Language acquisition in developmental disorders

In this chapter, I review recent research into language acquisition in developmental disorders, and the light that these findings shed on the nature of language acquisition in typically developing children. Disorders considered include Specific Language Impairment, autism, Down syndrome, and Williams syndrome. I argue that disorders of language should be construed in terms of differences in the constraints that shape the learning process, rather than in terms of the normal system with components missing or malfunctioning. I outline the integrative nature of this learning process and how properties such as redundancy and compensation may be key characteristics of learning systems with atypical constraints. These ideas, as well as the new methodologies now being used to study variations in pathways of language acquisition, are illustrated with case studies from Williams syndrome and Specific Language Impairment

Bilingualism and the single route/dual route debate

The debate between single and dual route accounts of cognitive processes has been generated predominantly by the application of connectionist modeling techniques to two areas of psycholinguistics. This paper draws an analogy between this debate and bilingual language processing. A prominent question within bilingual word recognition is whether the bilingual has functionally separate lexicons for each language, or a single system able to recognize the words in both languages. Empirical evidence has been taken to support a model which includes two separate lexicons working in parallel (Smith, 1991; Gerard and Scarborough, 1989). However, a range of interference effects has been found between the bilingual’s two sets of lexical knowledge (Thomas, 1997a). Connectionist models have been put forward which suggest that a single representational resource may deal with these data, so long as words are coded according to language membership (Thomas, 1997a, 1997b, Dijkstra and van Heuven, 1998). This paper discusses the criteria which might be used to differentiate single route and dual route models. An empirical study is introduced to address one of these criteria, parallel access, with regard to bilingual word recognition. The study fails to find support for the dual route model

Ageing, plasticity, and cognitive reserve in connectionist networks

Neurocomputational modeling has suggested that a range of mechanisms can lead to reductions in functional plasticity across development (Thomas & Johnson, 2006). In this paper, we consider whether ageing might also produce a reduction in plasticity. Marchman’s (1993) model of damage and recovery in past tense formation was extended to incorporate the two main proposals for implementing effects of ageing: altered neuromodulation and connection loss. Simulations showed that ageing did reduce plasticity (as assessed by the system’s ability to recover from damage) but that effects were modulated by (a) the mechanism used to implement ageing, (b) problem type, and (c) pre-existing levels of cognitive reserve

Theories that develop

The target article represents a significant advance in the level of sophistication applied to models of bilingual word recognition, and Dijkstra and van Heuven are to be congratulated on this endeavour. Bearing in mind the success of the (computational) BIA model in capturing detailed patterns of experimental data, I look forward to future simulation results from the BIA+ when the proposals of this new framework are implemented. It is an essential step to draw a distinction between recognition systems and the decision mechanisms that drive responses, and the authors have provided a novel way of apportioning empirical evidence of context effects in bilingual word recognition across this divide. Given the explanatory weight now being placed on decision mechanisms rather than the word recognition system itself, perhaps indeed it is now time to make some simplifying assumptions about the recognition system and start building detailed computational models of the decision component of the system. Implementation will provide the clarity of theorisation and evaluation of theory viability that have been the hallmark of the BIA model thus far

Metaphor as categorisation: a connectionist implementation

A key issue for models of metaphor comprehension is to explain how in some metaphorical comparison , only some features of B are transferred to A. The features of B that are transferred to A depend both on A and on B. This is the central thrust of Black's well known interaction theory of metaphor comprehension (1979). However, this theory is somewhat abstract, and it is not obvious how it may be implemented in terms of mental representations and processes. In this paper we describe a simple computational model of on-line metaphor comprehension which combines Black's interaction theory with the idea that metaphor comprehension is a type of categorisation process (Glucksberg & Keysar, 1990, 1993). The model is based on a distributed connectionist network depicting semantic memory (McClelland & Rumelhart, 1986). The network learns feature-based information about various concepts. A metaphor is comprehended by applying a representation of the first term A to the network storing knowledge of the second term B, in an attempt to categorise it as an exemplar of B. The output of this network is a representation of A transformed by the knowledge of B. We explain how this process embodies an interaction of knowledge between the two terms of the metaphor, how it accords with the contemporary theory of metaphor stating that comprehension for literal and metaphorical comparisons is carried out by identical mechanisms (Gibbs, 1994), and how it accounts for both existing empirical evidence (Glucksberg, McGlone, & Manfredi, 1997) and generates new predictions. In this model, the distinction between literal and metaphorical language is one of degree, not of kind

Representing the bilingual's two lexicons

A review of empirical work suggests that the lexical representations of a bilingual’s two languages are independent (Smith, 1991), but may also be sensitive to between language similarity patterns (e.g. Cristoffanini, Kirsner, and Milech, 1986). Some researchers hold that infant bilinguals do not initially differentiate between their two languages (e.g. Redlinger & Park, 1980). Yet by the age of two they appear to have acquired separate linguistic systems for each language (Lanza, 1992). This paper explores the hypothesis that the separation of lexical representations in bilinguals is a functional rather than an architectural one. It suggests that the separation may be driven by differences in the structure of the input to a common architectural system. Connectionist simulations are presented modelling the representation of two sets of lexical information. These simulations explore the conditions required to create functionally independent lexical representations in a single neural network. It is shown that a single network may acquire a second language after learning a first (avoiding the traditional problem of catastrophic interference in these networks). Further it is shown that in a single network, the functional independence of representations is dependent on inter-language similarity patterns. The latter finding is difficult to account for in a model that postulates architecturally separate lexical representations

Connectionism and psychological notions of similarity

Kitcher (1996) offers a critique of connectionism based on the belief that connectionist information processing relies inherently on metric similarity relations. Metric similarity measures are independent of the order of comparison (they are symmetrical) whereas human similarity judgments are asymmetrical. We answer this challenge by describing how connectionist systems naturally produce asymmetric similarity effects. Similarity is viewed as an implicit byproduct of information processing (in particular categorization) whereas the reporting of similarity judgments is a separate and explicit meta-cognitive process. The view of similarity as a process rather than the product of an explicit comparison is discussed in relation to the spatial, feature, and structural theories of similarity

Specific impairments in cognitive development: a dynamical systems approach

Neuropsychologists have frequently proposed that domain-specific deficits can be observed in developmental disorders (e.g., phonology in dyslexia, theory of mind in autism, grammar in specific language impairment, face recognition in prosopagnosia, mathematics in dyscalculia). These deficits appeal to a modular cognitive architecture. However, specific developmental deficits are at odds with theories that posit a high degree of interactivity between cognitive abilities across development. If there are early deficits, why do these not spread across the cognitive system during development? Or experience compensatory help from other initially intact components? We address these questions within a dynamical systems framework (van der Maas et al., 2006). We explore the conditions for deficit spread and compensation for a range of possible cognitive architectures, from modular to fully distributed. While preliminary, the results point to the importance of specifying precisely the normal developmental architecture of a system prior to characterizing patterns of impairment that might emerge from it

Developmental disorders

Introduction: Connectionist models have recently provided a concrete computational platform from which to explore how different initial constraints in the cognitive system can interact with an environment to generate the behaviors we find in normal development (Elman et al., 1996; Mareschal & Thomas, 2000). In this sense, networks embody several principles inherent to Piagetian theory, the major developmental theory of the twentieth century. By extension, these models provide the opportunity to explore how shifts in these initial constraints (or boundary conditions) can result in the emergence of the abnormal behaviors we find in atypical development. Although this field is very new, connectionist models have already been put forward to explain disordered language development in Specific Language Impairment (Hoeffner & McClelland, 1993), Williams Syndrome (Thomas & Karmiloff-Smith, 1999), and developmental dyslexia (Seidenberg and colleagues, see e.g. Harm & Seidenberg, in press); to explain unusual characteristics of perceptual discrimination in autism (Cohen, 1994; Gustafsson, 1997); and to explore the emergence of disordered cortical feature maps using a neurobiologically constrained model (Oliver, Johnson, Karmiloff-Smith, & Pennington, in press). In this entry, we will examine the types of initial constraints that connectionist modelers typically build in to their models, and how variations in these constraints have been proposed as possible accounts of the causes of particular developmental disorders. In particular, we will examine the claim that these constraints are candidates for what will constitute innate knowledge. First, however, we need to consider a current debate concerning whether developmental disorders are a useful tool to explore the (possibly innate) structure of the normal cognitive system. We will find that connectionist approaches are much more consistent with one side of this debate than the other

What can developmental disorders tell us about the neurocomputational constraints that shape development? the case of Williams syndrome

The uneven cognitive phenotype in the adult outcome of Williams syndrome has led some researchers to make strong claims about the modularity of the brain and the purported genetically determined, innate specification of cognitive modules. Such arguments have particularly been marshaled with respect to language. We challenge this direct generalization from adult phenotypic outcomes to genetic specification and consider instead how genetic disorders provide clues to the constraints on plasticity that shape the outcome of development. We specifically examine behavioral studies, brain imaging, and computational modeling of language in Williams syndrome but contend that our theoretical arguments apply equally to other cognitive domains and other developmental disorders. While acknowledging that selective deficits in normal adult patients might justify claims about cognitive modularity, we question whether similar, seemingly selective deficits found in genetic disorders can be used to argue that such cognitive modules are prespecified in infant brains. Cognitive modules are, in our view, the outcome of development, not its starting point. We note that most work on genetic disorders ignores one vital factor, the actual process of ontogenetic development, and argue that it is vital to view genetic disorders as proceeding under different neurocomputational constraints, not as demonstrations of static modularity