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This chapter discusses the question of how dynamic systems theory can be fruitfully applied to the development of the kind of phenomena and variables that have been of interest for a long time. Examples of these phenomena are (a) the development of language, including the development of the lexicon and syntactic and grammatical knowledge and skill; (b) the development of cognition and thinking, including the emergence and acquisition of cognitive skills and knowledge in various domains; (c) the development of reflective judgment, including metacognition and social understanding; and (d) the development of social skills and behavior. Behind all these phenomena are the development of context-specific but overarching principles of skill formation, such as principles of relationships, systems of relationships, and so on.

This chapter presents a dynamic systems analysis of the variables contributing to the transition to reference, integrating material from the previous chapters. Topics discussed include dynamic systems in language development, control parameters and the shift to referential language, mental representation and the other dynamic variables, production of context-limited and referential words in real time, considering neurological aspects of word knowledge, and form/meaning synergies.

This chapter addresses the question of whether dynamic systems and connectionist approaches are an alternative to good old-fashioned cognitive development (GOFCD). The chapter is organized as follows. The first section discusses what connectionism and dynamic systems bring to the study of cognitive development. The second section examines how connectionist and dynamic systems theories relate to other GOFCD theories of developmental change. The third section evaluates the contribution of connectionism and dynamic systems in more depth by examining explanations of two historically important issues in cognitive development: infants' behavior in the A-not-B task and children's solutions to the balance scale problem. Finally, the chapter considers how well connectionist and dynamic systems approaches address criticisms often leveled at other theories of cognitive development.

This chapter seeks to articulate and clarify cases of perceived differences between dynamical systems theory (DST) and the connectionist (CN) approaches that are not real, as well as cases of perceived differences that are real. It discusses the implications of efforts to integrate the two approaches for developmental science more generally. Clarifying similarities/differences between approaches offers far more that just technical clarity for co-called modeler types; it offers a vision of a new, integrative, developmental theory.

It's in the Eye of the Beholder: Spatial Language and Spatial Memory Use the Same Perceptual Reference Frames Lipinski et al.Spatial language provides an effective domain to examine the connection between non‐linguistic and linguistic systems because it is an unambiguous case of linguistic and sensori‐motor systems coming together. In the present work we use a process‐based theory of spatial working memory—the Dynamic Field Theory—to generate and test novel predictions regarding the time‐dependent link between spatial memory and spatial language. Our analysis and empirical findings suggest that focusing on the processes underlying spatial language, rather than representations per se, can produce more constrained theories of the connection between sensorimotor and linguistic systems.

This chapter lays the theoretical foundations of the analyses in this book. The book addresses two major themes. First, language does not stand alone as the crowning achievement of infancy. Rather, other equally complex achievements are ongoing and contribute to linguistic development. Second, a set of precursor achievements organized from a dynamic systems perspective can successfully predict, for individual children, the onset of referential word use. The use of dynamic systems theory to study how infants acquire language is discussed. An overview of the succeeding chapters is presented.

This chapter describes model of the development of simple analogical reasoning and shows how the model accounts for seven characteristics of children's developing abilities to reason analogically. It argues that the model's success is critically dependent upon principles of both connectionism and dynamic systems theory. Thus, the model demonstrates complementarity between the approaches.

This chapter presents an overview of a dynamic systems account of the A-not-B error in infants. It presents evidence on how the processes that give rise to perseveration in infants are also processes that, in a quite positive way, create coherence and stability. It also presents evidence on how flexibility emerges in this same system and considers the role of sensorimotor processes and implications of this work.

This chapter examines the interplay of dynamical systems and connectionism at the level of both theory and computation. It begins with a discussion of developmental mechanism focusing on two particular processes—one typically associated with connectionist approaches and one typically associated with dynamical systems. It then illustrates potential hybrid approaches with case studies from the field of language acquisition. The first—a model of speech category learning—illustrates how a dynamical systems perspective may inform a classic connectionist mechanism (i.e., statistical learning). The second—a model of early word learning—combines connectionist and dynamical systems principles. Both suggest that we can no longer treat these two paradigms as independent.

This chapter provides an optimistic forecast for the future of connectionism and dynamic systems theory (DST). In particular, it focuses on the idea that regardless of how similar or dissimilar connectionism and DST appear to be at this moment in their development, there are numerous signs that hybridization of the two approaches is not only possible, but also has begun to occur. The chapter begins by reviewing three major, crosscutting themes that are shared by connectionism and DST. It then highlights the evidence for an optimistic outlook by describing recent work in the field of adaptive behavior and robotics, which is illustrated by numerous examples of models that blend elements of connectionism and DST. Finally, it returns to the crosscutting themes and elaborates on each in light of the progress that robotics researchers have made toward a hybrid approach.

This chapter focuses on the state of research and theory concerning relations among emotion, developmental context, and memory in development, with a particular emphasis on how psychobiological processes play an integral role in these relations. Because memory is a skill relying heavily on a variety of cognitive, social, and biological factors, it posits that a dynamic systems framework is essential to understanding the development of memory for emotional and stressful experiences. The chapter begins with an overview of this theoretical framework in the context of emotional memory. It then turns to factors within the dynamic model by providing an overview of the psychophysiological systems involved in emotional memory. With this lens, memory for emotional experiences is further considered, beginning with the nature of the emotional event itself. Next, the chapter reviews developmental and individual differences related to children's processing of emotional experiences, focusing on individual differences related to social and cognitive processes and emotion regulation. The chapter concludes with applications of this model to clinical and legal domains and suggestions for new directions of future research.

This chapter focuses on the role that the body plays in the process of brain and mind formation. It begins by reviewing some theoretical concepts about embodiment and the dynamic systems approach. It then considers three examples of infant motor development that illustrate the strong coupling existing between the body and the mind in development, and that highlight the usefulness of accounting for the body and its properties when investigating a developmental question. The concluding section of this chapter extends the theme to situations that do not involve motor activities per se, to illustrate that even such activities can be embodied. The chapter shows that development is a process marked by continuous perceptual and sensorimotor experiences, which involve a brain with a body that can act and sense. It argues that those perceptual and sensorimotor experiences are crucial for brain, mind, and behavioral development, and that they create the foundation of many forms of thinking in development.

This survey provides a route map, sketching the major issues, models, concepts, and techniques. A taxonomy of model types is presented, each being examined for advantages and drawbacks as a generic form. Exogeneity and the overall model reduction framework are described. Systems are considered, and the problem of testing autoregressive errors against mis‐specification of the lag structure is resolved using the notion of common factors in lag polynomials.

This chapter draws attention to some aspects of development that are considered underrepresented in both dynamic systems theory (DST) and connectionism. The approach taken is that of developmental systems theory, which shares with DST a focus on the whole organism in its environment, and with connectionism a focus on the biological support for psychological change. It adds to those perspectives, a concern with more levels of biological analysis (including genetics), the incorporation of comparative, animal-based research, and attention to evolutionary considerations in the analysis of psychological change.

A tension has existed between connectionism and dynamic systems theory (DST), and this chapter considers why this should be the case. The chapter argues that much of the tension arises from a tenet that the two approaches share: they both rely on the explicit, quantitative instantiation of ideas in mathematical or computational models. The use of such models is responsible for much of the theoretical progress generated by connectionism and DST beyond the theories of good old-fashioned cognitive development (GOFCD). But the use of explicit, quantitative models brings with it a new set of problems. The chapter discusses several consequences of the use of such models and considers three points of apparent disagreement between connectionism and DST.

This chapter argues that connectionist and dynamic systems models complement each other and collectively move toward a unified theory of development if they subscribe to the second view of mechanism—one that treats behavior as soft assembled in the immediate context. The chapter is organized as follows. It first addresses why models aimed at reducing behavior to cognitive components cannot make clear headway. The argument is that a reduction of behavior requires human performance to be relatively context free. However, it is shown with the example of balance task performance that human performance is highly context dependent, even in the sterile laboratory context of balance experiments. The chapter then elaborates on what such context dependence could mean. The chapter reviews more pointed evidence for soft assembly and discusses why models that take soft assembly seriously—connectionist or dynamic systems—anticipate the unified theory.

This concluding chapter summarizes key themes and presents some final thoughts. This book started with the twin premises that understanding multiparty competition is a core concern for everyone interested in representative democracy and that multiparty competition should be understood as an evolving dynamic system, not a stationary state. Given these premises, it investigated the dynamics of multiparty competition using computational agent-based modeling, a new technology that is ideally suited to providing systematic answers to the types of question we want to ask. This allows the modeling of decision making by party leaders, in what is clearly an analytically intractable setting, in terms of the informal rules of thumb that might be used by real human beings, rather than the formally provable best response strategies used by traditional formal theorists. Whether people use the dynamic model of multiparty competition or some better model of this vital but complex political process, there is no doubt that the computational approach deployed in this book offers vast potential to ask and answer interesting and important questions.

In this chapter a radically different perspective to “stage theory” is taken. Hence, the difficulties inherent in defining the notions of “adolescence”, “adulthood” and, as a consequence, “transitions” are discussed; and it is argued that trying to describe human development by these vague, ill-defined concepts, or by the simple passing of time through “stages”, does not add to our understanding of what actually causes human change across the lifespan. An alternative theoretical viewpoint that seeks to analyse the processes and mechanisms underlying human transformations is offered. From a systemic perspective human development is seen as the interplay between the individual and micro-and macro-level elements. The underlying mechanisms involved in meeting normative and quasi-normative shifts do not vary between cultures and historic cohorts, though, cultural differences and their associated challenges do vary enormously.

Chapter 2 introduces the reader to theoretical perspectives which provide the framework for the book and inform all subsequent chapters. Dynamic nonlinear systems theory, based on general systems theory, suggests the continuous interactive and reciprocally influencing nature of individuals and their environments. The developmental perspective includes development from infancy through adulthood and developmental traumatology. Attachment theory is the primary interpersonal perspective of the book. The biopsychosocial perspective incorporates aspects of all of these theories and underscores the importance of considering how each individual young person is situated biologically, psychologically, and socially and where practice and policy interventions might best be made. Finally, resiliency theory assists the reader in developing a strengths-based approach to working with youth. An extended case example of a former foster youth illustrates aspects of the theories.