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Biomedical subjects

Yuko Munakata

Publications and source records attributed to Yuko Munakata.

10 recordsLinked to original sources
PubMed2005

Processes of change in brain and cognitive development.

We review recent advances in the understanding of the mechanisms of change that underlie cognitive development. We begin by describing error-driven, self-organizing and constructivist learning systems. These powerful mechanisms can be constrained by intrinsic factors, other brain systems and/or the physical and social environment of the developing child. The results of constrained learning are representations that themselves are transformed during development. One type of transformation involves the increasing specialization and localization of representations, resulting in a neurocognitive system with more dissociated streams of processing with complementary computational functions. In human development, integration between such streams of processing might occur through the mediation of language.

Adolescent↗
PubMed2005

What's the difference? Contrasting modular and neural network approaches to understanding developmental variability.

Understanding why development differs across individuals is an important challenge for developmental theory. This paper evaluates two approaches to developmental variability observed in domains such as language processing and across populations such as typically developing children, children with developmental disorders, and typical adults. Modular accounts attribute developmental variability to delay, damage, or dysfunction in discrete underlying structures. Neural network approaches attribute developmental variability to emergent effects of graded variations in an interactive, developing system. The authors conclude that neural network approaches offer more formal and parsimonious accounts of the nature and sources of developmental variability.

Child↗
PubMed2005

Common mechanisms for working memory and attention: the case of perseveration with visible solutions.

Everyone perseverates at one time or another, repeating previous behaviors when they are no longer appropriate. Such perseveration often occurs in situations with working memory demands, and the ability to overcome perseveration has been linked to brain regions critical for working memory. Many theories thus explain perseveration in terms of working memory deficits. However, perseveration also occurs in situations without apparent working memory demands, in which the visible environment specifies appropriate behavior. Such findings appear to challenge working memory accounts of perseveration. To evaluate this challenge, a neural network model of a working memory account of perseveration was tested on tasks with visible solutions. With advances in the mechanisms that support working memory, networks became increasingly able to attend to relevant information in the environment. These developments led to improvements in performance on tasks with visible solutions, paralleling the developmental progression observed in infants. The simulations demonstrate how mechanisms of working memory can subserve perseveration and success on tasks with and without obvious memory demands. In both types of tasks, controlled processing occurs through the activation of task-relevant representations, which provide top-down biasing of other processing pathways. More generally, the simulations demonstrate how common mechanisms can support working memory and attention.

Age Factors↗
PubMed2004

Developmental cognitive neuroscience: progress and potential.

Developmental cognitive neuroscience is an evolving field that investigates the relations between neural and cognitive development. Lying at the intersection of diverse disciplines, work in this area promises to shed light on classic developmental questions, mechanisms subserving developmental change, diagnosis and treatment of developmental disorders, and cognitive and neuroscientific topics traditionally considered outside the domain of development. Fundamental questions include: What are the interrelations between developmental changes in the brain (e.g. in connectivity, chemistry, morphology) and developmental changes in children's behavior and cognitive abilities (e.g. representational complexity, ability to sustain selective attention, speed of processing)? Why, and how, is learning enhanced during certain periods in development? How is our knowledge organized, and how does this change with development? We discuss preliminary investigations of such questions and directions for future work.

Aptitude↗
PubMed2004

Hebbian learning and development.

Hebbian learning is a biologically plausible and ecologically valid learning mechanism. In Hebbian learning, 'units that fire together, wire together'. Such learning may occur at the neural level in terms of long-term potentiation (LTP) and long-term depression (LTD). Many features of Hebbian learning are relevant to developmental theorizing, including its self-organizing nature and its ability to extract statistical regularities from the environment. Hebbian learning mechanisms may also play an important role in critical periods during development, and in a number of other developmental phenomena.

Animals↗
PubMed2003

Reasoning about a hidden object after a delay: evidence for robust representations in 5-month-old infants.

The present research examined two alternative interpretations of violation-of-expectation findings that young infants can represent hidden objects. One interpretation is that, when watching an event in which an object becomes hidden behind another object, infants form a prediction about the event's outcome while both objects are still visible, and then check whether this prediction was accurate. The other interpretation is that infants' initial representations of hidden objects are weak and short-lived and as such sufficient for success in most violation-of-expectation tasks (as objects are typically hidden for only a few seconds at a time), but not more challenging tasks. Five-month-old infants succeeded in reasoning about the interaction of a visible and a hidden object even though (1) the two objects were never simultaneously visible, and (2) a 3- or 4-min delay preceded the test trials. These results provide evidence for robust representations of hidden objects in young infants.

Child Development↗
PubMed2002

Converging methods in developmental science: an introduction.

This special issue of Developmental Psychobiology reflects a number of recent advances in the field of developmental neuroscience. The most evident are methodological advances in noninvasive neuroimaging such as those described in a parallel special issue of Developmental Science, Volume 5, 2002. While advances in imaging methods offer a new era in developmental research, other methods (e.g., animal, computational, lesion, and genetic) remain essential in constraining and informing theories of brain and behavioral development. The papers in this issue highlight the importance of a converging methods approach to the study of developmental science and illustrate how a variety of available tools allow insights into both new and classic developmental questions.

Developmental Biology↗
PubMed2002

Active versus latent representations: a neural network model of perseveration, dissociation, and decalage.

Children of different ages often perseverate, repeating previous behaviors when they are no longer appropriate, despite appearing to know what they should be doing. Using neural network models, we explore an account of these phenomena based on a distinction between active memory (subserved by the prefrontal cortex) and latent memory (subserved by posterior cortex). The models demonstrate how (a) perseveration occurs when an active memory of currently relevant knowledge is insufficiently strong to overcome a latent bias established by previous experience, (b) apparent dissociations between children's knowledge and action may reflect differences in the amount of conflict between active and latent memories that children need to resolve in the tasks, and (c) differences in when children master formally similar tasks (decalage) may result from differences in the strength of children's initial biases. The models help to clarify how prefrontal development may lead to advances in flexible thinking.

Child↗
PubMed2002

Rich interpretation vs. deflationary accounts in cognitive development: the case of means-end skills in 7-month-old infants.

Seven-month-old infants appear to learn means-end skills, such as pushing a button to retrieve a distant toy (Psychological Review 104 (1997) 686). The present studies tested whether such apparent means-end behaviors are genuine, or simply the repetition of trained behaviors under conditions of greatest arousal, as suggested by a dynamic systems reinterpretation. When infants were trained to repeat behaviors that did not serve as means to retrieving toys (pushing a button to light a set of distant lights), their button-pushing differed significantly from infants for whom button-pushing served as a means for retrieving toys. Further, infants demonstrated means-end skills with behaviors that they had not been trained to repeat. Implications for early means-end abilities and for debates surrounding the interpretation of infant behavior are discussed.

Age Factors↗