2. Border Disputes

God, grant me the serenity

To accept the things I cannot change

Courage to change the things I can

And wisdom to know the difference.

 

The serenity prayer has been adopted by Alcoholics Anonymous and other organizations that help members recover from addiction. It reveals why the brain fascinates people so much: They are always hoping to change it. Just stroll through the self-help section of your local bookstore—you’ll see hundreds of titles on how to drink less, quit drugs, eat right, manage money, discipline your kids, and save your marriage. All these things seem possible, but they are difficult to achieve.

Certainly normal, healthy adults would like to change their behaviors, but this goal is even more critical for those with mental disabilities and disorders. Can a young adult ever be cured of schizophrenia? Can a grandparent learn to speak again after a stroke? And we all want our schools and our childrearing to mold young minds for the better. Can we improve the way this is done?

The Serenity Prayer asks for courage and wisdom about change. Wouldn’t it be better to have answers from neuroscience as well? After all, changing the mind is ultimately about changing the brain. But neuroscience can never aid the quest for self-improvement without answering a more fundamental question: How exactly does the brain change when we learn to behave in a new way?

Parents marvel at the speed of their babies’ development, excitedly celebrating every new action or word as a wondrous occasion. The infant brain grows rapidly, reaching close to adult size by two years of age. This suggests a simple theory: Perhaps learning is nothing more than brain growth, and children can be made smarter by enhancing this growth.

This theory goes back yet again to the phrenologists. Johann Spurzheim argued that mental exercise could enlarge cortical organs, much as muscles bulk up after physical training. Based on this theory, Spurzheim went on to develop an entire philosophy of education for both children and adults.

More than a century passed before his theory was finally tested scientifically. By that time, psychologists had invented a way of studying the effects of stimulation on the animal mind. Laboratory rats were placed in two different environments, one dull and the other “enriched.” In the dull cage, a solitary rat lived with food and water containers as the only decoration. In the enriched cage, many rats lived together in a group and were provided daily with new toys. By running the rats through simple mazes, researchers found that the enriched rats were smarter. Presumably their brains were different, but exactly how?

In the 1960s Mark Rosenzweig and his colleagues decided to find out. Their method was startlingly simple: They weighed the cortex. It turned out that the enriched cage slightly enlarged the cortex on average. This was the first demonstration that experience causes the brain’s structure to change.

You might not be surprised. After all, what about those MRI studies showing that London taxi drivers, musicians, and bilinguals have enlarged brain regions? Once again we must be careful not to read too much into statistical findings. The MRI studies showed correlation, but they did not prove causation.

Did driving a taxi, playing a musical instrument, and speaking a second language cause the brain to enlarge, as in Spurzheim’s theory? Causation could be claimed if the brains of musicians and non-musicians were the same before musical training, and only became different afterward. But since the MRI study only collected data about “after,” it cannot rule out an alternate interpretation: Perhaps some people are born with a brain enlargement that endows musical talent, and these gifted people are more likely to become musicians. Enlarged brains cause musical training, not the other way around.

Musicians may be selected on the basis of innate talent by music teachers and competitions. And musicians may be self-selecting, since people generally prefer activities at which they excel. This sort of problem, known as selection bias, complicates the interpretation of many statistical studies. Rosenzweig eliminated selection bias by randomly installing some rats in the enriched cage and others in the dull cage. This ensured that the two groups of rats started out statistically identical, enabling him to interpret any differences after the cage experience as having been caused by it.

For an even more direct demonstration of causation, one can use MRI to compare human brains before and after an experience. In this way, researchers found that learning to juggle balls thickened the cortex in the parietal and temporal lobes. And intensive study for exams caused the parietal cortex and the hippocampus to enlarge in medical students.

These results are impressive, but they are still not what we want. It is not enough to show that experience changes the brain. We also want to know whether the change is the cause of the improved performance. To understand why proof is still lacking, consider the following analogy. Imagine that musical training causes musicians to become more obese by forcing a sedentary lifestyle of practicing all day long. It would be wrong to conclude that obesity causes their improved musical performance. Similarly, showing that musical training enlarges the brains of musicians does not prove that this growth causes them to play their instruments better.

Rosenzweig showed that living in the enriched cage made rats smarter and also thickened their cortex. He did not prove, however, that it was the thickening that caused the improvement in intelligence. In fact, this seems unlikely, given what we know about the functions of cortical regions. The frontal lobe is thought to be important for skills like maze-running, but it showed little or no increase in size. The occipital lobe, which is responsible for visual perception, showed the largest increase.

In the end, we cannot equate cortical thickening with learning. We can say only that these two phenomena are correlated. Furthermore, the correlation is weak, once again revealed only by averages over groups. Cortical thickening is not a reliable predictor of learning in individuals.

 

Perhaps studying maze-running or juggling is the wrong approach. Maybe we should study more dramatic changes. Immediately after a stroke, for example, a patient usually experiences weakness or paralysis and may also lose speech and other mental abilities. Many patients improve dramatically over the next few months. What happens to the brain during recovery? Research on this question is of clear practical importance, as it could help us develop better therapies.

Strokes are caused by blocked or leaking blood vessels that damage the brain. The symptoms often indicate which side of the brain has been damaged. If patients struggle to control one side of the body, as is frequently the case, it means that the opposite side of the brain has been damaged, because each side of the brain controls muscles on the opposite side of the body. Neurologists can sometimes further pinpoint the affected brain region. To describe the location of cortical injury, a neurologist may specify a lobe or, if more precision is needed, a particular fold in a lobe. The folds have fancy-sounding names like “superior temporal gyrus,” which means the uppermost fold in the temporal lobe. Alternatively, a cortical area may be specified by a number rather than a name, using a map published by the German neuroanatomist Korbinian Brodmann in 1909 (see Figure 11). In this book I will use the term area to mean a subdivision of Brodmann’s map, and region to refer to any subdivision of the brain.

 

 

 

Figure 11. Brodmann’s map of the cortex

 

Loss of movement after a stroke can result from damage to areas 4 and 6. Area 4 is the rearmost strip of the frontal lobe, just in front of the central sulcus, and area 6 is in front of area 4. Both are known to be important for control of movement. Language, too, is commonly impaired by stroke. That’s a sign of damage to Broca’s region (areas 44 and 45) or Wernicke’s region (the back end of area 22), both in the left hemisphere.

Friends and family desperately want to know how much recovery is possible. Will Grandpa walk again? Will he talk? Movement tends to improve over time, but not much more after three months. Language also recovers most rapidly during the first three months, though it can continue to improve for months or years afterward. Neurologists know the three-month mark is important, but they do not know exactly why. More fundamentally, they don’t know exactly what changes are taking place inside the brain as the patient recovers.

Obviously, the affected brain region might recover part or all of its function. But some cells near the malfunctioning blood vessel actually die, causing irreversible damage. Could the spared regions take over for the damaged region? Imagine that one of the players on a soccer team suffers an injury and is carried in agony off the playing field. There are no substitute players sitting on the bench, so the shorthanded (or shortfooted) team now plays worse. But as the game proceeds, the remaining players may adapt to the situation. If their comrade played in an attacking position before the injury, the defenders might compensate by starting to double as attackers.

So this is an important question: Can a cortical area acquire a new function after brain injury? There is some evidence for this after stroke, but stronger confirmation comes from cases of brain damage in early life. The disorder of epilepsy is defined by repeated spontaneous “seizures,” or episodes of excessive neural activity. Children with very frequent and debilitating seizures are sometimes treated by removing one hemisphere of the cerebrum entirely. This is one of the most radical neurosurgical procedures, and it’s astonishing that most children recover very well from it. Afterward they walk and even run, though movements of the hand on the opposite side are impaired. Their intellectual abilities are generally intact, and can even improve after surgery if the seizures are successfully eliminated.

One might argue that the recovery after hemispherectomy is not so surprising. Perhaps it’s like losing a kidney. The remaining kidney need not do anything different; it just performs more of the same. But remember that some mental functions are lateralized, so the left and right sides of the brain are not equivalent. Because the left hemisphere specializes in language, its removal almost invariably leads to aphasia in adults. This is not true for children; linguistic functions migrate to the right hemisphere, demonstrating that cortical areas can indeed change their functions.

Given what we know about localization, it’s not surprising that neurologists can guess the location of brain injury from the symptoms. Here’s the surprising “yes, but”: There may be a map dividing the cortex into areas with distinct functions, but the map is not fixed. The injured brain can redraw it.

 

The remapping of the cortex seen after stroke or surgery is more dramatic than the thickening reported by the neo-phrenologists. Can remapping also happen in healthy brains? Once again, insight can be gained from cases of severe injury—but to the body, not the brain. The following passage comes from an article by the neuroscientist Miguel Nicolelis :

 

One morning in my fourth year of medical school, a vascular surgeon at the University Hospital in São Paulo, Brazil, invited me to visit the orthopedics inpatient ward. “Today we will talk to a ghost,” the doctor said. “Do not get frightened. Try to stay calm. The patient has not accepted what has happened yet, and he is very shaken.”

A boy around 12 years old with hazy blue eyes and blond curly hair sat before me. Drops of sweat soaked his face, contorted in an expression of horror. The child’s body, which I now watched closely, writhed from pain of uncertain origin. “It really hurts, doctor; it burns. It seems as if something is crushing my leg,” he said. I felt a lump in my throat, slowly strangling me. “Where does it hurt?” I asked. He replied: “In my left foot, my calf, the whole leg, everywhere below my knee!”

As I lifted the sheets that covered the boy, I was stunned to find that his left leg was half-missing; it had been amputated right below the knee after being run over by a car. I suddenly realized that the child’s pain came from a part of his body that no longer existed. Outside the ward I heard the surgeon saying, “It was not him speaking; it was his phantom limb.”

 

Modern methods of amputation were invented in the sixteenth century by Ambroise Paré, who perfected his art as a surgeon for the French army. Paré was born at a time when surgery was performed by barbers, because it seemed like a crude act of butchery too lowly for physicians. Working on the battlefield, Paré learned how to tie off large arteries to prevent amputees from bleeding to death. He eventually earned employment with several French kings and a place in the history books as the “father of modern surgery.”

Paré was the first to report that amputees complained of an imaginary limb still attached to the body where the real limb used to be. Centuries later, the American physician Silas Weir Mitchell coined the term phantom limb to describe the same phenomenon in Civil War soldiers. His many case studies established that phantom limbs are the rule, not the exception. Why had they gone unremarked for so long? Before the surgical innovations of Paré, very few people survived amputation, and the complaints of those who did may have been dismissed as mere delusions. But far from being irrational, amputees are well aware that the phantom is not real, and because its sensations are usually painful, they beg doctors to make it go away.

Along with naming it, Mitchell proposed a theory to explain the phenomenon. He suggested that irritated nerve endings in the stump were sending signals to the brain, which interpreted them as sensations from the missing limb. Inspired by the theory, some surgeons tried amputating the stump, but this didn’t help. Today many neuroscientists believe a different theory: Phantom limbs are caused by a remapping of the cortex.

The reorganization is not of the entire cortex; it’s thought to be confined to a particular area. We previously learned about area 4, the strip in front of the central sulcus that controls movement. Just behind the central sulcus is area 3, which is involved in the bodily sensations of touch, temperature, and pain. In the 1930s the Canadian neurosurgeon Wilder Penfield mapped both areas in his patients by using electrical stimulation. After opening the skull to expose the brain for epilepsy surgery, Penfield applied his electrode to different locations in area 4. Each stimulation caused some part of the patient’s body to move. Penfield drew the correspondence between area 4 locations and body parts (Figure 12, right), calling the map a “motor homunculus.” (Homunculus is from the Latin for “little human.”) Likewise, after each stimulation of area 3, the patient reported feeling a sensation in some part of the body. Penfield mapped the “sensory homunculus” in area 3 (left), and it looked similar to the motor one. Both ran in parallel along opposite banks of the central sulcus. (Roughly speaking, these maps represent vertical planes passing through the brain from ear to ear. The plane of the sensory map is just behind the central sulcus, and that of the motor map just in front. Only the outer border is cortex; the rest is the interior of the cerebrum.)

 

 

 

Figure 12. Functional maps of cortical areas 3 and 4: the “sensory homunculus” (left) and the “motor homunculus” (right)

 

The face and hands dominate the maps, even though they are small parts of the body. Their cortical magnification reflects their disproportionate importance in sensation and movement. Could the sizes of their territories be changed by amputation, which suddenly reduces the importance of a body part to zero? Using such reasoning, the neurologist V. S. Ramachandran and his collaborators have proposed that phantom limbs are caused by remapping of area 3. If the lower arm is amputated, its territory in the sensory homunculus loses its function. The surrounding territories, dedicated to the face and upper arm, encroach upon the nonfunctional one by advancing their borders. (You can see the adjacencies in Penfield’s drawing.) These two intruders start to represent the lower arm as well as their original body parts, giving the amputee the sensation of a phantom limb.

According to the theory, the remapped face territory should represent the lower arm as well as the face. Therefore Ramachandran predicted that stimulation of the face would cause sensations in the phantom limb. Indeed, when he stroked the face of an amputee with a Q-tip, the patient reported feeling sensations not only in his face but also in his phantom hand. The theory likewise predicts that the remapped upper-arm territory should represent the lower arm as well as the upper arm. When Ramachandran touched the stump, the patient felt sensations in both the stump and his phantom hand. These ingenious experiments strikingly confirmed the theory that amputation caused remapping of area 3.

 

Ramachandran and his collaborators used technology no more advanced than a Q-tip. In the 1990s an exciting new method of brain imaging was introduced. Functional MRI revealed every region’s “activity,” or how much that part of the brain was being used. By now the images of functional MRI (fMRI) are familiar from their frequent appearance in the news media. They are usually shown superimposed on regular MRI images. The black-and-white MRI image shows the brain, and laid on top are the colored blotches of the fMRI image, which indicate the active regions. You can always recognize fMRI+MRI as “spots on brains,” while MRI is just brains.

Researchers imaged volunteers while they performed mental tasks in the laboratory. If a task activated a region, causing it to “light up” in the image, that was a clue to the region’s function. Neurology had always been hampered by the accidental nature of brain lesions, but fMRI enabled precise and repeatable experiments on localization of function. Brodmann’s map became indispensable as researchers worked hard to assign functions to each of its areas. The boom in scientific papers spurred many universities to invest large sums of money in fMRI machines, or “brain scanners.”

Researchers also repeated Penfield’s mapping of the sensory and motor homunculi. They observed which locations in area 3 were activated by touching parts of the body, and which locations in area 4 were activated when the subject moved parts of the body. It was thrilling to reproduce Penfield’s maps with fMRI rather than his crude method of opening up the skull. Researchers also studied remapping, verifying Ramachandran’s claim of a downward shift of the face representation in area 3 of amputees. As the theory predicted, the shift occurred only in those amputees who experienced phantom limb pain, not in pain-free amputees.

Amputation may not be injury to the brain, but it’s still a highly abnormal kind of experience. Do brains remap in more normal forms of learning? Violinists and other string musicians use the left hand to finger the strings of their instruments. Studies show enlargement of the left-hand representation within area 3, which is likely due to extensive musical practice. It’s impressive that fMRI can not only assign functions to Brodmann areas but also resolve fine changes within a single area. This research is far more sophisticated than studies of total brain size like Galton’s. It is bound to tell us more interesting things about cortical remapping, and it may even be useful for understanding crippling disorders of movement that seem to be caused by too much practice. Such disorders, known as focal dystonias, have tragically ended the careers of brilliant musicians.

Explaining learning in terms of the expansion of cortical areas or subareas, however, is still in the spirit of phrenology. It’s not so different in concept from the studies of cortical thickening, and the correlations are still statistically weak. The approach may be powerful, but it has limitations. For example, studies of Braille readers also show an enlarged hand representation. The remapping approach cannot easily distinguish between learning violin and Braille, which are two very different skills. And even if this particular problem can be solved, the general difficulty will remain.

Researchers have one other way of studying changes in the brain, which does not depend on the concept of remapping. Using fMRI, they have attempted to find differences in the level of activation of brain regions. For example, they have reported lower activation of the frontal lobe in schizophrenics performing certain mental tasks. At the moment such correlations are statistically weak, but this intriguing line of research may well tell us much about brain disorders and possibly lead to superior methods of diagnosing them.

At the same time, fMRI studies may have a fundamental limitation. Brain activation changes from moment to moment, roughly as quickly as thoughts and actions change. To find the cause of schizophrenia, we must identify some brain anomaly that is constant. Suppose that your car starts to shake whenever you drive faster than 30 miles per hour and turn the steering wheel to the right. This behavior is intermittent, so it’s only a symptom. It’s caused by something wrong with your car at a more basic level. Noticing symptoms is crucial, but it’s only the first step toward identifying the underlying cause.

 

Why are we still trying to use phrenology to explain mental differences? It’s not because the strategy is good. It’s because we have failed to come up with a better one. Do you know the joke about the policeman who comes upon a drunk crawling on the ground near a lamppost? The drunk explains, “I lost my keys around the corner.” The policeman asks, “Well, why don’t you search over there?” The drunk replies, “I would, but there’s more light under the lamppost.” Like the drunk who works with what he’s got, we know that size reveals little about function, but we look at it anyway because that’s what we can see with existing technologies.

To understand the failings of phrenology, can we compare with a more successful example of relating function to size? Instead of investigating whether brainy people are smarter, let’s ask whether brawny people are stronger. The size of a muscle can be measured via MRI, and its strength with a machine that looks like one in the weight room at your health club. Researchers have found correlation coefficients ranging from 0.7 to 0.9, which is much stronger than the correlation between brain size and IQ. Muscle size accurately predicts strength, just as we’d expect.

Why are size and function so closely related for muscles but not for brains? Think of a muscle as operating like a factory in which all workers do the same thing. If every worker singlehandedly performs all the steps required for making an entire widget, doubling the size of the workforce will double the factory’s output of widgets. Likewise, every fiber of a muscle performs the same task. All the fibers are lined up in parallel, and all pull in the same direction. Their contributions to the force are additive (you can simply add them together to get the total), so a muscle with more fibers should be stronger.

Now consider a factory with a more complex organization. Each worker performs a different task, like fastening a screw or welding a joint. To make even a single widget, all the workers must cooperate. Economists say that such division of labor is efficient because specialization allows each worker to become highly skilled at each task. However, doubling the number of workers will likely fail to double the output of widgets. It’s not easy to integrate the new workers into the existing organization in a way that increases output. In fact, adding more workers could even reduce output by disrupting the workflow. As Brooks’ Law—a maxim of software engineers—puts it, “Adding more programmers to a late software project makes it later.”

The brain works like the more complex factory. Each of its neurons performs a tiny task, and they cooperate in intricate ways to carry out mental functions. That’s why performance depends less on the number of neurons and more on how they are organized.

The factory analogy explains the limitations of phrenology. Can it also explain remapping? The American neuropsychologist Karl Lashley believed that mental functions were widely distributed across the cortex, and charged that most of the boundaries of Brodmann’s map were figments of the imagination. Nevertheless, this archenemy of localizationism could not completely deny the experimental evidence in its favor. In 1929 he countered with his doctrine of cortical equipotentiality. Lashley granted that every cortical area is dedicated to a specific function, but every area also has the potential to assume some other function, he claimed.

Returning to our imaginary factory—the more complex one—let’s suppose that a worker is reassigned to a new task. The initial clumsiness will eventually give way to proficiency. Workers may be specialized, but they are also equipotential. When provided with new inputs, they can change their functions.

Lashley’s doctrine has some element of truth but is too sweeping. The cortex is not infinitely adaptable. If it were, every stroke patient would recover completely. To understand the limits of adaptation and develop ways to enhance it, we need a deeper understanding. We know that the cortex can remap, but how exactly does the function of an area change?

We can’t answer this without addressing a more basic issue: What defines the function of a cortical area in the first place? Broca’s and Wernicke’s regions are dedicated to language, and Brodmann areas 3 and 4 are dedicated to bodily sensation and movement. But why these functions? And how are they executed?

It’s hopeless to answer these questions by studying only brain regions, their sizes, and their activity levels. We must look at the organization of the brain on a much finer scale. A cortical area can contain over 100 million neurons. How are they organized to perform mental functions? In the next few chapters we’ll explore this question, along with the idea that brain function depends heavily on the connections between neurons.