Detection of Developmental Transitions

British Journal of Developmental Psychology, 1998

Catastrophe theory can be very useful in research concerning developmental transitions. It provides a number of canonical transition models as well as criteria which can be used for the detection of transitions in experimental research. In this contribution the relevance of using catastrophe theory in cognitive developmental research is discussed. In particular, emphasis is placed on the detection criteria and their operationalizations in conservation research, as well as to fitting techniques for canonical transition models with respect to their applicability and robustness.

British Journal of Developmental Psychology, 1998

Structural approaches to development, such as Piaget's stage theory, have proved to be problematic in dealing with developmental transitions. More promising in this respect are models of qualitative change that address macroscopical phase shifts in non-linear dynamical systems that arise from quantitative changes at the microscopical level. In this introductory paper, we attempt to clarify the meanings of some of the core terms used in these models so as to set the scene for the subsequent contributions. W e stress the relevance of recent advances in catastrophe theory for detecting developmental transitions and suggest that the concept of self-organization as formulated in irreversible thermodynamics provides a framework for explaining them. As yet, there is a lack of convincing evidence that transitions of interest to developmental psychologists comply with principles of self-organization that have become well established for time-evolving systems in other disciplines such as chemistry and biology. Demonstrations of self-organization in psychologically relevant simulation models are a first step in attaining such evidence. In this special issue, we concentrate primarily on a common approach to the detection of transitions across a number of domains of development. However, in doing so illustrations are given of the ways in which the hypothesis of self-organization can be used to account for the mechanisms of developmental transitions.

Springer eBooks, 2014

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Human Development

At the end of the 20th century, as new tools and techniques from the interdisciplinary field of nonlinear dynamics began enjoying increased application to the study of development, interest in dynamics flourished in the developmental sciences. In the eyes of many prominent dynamics thinkers of the time, these new dynamics approaches-by virtue of their grounding in time and variability-not only established a thoroughgoing process orientation to development but also stood in marked opposition to the structural, or organizational, focus that had marked classic organicist and systems treatments of development from earlier in the century. Treatments of developmental dynamics today, however, are embarking on exciting new ways to integrate the organizational focus of classic systems accounts with modern principles of nonlinear dynamics. As a consequence, today's dynamics orientations are taking seriously the explanatory significance of phenomena like purposiveness, end-directedness, normativity, and subjectivity that characterize organisms as unique levels of process organization. Many challenges lie ahead for fully realizing such an integration, and we highlight two noteworthy conceptual issues that today's treatments need to confront: (1) the notion of abilities or powers as potentials for action and what it means for "potential" to explain action; and (2) the notions of real time change, developmental time change, and what it means for these different timescales to interrelate.

The model of hierarchical complexity (mhc) is known to have 16 orders so far. However, applying the model to explain the development of operant conditioning (original order 2) from respondent conditioning (original order 1) in non-human animals has led to the recent discovery of a new stage. Actions that make up respondent conditioning are more hierarchically complex than habituation, sensitization, and other simple actions or behavioral tendencies that were also included in original order 1. Thus, the original order 1 has now been separated into the new automatic order 1 and the new sensory or motor order 2. All the orders above the original order 1 also had their numbers incremented by one. Thus, there are now 17 orders of hierarchical complexity. This paper describes this new sequence of orders at the lowest end of the model.

Human Development, 1974

The logic of set theory is applied to the problem of infrastructure and transition in developmental analysis. The analysis necessitates the decomposition of stages into components. The decomposition generates sets within sets, and from a sequential perspective, progressions within progressions. The relation of lower to higher, and precursor to successor items varies from the trivial to the rigorous. In a trivial analysis, a precursor is neither necessary nor sufficient for a successor; in a rigorous analysis, a precursor is necessary and sufficient. Infrastructure and transition are interdependent. When components are common to successive stages, stages are transformed or correlatively transformed; when components are discrete, stages are substituted, added, or deleted; and when some components are common and some discrete, stages are hybrid. Any transformation or correlative transformation implies a correspondence, integration, or differentiation with parallelism, subordination, or emergence. Any substitution, addition, or deletion implies a coincidence, augmentation, or reduction with coplanarity, expansion, or contraction. The implications of this analysis are discussed in relation to developmental theory and theory evaluation.

New Directions for Child and Adolescent Development, 1981

Developmental sequences are an important tool for analyring the contmt and process uf dcnelopmmt.

This article discusses some of the ways in which dynamic systems approaches have been applied to developmental science. Dynamic systems thinking suggests that (a) there is always change within stability at the level of real-time (microscopic) behavior, and (b) microlevel change provides the seeds for developmental (macroscopic) change. It is only possible to study these propositions using microgenetic designs, case-based studies of change using frequent observations across development. Normal parent-infant relationships smooth out otherwise abrupt developmental transitions using a bridging process. The absence of developmental bridging may reflect problematic or even traumatic growth patterns, suggesting that bridging, a feature of a developmental trajectory, may serve as a diagnostic individual differences variable.

Cognition, 2006

Biological contributions to cognitive development continue to be conceived predominantly along deterministic lines, with proponents of diVerent positions arguing about the preponderance of gene-based versus experience-based inXuences that organize brain circuits irreversibly during prenatal or early postnatal life, and evolutionary inXuences acting through selection on small numbers of genes. This article discusses evolutionary, mechanistic and probabilistic aspects of developmental processes that cognitive scientists need to better integrate. Developmental processes inseparably fuse experience-dependent and experience-independent components, have important stochastic contributions, and exhibit a greater degree of mechanistic continuity between developing and adult nervous systems than previously thought. Their balanced integration leads to new models for "critical or sensitive" period phenomena and behavioral biases. A general understanding of behavioral development-cognitive developmental biology-will require better coordination between comparative animal and human developmental research programs.

Child Development, 2000

The field of developmental psychology is part of a continuum of disciplines, from cell biology to cultural anthropology, that are focused on understanding developing and potentially evolving phenotypes; the reciprocal interactions between genetics and experiences produce variation in developing phenotypes and this variation is the grist for evolutionary selection. The articles in this issue provide cutting edge and multidisciplinary analyses of developing and potentially evolving phenotypes in areas that are of central interest to developmental scientists, including mother-infant attachments, stress-responses in children, social cognition, and life span development. The articles and other recent works signal the reemergence of developmental psychology as an evolutionarily-informed, multidisciplinary field. In this view, it is not about nature versus nurture or biology versus psychology, it is about tackling difficult problems at multiple levels of analysis, each of which has something to contribute and none of which is sufficient in and of itself.