The Neuroscience of Intelligence

by Richard J Haier

  Three laws govern this book: (1) no story about the brain is simple; (2) no one study is definitive; (3) it takes many years to sort out conflicting and inconsistent findings and establish a compelling weight of evidence. With these in mind, Chapter 1 aims to correct popular misinformation and summarizes how intelligence is defined and measured for scientific research. Some of the validity data will surprise you. For example, childhood IQ scores predict adult mortality. Chapter 2 reviews the overwhelming evidence that there are major genetic effects on intelligence and its development. Conclusive studies from quantitative and molecular genetics leave no doubt about this. Because genes always work through biological mechanisms, there must be a neurobiological basis for intelligence, even when there are environmental influences on those mechanisms. Genes do not work in a vacuum; they are expressed and function in an environment. This interaction is a theme of “epigenetics” and we will discuss its role in intelligence research.

  Chapters 3 and 4 delve into neuroimaging and how these revolutionary technologies visualize intelligence in the brain, and indicate the neurobiological mechanisms involved. New twin studies of intelligence, for example, combine neuroimaging and DNA analyses. Key results show common genes for brain structure and intelligence. Chapter 5 focuses on enhancement. It begins with critiques of three widely publicized but incorrect claims about increasing IQ and ends with electrical brain stimulation. So far, there is no proven way to enhance intelligence, but I explain why there is a strong possibility that manipulation of some genes and their biological processes may achieve dramatic increases. Imagine a moonshot-like national research effort to reach this goal; guess which nation apparently is making this commitment (it is not the USA).

  Chapter 6 introduces several astonishing neuroscience methods for studying synapses, neurons, circuits, and networks that move intelligence research even deeper into the brain. Soon we might measure intelligence based on brain speed, and build intelligent machines based on how the brain actually works. Large collaborative efforts around the world are hunting intelligence genes, creating virtual brains, and mapping brain fingerprints unique to individuals – fingerprints that predict intelligence. Overlapping neuro-circuits for intelligence, consciousness, and creativity are explored. Finally, I introduce the terms “neuro-poverty” and “neuro-SES” (social–economic status) and explain why neuroscience advances in intelligence research may inform education policies.

  Personally, I believe we are entering a Golden Age of intelligence research that goes far beyond nearly extinct controversies about whether intelligence can be defined or measured and whether genes are involved. My enthusiasm about this field is intended to permeate every chapter. If you are an educator, policy maker, parent, or student you need to know what twenty-first century neuroscience says about intelligence. If any of you are drawn to a career in psychology or neuroscience and pursue the challenges of intelligence research, then that is quite a bonus.

  Acknowledgments

  Because my academic appointments have been in medical schools, I have never had psychology graduate students working with me on research, so I have none to thank. I have had fabulous collaborators over the years and they have made all the difference. Most of my neuroimaging studies of intelligence are co-authored by friends Rex Jung, Roberto Colom, Kevin Head, Sherif Karama, and Michael Alkire. Many others, too numerous to name, contributed time, effort, and ideas over the last 40 years. I am indebted to all of them. I am especially grateful to Matthew Bennett at Cambridge University Press for inviting me to contribute to their Neuroscience series. It is the first time intelligence has been included. Drafts of this book were read all or in part by Rosalind Arden, Roberto Colom, Doug Detterman, George Goodfellow, Earl Hunt, Rex Jung, Sherif Karama, Marty Nemko, Aljoscha Neubauer, Yulia Kovas, and Lars Penke. Their corrections and insights were invaluable; any remaining errors are mine. Although I have included a substantial number of citations to relevant work, I could not possibility include everything I would have liked to. In fact, the field is moving so quickly, I added newly published papers right up to the last days before my deadline. I apologize to anyone who feels his or her work was left out. Some topics, explanations, and illustrations in this book were included in a set of my video lectures, The Intelligence Brain (©2013 The Teaching Company, LLC: www.thegreatcourses.com). Most of all, my wife protected my work time against all intrusions and that is why this book exists.

  Chapter One

  What We Know About Intelligence From the Weight of Studies

  … the attack on tests is, to a very considerable and very frightening degree, an attack on truth itself by those who deal with unpleasant and unflattering truths by denying them and by attacking and trying to destroy the evidence for them.

  (Lerner, 1980, page 11)

  Intelligence is surely not the only important ability, but without a fair share of intelligence, other abilities and talents usually cannot be fully developed and effectively used … It [intelligence] has been referred to as the “integrative capacity” of the mind.

  (Jensen, 1981, page 11)

  The good thing about science is that it’s true whether or not you believe in it.

  (Neil deGrasse Tyson, HBO’s Real Time with Bill Maher, April 2, 2011)

  Learning Objectives

  How is intelligence defined for most scientific research?

  How does the structure of mental abilities relate to the concept of a general intelligence factor?

  Why do intelligence test scores estimate but not measure intelligence?

  What are four kinds of evidence that intelligence test scores have predictive value?

  Why do myths about intelligence persist?

  Introduction

  When a computer beats a human champion at chess or a verbal knowledge game like Jeopardy, is the computer smarter than the person? Why can some people memorize exceptionally long strings of random numbers or tell the day of the week on any date in the past, present, or future? What is artistic genius and is it related to intelligence? These are some of the challenges to defining intelligence for research. It is obvious that no matter how you define intelligence, it must have something to do with the brain. Among the many myths about intelligence, perhaps the most pernicious is that intelligence is a concept too amorphous and ill-defined for scientific study. In fact, the definitions and measures used for research are sufficiently developed for empirical investigations and have been so for over 100 years. This long research tradition used various kinds of mental ability tests and sophisticated statistical methods known collectively as psychometrics. The new science of intelligence builds on that database and melds it with new technologies of the last two decades or so, especially genetic and neuroimaging methods. These advances, the main focus of this book, are helping evolve a more neuroscience-oriented approach to intelligence research. The trajectory of this research is similar to that in other scientific fields, which has led from better measurement tools to more sophisticated definitions and understandings of, for example, an “atom” and a “gene”. Before we address the brain in subsequent chapters, this chapter reviews the current state of basic intelligence research issues regarding the definition of intelligence as a general mental ability, the measurement of intelligence relative to other people, and the validity of intelligence test scores for predicting real-world variables.

  1.1 What is Intelligence? Do You Know It When You See It?

  It may seem odd, but let’s start our discussion of intelligence with the value of pi, the circumference of a circle divided by its diameter. As you know, the value of pi is always the same: 3.14 … carried out to an infinite, non-repeating sequence of decimals. For our purpose here, it’s just a very long string of numbers in seemingly random order that is always the same. This string of numbers has been used as a simple test of memory. Some people can memorize a longer string of the pi sequence than others. And, a few people can memorize a very long string.

  Daniel Tammet, a young British man, s
tudied a computer printout of the pi sequence for a month. Then, for a demonstration organized by the BBC, Daniel repeated the sequence from memory publically while checkers with the computer printout followed along. Daniel stopped over 5 hours later after correctly repeating 22,514 digits in the sequence. He stopped because he was tired and feared making a mistake (Tammet, 2007).

  In addition to his ability to memorize long strings of numbers, Daniel also has a facility to learn difficult languages. The BBC also arranged a demonstration of his language ability when they moved him to Iceland to learn the local language with a tutor. Two weeks later he conversed on Icelandic TV in the native tongue. Do these abilities indicate that Daniel is a genius or, at least, more intelligent than people who do not have these mental abilities?

  Daniel has a diagnosis of autism and he may have a brain condition called synesthesia. Synesthesia is a mysterious disorder of sensory perception where numbers, for example, may be perceived as colors, shapes, or even odors. Something about brain wiring seems to be amiss, but it is so rare a condition that research is quite limited. In Daniel’s case, he reports that he sees each digit as a different color and shape and when he recalls the pi sequence, he sees a changing “landscape” of colors and shapes rather than numerical digits. Daniel is also atypical among people with autism because he has a higher than average IQ.

  Recalling 22,514 digits of pi from memory is a fascinating achievement no matter how it is accomplished (the record is an astonishing 67,890 digits – see Section 6.2). So is learning to converse in the Icelandic language in two weeks. There are people with extraordinary, specific mental abilities. The term “savant” typically is used to describe these rare individuals. Sometimes the savant ability is an astonishing memory or the ability to calculate rapidly large numbers mentally, or the ability to play any piece of music after only hearing it once, or the ability to create artistic drawings or sculptures.

  Kim Peek, for example, was able to remember an extraordinary range of facts and figures. He read thousands of books, especially almanacs, and he read each one by quickly scanning page after page. He could then recall this information at will as he demonstrated many times in public forums in response to audience questions: Who was the 10th king of England? When and where was he born? Who were his wives? And so on. Kim’s IQ was quite low and he could not care for himself. His father managed all aspects of his life except when he answered questions from memory.

  Steven Wilshire has different savant ability. Steven draws accurate, detailed pictures of city skylines and he does so from memory after a short helicopter tour of the city. He even gets the number of windows in buildings correct. You can buy one of his many city skyline drawings at a gallery in London or online. Alonso Clemons is a sculptor. He also has a low IQ. His mother claims he was dropped on his head as a baby. Alonso creates animal sculptures in precise detail, typically after only a brief look at his subject. The artistry is amazing. Derek Pavacinni has a low IQ and cannot care for himself. He is blind from birth. Derek is a virtuoso piano player. He amazes audiences by playing any piece of music after hearing it only once, and he can play it in any musical style. It is worth noting that Albert Einstein and Isaac Newton did not have any of these memory, drawing, sculpting, or musical abilities.

  Savants raise two obvious questions: How do they do it, and why can’t I? We don’t really know the answer to either question. These individuals also raise a core question about the definition of intelligence. They are important examples of the existence of specific mental abilities. But is extraordinary specific mental ability evidence of intelligence? Most savants are not intelligent. In fact, savants typically have low IQ and often cannot care for themselves. Clearly extraordinary but narrow mental ability is not what we usually mean by intelligence.

  One more example is Watson, the IBM computer that beat two all-time Jeopardy champions. Jeopardy is a game where answers are provided and players must deduce the question. The rules were that Watson could not search the web. All information had to be stored inside Watson’s 15 petabytes of memory, which was about the size of 10 refrigerators. Here’s an example: In the Category, “Chicks Dig Me,” the answer is: This mystery writer and her archeologist husband dug to find the lost Syrian city of Arkash. This sentence is actually quite complex for a computer to understand, let alone formulate the answer in the form of a question. In case you’re still thinking, the answer, in the form of a question is: Who was Agatha Christie? Watson answered this faster than the humans, and in the actual match, Watson trounced the two human champions. Does Watson have the same kind of intelligence as humans, or better? Let’s look at some definitions to consider if Watson is more like a savant or Albert Einstein.

  1.2 Defining Intelligence for Empirical Research

  No matter how you define intelligence, you know someone who is not as smart as you are. It would be unusual if you have never called someone an “idiot” or a “moron” or just plain dumb, and meant it literally. And, in honesty, you know someone who is smarter than you are. Perhaps you refer to such a person in equally pejorative terms like “nerd” or “egghead,” even if in your innermost self, you wish you had more “brains.” Given their rarity, it is less likely you know a true genius, even if many mothers and fathers say they know at least one.

  There are everyday definitions of intelligence that do not lend themselves to scientific inquiry: Intelligence is being smart. Intelligence is what you use when you don’t know what to do. Intelligence is the opposite of stupidity. Intelligence is what we call individual differences in learning, memory, and attention. Researchers, however, have proposed a number of definitions and mostly they all share a single attribute. Intelligence is a general mental ability. Here are two examples:

  1. From the American Psychological Association (APA) Task Force on Intelligence:

  “Individuals differ from one another in their ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought” (Neisser et al., 1996).

  2. Here’s a widely accepted definition among researchers:

  [Intelligence is] “a very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience … It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather it reflects a broader and deeper capability for comprehending our surroundings – ‘catching on’, ‘making sense’ of things, or ‘figuring out’ what to do” (Gottfredson, 1997a).

  The concept of intelligence as a general mental ability is widely accepted among many researchers, but it is not the only concept. What evidence supports the concept of intelligence as a general mental ability, and what other mental abilities are relevant for defining intelligence? How do we reconcile intelligence as a general ability with the specific abilities of savants?

  1.3 The Structure of Mental Abilities and the g-Factor

  We all know from our experience that there are many mental abilities. Some are very specific, like spelling or the ability to mentally rotate 3D objects or to rapidly calculate winning probabilities of various poker hands. There are many tests of specific mental abilities. We have over 100 years of research about how such tests relate to each other. Here’s what we know: Different mental abilities are not independent. They are all related to each other and the correlations among mental tests are always positive. That means if you do well on one kind of mental ability test, you tend to do well on other tests.

  This is the core finding about intelligence assessment and, as we’ll see throughout this book, it’s the basis for most modern research. Please note this important point: tend means there is a higher probability, not a perfect prediction. Whenever we say that one score predicts something, we always mean that the score predicts a higher probability for the something.

  The relationship among mental tests is called the
structure of mental abilities. To picture the structure, imagine a three-level pyramid, as shown in Figure 1.1.

  Figure 1.1 The structure of mental abilities. The g-factor is common to all mental tests. Numbers are correlations that show the strength of relationship between tests, factors, and g. Note all correlations are positive.

  Adapted from Deary et al. (2010).

  At the bottom of Figure 1.1, we have a row of 15 different tests of specific abilities. At the next level up, tests of similar abilities are grouped into more specific factors: reasoning, spatial ability, memory, speed of information processing, and vocabulary. In the illustration, tests 1, 2, and 3, for example, are all reasoning tests and tests 7, 8, and 9 are all memory tests. However, all these more specific factors also are related to each other. Basically, people who score high on one test or factor tend to score high on the others (the numbers in the figure are illustrative correlations that show the strength of relationship between tests and factors; see more about correlations in Textbox 1.1). This is a key finding demonstrated over and over again. It strongly implies that all the factors derived from individual tests have something in common, and this common factor is called the general factor of intelligence, or g for short. g sits at the highest point on the pyramid in Figure 1.1. The g-factor provides a bridge between the definitions of intelligence that emphasize a general mental ability and individual tests that measure (or more accurately, estimate) specific abilities.