Assignment: neuropsychology

Assignment: neuropsychology

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Assignment: How neuropsychology informs our understanding of developmental disorders 73

How neuropsychology informs our understanding of developmental disorders 73

� 2008 The Author Journal compilation � 2008 Association for Child and Adolescent Mental Health.

The beginnings of the field of developmental cog- nitive neuroscience can be traced to Lenneberg’s seminal book, Biological Foundations of Language (1967) and subsequent work, such as the work of Bates and Neville discussed earlier, on whether the specialization of the left hemisphere for language was innate. Inspired by Lenneberg’s book, consid- erable research in the 1970s and 1980s was con- ducted to test whether hemispheric specialization for language was invariant across development. Many of these studies used a relatively weak method, dich- otic listening, to answer this question. Since they failed to find developmental increases in hemi- spheric specialization, they often accepted the innate (null) hypothesis. The classic studies of Bates and Neville using more powerful methods eventually made it clear that the answer to this fundamental question was ‘no’, consistent with Lenneberg’s ori- ginal hypothesis of progressive specialization.

There were other advances in the mid-1980s in our understanding of the development of brain–behavior relations. Some of these were contained in a special section in Child Development titled ‘Developmental Psychology and the Neurosciences: Building a Bridge’ (Crnic & Pennington, 1987). This special section contained Greenough, Black, and Wallace’s (1987) now classic article on experience-dependent and experience-expectant synaptogenesis, as well as a review by the late Patricia Goldman-Rakic (1987) on her seminal work on the development and func- tions of the prefrontal cortex. Greenough and colleagues elegantly demonstrated that experience shapes the brain and Goldman-Rakic demonstrated that a classic developmental milestone, object permanence, depended on the development of the prefrontal cortex.

So, the field of developmental cognitive neurosci- ence was rapidly emerging by the mid-1980s, although its name came somewhat later. I first encountered this term in a grant that Liz Bates had written, seeking funding for her pioneering studies of children with early unilateral lesions. By adding the adjective ‘developmental’ to the term ‘cognitive neuroscience,’ Liz and other pioneers in this field who used this term, like Mark Johnson (Johnson, 1997, 2005) and Chuck Nelson (Nelson & Luciana, 2001), were doing more than saying we ought to study brain–behavior relations in children as well as adults. Instead, this addition signaled a bold theo- retical claim, that cognitive neuroscience would be fundamentally incomplete without an understand- ing of how brain–behavior relations develop. In other words, we cannot understand how the mature brain functions without understanding how it develops. This claim rested in part on dramatic advances in developmental neurobiology made by Hubel and Wiesel (1963), Hubel, Wiesel, and Stryker (1977), Greenough (Greenough et al., 1987), Shatz (1992) and others. These advances made it clear that plas- ticity was an intrinsic and necessary property of

normal brain development, and that instead of being ‘hardwired’ at birth, neural circuits (and the mental structures they mediate) emerge as a result of inter- actions among neurons, whose activity is initially endogenous and then increasingly responsive to environmental stimulation.

Assignment: neuropsychology

So mental structures are a product of probabilistic epigenesis (Gottlieb, 1992) or neural constructivism (Quartz & Sejnowski, 1997). Hence, Piaget’s emer- gentist theory about the ontogeny of a child’s concepts and mental operations could be potentially grounded in the materialist details of interactions among neurons in neural networks. Hence, the cognitive architecture of a ‘typical’ adult is the product of a developmental process, just as is cognitive devolu- tion in aging, and we cannot full understand that cognitive architecture without understanding how it developed (and keeps developing, because plasticity also characterizes the adult brain).

Another important scientific breakthrough con- tributed to this perspective, namely the development of connectionist or neural network models (O’Reilly & Munakata, 2000; Rumelhart & McClelland, 1986). These networks modeled the emergence of mental structures from the interactions of artificial neurons exposed to a particular learning history, and became an extremely powerful tool for studying typical and atypical development.

The fact that a given individual’s cognitive architecture is a product of their own developmen- tal and learning history leads to an important corollary: the study of individual differences will provide important insights about what is con- strained and what can vary in brain and behavior development. Atypical development provides an important test of the universality of developmental processes and sequences. As Neville’s work with the congenitally deaf demonstrated, differences in experience will change brain development and the localization of functions. We now have many more examples of this phenomenon, from musicians, blind readers of Braille, and others (e.g., Galaburda & Pascual-Leone, 2003). These examples make one wonder how many individuals actually have typical development or whether typical development is more of an average across diverse developmental trajectories.

But individual differences also arise from genetic differences and the interaction of genes and envir- onment. So, another important component of developmental cognitive neuroscience is behavioral and molecular genetics. We are beginning to understand how the typical chemistry and wiring of the brain is influenced by genes, how genetic vari- ations alter this chemistry and wiring, and how these genetic variations interact with environmental factors to alter developmental trajectories (Rutter, 2006). We now turn to particular examples of the power of the developmental cognitive neuroscience approach.

74 Bruce F. Pennington

� 2008 The Author Journal compilation � 2008 Association for Child and Adolescent Mental Health.

Examples of a multilevel understanding of atypical development

There are now several examples of the successful application of a developmental cognitive neurosci- ence approach. In each of these examples, we can now trace a causal path from etiology to brain development to cognition and finally to an indi- vidual’s conscious experience. We consider three examples here: children with infantile cataracts, early treated phenylketonuria (PKU), and develop- mental dyslexia. Children with each condition experience a somewhat different world as a result of early changes in brain development. In the case of infantile cataracts, the effect on brain development is environmentally mediated, whereas in dyslexia and early treated PKU it is genetically mediated. In the cases of early treated PKU and infantile cataracts, the analysis began with a known medical syndrome and worked ‘forward’ to behavior. In contrast, in the case of developmental dyslexia, the analysis began with behavior and worked ‘backwards’ to the brain and to genes. A brief description of each of these examples follows.

Unless removed early, infantile (but not adult) cataracts cause blindness in the affected eye, thus disrupting the binocular visual input necessary for the formation of ocular dominance columns, which segregate visual input from each eye in primary visual cortex (Shatz, 1992). A similar problem can result from early misalignment of the eyes, termed esotropia and colloquially known as ‘cross-eyes’ (Held, 1985). Either condition disrupts the segrega- tion of visual input from each eye to the brain. This segregation of input is necessary for the brain to detect when each eye is fixating on the same object in the world and to compute information about depth in the visual scene. Neural network models of typical and atypical development of ocular dominance columns (Miller, Keller, & Stryker, 1989) and of stereopsis (Churchland, 1995) have been developed. In sum, we have a fairly complete account in neural terms of how an alteration in early environmental input changes brain development and the compu- tations performed by neural networks to lead to a change in conscious experience – loss of three- dimensional vision.

In the second example, early treated PKU, it has become clear that even mild elevations of phenylal- anine levels lead to a dopamine depletion syndrome that differentially affects prefrontal and retinal neurons, leading to deficits in working memory and contrast sensitivity (Diamond, Prevor, Callender, & Druin, 1997; Welsh, Pennington, Ozonoff, Rouse, & McCabe, 1990). PKU is a classic inherited metabolic disorder due to a single autosomal recessive muta- tion of the gene that codes for the enzyme phenylal- anine hydroxylase. Without this enzyme, the child cannot convert phenylalanine to tyrosine, the nec- essary precursor for dopamine synthesis.