An understanding of how extrinsic factors like the environment, mothering, and experience can regulate gene expression and the developing brain provides the basis for considering two of the most common developmental disorders. Many genes have been implicated in both attention deficit disorder and autism, but it is equally clear that no single gene alone can cause either condition. Rather, many different genes each have a small, contributing effect, which means that extrinsic factors also play a role. What’s more, both autism and attention deficit disorder are clearly part of a spectrum in which some children show very few symptoms and other children are affected severely. This range of behavior may cause you to wonder whether these are “disorders” at all.

Some children have a hard time paying attention in school

The core symptoms of attention deficit hyperactivity disorder (ADHD) are distractibility, hyperactivity, and impulsiveness. ADHD is seen in as many as 5% of children, and it is 2–3 times more common in boys than in girls. It is a controversial disorder for several reasons. For one thing, the symptoms are seen in nearly all children at one time or another, so diagnosis depends on the extent to which these commonplace symptoms arise and interfere with normal functioning, rather than on the appearance of any rare or distinctive behavior.

When researchers compare children diagnosed with ADHD to other children, the differences they observe suggest that the syndrome is real. For example, children with ADHD have brain volumes that are 3–4% smaller than those of controls (Castellanos et al., 2002). Differences are most prominent in prefrontal cortex (which is thought to play a role in inhibiting behavior; see Chapter 14) and the cerebellum (Arnsten, 2006). Children with ADHD also differ from controls in terms of brain activity (Ashtari et al., 2005), and they display a delay in the thinning of cortical thickness that is normal in development (see Figure 13.31 in the textbook) (Shaw et al., 2007). Children with ADHD also seem to have reduced signaling in the dopamine “reward” pathways that we discuss in Chapter 4 (Volkow et al., 2009). But for all these differences, there is considerable overlap between the groups, so none of the differences can be used to diagnose the condition.

Because brain differences and symptoms of ADHD form part of a continuum, we can question whether it is a separate disorder or simply another way in which individuals differ from one another. Even the name may be a misnomer, since many people with ADHD have very good attention spans when they’re doing something they find interesting, or something that is more “hands-on.” But clearly, children with ADHD have difficulty performing well in the traditional classroom.

There is also disagreement about whether ADHD should be treated with drugs, typically stimulants such as methylphenidate (Ritalin) or the amphetamine Adderall. Although the drugs improve attention in children with ADHD (as they do in adults, whether they have ADHD or not), some people question whether the improved performance in school is worth the risk of long-term exposure to psychoactive drugs. Reports of rare but serious side effects of stimulant treatment, such as hallucinations (Edelsohn, 2006) and heart attacks (Wilens et al., 2006), complicate the decision of whether to medicate children who have ADHD.

Autism is a disorder of social competence

Autism spectrum disorder (ASD) is a lifelong developmental disorder characterized by impaired social interactions and language, and a narrow range of interests and activities. The disorder is found in about one to two children per thousand, is much more common in males than females, and has a strong heritable component (Weiss et al., 2009). Usually autism is discovered when apparently normal toddlers begin regressing, losing language skills, and withdrawing from family interaction. Children with autism may or may not appear mentally deficient, but they tend to perseverate (such as by continually nodding the head or making stereotyped finger movements), actively avoid making eye contact with other people, and have a difficult time judging other people’s thoughts or feelings (Senju et al., 2009). When shown photos of the faces of family members, autistic individuals reveal a pattern of brain activation quite different from that exhibited by controls (Pierce et al., 2001), suggesting a very different brain organization for the fundamental social skill of recognizing others.

Several structural differences between the brains of people with autism and those of controls have been reported, including a reduction in the size of the corpus callosum and certain cerebellar regions (Egaas et al., 1995). Even though people with autism have fewer neurons in the amygdala than control subjects have (Schumann and Amaral, 2006), they show greater activation of the amygdala when they’re gazing at faces (Dalton et al., 2005). The amygdala has been associated with fear (see Chapter 11), so this finding suggests that children with autism avoid making eye contact with people because they find it aversive.

The underlying problem with autism may be an inability to empathize with others, as reflected in the difficulty that individuals with autism display in making “copycat” movements of the fingers or body. When people with autism do this task, a particular part of the frontal cortex is less activated than in control subjects (Villalobos et al., 2005). The same region is also underactivated when people with autism try to mimic emotional facial expressions of others (see Figure 1) (Dapretto et al., 2006). This hypoactivated region contains mirror neurons (discussed further in Chapter 5), which are active whenever the individual either makes a particular hand movement or sees someone else make that same hand movement. A child with a deficit in such a brain region underlying imitation and empathy might find other people’s behaviors so bewildering that he or she would withdraw from social relations and language.

Figure 1  Underactivation of Mirror Cells in Autism
(a) When control children are asked to imitate the emotional facial expressions displayed in photographs of other people, many brain regions show activation. (b) When children with autism do this task, the same brain regions are active except for a region in the inferior frontal cortex. (c) Mathematical subtraction pinpoints the site that contains “mirror neurons” as the pars opercularis region (see Chapter 5). This deficit in activating brain regions underlying imitation and empathy may be at the root of the social impairments of autism. (After Dapretto et al., 2006; courtesy of Mirella Dapretto.)

What was once called Asperger’s syndrome is no longer considered a separate disorder, but represents the less severe end of the autism spectrum. As is typical of ASD, people with Asperger’s have difficulties in understanding social interactions, but they do not lose their language capabilities as children, and they may indeed be quite articulate. They have difficulty interpreting other people’s emotional facial expressions, but they tend to be very good at classifying objects and noting details (Baron-Cohen, 2003). Not surprisingly, individuals with Asperger’s tend to become scientists and engineers. The number of children diagnosed with autism and Asperger’s is increasing steadily, but no one knows why. One hypothesis, that childhood vaccines may act as a neurotoxin to cause autism, is a favorite of celebrities and trial lawyers, but it has been thoroughly discredited (Aschner and Ceccatelli, 2010). There is no cure for autism, but some affected children are helped by highly structured training in language and behavior.

Visual deprivation can lead to blindness

Some people do not see forms clearly with one of their eyes, even though the eye is intact and a sharp image is focused on the retina. Such impairments of vision are known as amblyopia (from the Greek amblys, “dull” or “blunt,” and ops, “eye”). Some people with this disorder have an eye that is turned inward (cross-eyed) or outward. Children born with such a misalignment see a double image rather than a single fused image. By the time an untreated person reaches the age of 7 or 8, pattern vision in the deviated eye is almost completely suppressed. If the eyes are realigned during childhood, the person learns to fuse the two images and has good depth perception. But if the realignment is not done until adulthood, it’s too late to restore acute vision to the turned eye.

Understanding the cause of amblyopia has been greatly advanced by visual-deprivation experiments with animals. These experiments revealed startling changes related to disuse of the visual system in early life. Depriving animals of light to both eyes (binocular deprivation) produces structural changes in visual cortical neurons: a loss of dendritic spines and a reduction in synapses. If such deprivation is maintained for several weeks during development, when the animal’s eyes are opened it will be blind. Although light enters the eyes and the cells of the eyes send messages to the brain, the brain seems to ignore the messages and the animal is unable to detect visual stimuli. If the deprivation lasts long enough, the animal is never able to recover eyesight. These findings indicate that early visual experience is crucial for the proper development of vision, and there is a sensitive period during which these manipulations of experience can exert long-lasting effects on the system. These effects are most extensive during the early period of synaptic development in the visual cortex (see Figure 2). After the sensitive period, the manipulations have little or no effect.

Figure 2  Brain Development in the Visual Cortex of Cats
Synaptic development in cats is most intense from 8 to 37 days after birth—a period during which visual experience can have profound influence. Note that increases in brain weight and cell volume are parallel and precede synaptic development. Note also the decline in synapse numbers after 108 days of age—evidence of synapse rearrangement. (After Cragg, 1975.)

Depriving only one eye of light (monocular deprivation) produces profound structural and functional changes in the thalamus and visual cortex. Monocular deprivation in an infant cat or monkey causes the deprived eye not to respond when the animal reaches adulthood. The effect of visual deprivation can be illustrated graphically by an ocular dominance histogram, which portrays how strongly a brain neuron responds to stimuli presented to either the left or the right eye. Normally, most cortical neurons (except those in layer IV) are excited equally by light presented to either eye (see Figure 3a).

Figure 3  Ocular Dominance Histograms
These histograms show responses of cells in the visual cortex of cats: (a) normal adults; (b) after monocular deprivation through the early critical period; (c) after early deviation of one eye (squint); (d) after binocular deprivation. The numbers along the x-axis represent a gradation in response: Cells that respond only to stimulation of the opposite eye are class 1 cells. Class 2 cells respond mainly to stimulation of the opposite eye, class 4 cells respond equally to either eye, class 7 cells respond only to stimulation of the eye on the same side, and so on. (After Hubel and Wiesel, 1965; Wiesel and Hubel, 1965.

Monocular deprivation early in development, by keeping one eye closed or covered, results in a striking shift from the normal graph: most cortical neurons respond only to input from the nondeprived eye (see Figure 3b). In cats, the susceptible period for this effect is the first 4 months of life. In rhesus monkeys, the sensitive period extends to age 6 months. After these ages, visual deprivation has little effect.

During early development, synapses are rearranged in the visual cortex, and axons representing input from each eye “compete” for synaptic places. Active, effective synapses predominate over inactive synapses. If one eye is “silenced,” synapses carrying information from that eye are retracted while synapses driven by the other eye are maintained. Donald O. Hebb (1949) proposed that effective synapses (those that successfully drive the postsynaptic cell) might grow stronger at the expense of ineffective synapses. Thus, synapses that grow stronger or weaker depending on their effectiveness in driving their target cell are known as Hebbian synapses (see Figure 4). In Chapter 13 we see that the maintenance of active synapses and retraction of inactive synapses may also play a role in learning and memory.

Figure 4  Hebbian Synapses Can Account for Changes after Monocular Deprivation
Researchers offer a similar explanation for amblyopia produced by misalignment of the eyes. Hubel and Wiesel (1965) produced an animal replica of this human condition by surgically causing the eyes to diverge in kittens. The ocular dominance histogram of these animals reveals that the normal binocular sensitivity of visual cortical cells is greatly reduced (see Figure 3c). A much larger proportion of visual cortical cells are excited by stimulation of either the right or the left eye in these animals than in control animals. The reason for this effect is that, after surgery, visual stimuli falling on the misaligned eyes no longer provide simultaneous, convergent input to the cells of the visual cortex.

The competitive interaction between the eyes results in a paradox: brief deprivation of both eyes can have less of an effect on neuronal connections than an equal period of deprivation to only one eye has (compare Figures 3d and b with the normal case depicted in Figure 3a). Presumably the binocular deprivation keeps both eyes on an equal footing for stimulating cells in the visual cortex, so the predominantly binocular input to the cortical cells is retained.

One popular notion is that neurotrophic factors may play a role in experience-driven synapse rearrangement. For example, if the postsynaptic cells are making a limited supply of a neurotrophic factor, and if active synapses take up more of the factor than inactive synapses do, then perhaps the inactive axons retract for lack of neurotrophic factor. Brain-derived neurotrophic factor (BDNF) has been implicated as the trophic factor that is competed for in the kitten visual cortex (McAllister et al., 1997) and in the frog retinotectal system (Du and Poo, 2004). So perhaps ineffective synapses wither for lack of neurotrophic support.


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