The Neuroscience of Intelligence

by Richard J Haier

  The Blank Slate belief, discussed in Chapter 2, promotes SES and other social/cultural influences as critical to intelligence and its development. As noted throughout this book, the weight of evidence does not support the primacy of this view over a genetic one. There is also growing recognition that this view has failed to invigorate successful public policies aimed at closing widely acknowledged gaps in education achievement and cognitive skills shown by many disadvantaged children. A main implication of this book is that the empirical evidence overwhelmingly supports paying more attention to neurobiology as a foundation for changing the status quo. As argued in previous chapters, neurobiology can be modified, even if there are strong genetic components involved. This simple fact combined with advances in neuroscience research like the ones discussed in this chapter provide new optimism for addressing serious problems that have persisted for decades.

  What are the possible policy implications of introducing neurobiology perspectives to research on these problems? Not all individuals have a pattern of cognitive strengths that allow barely minimum success in modern, complex society. This is evident with respect to g and other factors of intelligence. To the extent that different patterns of cognitive strengths and weaknesses are rooted more in neurobiology and genetics than in childhood experience, it is incorrect to blame lack of economic or educational success entirely on poor motivation, poor education, or other social factors. All these things matter, but with respect to intelligence, they do not appear to matter that much, as the weight of evidence indicates.

  Here is my political bias. I believe government has a proper role, and a moral imperative, to provide resources for people who lack the cognitive capabilities required for education, jobs, and other opportunities that lead to economic success and increased SES. This goes beyond providing economic opportunities that might be unrealistic for individuals lacking the requisite mental abilities. It goes beyond demanding more complex thinking and higher expectations for every student irrespective of their capabilities (a demand that is likely to accentuate cognitive gaps). It even goes beyond supporting programs for early childhood education, jobs training, affordable childcare, food assistance, and access to higher education. There is no compelling evidence that any of these things increase intelligence, but I support all these efforts because they will help many people advance in other ways and because they are the right thing to do. However, even if this support becomes widely available, there will be many people at the lower end of the g-distribution who do not benefit very much, despite best efforts. Recall from Chapter 1 that the normal distribution of IQ scores with a mean of 100 and a standard deviation of 15 estimates that 16% of people will score below an IQ of 85 (the minimum for military service in the USA). In the USA, about 51 million people have IQs lower than 85 through no fault of their own. There are many useful, affirming jobs available for these individuals, usually at low wages, but generally they are not strong candidates for college or for technical training in many vocational areas. Sometimes they are referred to as a permanent underclass, although this term is hardly ever explicitly defined by low intelligence. Poverty and near-poverty for them is a condition that may have some roots in the neurobiology of intelligence beyond anyone’s control.

  The sentence you just read is the most provocative sentence in this book. It may be a profoundly inconvenient truth or profoundly wrong. But if scientific data support the concept, is that not a jarring reason to fund supportive programs that do not stigmatize people as lazy or unworthy? Is that not a reason to prioritize neuroscience research on intelligence and how to enhance it? The term “neuro-poverty” is meant to focus on those aspects of poverty that result mostly from the genetic aspects of intelligence. The term may overstate the case. It is a hard and uncomfortable concept, but I hope it gets your attention. This book argues that intelligence is strongly rooted in neurobiology. To the extent that intelligence is a major contributing factor for managing daily life and increasing the probability of life success, neuro-poverty is a concept to consider when thinking about how to ameliorate the serious problems associated with tangible cognitive limitations that characterize many individuals through no fault of their own.

  Public policy and social justice debates might be more informed if what we know about intelligence, especially with respect to genetics, is part of the conversation. In the past, attempts to do this were met mostly with acrimony, as evidenced by the fierce criticisms of Arthur Jensen (Jensen, 1969; Snyderman & Rothman, 1988), Richard Herrnstein (1973), and Charles Murray (Herrnstein & Murray, 1994; Murray, 1995). After Jensen’s 1969 article, both IQ in the Meritocracy and The Bell Curve raised this prospect in considerable detail. Advances in neuroscience research on intelligence now offer a different starting point for discussion. Given that approaches devoid of neuroscience input have failed for 50 years to minimize the root causes of poverty and the problems that go with it, is it not time to consider another perspective?

  Here is the second most provocative sentence in this book: The uncomfortable concept of “treating” neuro-poverty by enhancing intelligence based on neurobiology, in my view, affords an alternative, optimistic concept for positive change as neuroscience research advances. This is in contrast to the view that programs which target only social/cultural influences on intelligence can diminish cognitive gaps and overcome biological/genetic influences. The weight of evidence suggests a neuroscience approach might be even more effective as we learn more about the roots of intelligence. I am not arguing that neurobiology alone is the only approach, but it should not be ignored any longer in favor of SES-only approaches. What works best is an empirical question, although political context cannot be ignored. On the political level, the idea of treating neuro-poverty like it is a neurological disorder is supremely naïve. This might change in the long run if neuroscience research ever leads to ways to enhance intelligence, as I believe it will. For now, epigenetics is one concept that might bridge both neuroscience and social science approaches. Nothing will advance epigenetic research faster than identifying specific genes related to intelligence so that the ways environmental factors influence those genes can be determined. There is common ground to discuss and that includes what we know about the neuroscience of intelligence from the weight of empirical evidence. It is time to bring “intelligence” back from a 45-year exile and into reasonable discussions about education and social policies without acrimony.

  A recent book explores this possibility. Authored by two behavioral genetics researchers, the starting point is acknowledgment that all students enter the education system with different genetic propensities for learning reading, writing, and arithmetic (Asbury & Plomin, 2014). The authors propose policy ideas for tailoring the education environment to help each student learn core material in a way that is likely best suited to that student’s genetic endowment. This is a long way from the incorrect assumption that genes are deterministic; actually, genes are starting points. As the authors note, genetic research findings are uniquely excluded from discussions about education while at the same time genetic research has transformed aspects of medicine, public health, agriculture, energy, and the law. Individualized education is a long-time goal for educators, and genetic research supports that goal. Asbury and Plomin conclude, “We aim to treat all children with equal respect and provide them with equal opportunities, but we do not believe that all our pupils are the same. Children come in all shapes and sizes, with all sorts of talents and personalities. It’s time to use the lessons of behavioral genetics to create a school system that celebrates and encourages this wonderful diversity” (p. 187).

  This view is strikingly similar to Jensen’s conclusion more than 45 years ago (Jensen, 1969), “Diversity rather than uniformity of approaches and aims would seem to be the key to making education rewarding for children of different patterns of ability. The reality of individual differences thus need not mean educational rewards for some children and frustration and defeat for others” (p. 117). Both views
are common among neuroscientists who study intelligence and understand the probabilistic nature of genes. Nonetheless, failure to acknowledge the conclusive findings about the role of genetics for individual differences in intelligence and other cognitive abilities perpetuates the ineffective “one size fits all” approach to education reform. It is easy to see how ignoring what we know about intelligence has led, and will continue to lead, to frustration and failure for addressing any issue where intelligence matters (Gottfredson, 2005). Nonetheless, intelligence remains missing from public conversations.

  In the USA, for example, considerable rancor pervades discussions about education reform even without any reference whatsoever to intelligence differences among students. The idea that every high school student be held to a graduation standard of four-year college-readiness, irrespective of mental ability, is naïve and grossly unfair to those students for whom this expectation is unrealistic. Remember, statistically half of the high school student population has an IQ score of 100 or lower, making college work considerably difficult even in highly motivated individuals. It is similarly naïve and unfair to evaluate teachers by student test score changes when many tests are largely de facto measures of general intelligence rather than of the amount of course material learned over a short time period. Perhaps the greatest disservice to students will come from purposefully increasing the difficulty of evaluation tests by requiring more complex thinking to get the right answers. The odds are that this change alone will increase performance gaps because the tests are now more g-loaded. [The last sentence was drafted months before the Los Angeles Times reported a front-page story with the headline: “New scores show wider ethnic gap” (September 12, 2015)].

  In principle, there is nothing wrong with evaluation testing or having high expectations and standards. These examples, however, illustrate the consequences of ignoring what we know about intelligence from empirical studies when crafting well-intentioned policies for education, especially those policies that assume thinking skills can be taught to the same degree to all students, or that buying iPads for everyone in the education system will increase school achievement. As most teachers recognize, maximizing a student’s cognitive strengths, whatever they may be, is a worthy goal. Everything we know from the research literature on intelligence supports this view, including why the g-factor is important, how the brain develops, and the major role genetics plays in explaining intelligence differences among individuals. In the future, the potential for enhancing intelligence based on neuroscience research just might make this goal more achievable for all students and result in greater school and life achievement. As the twenty-first century progresses, we all need to be aware of neuroscience research findings on intelligence and what they could mean for our lives.

  6.7 Final Thoughts

  I have focused this book on progress in neuroscience research on intelligence, especially based on genetic and neuroimaging methods. Many questions have yet to be answered by a solid weight of evidence. Some of the major outstanding issues include: more understanding of the mechanisms of how the brain develops in early childhood; how brain development relates to adult intelligence; whether the g-factor and other intelligence factors have specific sets of brain structural and/or functional networks that explain individual differences and whether there are network sex differences; and what epigenetic factors influence intelligence. There are also bigger questions that will require new methods and technologies to work down the temporal and spatial resolution scales to circuits, neurons, and synapses to create an advanced molecular neurobiology of intelligence based on how genes function. Perhaps the most important questions to answer involve whether intelligence research findings can be used to inform education issues and public policy, especially regarding individuals who may lack the mental abilities to succeed in modern life. Also, it is not too early to discuss issues around any eventual enhancement of intelligence implied by neuroscience research.

  Writing forces thinking. I have thought about the research I have reviewed as this book materialized and what I have learned from writing it. I believe my explicit bias toward biological explanations of intelligence, developed over my 40-plus years of conducting research, is supported by many of the newest findings from psychometrics, quantitative genetics, molecular genetics, and neuroimaging. Not all studies are consistent with this view but, as I see it, the weight of evidence continues to favor neuroscience approaches for understanding what intelligence is, where it comes from, and how it can be changed. That is the focus of this book and I will leave it to others to present alternative evaluations about the weight of evidence from other perspectives on these issues. I am open to compelling arguments about where I may be incorrect in my evaluation and I am prepared to change my mind if new data shift the weight of evidence. I also believe that neuroscience perspectives on intelligence offer the best hope to resolve pressing issues about education and public policy that have not yet been resolved or ameliorated after 50 years of attempts based on blank-slate assumptions about individual differences in intelligence and where they come from. Neuroscience has the potential to change the status quo in ways that other approaches have yet to accomplish. You may not agree, but if you are now thinking about intelligence differently than when you started reading this book, my primary goal is met.

  Speaking of you, reading also forces thinking. Even if you are convinced by my arguments, I challenge you to think critically about the studies I have presented throughout this book as representative of neuroscience progress and about what I think they mean. My challenge to you is to find weak links and loopholes in my presentation, and when you do, design a new research study to fix or falsify them.

  I have a not-so-secret wish that I suspect many of you share. I would like to be transported 40 or 50 years into the future to see what has transpired. Perhaps you will be there working on brain research and nearing retirement. What have you learned? Are there specific intelligence genes? How many? How do they work? Can genetic engineering, drugs, or some experiences enhance intelligence dramatically? How does brain development during childhood or teenage years affect intelligence? Is there a realistic virtual human brain that can simulate all manner of cognition, especially intelligence? Are simulations the same for men and women? How smart is the most intelligent machine? Can we see intelligence in the structure and function of networks, circuits, neurons, and synapses? How has intelligence research been used to address problems in education and other social areas? Is there a new neuroscience-based definition of intelligence? Is chronometric testing now the new standard for assessing intelligence? What do brain fingerprints predict and how will they be used? What new neuroscience research tools and methods are available to study intelligence?

  It would please me to know these things, even if I learn that my bets written in 2015 were badly misplaced. I was born at the midpoint of the twentieth century. As a college student from a modest background, I had no concept of the future I am now living, let alone developments in brain research. Now I can only imagine the answers and the new questions that will come by the midpoint of the twenty-first century. If you are thinking about whether to have a career studying intelligence and the brain, here is a statement that will always be true: Get started – science is a never-ending story; whenever you begin will be the most exciting time to work on the puzzles that define the neuroscience of intelligence.

  Chapter 6 Summary

  Chronometrics refers to a method of measuring information processing in the brain while performing standard cognitive tasks. The measurements are made in units of time (milliseconds) and therefore provide a quantitative assessment of intelligence on a ratio scale.

  Memory is a key component of intelligence and neuroscience studies of memory can identify brain circuits that help explain individual differences.

  New neuroscience techniques like optogenetics and chemogenetics allow animal studies of neurons and circuits that may be important for intelligence research in humans.

&
nbsp; A neuroscience understanding of actual brain circuits may lead to profound advances for building truly intelligent machines based on how the brain works.

  Brain fingerprints made from neuroimaging are stable and unique to individuals and they predict intelligence.

  Neuroimaging studies of consciousness and creativity are providing some insights about intelligence.