Human control of action in routine situations involves a flexible interplay between (a) task-dependent serial ordering constraints; (b) top-down, or intentional, control processes; and (c) bottom-up, or environmentally triggered, affordances. In addition, the interaction between these influences is modulated by learning mechanisms that, over time, appear to reduce the need for top-down control processes while still allowing those processes to intervene at any point if necessary or if desired. We present a model of the acquisition and control of goal-directed action (...) that goes beyond existing models by operationalizing an interface between two putative systems—a routine and a non-routine system—thereby demonstrating how explicitly represented goals can interact with the emergent task representations that develop through learning in the routine system. The gradual emergence of task representations offers an explanation for the transfer of control with experience from the non-routine goal-based system to the routine system. At the same time it allows action selection to be sensitive both to environmental triggers and to biasing from multiple levels within the goal system. (shrink)
Human adults appear different from other animals in their ability to form abstract mental representations that go beyond perceptual similarity. In short, they can conceptualize the world. This apparent uniqueness leads to an immediate puzzle: WHEN and HOW does this abstract system come into being? To answer this question we need to explore the origins of adult concepts, both developmentally and phylogenetically; When does the developing child acquire the ability to use abstract concepts? Does the transition occur around 2 years, (...) with the onset of symbolic representation and language? Or, is it independent of the emergence of language? When in evolutionary history did an abstract representational system emerge? Is there something unique about the human brain? How would a computational system operating on the basis of perceptual associations develop into a system operating on the basis of abstract relations? Is this ability present in other species, but masked by their inability to verbalise abstractions? Perhaps the very notion of concepts is empty and should be done away with altogether. -/- This book tackles the age-old puzzle of what might be unique about human concepts. Intuitively, we have a sense that our thoughts are somehow different from those of animals and young children such as infants. Yet, if true, this raises the question of where and how this uniqueness arises. What are the factors that have played out during the life course of the individual and over the evolution of humans that have contributed to the emergence of this apparently unique ability? This volume brings together a collection of world specialists who have grappled with these questions from different perspectives to try to resolve the issue. It includes contributions from leading psychologists, neuroscientists, child and infant specialists, and animal cognition specialists. Taken together, this story leads to the idea that there is no unique ingredient in the emergence of human concepts, but rather a powerful and potentially unique mix of biological abilities and personal and social history that has led to where the human mind now stands. A 'must-read' for students and researchers in the cognitive sciences. (shrink)
What are the processes, from conception to adulthood, that enable a single cell to grow into a sentient adult? The processes that occur along the way are so complex that any attempt to understand development necessitates a multi-disciplinary approach, integrating data from cognitive studies, computational work, and neuroimaging - an approach till now seldom taken in the study of child development. -/- Neuroconstructivism is a major new 2 volume publication that seeks to redress this balance, presenting an integrative new framework (...) for considering development. In the first volume, the authors review up-to-to date findings from neurobiology, brain imaging, child development, computer and robotic modelling to consider why children's thinking develops the way it does. They propose a new synthesis of development that is based on 5 key principles found to operate at many levels of descriptions. They use these principles to explain what causes a number of key developmental phenomena, including infants' interacting with objects, early social cognitive interactions, and the causes of dyslexia. The "neuroconstructivist" framework also shows how developmental disorders do not arise from selective damage to the normal cognitive system, but instead arise from developmental processes that operate under atypical constraints. How these principles work is illustrated in several case studies ranging from perceptual to social and reading development. Finally, the authors use neuroimaging, behavioural analyses, computational simulations and robotic models to provide a way of understanding the mechanisms and processes that cause development to occur. (shrink)
What are the processes, from conception to adulthood, that enable a single cell to grow into a sentient adult? The processes that occur along the way are so complex that any attempt to understand development necessitates a multi-disciplinary approach, integrating data from cognitive studies, computational work, and neuroimaging - an approach till now seldom taken in the study of child development. -/- Neuroconstructivism is a major new 2 volume publication that seeks to redress this balance, presenting an integrative new framework (...) for considering development. Computer and robotic models provide concrete tools for investigating the processes and mechanisms involved in learning and development. Volume 2 illustrates the principles of Neuroconstructivist development, with contributions from 9 different labs across the world. Each of the contributions illustrates how models play a central role in understanding development. The models presented include standard connectionist neural network models as well as multi-agent models. Also included are robotic models emphasizing the need to take embodiment and brain-system interactions seriously. A model of Autism and one of Specific Language Impairment also illustrate how atypical development can be understood in terms of the typical processes of development but operating under restricted conditions. This volume complements Volume 1 by providing concrete examples of how the Neuroconstructivist principles can be grounded within a diverse range of domains, thereby shaping the research agenda in those domains. (shrink)
Connectionist models aiming to reveal the mechanisms of atypical development must in their undamaged form constitute plausible models of normal development and follow a developmental trajectory that matches empirical data. Constructivist models that adapt their structure to the learning task satisfy this demand. They are therefore more informative in the study of atypical development than the static models employed by Thomas & Karmiloff-Smith (T&K-S).
A mature science strives to provide causal explanations of observed phenomena rather than focusing on taxonomic descriptions of data. A field theory model is a step towards providing a truly scientific account of development. However, the model is under-constrained in that it ignores the boundary conditions defined by the physical constraints imposed by the infant's developing brain and body.
Norman presents intriguing arguments in support of a mapping between ecological and constructivist visual cognition, on the one hand, onto the dorsal ventral dual route processing hypothesis, on the other hand. Unfortunately, his account is incompatible with developmental data on the functional emergence of the dorsal and ventral routes. We argue that it is essential for theories of adult visual cognition to take constraints from development seriously.
Missing from Quartz & Sejnowski's (Q&S's) unique and valuable effort to relate cognitive development to neural constructivism is an examination of the global emergent properties of adding new neural circuits. Such emergent properties can be studied with computational models. Modeling with generative connectionist networks shows that synaptogenic mechanisms can account for progressive increases in children's representational power.