Dynamical Models In Neurocognitive Psychology
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Dynamical Models In Neurocognitive Psychology
The development of cognitive models is a key step in the challenging research program to advance our understanding of human cognition and behavior. Dynamical models represent a general and flexible approach to cognitive modeling. This introduction focuses on applications of stochastic processes and dynamical systems to model cognition. The dynamical approach is particularly useful to emphasize the strong link between experimental research (and its paradigms), data analysis, and mathematical models including their computer implementation for numerical simulation. Most of specific examples are from the domain of eye movement research, with concepts being applicable to a broad range of problems in cognitive modeling. The textbook aims at the graduate and/or advanced undergraduate level for students in Cognitive Science and related disciplines such as Psychology and Computer Science. Joint introduction of the theory of cognitive processes and mathematical models, their underlying mathematical concepts, numerical simulation, and analysis; The focus on eye movements provide a theoretically coherent, but very general application area; Computer code in R Programming Language for Statistical Computing is available for all examples, figures, and solutions to exercises.
Dynamic Cognitive Processes
Author: Nobuo Ohta
language: en
Publisher: Springer Science & Business Media
Release Date: 2005-04-04
The conference from which this book derives took place in Tsukuba, Japan in March 2004. The fifth in a continuing series of conferences, this one was organized to examine dynamic processes in "lower order" cognition from perception to attention to memory, considering both the behavioral and the neural levels. We were fortunate to attract a terrific group of con tributors representing five countries, which resulted in an exciting confer ence and, as the reader will quickly discover, an excellent set of chapters. In Chapter 1, we will provide a sketchy "road map" to these chapters, elu cidating some of the themes that emerged at the conference. The conference itself was wonderful. We very much enjoyed the vari ety of viewpoints and issues that we all had the opportunity to grapple with. There were lively and spirited exchanges, and many chances to talk to each other about exciting new research, precisely what a good confer ence should promote. We hope that the readers of this book will have the same experience—moving from careful experimental designs in the cogni tive laboratory to neural mechanisms measured by new technologies, from the laboratory to the emergency room, from perceptual learning to changes in memory over decades, all the while squarely focusing on how best to explain cognition, not simply to measure it. Ultimately, the goal of science is, of course, explanation. We also hope that the reader will come away absolutely convinced that cognition is a thoroughly dynamic, interactive system.
Neurocognitive Mechanisms
Author: Gualtiero Piccinini
language: en
Publisher: Oxford University Press
Release Date: 2020-11-12
In Neurocognitive Mechanisms Gualtiero Piccinini presents the most systematic, rigorous, and comprehensive philosophical defence to date of the computational theory of cognition. His view posits that cognition involves neural computation within multilevel neurocognitive mechanisms, and includes novel ideas about ontology, functions, neural representation, neural computation, and consciousness. He begins by defending an ontologically egalitarian account of composition and realization, according to which all levels are equally real. He then explicates multiple realizability and mechanisms within this ontologically egalitarian framework, defends a goal-contribution account of teleological functions, and defends a mechanistic version of functionalism. This provides the foundation for a mechanistic account of computation, which in turn clarifies the ways in which the computational theory of cognition is a multilevel mechanistic theory supported by contemporary cognitive neuroscience. Piccinini argues that cognition is computational at least in a generic sense. He defends the computational theory of cognition from standard objections, yet also rebuts putative a priori arguments. He contends that the typical vehicles of neural computations are representations, and that, contrary to the received view, the representations posited by the computational theory of cognition are observable and manipulatable in the laboratory. He also contends that neural computations are neither digital nor analog; instead, neural computations are sui generis. He concludes by investigating the relation between computation and consciousness, suggesting that consciousness may be a functional phenomenon without being computational in nature. This book will be of interest to philosophers of cognitive science as well as neuroscientists.