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We here examine the relationship between similarity and inductive inference, as well as the relationship between those types of judgments and neural representations of knowledge. We first present a model of category-based induction that estimates the probabilities of conditional sentences from the similarities and probabilities that govern their constituents (Chapter 2). We then present data from a published experiment showing that similarity information is retrievable from patterns of neural activity collected when participants are simply judging the category membership of images: Simple vectorwise metrics and measures derived from machine learning can extract similarities from the lateral occipital cortex that correlate strongly with similarity judgment (Chapter 3). Finally, we present results using new fMRI data that replicate our ability to extract similarity information from lateral occipital as well as posterior temporal cortices (BA 37) and show that those similarities, when supplied to our model, yield excellent predictions of probability rated for conditional sentences. Information-based analyses pick out regions strongly overlapping the lateral occipital and posterior temporal cortices as highly informative about conditional probability (Chapter 4). Curiously, however, rated similarity does not predict conditional probability when supplied to our model; this matter is discussed in Chapters 4 and 5. Overall, our results support the storage of semantic knowledge in distributed patterns of activity over sensory areas and the usefulness of similarity derived from simple operations on that knowledge as an input to inductive judgment.
Category-specific knowledge disorders are among the most intriguing and perplexing syndromes in cognitive neuropsychology. The past decade has witnessed increased interest in these disorders, due largely to a heightened appreciation of the profound implications that an understanding of concept representation has for such diverse topics as object recognition, the organisation of the lexicon, and storage of long-term memories. Until recently, information about the representation of concepts was limited to findings from patients with brain injury and disease. This state of affairs has now changed with the advent and wide-spread availability of functional imaging for studying cognition in the normal human brain. The purpose of this special issue is to provide a forum for new findings and critical, theoretical analyses of existing data from patient and functional brain imaging studies. The contributions, all from major investigators in the field, range from studies of specific object categories such as animals, tools, fruit and vegetables, and faces, to the more general domains of number processing, social interaction, and mechanical knowledge. A unifying theme of these papers is the extent to which the findings can be best understood within the context of models that posit an innate, domain-specific organisation, those that appeal to an organisation by sensory- and motor-based features and properties, and those that propose an undifferentiated, distributed neural organisation.
Fully revised and updated, this second edition updates Novak’s theory for meaningful learning and autonomous knowledge-building along with tools to make it operational – that is, concept maps, created with the use of CMapTools and the V diagram. It is essential reading for educators at all levels and corporate managers who seek to enhance worker productivity.
Education for the Human Brain: A Road Map for Natural Learning in Schools is an all inclusive book on understanding and implementing a natural and brain-compatible instructional strategy from early childhood to adult learners. It informs the reader on the science, motivates the reader with the evidence and provides a road map for implementing, making this book unlike any other available. No matter what role you play in education, Education for the Human Brain can help students within your reach learn faster and remember more all while having fun learning the way that is natural!
A mechanistic theory of the representation and use of semantic knowledge that uses distributed connectionist networks as a starting point for a psychological theory of semantic cognition.
Featuring new research and examples, this practical resource focuses on brainstorming webs, graphic organizers, and concept maps to improve instruction and enhance students' cognitive development.
Brain mapping has forever altered and extended our understanding of the systems of the brain. The integrative capacity of brain maps enables the inclusion of a diverse array of observations and experimental results. Maps are used to describe brain structure, function, and connectivity, to catalog the ever-expanding knowledge base of human and animal nervous systems, to compare healthy tissue with diseased tissue, and to show detailed subsystems and circuits. This 3-Volume Set includes: Brain Mapping: The Systems, Brain Mapping: The Disorders, and Brain Mapping: The Methods, Second Edition. * Three superb volumes providing coverage of all aspects of brain mapping * Up to the minute coverage of key topics * Invaluable to all students new to the subject, professionals using brain imaging techniques and neurosurgeons * All three volumes are available at an outstanding discounted price
The Knowledge Medium: Designing Effective Computer-Based Learning Environments suggests that the understanding of computers as a medium may be a key to reenvisioning educational technology. Because the subject is interdisciplinary, combining science with the humanities, the theoretical discussion draws from a broad range of disciplines: psychology, educational theory, film criticism, and more.
The ability to manage knowledge is relevant for millions of small and medium sized enterprises (SMEs) that operate in high-tech environments. They strongly depend on external knowledge about customers, technologies, and competitors because, as opposed to large companies, they have limited internal knowledge resources and little power to control their business environments. Present KM literature, however, mainly focuses on large companies and therefore does not explain, how SMEs, for example, can successfully apply groupware, data mining, semantic networks, and knowledge maps. This book addresses this problem by introducing the concept of knowledge integration (KI) that places emphasis on the identification, acquisition and use of external knowledge. Drawing from this theoretical basis, the book presents concepts and instruments specifically designed for SMEs, as well as examples of their implementation and use in practice.
The "sequel" to "Brain Mapping: The Methods", covers the utlization of methods for the study of brain structure and function. Organized by systems, it presents information on the normal as well as the diseased brain. It integrates the various methodologies with appropriate usage.