Neurocomputational Models Of Cognitive Development And Processing

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

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.

This book constitutes the proceedings of the )th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2020, held in Freiburg, Germany, in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 32 full and 7 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They deal with research on novel life-like technologies inspired by the scientific investigation of biological systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems.

Although computational modeling is now a widespread technique in cognitive science and in psychology, relatively little work in developmental psychology has used this technique. The approach is not entirely new, as a small group of researchers has attempted to create computational accounts of cognitive developmental phenomena since the inception of the technique. It should seem obvious that transition mechanisms -- or how the system progresses from one level of competence to the next -- ought to be the central question for investigation in cognitive developmental psychology. Yet, if one scans the literature of modern developmental studies, it appears that the question has been all but ignored. However, only recently have advances in computational technology enabled the researcher access to fully self-modifying computer languages capable of simulating cognitive change. By the beginning of the 1990s, increasing numbers of researchers in the cognitive sciences were of the opinion that the tools of mathematical modeling and computer simulation make theorizing about transition mechanisms both practical and beneficial -- by using both traditional symbolic computational systems and parallel distributed processing or connectionist approaches. Computational models make it possible to define the processes that lead to a system being transformed under environmental influence from one level of competence observed in children to the next most sophisticated level. By coding computational models into simulations of actual cognitive change, they become tangible entities that are accessible to systematic study. Unfortunately, little of what has been produced has been published in journals or books where many professionals would easily find them. Feeling that developmental psychologists should be exposed to this relatively new approach, a symposium was organized at the biennial meeting of the Society for Research in Child Development. The "cost of entry" was that speakers had to have a running computational model of a documented cognitive transition. Inspired by that conference, this volume is the first collection where each content chapter presents a fully implemented, self-modifying simulation of some aspect of cognitive development. Previous collections have tended to discuss general approaches -- less than fully implemented models -- or non self-modifying models. Along with introductory and review chapters, this volume presents a set of truly "developmental" computational models -- a collection that can inform the interested researcher as well as form the basis for graduate-level courses.

Perceptual and Cognitive Development illustrates how the developmental approach yields fundamental contributions to our understanding of perception and cognition as a whole. The book discusses how to relate developmental, comparative, and neurological considerations to early learning and development, and it presents fundamental problems in cognition and language, such as the acquisition of a coherent, organized, and shared understanding of concepts and language. Discussions of learning, memory, attention, and problem solving are embedded within specific accounts of the neurological status of developing minds and the nature of knowledge. Research advances and theoretical reorientations are updated in the Second Edition; the revision focuses more attention on the cognitive and biological sciences and neuroscience Illustrates how the developmental approach can yield fundamental contributions to our understanding of perception and cognition as a whole Discussions of learning, memory, and attention permeate individual chapters

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.