Cognitive Development In Infancy Research Paper

From the 1960s to the late 1980s biological approaches to human behavioral development were neglected for a variety of reasons, including the widely held belief among cognitive psychologists during that period that the ‘software’ of the mind is best studied without reference to the ‘hardware’ of the brain. However, the recent expansion of knowledge at the end of the twentieth century on brain development makes the task of relating it to behavioral changes considerably more viable than previously. In addition, new molecular and cellular methods, along with theories based on artificial neural networks, have led to great advances in our understanding of how primate brains are constructed during ontogeny. These advances, along with those in functional neuroimaging, have led to the recent emergence of the interdisciplinary science of developmental cognitive neuroscience (see Johnson 1997).

What benefits can accrue from taking a developmental cognitive neuroscience approach to infants? First, considering evidence from brain development may help constrain, or even change, the type of cognitive theories that we consider. Second, being able to relate brain to cognitive development will potentially allow a more complete explanation not only of normal development, but also of developmental disorders resulting from genetic abnormality, and the long-term effects of early brain damage.

2. Human Postnatal Brain Development

A number of lines of evidence indicate that there are substantive changes during postnatal development of the human brain. Perhaps most obviously, the volume of the brain quadruples between birth and adulthood. This increase comes from a number of sources such as more extensive fiber bundles, and nerve fibers be-coming myelinated. In addition, there is a dramatic increase in size and complexity of the dendritic tree of many neurons. Less apparent with standard microscopy, but evident with electron microscopy, is a corresponding increase in the density of synapses.

Huttenlocher (1990) and colleagues have reported a steady increase in the density of synapses in several regions of the human cerebral cortex. For example, in parts of the visual cortex, the generation of synapses (synaptogenesis) begins around the time of birth and reaches a peak at around 150 percent of adult levels toward the end of the first year. In the frontal cortex (the anterior portion of cortex, considered by most investigators to be critical for many higher cognitive abilities), the peak of synaptic density occurs later, at around 24 months of age (see Goldman-Rakic et al. 1997). Although there is variation in the timetable, in all regions of cortex studied so far, synaptogenesis begins around the time of birth and increases to a peak level well above that observed in adults.

Somewhat surprisingly, regressive events are commonly observed during the development of nerve cells and their connections in the brain. Due to the paucity of human data, the regional timetable for this decrease is still unclear and there is controversy about whether or not it shows differences between regions. Nevertheless, in humans, most neocortical regions and pathways appear to undergo this ‘rise and fall’ in synaptic density, with the density stabilizing to adult levels at different ages during later childhood. The postnatal rise-and-fall developmental sequence can also be seen in other measures of brain physiology and anatomy. For example, using PET, Chugani et al. (1987) observed an adult-like distribution of resting brain activity within and across brain regions by the end of the first year. However, the overall level of glucose uptake reaches a peak during early childhood, which is much higher than that observed in adults. The rates return to adult levels after about 9 years of age for some cortical regions. The extent to which these changes relate to those in synaptic density is currently the topic of further investigation.

A controversial issue in developmental neuroscience concerns the extent to which the differentiation of the cerebral neocortex into areas or regions with particular cognitive, perceptual, or motor functions can be shaped by postnatal interactions with the external world. This issue reflects the debate in cognitive development about whether infants are born with domain-specific ‘modules’ for particular cognitive functions such as language, or whether the formation of such modules is an activity-dependent process (see Elman et al. 1996, Karmiloff-Smith 1992). Since around 1900 neuropsychology has taught us that the majority of normal adults tend to have similar functions within approximately the same regions of cortex. However, we cannot necessarily infer from this that this pattern of differentiation is intrinsically prespecified (the product of genetic and molecular interactions), because most humans share very similar pre-and postnatal environments. In developmental neurobiology this issue has emerged as a debate about the relative importance of neural activity for cortical differentiation, as opposed to intrinsic molecular and genetic specification of cortical areas. Supporting the importance of the latter processes, Rakic (1988) proposed that the differentiation of the cortex into areas is due to a protomap. The hypothesized proto-map either involves prespecification of the tissue that gives rise to the cortex during prenatal life or the presence of intrinsic molecular markers specific to particular areas of cortex. An alternative viewpoint, advanced by O’Leary (1989) among others, is that genetic and molecular factors build an initially un-differentiated ‘protocortex,’ and that this is then subsequently divided into specialized areas as a result of neural activity. This activity within neural circuits need not necessarily be the result of input from the external world, but may result from intrinsic, spontaneous patterns of firing within sensory organs or subcortical structures that feed into the cortex, or from activity within the cortex itself (e.g., Katz and Shatz 1996).

Although the neurobiological evidence is complex, and probably differs between species and regions of the cortex, overall it tends to support the importance of neural activity-dependent processes (see Johnson 1997 for a review). With several notable exceptions, it seems likely that activity-dependent processes contribute to the differentiation of functional areas of the cortex, especially those involved in higher cognitive functions in humans. During prenatal life, this neural activity may be largely a spontaneous intrinsic process, while in postnatal life it is likely also to be influenced by sensory and motor experience.

3. Methods For Studying Human Postnatal Brain Development

Part of the reason for the recently renewed interest in relating brain development to cognitive change comes from advances in methodology which allow hypotheses to be generated and tested more readily than previously (see also Nelson and Bloom 1997). One set of tools relates to brain imaging. Some of these imaging methods, such as positron emission tomography (PET), are of limited utility for studying transitions in behavioral development in normal infants and children due to their invasive nature and their relatively coarse temporal resolution. However, two other methods may prove more useful.

Since the 1960s, scalp recorded event-related potentials have been used to assess brain function in infants and children for several decades. These recordings can either be of the spontaneous natural rhythms of the brain (EEG), or the electrical activity evoked by the presentation of a stimulus (ERP). Recent developments of the ERP method allow the relatively quick and easy installation of large numbers of sensors, thus making the method easier to use and also improving spatial resolution. Functional MRI allows the noninvasive measurement of cerebral blood flow with fine spatial resolution and temporal resolution on the order of seconds. Although this technique has been applied to children (Casey et al. 1997), the distracting noise and vibration, and the presently unknown possible effects of high magnetic fields on the developing brain, make its usefulness for healthy children under 4 or 5 years of age unclear. However, there has been at least one MRI study of infants initially scanned for clinical reasons (Tzourio et al. 1992), and the advent of ‘open’ scanners in which the mother can hold the infant may increase possibilities further.

Apart from brain imaging, the neural basis of cognitive development in infants can be examined by administering behavioral ‘marker tasks’ to infants who have suffered perinatal brain damage or developmental disorders of genetic origin. These marker tasks are adapted from tasks previously linked to a brain region or pathway in adult primates and humans by cognitive neuroscience studies. By testing infants or children with versions of such a task at different ages, the researcher can use the success or otherwise of individuals as indicating the functional development of the relevant regions of the brain. Finally, there is a continuing need for the neuroanatomical study of postmortem tissue. For a variety of reasons such studies are difficult to conduct.

4. Relating Brain To Cognitive Development

A number of different approaches have been taken to relating brain to cognitive development. These differ-ent approaches depend on very different sets of assumptions about development.

4.1 Maturational Models

The most common approach to developmental cognitive neuroscience is based on a maturational frame-work, in which it is assumed that as particular brain regions mature they allow or enable new cognitive functions to come on line. By this view postnatal brain development is assumed to be heavily governed by genetic and molecular factors, and relatively (though not completely) independent of experience. In brief, postnatal brain development is seen as a necessary, but not sufficient, cause of change in cognitive abilities. Two areas in which this approach has been applied concern the transition from subcortical to cortical control over visually guided behavior, and the later onset of frontal and prefrontal cortex control.

In one of the first specific attempts to relate changes in behavior to brain development in infants, Bronson (1974) presented evidence that the subcortical retinocollicular visual pathway primarily controls visually guided action in the newborn human infant. He also showed that it is only by around 3 months of age that visually-guided behavior switches to cortical path-ways. More recent research indicates that there is probably some, albeit limited, cortical activity in newborns, and that the onset of cortical control over behavior is a gradual, rather than all-or-none, transition. Johnson (1990) updated Bronson’s thesis to incorporate several different cortical pathways now known to underlie visually guided action in adult primates. The logic underlying this model was that changes in visually guided behavior of infants over the first months of life could be attributed to the graded onset of each of several different cortical pathways. Further, which pathways were active could be predicted from the developmental neuroanatomy of the primary visual cortex at that age, since this structure was the gateway to most of these pathways. While this model had reasonable success in accounting for the sequence changes in behavior observed, in the past few years studies involving ERPs, and studies of infants with focal cortical damage, show that frontal cortical regions are active earlier than more posterior regions, a sequence not predicted by the original Johnson (1990) model.

Another prominent maturational model has concerned the onset of prefrontal cortex functioning. In terms of structural neuroanatomy, this part of the cortex shows the most prolonged development of any region of the human brain, with changes in synaptic density detectable even into the teenage years (Hutten-locher 1990). Diamond (1991) has argued that the maturation of prefrontal cortex during the period 6–12 months accounts for a number of transitions observed in the behavior of infants in object permanence and object retrieval tasks. In one such task infants younger than 8 months often fail to accurately retrieve a hidden object after a short delay period if the object’s location is changed from one where it was previously successfully retrieved. The basis for Diamond’s claims come from the observations that (a) monkeys with lesions to the dorsolateral prefrontal cortex (DLPC) show the same patterns of impairment as young human and monkey infants, and (b) there are neurochemical and neuranatomical changes in the human DLPC at around the age they begin to perform successfully. Diamond (1991) has speculated that the DLPC is critical for performance when (a) information has to be retained or related over time or space, and (b) a prepotent response has to be inhibited. She argues that prior to the maturation of the DLPC, infants do not successfully perform tasks that require both of these abilities.

Further evidence linking success in the object permanence task to frontal cortex maturation in the human infant comes from two sources. The first of these is a series of EEG studies with normal human infants (e.g., Bell and Fox 1992), in which increases in frontal EEG responses correlate with the ability to respond successfully over longer delays in delayed response tasks. The second source is work on cognitive deficits in children with a neurochemical deficit in the prefrontal cortex resulting from Phenylketonuria (PKU). Even when treated, this inborn error of metabolism can have the specific consequence of reducing the levels of a neurotransmitter, dopamine, in the dorsolateral prefrontal cortex. These reductions in dopamine levels in the dorsolateral prefrontal cortex, result in these infants and children being impaired on tasks thought to involve parts of the prefrontal cortex, such as the object permanence task and an object retrieval task, and being relatively normal in tasks thought to depend on other regions of the cortex (Diamond et al. 1997, Welsh et al. 1990).

4.2 Selectionist Models

As discussed earlier, during the postnatal development of the cortex there is a rise and fall in synaptic density. This observation has led to a number of ‘selectionist’ theories being advanced in which the essential notion is that there is experience related sculpting of neural connectivity. For example, Changuex (1985) proposes that molecular and genetic processes specify the initial overproduction of synaptic contacts. These initial connections are labile, but either stabilize or regress, depending on the activity in the postsynaptic cell, a process referred to as ‘selective stabilization.’ Changeux and Dehaene (1989) suggested that this model could be used to bridge from the brain to cognitive and behavioral levels, and that the same process of ‘Darwinian’ change could occur. Perhaps the best example of this type of change at the behavioral level comes from the work on phonemic discrimination in infants, showing that while they can initially discriminate a very large range of phonetic boundaries used in speech, including those not found in their native language, this ability becomes restricted to those boundaries important for their native language around 12 months of age.

Selectionist models have recently been criticized for the assumption that the initial stage of overproduction is not sensitive to experience (Quartz and Sejnowski 1997), and for focusing too heavily on only one aspect of neural development (Purves 1994). It is also important to remember that neuroanatomical measures of synaptic density are a static measure of dynamic processes. Since there is constant turnover of synapses, it is unlikely that there are clearly distinct phases of growth and pruning. Rather, both stages are likely to be simultaneously occurring within cortical regions.

4.3 Activity-Dependent Models

A number of factors suggest that the field needs to move beyond the maturational framework. First, increasing evidence from developmental neuroscience suggests that neuronal activity itself plays a vital role in prenatal brain development, and it would seem reasonable to suggest that the same processes may extend into postnatal life. Second, there is evidence from neuroimaging and the study of infants with focal brain damage to suggest that there are dynamic changes in the timing and pattern of cortical activation in infants relative to adults. These dynamic changes take a number of forms, including changes in the overall spatial extent in cortex-activated ones (loca-lization), changes in the extent to which the activation of a cortical region is stimulus-specific (specialization), and changes in the temporal stage of cortical processing at which specialization can be observed (see Johnson 2000).

Event-related potential experiments with infants have indicated that both for word learning (Neville 1991) and face processing (de Haan et al. submitted) there is increasing localization of processing with age experience of a stimulus class. That is, more widespread scalp leads show a difference between the words or faces that control stimuli in younger infants than in older ones. In the example of face processing, both the left and the right ventral visual pathways are differentially activated by faces in early infancy, but in many (but not all) adults this further localizes only to the right ventral pathway (de Haan et al. 1998). In the example of word recognition, differences are initially found over widespread cortical areas, but narrow to left temporal leads after further experience with this class of stimulus (Neville 1991). Johnson (2000) presented an ‘interactive specialization’ framework within which changes in localization are a direct consequence of increases in specialization within and between cortical pathways. He suggests that this framework also provides a way of thinking about the fact that the same behavior can be mediated by different patterns of cortical activation in infants from those observed in adults.

Activity-dependent models can also be extended more broadly to the view that, at a given stage in postnatal development, the human infant may actually seek out the sensory input it needs to enable the further specialization of it its own brain. In other words, the infant is not a passive absorber of experience, but rather an active and selective seeker of it. Thus, the infant changes its ‘effective environment’ during development. One example of this comes from the development of face processing, where it has been argued that primitive tendencies for the newborn to orient to face-like stimuli ensures that developing cortical circuitry is preferentially exposed to that class of stimulus (see Johnson 1997).

Bibliography:

1. Bell M A, Fox N A 1992 The relations between frontal brain electrical activity and cognitive development during infancy. Child Development 63: 1142–63
2. Bronson G 1974 The postnatal growth of visual capacity. Child Development 45: 873–90
3. Casey B J, Trainor R J, Orendi J L, Schubert A B, Nystrom L E, Giedd J N, Xavier Castellanos J L et al. 1997 A developmental functional MRI study of prefrontal activation during performance of a go-no-go task. Journal of Cognitive Neuroscience 9: 835–47
4. Changeux J P 1985 Neuronal Man: The Biology of Mind. Pantheon Books, New York
5. Changeux J P, Dehaene S 1989 Neuronal models of cognitive functions. Cognition 33: 63–109
6. Chugani H T, Phelps M E, Mazziotta J C 1987 Positron emission tomography study of human brain functional development. Annals of Neurology 22: 487–97
7. de Haan M, Oliver A, Johnson M H 1998 Electrophysiological correlates of face processing by adults and 6-month-old infants. Journal of Cognitive Neuroscience 36 Supp. S
8. de Haan M, Pascauis O, Johnson M H (submitted) Spatial and temporal characteristics of cortical activation in adults and infants viewing faces
9. Diamond A 1991 Neuropsychological insights into the meaning of object concept development. In: Carey S, Gelman R (eds.) The Epigenesis of Mind: Essays on Biology and Cognition. Erlbaum, Hillsdale, NJ, pp. 67–110
10. Diamond A, Hurwitz W, Lee E Y, Bockes T, Grover W, Minarcik C 1997 Cognitive deficits on frontal cortex tasks in children with early-treated PKU: Results of two years of longitudinal study. Monographs of the Society for Research in Child development, Monographs No. 252: 1–207
11. Elman J L, Bates E, Johnson M H, Karmiloff-Smith A, Parisi D, Plunkett K 1996 Rethinking Innateness: A Connectionist Perspective on Development. MIT Press, Cambridge, MA
12. Gesell A L 1928 Infancy and Human Growth. Macmillan, New York
13. Goldman-Rakic P S, Bourgeois J, Rakic P 1997 Synaptic substrate of cognitive development: Life-span analysis of synaptogenesis in the prefrontal cortex of the nonhuman primate. In: Krasnegor N A, Reid Lyon G, Goldman-Rakic P S (eds.) Development of the Prefrontal Cortex. Evolution, Neurobiology and Behavior. Paul H Brookes, Baltimore, MD, pp. 27–48
14. Huttenlocher P R 1990 Morphometric study of human cerebral cortex development. Neuropsychologia 28: 517–27
15. Johnson M H 1990 Cortical maturation and the development of visual attention in early infancy. Journal of Cognitive Neuro- science 2: 81–95
16. Johnson M H 1997 Developmental Cognitive Neuroscience: An Introduction. Blackwell, Oxford, UK
17. Johnson M H, de Haan M 2001 Developing cortical specialization for visual-cognitive function: The case of face recognition. In: McClelland J L, Siegler R S (eds.) Mechanisms of Cognitive Development: Behavioral & Neural Perspectives. Lawrence Erlbaum Associates, Mahwah, NJ
18. Johnson M H 2000 Functional brain development in infants: elements of an interactive specialization framework. Child Development 71(1): 75–81
19. Karmiloff-Smith A 1992 Beyond Modularity: A developmental Perspective on Cognitive Science. MIT Press Bradford Books, Cambridge, MA
20. Katz L C, Shatz C J 1996 Synaptic activity and the construction of cortical circuits. Science 274: 1133–8
21. McGraw M B 1943 The Neuromuscular Maturation of the Human Infant. Columbia University Press, New York
22. Nelson C A, Bloom F E 1997 Child Development and Neuro-science. Child Development 68: 970–87
23. Neville H J 1991 Neurobiology of cognitive and language processing: Effects of early experience. In: Gibson K R, Petersen A C (eds.) Brain Maturation and Cognitive Development: Comparative and cross-cultural Perspectives. Adaline de Gruyter Press, Hawthorne, NY, pp. 355–80
24. O’Leary D D 1989 Do cortical areas emerge from a protocor-tex? Trends in Neuroscience 12: 400–6
25. Purves D 1994 Neural Activity and the Growth of the Brain. Academia Nazionale Dei Lincei, Cambridge University Press, Cambridge, UK
26. Quartz S R, Sejnowski T J 1997 A neural basis of cognitive development: A constructivist manifesto. Behavioural and Brain Sciences 20: 537–96
27. Rakic P 1988 Specification of cerebral cortical areas. Science 241: 170–6
28. Tzourio N, de Schonen S, Mazoyer B, Bore A, Pietrzyk U, Bruck B, Aujard Y, Deruelle C 1992 Regional cerebral blood flow in two-month old alert infants. Society for Neuroscience Abstracts 18: 1121
29. Welsh M C, Pennington B F, Ozonoff S, Rouse B, McCabe E R 1990 Neuropsychology of early-treated phenylketo-nuria: Specific executive function deficits. Child Development 61: 1697–713