Models of atypical development must also be models of normal development

Functional magnetic resonance imaging studies of developmental disorders and normal cognition that include children are becoming increasingly common and represent part of a newly expanding field of developmental cognitive neuroscience. These studies have illustrated the importance of the process of development in understanding brain mechanisms underlying cognition and including children ill the study of the etiology of developmental disorders

Are developmental disorders like cases of adult brain damage? Implications from connectionist modelling

It is often assumed that similar domain-specific behavioural impairments found in cases of adult brain damage and developmental disorders correspond to similar underlying causes, and can serve as convergent evidence for the modular structure of the normal adult cognitive system. We argue that this correspondence is contingent on an unsupported assumption that atypical development can produce selective deficits while the rest of the system develops normally (Residual Normality), and that this assumption tends to bias data collection in the field. Based on a review of connectionist models of acquired and developmental disorders in the domains of reading and past tense, as well as on new simulations, we explore the computational viability of Residual Normality and the potential role of development in producing behavioural deficits. Simulations demonstrate that damage to a developmental model can produce very different effects depending on whether it occurs prior to or following the training process. Because developmental disorders typically involve damage prior to learning, we conclude that the developmental process is a key component of the explanation of endstate impairments in such disorders. Further simulations demonstrate that in simple connectionist learning systems, the assumption of Residual Normality is undermined by processes of compensation or alteration elsewhere in the system. We outline the precise computational conditions required for Residual Normality to hold in development, and suggest that in many cases it is an unlikely hypothesis. We conclude that in developmental disorders, inferences from behavioural deficits to underlying structure crucially depend on developmental conditions, and that the process of ontogenetic development cannot be ignored in constructing models of developmental disorders

Ontologies, Mental Disorders and Prototypes

As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field do not allow for the representation of concepts in terms of typical traits. However, the need of representing concepts in terms of typical traits concerns almost every domain of real world knowledge, including medical domains. In particular, in this article we take into account the domain of mental disorders, starting from the DSM-5 descriptions of some specific mental disorders. On this respect, we favor a hybrid approach to the representation of psychiatric concepts, in which ontology oriented formalisms are combined to a geometric representation of knowledge based on conceptual spaces

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

Culture and Cognitive Theory: Toward a Reformulation

In a provocative and important recent article Anthony Marsella (1998) makes an eloquent plea for the forging of a new metadiscipline of psychology that he labels global-community psychology. Marsella argues that we need a radical rethinking of the fundamental premises of psychology, rooted as they are in Western cultural traditions. Features of an emergent global-community psychology include an emphasis on multicultural and multidisciplinary approaches to human behavior that draw attention to the importance of context and meaning in human lives. Marsella's call for a global-community psychology reflects, in part, a growing body of literature that demonstrates the importance of cultural factors in a diver-sity of psychological domains such as cognition, emotion, social behavior, and psychopathology

Mechanisms for the generation and regulation of sequential behaviour

A critical aspect of much human behaviour is the generation and regulation of sequential activities. Such behaviour is seen in both naturalistic settings such as routine action and language production and laboratory tasks such as serial recall and many reaction time experiments. There are a variety of computational mechanisms that may support the generation and regulation of sequential behaviours, ranging from those underlying Turing machines to those employed by recurrent connectionist networks. This paper surveys a range of such mechanisms, together with a range of empirical phenomena related to human sequential behaviour. It is argued that the empirical phenomena pose difficulties for most sequencing mechanisms, but that converging evidence from behavioural flexibility, error data arising from when the system is stressed or when it is damaged following brain injury, and between-trial effects in reaction time tasks, point to a hybrid symbolic activation-based mechanism for the generation and regulation of sequential behaviour. Some implications of this view for the nature of mental computation are highlighted

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

A Robot Model of OC-Spectrum Disorders : Design Framework, Implementation and First Experiments

© 2019 Massachusetts Institute of TechnologyComputational psychiatry is increasingly establishing itself as valuable discipline for understanding human mental disorders. However, robot models and their potential for investigating embodied and contextual aspects of mental health have been, to date, largely unexplored. In this paper, we present an initial robot model of obsessive-compulsive (OC) spectrum disorders based on an embodied motivation-based control architecture for decision making in autonomous robots. The OC family of conditions is chiefly characterized by obsessions (recurrent, invasive thoughts) and/or compulsions (an urge to carry out certain repetitive or ritualized behaviors). The design of our robot model follows and illustrates a general design framework that we have proposed to ground research in robot models of mental disorders, and to link it with existing methodologies in psychiatry, and notably in the design of animal models. To test and validate our model, we present and discuss initial experiments, results and quantitative and qualitative analysis regarding the compulsive and obsessive elements of OC-spectrum disorders. While this initial stage of development only models basic elements of such disorders, our results already shed light on aspects of the underlying theoretical model that are not obvious simply from consideration of the model.Peer reviewe