Environment and the Nervous System Research Paper

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Remodeling of neural circuitry in response to experience occurs in diverse animal species, in numerous components of the brain, and at many points in development through adulthood. Some animal species have evolved special capabilities to extract information from the environment and put it to use in survival, but the abilities vary considerably. Some qualities of information are often quite simple, such as chemotaxis (e.g., moving away from noxious chemicals) or pheromones that initiate reproductive sequences.At first glance it would appear that many invertebrates do not learn much from experience, but the limited learning capacity of the lowly sea slug was the model system leading to one of the recent Nobel prizes in neuroscience (Kandel, 2001). The relative simplicity of that system made it accessible to study, but other invertebrate species have found niches where the ability to assimilate enormous amounts of information quickly has had survival value. Two species are of particular interest as illustrations: The honeybee leaving the hive for the first time incorporates a large amount of information about landmarks and food resources and undergoes substantial remodeling of its small brain (Fahrbach, Moore, Capaldi, Farris, & Robinson, 1998). Clearly there has been an adaptive value in this social species to develop a specialized brain system to store information rapidly on the very first flight out of the hive in a relatively permanent rewiring of the brain. Although less is known about what happens to the brain of octopuses, they have clearly adapted to a niche where survival is dependent on observation of the environment and incorporation of information about prey patterns. It is of considerable interest not only that octopuses are extremely smart in laboratory settings, but also that they can actually learn by observing one another, a type of learning one associates with higher animals. In other words, in their phylogenetic history, some species have found experience not useful for survival (e.g., jellyfish or lemmings), whereas other species facing challenging niches have evolved the capacity to extract enormous amounts of information. The information serves both to refine the structure of the brain and to incorporate information useful for survival. This evolutionary strategy apparently has developed independently in species as diverse as honeybees, octopuses, some species of birds, and some (but not all) mammals. In this research paper I review some recent neural plasticity research suggesting some general themes of how species use experience in organizing brain development.

One important theme is recognition that the vast majority of brain structure is not plastic; indeed, there are long-established mechanisms in place to protect or repair changes caused by the environment. Early development can be characterized by canalization (Waddington, 1971): When the developing brain is constructing complex, genetically determined neural systems, these should not be disturbed by minor changes in neuron number, temperature, or nutrients, for example. As noted in many neural network models of learning, a relatively rigid framework of neural connections laid down in early development helps organize and constrain the effects of experience (e.g., Quartz & Sejnowski, 1997). Although I emphasize the genetic regulation of early brain development, recent neuroscience research has demonstrated the potentially important influence of some environmental factors (e.g., prenatal stress or alcohol exposure) that can influence the organism’s later ability to incorporate experience into brain structure.

A second theme is recognition of the specialization of many neural systems to play orchestrated roles in brain development (Black & Greenough, 1986). In many ways the genetically programmed substrates set the stage for the safety of the young organism, the timing of experience, and its quality. For example, early in postnatal development many infant mammals will modify brain structures to help orient themselves to maternal protection and sustenance. Their cerebral cortex, on the other hand, is relatively undeveloped at this stage and will only become capable of structural changes in response to experience much later. Some systems respond to experience only within a narrow developmental window (i.e., a sensitive period), whereas other important systems are open-ended and can incorporate experience through all of adulthood. Aspects of play have their peak at a time when visual motor skills are progressing from rudimentary to refined through a process of nearly constant, safe practice. As discussed later, in may cases the developmentally programmed systems generally overproduce synaptic connections and use experience to prune away the unnecessary ones.

However, as Piaget (1980) pointed out toward the end of his life, there is a third important category: information that provides useful, idiosyncratic survival value to the individual that could not have been predicted in its nature or timing. For a small number of species this type of learning is quite important, and the species appear to have evolved specialized systems that allow storage of salient information whenever needed. Examples of such individualized, idiosyncratic information might be the location of food caches for a squirrel, new tricks for a falcon catching its rodent prey, a college student studying calculus, a person taking up tennis for the first time, or a taxi driver learning the roads in a new city. This lifelong, open-ended neural plasticity is necessarily regulated by neural and hormonal modulation and appears to create new synaptic connections to incorporate experience (Black & Greenough, 1986).

Gene-Driven Processes

It is sometimes easy to overemphasize the genetic contribution to behavior because of the recent explosion of knowledge in this area. We now know much of the molecular biology of cell differentiation, neuron migration, and cell regulation and signaling. These processes are capable of building enormously complex neural structures without any input from the external environment. Indeed, in order to protect brain development, much of the basic organization of most nervous systems is largely impervious to experience. Neural activity that is intrinsically driven, such as that arising from the retina of the cat or monkey in utero, can play a role in these organization processes. The entrenchment (or resistance to environmental influences) during embryonic development was termed canalization by Waddington (1971). Clearly, minor perturbations of pH or temperature should not have drastic effects on embryogenesis if a species is to survive. Extending that concept to the postnatal period, it would seem adaptive for many species that brain development not be too sensitive to variations in nutrition or experience. It would be adaptive for brain development to be resilient to fairly major trauma, which it often is through early childhood.

Tens of thousands of genes are uniquely expressed in brain development, helping regulate cell number, neuron migration, the overall pattern of brain organization, the shape and connections of individual cells, and even the microstructure of the molecules surrounding a synapse (Kandel, 2001). For perspective, consider that I received a version of the Human Genome Project’s DNAsequence distributed to fit on a single CD-ROM, and presumably the developing embryo is able to use this (relatively) simple information to sculpt and arrange one of the most complex objects in the universe, one that I can hold in my hands. This is not to imply that the process of going from genetic information to neural structure is at all easy, for this area is presently one of the most challenging and exciting areas of science and biotechnology.

I am not advocating a determinist view of brain development, however. Some species have a survival advantage if they can adapt to the environment or incorporate information from it. Indeed, many mammalian species have evolved specialized structures that can incorporate massive amounts of information. Because they have a long evolutionary history, the specialized systems vary across species and occur in multiple brain regions, such that there is not a single place or process for learning and memory. I will argue that some types of neural plasticity have evolved to be incorporated into the developmental schedule of brain development, whereas others have evolved to serve the individual’s needs by incorporating information unique to that individual’s environment.

Although I resort to metaphors of “schedules” and “scaffolding,” I would like to emphasize a more contemporary model of brain development: that derived from the study of dynamic, nonlinear systems. From the dynamic systems perspective, individuals can use the interaction of genetic constraints and environmental information to self-organize highly complex systems (especially brains). Each organism follows a potentially unique and partly self-determined developmental path of brain assembly to the extent that each has unique experiences. The genetically determined restrictions (e.g., the initial cortical architecture) serve as constraints to the system, allowing environmental information interacting with existing neural structures to organize and refine neural connections substantially.

I will not go into further detail here, but I wish to emphasize a balanced view of genotype-driven processes providing much of the basic structure of the brain, which is to an extent resistant to experience. Some of these genetically determined structures have evolved to constrain and organize experiential information, facilitating its storage in the brain in massive quantities. Although much of the remainder of this article focuses on neural plasticity, it is important to remember that such processes have a complex and genetically determined foundation. Deviations in that foundation (e.g., genetic disease or structural lesions) can have a profound impact on how experience shapes the brain, as well as on how therapeutic efforts can help restore it.

Experience-Expectant Development

Although numerous examples of neural plasticity have been found in mammalian species, much of plasticity can be classified into two basic categories. Experience-expectant development involves a readiness of the brain to receive specific types of information from the environment. This readiness occurs during critical or sensitive stages in development during which there are central adaptations to information that is reliably present for all members of the species. This information includes major sensory experience, such as patterned visual information, as well as information affecting social, emotional, and cognitive development. One aspect of the brain’s readiness to receive this expected information is the overproduction of neural connections, of which a subset is selectively retained on the basis of experience.

Ageneral process observed in many mammalian species is that a surplus of connections is produced, a large portion of which is subsequently eliminated. Evidence for overproduction and partial elimination of synapses during development has been found in many brain regions and species including cat (Cragg, 1975), rodent (Greenough & Chang, 1988), monkey (Boothe, Greenough, Lund, & Wrege, 1979; Bourgeois, Goldman-Rakic, & Rakic, 1994), and humans (Conel, 1939–1967). The overshoot in the number of synapses produced in cortical areas in many animals, including humans, has been estimated to be roughly double the number found in adults (P. R. Huttenlocher & de Courten, 1987; see P. R. Huttenlocher, 1994, for review). In humans, synaptic density and estimates of total synapse numbers in the visual cortex reach a peak at approximately 8 months of age, with synapse numbers declining thereafter (e.g., P. R. Huttenlocher & de Courten, 1987). Another important finding by P. R. Huttenlocher (1979) was that human frontal cortex has its blooming and pruning of synapse substantially delayed, with its peak occurring during childhood. A recent large-scale longitudinal magnetic resonance imaging (MRI) study found that many cortical regions will expand their gray matter volume and then contract during development, with frontal and parietal regions doing this in adolescence and later (Gledd et al., 1999).

The process of overproduction and selective elimination of synapses appears to be a mechanism whereby the brain is made ready to capture critical and highly reliable information from the environment.This possibility is supported by several lines of research, reviewed next, indicating that the pruning into structured patterns of functional neural connections requires appropriate patterns of neural activity that are obtained through experience. These events occur during known critical or sensitive periods. Furthermore, the pruning appears to be driven by competitive interactions between neural connections such that inactive neural connections are lost and connections that are most actively driven by experience are selectively maintained. In many cases it appears that regulation of neural plasticity systems has evolved to take advantage of information that could be expected for all juvenile members (i.e., it has an adaptive value for the whole species, not just for individuals). Many of the experiments described in this section disturb some aspect of the expected experience, often with substantial disruptions of further development.

Visual Deprivation

Studies of the effects of early visual deprivation have provided some of the strongest examples of experience inducing neural structure during development. Together they indicate a direct link between patterns of experience-expectant visual information and patterns of neural connectivity. Experimental visual deprivation falls into two main classes. Binocular deprivation of vision can be complete, depriving animals of all visual stimuli, or partial, depriving animals of patterned visual stimuli. This is achieved, for example, by raising animals in complete darkness or by suturing both eyelids shut, respectively. Partial deprivation reduces or distorts visual experience in some fashion. Complete deprivation of both eyes leads to a loss in complex visuomotor learning and in the precision of neuronal response properties, but it preserves balance in eye dominance and basic perceptual skills (e.g., Zablocka & Zernicki, 1990). In contrast, selective deprivation of one eye during the critical period leads to a drastic reduction in its control over visual cortex neurons and behavior, and the nondeprived eye correspondingly gains in control. The degree of recovery from deprivation depends on the species and the deprivation period’s onset and duration.

Binocular Deprivation

Studies of binocular deprivation have shown that appropriate visual stimulation during certain stages of development is critical for the development of normal neural connectivity in the visual system. Dark rearing or bilateral lid closure in developing animals results in behavioral, physiological, and structural abnormalities in visual pathways (e.g., Michalski & Wrobel, 1994; Riesen, 1965; Wiesel & Hubel, 1965). The severity and reversibility of the visual impairments are dependent on the onset and duration of the deprivation, corresponding to defined sensitive periods of a given species (Walk & Gibson, 1961). Even short periods of early visual deprivation can result in impairments in visuomotor skills, such as visually guided placement of the forepaw in cats (Crabtree & Riesen, 1979). The structural effects of dark rearing include smaller neuronal dendritic fields, reduced spine density, and reduced numbers of synapses per neuron within the visual cortex (Coleman & Riesen, 1968; Cragg, 1975; Valverde, 1971). In kittens, for example, developmental binocular deprivation results in a 40% reduction in the number of adult visual cortex synapses (Cragg, 1975).

Selective Deprivation

Selective deprivation experiments have indicated the importance of specific types of visual experience to normal brain development. For example, kittens reared in a strobeilluminated environment have plentiful visual patterns but are selectively deprived of any experience of movement (i.e., movement in the visual field would appear jerky or disconnected). Specific impairments in motion perception have been found in such kittens (Marchand, Cremieux, & Amblard, 1990). These animals had visual cortical neurons that were insensitive to visual motion (Cynader & Cmerneko, 1976), and they were impaired on visuomotor behavioral tasks that utilize motion (Hein, Held, & Gower, 1970).

Other work has limited visual experience to specific visual patterns, or contours. Hirsch and Spinelli (1970) raised kittens in chambers with one eye exposed to just horizontal stripes and the other eye to just vertical stripes. Physiological recordings of visual cortical neurons of these kittens revealed that they were most responsive to stimuli oriented in the direction of the stripes that they had experienced. Behaviorally, stripe-reared animals perform best on tests using stimuli in the orientation to which they were exposed during development (Corrigan & Carpenter, 1979; Pettigrew & Freeman, 1973). Unlike dark rearing or bilateral lid closure, stripe rearing does not appear to result in an overall diminishment of neuronal size, but it does alter the orientation of the neuronal dendritic arbors (Coleman, Flood, Whitehead, & Emerson, 1981; Tieman & Hirsch, 1982). Thus, neural function appears to be determined by the pattern, in addition to the overall number, of neural connections.

Monocular Deprivation

A great deal has been learned about experience-expectant processes from one particular deprivation model. In species with stereoscopic vision, including cats and monkeys, binocular regions of the cortex receive information from each eye via projections from the lateral geniculate nucleus in adjacent stripes or columns within cortical layer IV, termed ocular dominance columns. With normal experience early in development, the cortical input associated with each eye initially projects in overlapping terminal fields within layer IV. During development in normal animals, these axonal terminal fields are selectively pruned, resulting in sharply defined borders between ocular dominance columns in adult animals. The neurons of this layer send convergent input to other layers, made up in large majority of binocularly driven neurons (LeVay, Wiesel, & Hubel, 1980).

Early studies of monocular deprivation in stereoscopic animals appeared to show that the formation of the ocular dominance columns is dependent on the visual input from each eye during the critical period, becoming one of the most often cited examples in textbooks of experience shaping brain structure. In monocularly deprived monkeys, the axons projecting from the deprived eye regress, whereas the axons from the experienced eye do not. As a result, the columns corresponding to the deprived eye thin, whereas the columns of the nondeprived eye are enlarged relative to normal animals (Antonini & Stryker, 1993; LeVay et al., 1980). Thus, the axonal terminals from the dominant eye appear to be maintained selectively at the expense of the inactive input of the deprived eye, which has its excessive synapses eliminated. Physiologically, the number and responsiveness of cells activated by the deprived eye are severely decreased (Wiesel & Hubel, 1965). Functionally, monocular deprivation for an extended period during development results in near blindness to visual input in the deprived eye. In contrast, binocular deprivation principally results in a loss of visual acuity. Physiologically, it reduces but does not abolish the response of neurons to visual stimuli (Wiesel & Hubel, 1965).

It also does not prevent the formation of ocular dominance columns, although the segregation of columns is well below normal (LeVay et al., 1980; Mower, Caplan, Christen, & Duffy, 1985; Swindale, 1988). However, it now appears that in many respects the ocular dominance columns are established well before any visual experience and independently of competitive neural activity (Crowley & Katz, 2002). The effects of early experience and the critical period remain quite robust, so a revisionist interpretation is that the columns are established by genetically driven mechanisms and provide scaffolding for the effects of later experience.

The physiological and anatomical effects of monocular deprivation occur fairly rapidly. Antonini and Stryker (1993) found that the shrinkage of geniculocortical arbors corresponding to the deprived eye was profound in cats with only 6 to 7 days of monocular deprivation, similar to that found after 33 days of deprivation. Like binocular deprivation, the recovery from the deprivation is sensitive to the time of onset and the duration of the deprivation. Monocular deprivation corresponding to the sensitive period of a given species results in enduring impairments and physiological nonresponsiveness (e.g., Wiesel & Hubel, 1965), whereas even very extensive deprivation in adult animals has little effect (Blakemore, Garey, & Vital-Durand, 1978). In humans, early monocular deprivation resulting from congenital cataracts can have severe effects on acuity, even after treatment, whereas adults who develop cataracts in one eye show little posttreatment impairment (Bowering, Maurer, Lewis, & Brent, 1993). The sensitive period for monocular deprivation effects can be affected by prior experience. For example, the maximum sensitivity to monocular deprivation effects in kittens is normally during the fourth and fifth weeks after birth (Hubel & Wiesel, 1970; Olson & Freeman, 1978). Cynader and Mitchell (1980) found that kittens dark-reared from birth to several months of age maintained a physiological sensitivity to monocular deprivation at ages that normal kittens are insensitive. Dark-reared animals do not, however, simply show normal visual development at this later age. With binocular deprivation early in life, the ocular dominance columns of layer IV do not segregate in a fully normal pattern and do not maintain a structural sensitivity to monocular deprivation effects (Mower et al., 1985).

Deprivation in Other Sensory Systems

Although much of the research has utilized the visual system, experience-expectant processes can be observed in other sensory systems. Within layer IV of the somatosensory cortex in rodents, each whisker is represented by a distinctly clustered group of neurons arranged in what have been called barrels (Woolsey & Van der Loos, 1970). The cell bodies of these neurons form the barrel walls with a cell-sparse region forming the barrel hollow. In adult animals the input from each whisker (via the thalamus) terminates predominantly within the barrel hollows. Positioned to receive this input, most of the dendrites of the neurons lining the barrel wall are also oriented into the barrel hollow. This distinctive pattern of barrel walls surrounding a hollow forms after birth, prior to which neurons in this region appear homogenous. Because there is simultaneous regression of dendrites inside the barrel walls and continued growth of dendrites in the barrel hollows, these overlapping processes mask the expected synapse overproduction and pruning back because the overall pattern is one of dendritic expansion (Greenough & Chang, 1988). If not for the location of information provided by the structure of the barrel, this dendritic regression would be entirely masked.

Many rodents use their vibrissae (highly developed whiskers) to navigate in the dark (along with heightened olfactory perception). One might expect, therefore, that the whisker barrel region, with its overlapping blooming and pruning of synapses, would be sensitive to experience. Indeed, Glazewski and Fox (1996) were able to demonstrate experience-expectant plasticity in the barrel field cortex of young rats by reducing the complement of vibrissae on one side of the muzzle to a single whisker for a period of 7, 20, or 60 days. The vibrissa dominance distribution was shifted significantly toward the spared vibrissa, which gained control of more neurons in barrel cortex while the deprived whiskers lost control. As the deprived whiskers grew back in, they progressively gained back some control of neurons from the spared whisker. Whisker deprivation had the strongest effects in weanling animals, and very little in adult rats.

Humans appear to have something like a critical period for attachment, in that if the expected nurturing behavior does not occur in a timely manner, then subsequent emotional development will be disrupted. Human and primate studies have revealed substantial effects of disrupted attachment on behavior and endocrine function, but little is known about any underlying neural plasticity. The phenomenon known as imprinting (e.g., by which newly hatched chicks learn to recognize mothers) involves both the formation of new synapses and elimination of preexisting synapses (Horn, 1986; Patel, Rose, & Stewart, 1988). Imprinting fits our definition of experienceexpectant neural plasticity, but it is an example of social rather than perceptual development. It is important to note that various primate species are differentially sensitive to maternal deprivation and it would appear that humans are one of the relatively sensitive species. For example, rhesus monkeys raised in isolation show an enduring and heightened responses to stress; abnormal motor behaviors including stereotyped movements, sexual dysfunction, and eating disorders; and various extreme forms of social and emotional dysfunction (Sackett, 1972). The effects of total social isolation are more severe than the effects of partial isolation, which permits visual and auditory interactions with other animals but no direct contact. Martin, Spicer, Lewis, Gluck, and Cork (1991) found that socially deprived rhesus monkeys showed a marked reduction in the dopaminergic and peptidergic innervation within the caudate-putamen, substantia nigra, and globus pallidus. In addition to evidence of reduced neuronal growth and development, socially deprived monkeys show brain abnormalities more typical of neurological disorders. It is important to note, however, that many of these studies confound social deprivation with experiential deprivation, such that we still know relatively little about structural brain changes related to each social experience.

Experience-Dependent Development

Experience-dependent development involves the brain’s adaptation to information that is unique to an individual. This type of adaptation does not occur within strictly defined critical periods as the timing or nature of such experience cannot be reliably anticipated. Therefore, this type of neural plasticity is likely to be active throughout life. It is important to recognize, however, that such systems cannot be constantly “on” and recording information. They need to have some kind of regulatory process that helps filter important information from the extraneous material. Although this type of process does not have fixed windows of plasticity, there may be necessary sequential dependencies on prior development. For example, a child learns algebra before she masters calculus. Sometimes experience-dependent processes will depend on prior experience-expectant ones, as in language development with a universal sensitive period followed by more idiosyncratic expansion of grammar and vocabulary.

Manipulating Environmental Complexity

One important central mechanism for experience-dependent development is the formation of new neural connections, in contrast to the overproduction and pruning back of synapses often associated with experience-expectant processes. This idea was initially supported by experiments in which the overall complexity of an animal’s environment is manipulated as well as from experiments using specific learning tasks. Modifying the complexity of an animal’s environment can have profound effects on behavior and on brain structure both in late development (e.g., after weaning in rats) and in adulthood. In experimental manipulations, animals are typically housed in one of three conditions: individual cages (IC), in which the animals are housed alone in standard laboratory cages; social cages (SC), in which animals are housed with another rat in the same type of cage; and complex or enriched environments (EC), in which animals are housed in large groups in cages filled with changing arrangements of toys and other objects. Raising animals in an enriched environment provides ample opportunity for exploration and permits animals to experience complex social interactions, including play behavior, as well as the manipulation and spatial components of complex multidimensional arrangements of objects.

Following a tradition established by the well-known Berkeley group (e.g., Bennett, Diamond, Krech, & Rosenzweig, 1964), the experimental groups are often referred to as enriched and impoverished. It is important to emphasize that these are more accurately described in terms of varying degrees of deprivation, relative to the typical environment of feral rats. Barring considerations of stress or nutrition, I would argue that EC rats experience something close to normal brain development and that EC brains would closely resemble those of rats raised in the wild. Although a great deal of useful information can be obtained from laboratory animals, it is important in this research paper to understand that standard animals are generally overfed, understimulated, and physically out of shape.

Animals raised in complex environments are superior on many different types of learning tasks (reviewed in Black & Greenough, 1986). Various studies have suggested that EC animals may use more and different types of cues to solve tasks and may possess enhanced information-processing rates and capacities (Greenough, Volkmar, & Juraska, 1973; Juraska, Henderson, & Muller, 1984; Thinus-Blanc, 1981). Their superiority in complex mazes may rely in part on a greater familiarity with complicated spatial arrangements obtained through their rearing environment. These abilities are generalized across a wide range of other learning tests, however, suggesting that the EC’s abilities do not simply lie in specific types of information gathered from the rearing environment. Rather, the brain adaptation to complex environment rearing involves changing how information is processed (i.e., the EC rat appears to have learned to learn better).

Examinations of brain structures of animals reared in complex environments reveal a growth of neurons and synaptic connections in comparison to siblings raised in standard cages. This phenomenon has been most prominently studied in the visual cortex, which shows an overall increase in thickness, volume, and weight (e.g., Bennett et al., 1964); dendritic branching, complexity, and spine density (e.g., Greenough, Volkmar, & Juraska, 1973; Holloway, 1966); synapses per neuron (Turner & Greenough, 1983, 1985); and larger synaptic contacts (Sirevaag & Greenough, 1985) in rats reared in complex environments. The number of synapses in EC rats is elevated by approximately 20% to 25% within superficial layers of the visual cortex (Turner & Greenough, 1985). Comparable anatomical data have been reported in cats given complex experience (Beaulieu & Colonnier, 1987).

The effects of environmental complexity have many different dimensions. The EC effects on brain structure cannot be attributed to general metabolic, hormonal, or stress differences across the different rearing conditions (reviewed in Black, Sirevaag, Wallace, Savin, & Greenough, 1989). Thus, the structural brain changes may be specifically the result of altered neuronal activity and information storage. Young EC rats will add new capillaries to visual cortex, presumably in support of increased metabolic activity (Black, Sirevaag, & Greenough, 1987). Rats reared in a complex environment tend to have slower growth of skeleton and internal organs (Black et al., 1989), as well as altered immune system responsivity (Kingston & Hoffman-Goetz, 1996). Evidence that male and female rats differ in their responses to the complex environment in both the visual cortex and the hippocampus suggest at least a modulatory role for sex hormones in the EC-IC brain effects, at least in early postnatal development (Juraska, 1984). Multiple brain regions can show evidence of structural change in EC animals, including the temporal cortex (Greenough et al., 1973), the striatum (Comery, Shah, & Greenough, 1995), the hippocampus (Juraska, 1984), the superior colliculus (Fuchs, Montemayor, & Greenough, 1990), and cerebellum (Floeter & Greenough, 1979; Pysh & Weiss, 1979). Mice reared in a complex environment will have more neurons in the dentate gyrus (Kempermann, Kuhn, & Gage, 1997). Significant changes in rat cortical thickness and dendritic branching can be detected after just four days of enrichment (Wallace, Kilman, Withers, & Greenough, 1992). These effects are not limited to young animals, as changes in neuronal dendrites and synapses in adult rats placed in the complex environment are substantial, although smaller than those found in rats reared from weaning in EC (e.g., Green, Greenough, & Schlumpf, 1983; Juraska, Greenough, Elliott, Mack, & Berkowitz, 1980).

Structural Effects of Learning

Although many activities occur in an EC environment, clearly one of the most important is learning. If learning in the EC environment results in structural brain changes, then similar changes would be expected in animals in response to a variety of training procedures. Such studies have indeed demonstrated that major brain changes occur during learning. These changes have been found in the specific brain regions apparently involved in the learning. For example, training in complex mazes requiring visuospatial memory has been found to result in increased dendritic arbors of the visual cortex in adult rats (Greenough, Juraska, & Volkmar, 1979). When split-brain procedures were performed and unilateral occluders placed in one eye, dendrites of neurons in the monocular cortex mediating vision in the unoccluded eye showed greater growth in comparison to the ipsilateral cortex (Chang & Greenough, 1982).

Training animals on motor learning tasks has also been found to result in site-specific neuronal changes. Rats extensively trained to use one forelimb to reach through a tube to receive cookies show dendritic growth within the region of the cortex involved in forelimb function (Greenough, Larson, & Withers, 1985) in comparison to controls. When rats were allowed to use only one forelimb for reaching, dendritic arborizations within the cortex opposite the trained forelimb were significantly increased relative to the cortex opposite the untrained forelimb. Furthermore, reach training selectively alters only certain subpopulations of neurons (e.g., layer II/III pyramidal neurons showing forked apical shafts; Withers & Greenough, 1989). Reach training may produce similar results in developing animals as well. Rat pups trained to reach with one forelimb over 9 days beginning at weaning show increased cortical thickness in the hemisphere opposite the trained limb in comparison to the nontrained limb (Díaz, Pinto-Hamuy, & Fernández, 1994).

A critical question is whether these training-induced brain changes are due to special processes of information storage or simply are an effect of increased activity within the affected brain systems. This question has been addressed in a motor learning paradigm in which rats are required to master several new complex motor coordination tasks (“acrobatic” rats). These animals showed increased numbers of synapses per Purkinje neuron within the cerebellum in comparison to inactive controls (Black, Isaacs, Anderson, Alcantara, & Greenough, 1990). Animals exhibiting greater amounts of motor activity in running wheels or treadmills (Black et al., 1990), or yoked-control animals that made an equivalent amount of movement in a simple straight alley (Kleim et al., 1997), did not show significant alterations in synaptic connections in the cerebellum. Thus, learning, and not simply the repetitive use of synapses that may occur during dull physical exercise, led to synaptogenesis in the cerebellum.

It is interesting that the exercising animals did show some structural changes: The density of capillaries in the involved region of cerebellum was significantly increased, corresponding to what would be seen if new blood vessels developed to support increased metabolic demand (Black et al., 1990). This indicates that the brain can independently generate adaptive changes in different cellular components. When metabolic stamina is required, vasculature is added. When motor skills need to be learned or refined, new synapses modify neural organization.

Neural Plasticity in Humans

Due to ethical and technical limitations, it has been quite difficult to demonstrate that the human brain has neural plasticity processes similar to those for other species just described. If one considers the massive amount of information that humans incorporate (e.g., consider language learning alone) and that this material can be retained for decades without rehearsal, that information seemingly must be stored as lasting structural neural changes. Although present evidence cannot directly describe any changes in synaptic strength or number, human neural plasticity can be described in terms of experience-expectant and experience-dependent processes.

One kind of human experience-expectant process that is sensitive to selective deprivation involves perceptual mismatch from both eyes—for example, when one eye is deviated outward (strabismus) during early development. Similar to the cat and monkey studies described earlier, if the two eyes are sending competing and conflicting signals to the visual cortex during the sensitive period, the brain effectively shuts down or becomes insensitive to the nondominant eye. In humans, the resulting perceptual disorder is termed amblyopia (or lazy eye), and it results in clear perceptual deficits if surgery does not correct this visual misalignment during the critical period. The strabismus-related perceptual deficit was the first and still best established example of human neural plasticity (Crawford, Harwerth, Smith, & von Noorden, 1993). Recent technology, such as positron-emission tomography (PET), has demonstrated that patients with uncorrected strabismus use different areas of cortex for visual processing than do normal controls (e.g., Demer, 1993). Pharmacological manipulations suggest that human visual cortex plasticity is similarly influenced by gamma-aminobutyric acid (GABA), N-methyl-D-aspartate (NMDA), and acetylcholine as demonstrated in animal studies (Boroojerdi, Battaglia, Muellbacher, & Cohen, 2001). Although the timing, regulation, and structural changes of this sensitive period need further study, the early evidence suggests a clear parallel to the studies described earlier of kittens with selective deprivation of vision.

Some preliminary evidence exists that humans can alter brain function with extensive training, corresponding to the experience-dependent processes already described. For example, using functional magnetic resonance imaging (fMRI) to measure regional blood flow in the brain, Karni et al. (1995) demonstrated increased cortical involvement after training subjects in a finger-tapping sequence. Elbert, Pantev, Weinbruch, Rockstroh, and Taub (1995) showed substantial expansion of cortical involvement associated with the amount of training to play the violin. Rehabilitation therapy after brain injury produced similar fMRI changes (Frackowiak, 1996). Motor training also causes changes in cerebellum function (Doyon et al., 2002) that correspond to the anatomical changes observed with acrobatic training of rats. Nobody can yet show directly that humans produce new synapses with this type of learning, but these fMRI changes are what we would expect if synaptogenesis were occurring in an experience-dependent process.

In one of the few studies showing a structural, as opposed to functional, change in response to experience, Maguire et al. (2000) studied London taxi drivers with MRI. The researchers found larger volumes of anterior hippocampi associated with longer training. This finding suggests that there are structural changes in humans in response to the storing of enormous amounts of geographic information learned during two years of training.

Not all experience-related changes in human brain function are positive adaptations. Just as rats can suffer hippocampal damage and memory impairment when exposed to chronic stress, there is emerging evidence that stress can affect humans as well. Initial studies of Vietnam veterans who had experienced combat stress revealed memory impairment in otherwise healthy, middle-aged men (Bremner et al., 1993). Just as in the rat studies, early trauma can have lasting effects on stress regulation. For example, Yehuda et al. (1995) demonstrated endocrine dysregulation persisting for decades following exposure to trauma, in this case with survivors of the Holocaust. Bremner et al. (1995) later confirmed that the memory deficits in Vietnam veterans were associated with atrophy of the hippocampus, reflecting possible neuron damage or cell death. The size of the superior temporal gyrus, a structure involved in language, is also negatively affected by early trauma in children with posttraumatic stress disorder (De Bellis et al., 2002). Patients, both young and old, often describe an indelibility of the trauma memory with lasting effects on affective regulation (sometimes manifested as posttraumatic stress disorder or personality disorders), suggesting that structural changes may typically underlie these symptoms.


In conclusion, experience is increasingly important in building a brain as we look up the phylogenetic ladder toward humans. Recent neuroscience research reveals a number of important, interconnected principles of brain development of relevance to psychologists. First, many aspects of brain structure are genetically predetermined and serve as the scaffolding for the encoding of experience during development. Thus, the metaphor of the blank slate is inaccurate. A better metaphor for development is that of formatting the hard drive (genetics) before information may be stored (experience).

Second, I would like to emphasize the dynamic systems perspective, such that early brain pathology or distorted experience may set a maladaptive course for development, but the organism will often make efforts to compensate for it. At one level, different parts of the brain may try to compensate, and beyond that the organism may seek out new experience in areas where it has strength. Plasticity is a central feature of mammalian brains, and one should not consider early brain damage or aberrant experience as determining the organism’s fate forever. It is with this second principle of dynamic systems that the hard drive metaphor breaks down. Unlike brains, hard drives do not sculpt or mend themselves.

Third, in describing information storage mechanisms, I have tried to define the similarities and differences between maturation and learning. Maturation consists of experienceexpectant processes. Experiences leading to maturation have survival value for the entire species and may be critical to survival. Learning involves experience-dependent processes that may be critical for idiosyncratic information that may in turn be critical to the individual’s functioning. In addition, some aspects of experience (e.g., play in juvenile EC-IC rearing) may influence both experience-expectant and experience-dependent processes. In fact, these processes probably cannot be entirely isolated because they have substantial interactive consequences for how the brain processes information and because they share mechanisms at the cellular level.

Fourth, the evidence that different species have different susceptibilities to experience and that brain areas are differentially influenced by experience suggests that information storage mechanisms have not remained stable through evolution. As more complicated sensory, motor, and informationprocessing schemes evolved, experience was utilized in two ways: (a) to shape common features of the nervous system through experiences common to members of the species and (b) to provide for storage of information about the unique environment of the individual. The underlying mechanisms may have diverged to meet these separate needs, such that system-wide overproduction at a specific maturational stage, followed by selection, subserves storage of common information, whereas local activity-dependent synaptogenesis, again followed by selection, subserves later storage of unique information.

Fifth, I described experience-expectant processes in terms of the species-wide reliability of some types of experience. I suggested that species survival may be facilitated by information-storage processes anticipating an experience with identical timing and features for all juvenile members. A structural correlate of expectation may be a temporary overproduction of synapses during the sensitive period with a subsequent pruning back of inappropriate synapses. This experience-expectant blooming of new synapses is distributed more or less uniformly across the entire population of homologous cells. The neuromodulatory event that triggers this synapse overproduction may be under maturational control or may be activity dependent (as after eye opening), but it is diffuse and pervasive. The expected experience produces patterned activity of neurons, effectively targeting which synapses will be selected, as illustrated for monocular deprivation in binocular species.

Experience-dependent mechanisms, on the other hand, may utilize synapse generation and preservation in different balance for a quite different effect. Because these neural plasticity mechanisms cannot anticipate the timing or specific features of such idiosyncratic experience, the sensitive period is necessarily left wide open. Here synapses are generated locally, upon demand of some modulatory signal. The specific nature of modulation, which could be locally elicited by neural activity or by hormonal signals, remains an open question for future research. The organism’s active participation is important in obtaining and stabilizing experience. For example, juvenile play or adult attention may serve both to extract new information (increase contrast) and to help repeat it or stabilize it (increase coherence). This experiencedependent localized shaping of connectivity suggests that very multimodal and diverse experience (as in EC) would produce widespread increases in synaptic frequency, but that relatively specific experience (as in training tasks) would produce more localized increases.

Sixth, animals raised in EC differ from ICs primarily in the complexity of experience available, so that self-initiation of experience (e.g., exploratory activity) is a key determinant of timing and quality of experience. This feature is consistent with the dynamic systems perspective of development (e.g., Thelen & Smith, 1995) in that the connectivity modifications observed in the EC animals appear more related to how neural activity is processed than how much is processed. For example, both EC and IC animals use approximately the same amount of light (average intensity on the retina) quite differently—one with self-initiated activity and its visual consequences, the other with dull routine. Some species (probably including humans) have altered behavior so as to increase the likelihood of obtaining enriched experience. For example, weanling rats are generally quite playful and active in comparison to adults, probably due to the same burst of playful activity we observe in kittens, puppies, and toddlers. The burst of playfulness may be developmentally programmed and generally useful to all members of a species (Haight & Black, 2001; Ikemoto & Panksepp, 1992; Smith, 1982).

Seventh, I argued earlier that brain development can be viewed as an elaborate scaffolding of gene-driven, experience-expectant, and experience-dependent processes. Althoughitis oversimplifying to use linear terms like scaffolding or schedule, it is important to see that many components are quite dependent on the completion of earlier steps. Thus, the later synaptic blooming and pruning of human frontal cortex compared to visual cortex may reflect a sequential dependency. Neural and cognitive development may require the strictly ordered sequence of the development of sensory modalities (e.g., touch before vision; Gottlieb, 1973; Turkewitz & Kenny, 1982). Multiple sensitive periods may (a) prevent competition between modalities and (b) help integrate information across modalities (e.g., touch coming before vision may help in the development of visuomotor skills). It is interesting to speculate on the specific roles of the protracted overproduction and loss of synapses observed by P. R. Huttenlocher (1994) in human prefrontal cortex. In visual cortex, properties such as stereoscopic depth perception and the orientation tuning of receptive fields develop through experience during the early part of postnatal life. If a particular aspect of experience is missing, then subsequent visual function is disturbed. It might be of value for students of cognitive development to consider, for prefrontal cortex, what constitutes the cognitive equivalent of exposure to expected visual experience.

Another developmental process with innate roots but nonetheless quite dependent on early experience is language acquisition. Although the question of whether language has an innate deep structure is still debated, it is clear that children rapidly acquire an enormous amount of vocabulary, grammar, and related information, and that there is a critical period for language acquisition. One of possibly hundreds of genes involved has been tentatively identified. The specialized cortical adaptation of Broca’s area also exists in the great apes, suggesting that it has been present for some 5 million years and is now part of the scaffolding structure on which humans have hung language (Cantalupo & Hopkins, 2001). For middle-class American families, the rate of vocabulary acquisition is directly related to the amount of verbal stimulation the mother provides (e.g., J. Huttenlocher, Haight, Bryk, Seltzer, & Lyons, 1991). There is apparently a sensitive period for acquiring the ability to discriminate speech contrasts. For example, prior to 6 or so months of life, infants from English-speaking homes are able to discriminate speech contrasts from a variety of languages, including Thai, Czech, and Swedish, much the way native adult speakers are able to. However, sometime between 6 and 12 months, this ability is gradually lost, such that after this age infants become more like adults who are most proficient in discriminating the speech contrasts from their native language (Kuhl, 1993). Language is another area where play and childdirected experience are important parts of learning, as is reciprocity between parent and child. Preliminary findings suggestive of experience-dependent neural plasticity in language were from a quantitative neuroanatomy of Jacobs, Schall, and Scheibel (1993), who found a clear relationship between the amount of education up to the university level and the amount of dendritic branching of neurons in Broca’s area. Thus, language provides a vertical example that includes influences from genetic and neuroanatomical domains, evidence suggestive of an experience-expectant process, the coconstruction of enriched experience, and the possibility of lifelong or experience-dependent information storage.

Finally, the scaffolding of information from one domain being used to support a new domain of development can be seen in an older but still elegant series of experiments (Hein & Diamond, 1971; Held & Hein, 1963), in which kittens rode in a gondola that allowed vision but restricted movement, wore large collars that allowed free movement but prevented visualization of their paws, or had surgery that prevented their eyes from tracking their paws in space. These kittens had normal overall amounts of visual and proprioceptive information, but the lack of perceptual integration in these modalities caused profound behavioral pathology. Note that all of the types of deprivation described here either interfere with contrast (less information; e.g., monocular deprivation, strobe rearing, or stripe rearing) or coherence (less consistency of input; e.g., strabismus, wearing prisms, or riding in gondolas).

An important direction for future research is the examination of behavioral changes that may lead to synaptic changes in several of the functions known to be subserved by the human prefrontal cortex. For example, it has long been known that the ability to use strategies to solve problems and to engage in hypothetico-deductive reasoning are abilities that are heavily dependent on regions of the prefrontal cortex. Generally, it is not until formal schooling begins that these problem-solving skills are fostered, encouraged, and eventually required. Given the long trajectory of synaptic pruning that goes on in this region of the brain (see P. R. Huttenlocher, 1994, for review), it would stand to reason that these experiences may cultivate the circuits that will lead eventually to more sophisticated forms of thought, such as the cluster of abilities referred to as executive functions and social behavior (Post, 1992).


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