This volume presents peer-reviewed versions of papers presented at the 14th Neural Computation and Psychology Workshop (NCPW14), which took place in July 2014 at Lancaster University, UK. The workshop draws international attendees from the cutting edge of interdisciplinary research in psychology, computational modeling, artificial intelligence and psychology, and aims to drive forward our understanding of the mechanisms underlying a range of cognitive processes.
"This volume presents peer-reviewed versions of papers presented at the 14th Neural Computation and Psychology Workshop (NCPW14), which took place in July 2014 at Lancaster University, UK. The workshop draws international attendees from the cutting edge of interdisciplinary research in psychology, computational modeling, artificial intelligence and psychology, and aims to drive forward our understanding of the mechanisms underlying a range of cognitive processes."--Publisher's website.
Introduction / Eddy J. Davelaar -- An ecology-based approach to perceptual modelling / E.L. Byrne, D.P.A Corney and R.B. Lotto -- Early development of visual abilities / Alessio Plebe -- A dynamical neural simulation of feature-based attention and binding in a recurrent model of the ventral stream / D.G. Harrison and M. De Kamps -- Model selection for eye movements : assessing the role of attentional cues in infant learning / Daniel Yurovsky [und weitere] -- The importance of low spatial frequencies for categorization of emotional facial expressions / L. Lopez [und weitere] -- Modeling speech perception with restricted Boltzmann machines / Michael Klein, Louis ten Bosch and Lou Boves -- Early language as multimodal learning / Nadja Althaus and Denis Mareschal -- From Motherese to one-word and two-word child language : a multimodal temporal connectionist model / Abel Nyamapfene -- Learning the visual word code / T. Hannagan and J. Grainger -- What are the functional units in reading? Evidence for statistical variation influencing word processing / Alastair C. Smith and Padraic Monaghan -- Testing computational accounts of response congruency in lexical decision / Sebastian Loth and Colin J. Davis -- Sentence comprehension as mental simulation : an information-theoretic analysis and a connectionist model / Stefan L. Frank -- Modelling free recall - a combined activation-buffer and distributed-context model / Anat Elhalal and Marius Usher -- Inference, ontologies and the pump of thought / Andrzej Wichert -- Modelling correlations in "response inhibition" Richard P. Cooper and Eddy J. Davelaar -- A first approach to an artificial networked cognitive control system based on the shared circuits model of sociocognitive capacities / A. Sanchez Boza and R. Haber Guerra -- Digital typology modelling of cognitive abilities / Agnes Garletti -- Using enriched semantic representations in predictions of human brain activity / Joseph P. Levy and John A. Bullinaria -- Variability in the severity of developmental disorders : a neurocomputational account of developmental regression in autism / Michael SC Thomas, Victoria CP Knowland and Annette Karmiloff-Smith -- How do we use computational models of cognitive processes? / T. Stafford -- Some issues in computational modelling; Occam's razor and Hegel' hair gel / Richard Shillcock [und weitere] -- How is hair gel quantified? / Mark A. Pitt and Jay I. Myung -- What do humanoid robots offer to experimental psychology? / Jochen J. Steil
This volume considers how children's thinking evolves during development, with a focus on the role of experience in causing change. It brings together cutting-edge research by leaders in the psychology and neurobiology of child development to examine the processes by which children learn and those that make children ready and able to learn at particular points in development. Behavioral approaches include research on the "microgenesis" of cognitive change over short time periods (e.g., several hour-long sessions) in specific task situations. Research on cognitive change over longer time scales (months and years) is also presented, as well as research that uses computational modeling and dynamical systems approaches to understand learning and development. Neural approaches include the study of how neuronal activity and connectivity change during acquisition of cognitive skills in children and adults. Other investigations consider the possible emergence of cognitive abilities through the maturation of brain structures and the effects of experience on the organization of functions in the brain. Developmental anomalies, such as autism and attention deficit disorder are also examined as windows on normal development. Four questions drive the volume: *Why do cognitive abilities emerge when they do during development? *What are the sources of developmental and individual differences, and of developmental anomalies in learning? *What happens in the brain when people learn? *How can experiences be ordered and timed to optimize learning? The answers to these questions have strong implications for how we educate children and remediate deficits that have impeded the development of thinking abilities. These implications are explored in several chapters in the volume, as well as in the commentaries by leading discussants.
Computational Models of Cognitive Processes collects refereed versions of papers presented at the 13th Neural Computation and Psychology Workshop (NCPW13) that took place July 2012, in San Sebastian (Spain). This workshop series is a well-established and unique forum that brings together researchers from such diverse disciplines as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their latest work on models of cognitive processes.
A comprehensive Introduction to the world of brain and behavior computational models This book provides a broad collection of articles covering different aspects of computational modeling efforts in psychology and neuroscience. Specifically, it discusses models that span different brain regions (hippocampus, amygdala, basal ganglia, visual cortex), different species (humans, rats, fruit flies), and different modeling methods (neural network, Bayesian, reinforcement learning, data fitting, and Hodgkin-Huxley models, among others). Computational Models of Brain and Behavior is divided into four sections: (a) Models of brain disorders; (b) Neural models of behavioral processes; (c) Models of neural processes, brain regions and neurotransmitters, and (d) Neural modeling approaches. It provides in-depth coverage of models of psychiatric disorders, including depression, posttraumatic stress disorder (PTSD), schizophrenia, and dyslexia; models of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, and epilepsy; early sensory and perceptual processes; models of olfaction; higher/systems level models and low-level models; Pavlovian and instrumental conditioning; linking information theory to neurobiology; and more. Covers computational approximations to intellectual disability in down syndrome Discusses computational models of pharmacological and immunological treatment in Alzheimer's disease Examines neural circuit models of serotonergic system (from microcircuits to cognition) Educates on information theory, memory, prediction, and timing in associative learning Computational Models of Brain and Behavior is written for advanced undergraduate, Master's and PhD-level students—as well as researchers involved in computational neuroscience modeling research.
Connectionist Models of Development is an edited collection of essays on the current work concerning connectionist or neural network models of human development. The brain comprises millions of nerve cells that share myriad connections, and this book looks at how human development in these systems is typically characterised as adaptive changes to the strengths of these connections. The traditional accounts of connectionist learning, based on adaptive changes to weighted connections, are explored alongside the dynamic accounts in which networks generate their own structures as learning proceeds. Unlike most connectionist accounts of psychological processes which deal with the fully-mature system, this text brings to the fore a discussion of developmental processes. To investigate human cognitive and perceptual development, connectionist models of learning and representation are adopted alongside various aspects of language and knowledge acquisition. There are sections on artificial intelligence and how computer programs have been designed to mimic the development processes, as well as chapters which describe what is currently known about how real brains develop. This book is a much-needed addition to the existing literature on connectionist development as it includes up-to-date examples of research on current controversies in the field as well as new features such as genetic connectionism and biological theories of the brain. It will be invaluable to academic researchers, post-graduates and undergraduates in developmental psychology and those researching connectionist/neural networks as well as those in related fields such as psycholinguistics.
This thoroughly, thoughtfully revised edition of a very successful textbook makes the principles and the details of neural network modeling accessible to cognitive scientists of all varieties as well as to others interested in these models. Research since the publication of the first edition has been systematically incorporated into a framework of proven pedagogical value. Features of the second edition include: * A new section on spatiotemporal pattern processing * Coverage of ARTMAP networks (the supervised version of adaptive resonance networks) and recurrent back-propagation networks * A vastly expanded section on models of specific brain areas, such as the cerebellum, hippocampus, basal ganglia, and visual and motor cortex * Up-to-date coverage of applications of neural networks in areas such as combinatorial optimization and knowledge representation As in the first edition, the text includes extensive introductions to neuroscience and to differential and difference equations as appendices for students without the requisite background in these areas. As graphically revealed in the flowchart in the front of the book, the text begins with simpler processes and builds up to more complex multilevel functional systems. For more information visit the author's personal Web site at www.uta.edu/psychology/faculty/levine/
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.
Connectionist Models in Cognitive Psychology is a state-of-the-art review of neural network modelling in core areas of cognitive psychology including: memory and learning, language (written and spoken), cognitive development, cognitive control, attention and action. The chapters discuss neural network models in a clear and accessible style, with an emphasis on the relationship between the models and relevant experimental data drawn from experimental psychology, neuropsychology and cognitive neuroscience. These lucid high-level contributions will serve as introductory articles for postgraduates and researchers whilst being of great use to undergraduates with an interest in the area of connectionist modelling.
