistic individuals experience in their early years, because both as an individual and as a member of a species that has built its environmental surroundings out of a shared perceptual experience, an autistic individual would find himself closed off from those species-shared experiences and all their coalescing and foregrounding effects. As was stated in the discussion for Entity 1, the possession of a perfectly veridical representation is actually a huge liability when it comes to acting as a biological or responsive agent.

The saving grace for autistics is that there are features within the sensory environment that seem to inherently foreground in the absence of any stronger means of perceptual organization. It's not entirely clear to me (logically or biologically) what causes these particular elements to form signal against an otherwise chaotic background, but we recognize these mostly non-biological features through such names as symmetry, repetition, pattern, mapping, structure, and form. The authors of (Soulières 2011) routinely invoke said features in describing the distinguishing characteristics of autistic perception and cognition [see for instance (Mottron 2009) and Principles 6 and 7 in (Mottron 2006)], and in my depiction of Entity 3's perception, you'll notice the emphasis being placed on such things as number, repetition, pattern, geometry and so on. And just as non-autistics will often apprehend non-biological features in their sensory environment through a referential connection to humanity, autistics will often reverse this process, apprehending humans through such things as number, categorization and measure. It seems to me that there is a good deal of evidence backing the idea that autistic perception is drawn primarily to those environmental features consisting of non-biological pattern, structure and form, and it is out of such features that autistics gain the majority of their perceptual foregrounding. Apprehension of non-biological environmental structure forms the backbone of an autistic individual's atypical means of overcoming sensory chaos, allowing that individual to respond productively as a biological agent.

One of the fascinating aspects of autistic perceptual foregrounding is that it can bring forth incredible variety and novelty. An autistic individual is apt to pull almost any kind of information from a sensory environment (it wouldn't have been all that surprising, for instance, if Entity 3 had ignored both the light poles and the people on the bench and had fixated instead on the harmonious colors in the clouds and sky). Because of the variety, novelty and non-biological (objective) nature of the information autistic individuals tend to gather, this too might be considered a valid reason for classifying autistic representations as more veridical (and I think the authors of (Soulières 2011) actually have something of this consideration in mind). But here I think we should be a bit more cautious. Once an autistic individual has actually foregrounded some aspect of the sensory environment, he has already moved far away from the realm of true veridical representation, is no longer perceiving reality anything at all like a camera. And no matter what structure is being applied to the environmental stimulus—be it the biological, species-driven form common to non-autistic perception, or the more pattern-based variety familiar to autistic perception—it can have equally valid potential to be a good or poor reflector of environmental reality. When we consider the entirety of human history, as well as the entirety of modern human society, I think it's fair to say that all types of human perceptual foregrounding are potentially informative and valuable, we wouldn't want to be deprived of hardly any of these perspectives.

In summary, I think there is merit and truth in the (Soulières 2011) claim that autistic individuals have a tendency to experience more veridical representations under many circumstances, but I wouldn't want to make that statement as obvious, simple fact. To come to that conclusion requires a deep understanding of both autistic perception and non-autistic perception, and in particular a deep understanding of what fundamentally distinguishes them. And this is just one more example of why I think it's inadequate to describe either autistic or non-autistic cognition as merely a deficit or norm. What's needed here are clear, affirmative, distinguishing descriptions—descriptions that enlighten us about both autism and non-autism, descriptions that bring out the essential value in each of these points of view.

(Soulières 2011): Soulières I, Dawson M, Gernsbacher MA, Mottron L, 2011 The Level and Nature of Autistic Intelligence II: What about Asperger Syndrome? PLoS ONE 6(9): e25372. doi:10.1371/journal.pone.0025372

(Mottron 2009): Mottron L, Dawson M, Soulières I (2009) Enhanced perception in savant syndrome: patterns, structure and creativity. Philosophical Transactions of the Royal Society B: Biological Sciences 364: 1385–1391.

(Mottron 2006): Mottron L, Dawson M, Soulières I, Hubert B, Burack J (2006) Enhanced perceptual functioning in autism: an update, and eight principles of autistic perception. Journal of Autism and Developmental Disorders 36: 27–43.