BIG BRAINS, SLOW DEVELOPMENT, AND PLASTICITY Throughout this chapter, we have asserted that humans, more than

be the mechanism most susceptible to selection forces, and thus the linchpin in the evolutionary process that produced modem humans.

A

related argument for the importance of delayed development to human evolution centers on the foundation of the human family and social structures (Allman,

1999;

Crook, 1980;

S. J.

Gould,

1977;

Hattori,

1998;

Wesson,

1991).

The human infant is totally dependent at birth and will remain dependent on adults for well over a decade. Pair-bonding and some division of labor (both within and between families) may have been necessary adaptations to the pressures of slow-growing offspring to increase the likeli- hood that children would survive to sexual maturity. The long period of dependency also meant that a male’s genetic success could not be measured just

by

how many females he inseminated or

by

how many children he sired. His inclusive fitness would depend on how many of his offspring reached sexual maturity, assuring him of becoming a grandfather. To increase the odds of this happening, his help in the rearing of

his

children would be needed.

It has also been speculated that the juvenile features of human infants (babies are “cute”) invoke positive feelings toward the infant in both males and females, and such feelings in men foster attachment to and paternal care for the infant. In fact, Hrdy

(1986)

suggested that the father-child bond may have been the basis of the father-mother-child bonds in human families. Noting that male primates are unique in the mammal world in the attention and care they give to infants, Hrdy suggested that perhaps this capacity preadapted “members of this order for the sort of close, long- term relationships between males and females that, under some ecological circumstances, leads to monogamy” (p. 152).

BIG BRAINS, SLOW DEVELOPMENT, AND PLASTICITY

The Plasticity of the Developing Brain

Human brains, in particular, display an extended period of growth.

The human brain continues to gain weight into the third decade of life, and neurons in the associative areas of the brain are not fully myelinated until adulthood (Gibson, 1991; Yakovlev & Lecours, 1967). This slow growth provides humans with the flexibility to make many changes within their lifetimes.

Although brains grow in size, most of the growth appears to be due to increases in the size of neurons.

(It

has only recently been learned that new neurons continue to be produced past early infancy;

E.

Gould, Reeves, Graziano, & Gross, 1999.) Moreover, new connections among neurons (synapses) continue to develop throughout life. Brain (and thus behavioral and cognitive) plasticity is primarily due to the creation of new synapses (synaptogenesis). Although synapse formation must be under genetic influ- ence to some degree, research over the past several decades has indicated quite clearly that experience is the primary factor in synaptogenesis and that this process is not limited to infancy, as was once believed, but continues even into old age (see Edelman,

1987;

Gottlieb, 1992; Greenough, Black,

& Wallace,

1987; M. H.

Johnson, 1998).

Researchers have repeatedly demonstrated in laboratory animals the role of experience in the formation of synapses and the production of neurotransmitters that facilitate the conveying of messages between neurons.

Animals raised in “enriched” versus “deprived” environments show different patterns of neural development, which is related to certain aspects of learn- ing. Enriched environments usually include animals raised together in large cages that are filled with a variety of objects with which they can interact.

Deprived environments often include animals raised in isolation or in smaller cages with few objects with which to interact (Hebb,

1949;

Hymovitch,

1952;

Turner & Greenough, 1985).

A

typical finding is that animals raised in enriched environments have heavier and thicker neocortexes, larger neurons with more dendrites, and more synaptic connections than animals raised in deprived environments. They also display enhanced learning abili- ties on a wide range of tasks. These effects are not limited to infant animals, but have also been reported for older animals (Greenough, McDonald, Parnisari, & Camel, 1986).

Results illustrating the plasticity of the animal brain as a result of experience led Quartz and Sejnowski

(1997)

to propose a model of neural constmctivism, in which brain and cognitive development proceed via a dynamic interaction between the developing neural substrate and the envi- ronment. Experience changes the brain, which in turn affects what new information can be learned. The process is a constructive one, similar to the process proposed by Piaget to describe cognitive development. One

THE BENEFITS OF YOUTH

105

interpretation that emanates from this perspective is that there are few areas in the brain that at birth are “implanted with knowledge,” or what Elman and his colleagues

(1996)

referred to as representation constraints (see discussion in chapter

3).

This does not preclude the very real possibility that there are processing constraints, what Elman and colleagues referred to as architectural constraints. Rather, experiences (many of which all normal members of a species would receive) play a critical role in shaping the brain.

Our point here is that the development of the mammalian brain is not exclusively under genetic control, a position consistent with the developmental systems approach discussed in chapters

2

and

3.

The brain becomes organized from electrical and chemical activities of developing neurons and from information received through the senses as much as or more than

by

the unfolding of a genetic “blueprint.” And Homo sapiens, with a large brain and an extended period of growth, should show greater plasticity over the course of its ontogeny than any species.

With respect to behavioral flexibility, Mason (1968a, 196810) noted that the extended juvenile period in primates in general and in humans particularly, is accompanied by weaker and less persistence of primitive infantile responses (reflexive grasp, rooting, oral grasping) and a “loosening”

of behavioral organization.

As

a result, Mason (1968a) stated, Developmental stages are less sharply delimited in humans than in other primates. Sensitive periods in development are more difficult to establish, there is less likelihood that the withholding of any specific experience will result in developmental arrest, and there is a much stronger tendency for behavior to reflect a blending or intermingling of different developmental stages, different response patterns, and different motivational systems. (p. 101)

Developmental scientist Robert Cairns (1976) made a similar argu- ment, noting that the instability of individual differences and the

high

malleability of social behavior throughout infancy, characteristic of all social mammals, are extended in human children. From this perspective, an ex- tended juvenile period provides not only more time to learn but, when accompanied

by

a reduced reliance on “hardwired” or “instinctive” behaviors, may in fact require a greater need for learning.

Although we cannot turn back the clock and observe directly hetero- chronic changes that produce variations in a species’ morphology or behav- ior, some experimental evidence exists that demonstrates the effects of changes in developmental timing on social behavior across several genera- tions. Cairns and his colleagues (Cairns, Gariepy, & Hood, 1990; Cairns, MacCombie, & Hood,

1983)

noted that aggressive behavior in mice, mea- sured by latency to attack, increased with age and experience. Cairns and

colleagues selectively bred mice for latency to attack; one line was selected for low aggression and another line was selected for high aggression. Subsequent generations of low-aggression mice did not display the typical age-related increases in aggression observed in the foundational generation. Changes in the timing of development (“the progressively longer persistence of ‘imma- ture’ features in the ontogeny of descendent generations”; Cairns et al., 1990, p.

59)

affected the social behavior of individuals and, over several generations, altered the average value of this behavior in the genetic line.

Results such as these make more plausible the hypothesis that variations in developmental timing (heterochrony ) can influence the behavioral devel- opment of the species (Cairns et al.,

1990;

Gottlieb,

1987, 1992).

If

plasticity is to be extended into later life, then neural circuits cannot be “fixed” early in life. Moreover, if immaturity of parts of the brain is responsible for this extended plasticity (e.g., incomplete myelination of neurons, resulting in slower and less-efficient neural transmission), then the young brain (and thus the young child) must be limited in general learning ability. Young children actually learn some things, such as language, faster than adults. The decreasing ability to acquire a second language with increas- ing age (much past

8

or

9

years) reflects a loss of plasticity for this

skill

(see chapter

6). A

loss of plasticity is not always a detriment, however.

As

a result of genetic programming and experience, neurons become dedicated to certain functions. Such specialization, particularly when pertaining to some aspect of human life that does not change substantially over time and circumstances (e.g., which language one’s social group speaks), can be greatly beneficial, and individuals are best served

by

a nervous system that commits neurons early in life to such basic functions. However, for a long-lived species such as humans who must contend with a large diversity of social circumstances, retaining some plasticity into adulthood is necessary (see Geary, 2001).

Despite some of the exceptional learning abilities of young children, for more general learning, the brains of infants and young children are inefficient. They process information more slowly than adults (Canfield, Smith, Brezsnyak, & Snow, 1997; Kail, 1997), which translates directly into less-efficient cognitive processing (Bjorklund & Harnishfeger,

1990;

Case, 1992; Dempster, 1985). The slower processing of young children means that more of their processing is “effortful” in that it uses substantial portions of their limited mental resources (Hasher & Zacks, 1979). In contrast, more of older children’s and adults’ cognitive processing is automatic, in that it requires little or none of one’s limited capacity. Thus, young children must exert greater effort to obtain the same results as older children. Despite the obvious disadvantages to such an inefficient system, it also has its benefits.

According to Bjorklund and Green (1992),

THE BENEFITS OF YOUTH

107

Because little in the way of cognitive processing can be automatized early, presumably because of children’s incomplete myelination, they are better prepared to adapt, cognitively, to later environments. If expe- riences early in life yielded automization, the child would lose the flexibility necessary for adult life. Processes automatized in response to the demands of early childhood may be useless and likely detrimental for coping with the very different cognitive demands faced by adults.

Cognitive flexibility in the species is maintained by an immature nervous system that gradually permits the automization of more mental opera- tions, increasing the likelihood that lessons learned as a young child will not interfere with the qualitatively different tasks required of the adult. (pp. 49-50)

Reversal of the Effects of Early Deprivation

Plasticity is often more easily seen in situations in which children who experienced deprivation early in life demonstrate subsequent reversibility of those effects. Although psychologists and educators earlier in this century deemed such reversibility unlikely, both human and animal work has clearly shown that reversibility is a reality (Clark & Hanisee,

1982;

O’Connor et al., 2000; Skeels,

1966;

Suomi & Harlow,

1972).

We start with an example from the animal literature because the notions of “critical period”

and

its intellectual offspring, early deprivation, are rooted there in the form of “imprinting.”

As

we discussed in chapter

3,

the most famous example of imprinting comes from the work of ethologist Konrad Lorenz

(1937,

1965) with geese, in which early exposure during a

“critical period” resulted in goslings’ preference for specific partners in specific situations. Current evidence on imprinting, specifically,

and

critical periods and timing more generally, suggests that the generalizability of early effects depends on several factors (Bateson, 1981a). For example, imprinting effects are generalized only to very similar contexts. Individuals’ willingness to learn different preferences beyond a critical period can be changed. In this regard, imprinting is treated as a dimension of learning and is influenced

by

experiences and developmental age. This view is consistent with our view that development can be represented as a transaction between individu- als and their environments.

This ability to change after a critical period is further illustrated by recent studies that examined the recovery of intellectual function of children reared in stultifying orphanages in Romania who were later adopted (Kaler &

Freedman,

1994;

O’Connor et al., 2000; Rutter & the English and Romanian Adoptees Study Team, 1998). For example, O’Connor and his colleagues (2000) evaluated the psychometric intelligence of children at age

6

who had been reared in Romanian orphanages as a function of their age at adoption and immigration to the United Kingdom. These children were

also compared with a group of

UK

children who were adopted

by UK

parents between the ages of birth and 8 months of age. Scores on the General Cognitive Index

(GCI)

of the McCarthy scale are presented for the various groups of children in Table

4.2.

The

GCI

can be interpreted much as an

IQ

score, with a value of

100

representing the population average. Note that, despite the substantial developmental delay that all of the Romanian adoptees displayed on arrival in the United Kingdom,

by

age

6

years, each group had mean scores within the normal range. There was no difference in scores between the

UK

adoptees and the Romanian children adopted within their first

6

months of life. Scores were lower, however, for the Romanian children who had been adopted later; those who spent the most time in the institution had the lowest scores.

These results reflect the remarkable resiliency of children to the effects of early deprivation, but they also demonstrate that there are limits to intellectual plasticity. The more time children spent in the deprived environ- ment, the less able their brains were to change, at least

by

age

6. (Of

course, children who had spent more time in the orphanage had spent less time in their adoptive homes. Perhaps the negative effects of the early deprivation will be reversed when they spend more time in their adoptive homes.) Nonetheless, the overall impression of these findings is that, given proper stimulation, children can overcome the effects of an early negative environ- ment. Young brains are not like tape recorders, recording everything for posterity. Rather, young brains are pliable. Were children born with more mature brains, or if development proceeded more rapidly, the mental, social, and emotional flexibility of young children would be severely compromised.

This behavioral and cognitive flexibility is perhaps our species' greatest adaptive advantage, and it is afforded

by

the prolonged period of mental (and thus brain) inefficiency.

TABLE 4.2

Scores on the General Cognitive Index (GCI) at Age 6 Years

for

UK and Romanian Children by

Age They Were Adopted

Nation Age (Months) GCI Score

United Kingdom 0-8

Romania 0-6

Romania 6-24

Romania 24-42

117 114 99 90

Note. From 'The Effects of Global Severe Privation on Cognitive Compe- tence: Extension and Longitudinal Follow-Up," by T. G. OConnor, M. Rutter, C. Beckett, L. Keaveney, J. M. Kreppner, and the English and Romanian Adoptees Study Team, 2000, Child Development, 71, pp. 376390. Copy- right 2000 by Society for Research in Child Development. Adapted with per- mission.

THE BENEFITS OF YOUTH

109

Plasticity and Evolution

As we noted earlier, Gilbert Gottlieb

(1992)

has proposed that animals with larger brains relative to body size should show greater behavioral plas- ticity. When using exploratory behavior and general learning ability as indicators of behavioral plasticity, such a relationship is indeed found (see Gottlieb,

1992).

Gottlieb has extended this argument to propose that big-brained and behaviorally plastic animals are able to adapt to environ- ments more readily than animals with smaller brains and less behavioral plasticity, not only in ontogeny but also in phylogeny. That is, animals with larger brains should show a faster evolutionary pace than smaller- brained animals.

Evidence for this contention comes from a study

by

Wyles, Kunkel, and Wilson (1983), who compared the average relative brain size with the rate of anatomical changes from the fossil records for different groups of animals. Results from their study are shown in Table

4.3. To

interpret the table, all one needs to know is that higher scores reflect greater relative brain size and faster rate of anatomical change, respectively.

As

can be seen, the relation between these two factors was almost perfect (correlation ⁼

.97).

Homo sapiens had both the largest relative brain size and the fastest rate of anatomical change, followed in

both

categories by the hominoids (which include the lesser and great apes). Wyles and colleagues (1983) interpreted their findings as reflecting the importance of behavioral flexibility and innovation in evolutionary change:

Behavioral innovation refers to the nongenetic (or genetic) origin of a new skill in a particular individual, leading it to exploit the environ- ment in a new way

. . .

[the] nongenetic propagation of new skills and mobility in large populations will accelerate anatomical evolution by increasing the rate at which anatomical mutants of potentially high fitness are exposed to selection in new contexts. (p. 4396)

According to Gottlieb ( 1992), changes in developmental conditions activate heretofore inactive genes, which can result in behavioral and morphological modifications, which in turn can be influenced by natural selection.

Al-

though Gottlieb’s model can be applied to all levels of animal life, these types of changes are most apt to be found in behaviorally flexible species, which have large brains and an extended juvenile period.

McKinney

(1998)

made a similar argument; he proposed that the extension of brain and cognitive development over ontogeny is an important mechanism for overcoming the limitations of morphological complexity.

Although there is no single “progressive” tendency in evolution (i.e., every- thing gets more complex with time), there has been a trend toward greater complexity over evolutionary time (Bonner,

1988).

For example, the maxi-

TABLE 4.3

Brain Size in Relation to Rate

of

Anatomical Evolution Taxonomic Group

Homo

Hominoids (apes)”

Songbirds Other mammals Other birds Lizards Frogs Salamanders

Relative Brain Size Anatomical Rate 114 26

23 12 4.3 1.2 0.9 0.8

>I0 2.5 1.6 0.7 0.7 0.25 0.23 0.26

’Including Austraopithecus but excluding Homo.

Note. From ”Birds, Behavior, and Anatomical Evolution” by J. S. Wyles, J. G. Kunkel, and A. C. Wilson, 1983, Proceedings of the National Academy of Sciences USA, 80, pp. 4394- 4397. Copyright 1983 by J. G. Kunkel. Adapted with permission.

mum number of cell types in multicellular organisms has increased over geological time. However, there is an upper limit to morphological complex- ity, and evidence suggests that morphological change has plateaued. How- ever, organisms that are limited in evolving greater morphological complex- ity to meet the demands of changing environments can respond

by

evolving larger and more efficient brains and the behavioral and cognitive flexibility that they afford (see also Parker & Gibson, 1979).

Some examples of how modified early environments can alter species- typical behavior that is particularly pertinent to human evolution come from observations of human-reared (enculturated) great apes. Great apes (mostly common chimpanzees) that have been raised

by

humans, much as human children, often display cognitive abilities that are more like those of children than those displayed

by

mother-reared animals (see Call &

Tomasello, 1996). For example, the most successful of the “language-trained”

chimpanzees have been enculturated (Gardner & Gardner,

1969;

Savage- Rumbaugh et al., 1993). Similarly, mother-reared chimpanzees rarely imitate tool use, particularly deferred imitation (imitating a behavior following a significant delay). In contrast, enculturated common chimpanzees, bonobos, and orangutans have all been shown to display above-chance levels of deferred imitation of object manipulation (Bering, Bjorklund, & Ragan,

2000;

Bjorklund, Bering, & Ragan, 2000; Bjorklund, Yunger, Bering, &

Ragan, in press; Tomasello, Savage-Rumbaugh, & Kruger,

1993).

Deferred imitation has traditionally been interpreted as requiring symbolic representa- tion (Meltzoff,

1995;

Piaget, 1962), and aspects of these apes’ atypical, human-like rearing history apparently prompted the emergence of represen- tational skills, at least in limited contexts, which are absent from their mother-reared conspecifics (see chapter

7).

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111