Neural Machines A Defense Of Non Representationalism In Cognitive Neuroscience

In this book, Matej Kohar demonstrates how the new mechanistic account of explanation can be used to support a non-representationalist view of explanations in cognitive neuroscience, and therefore can bring new conceptual tools to the non-representationalist arsenal. Kohar focuses on the explanatory relevance of representational content in constitutive mechanistic explanations typical in cognitive neuroscience. The work significantly contributes to two areas of literature: 1) the debate between representationalism and non-representationalism, and 2) the literature on mechanistic explanation. Kohar begins with an introduction to the mechanistic theory of explanation, focusing on the analysis of mechanistic constitution as the basis of explanatory relevance in constitutive mechanistic explanation. He argues that any viable analysis of representational contents implies that content is not constitutively relevant to cognitive phenomena. The author also addresses objections against his argument and concludes with an examination of the consequences of his account for both traditional cognitive neuroscience and non-representationalist alternatives. This book is of interest to readers in philosophy of mind, cognitive science and neuroscience.

In this book, Matej Kohar demonstrates how the new mechanistic account of explanation can be used to support a non-representationalist view of explanations in cognitive neuroscience, and therefore can bring new conceptual tools to the non-representationalist arsenal. Kohar focuses on the explanatory relevance of representational content in constitutive mechanistic explanations typical in cognitive neuroscience. The work significantly contributes to two areas of literature: 1) the debate between representationalism and non-representationalism, and 2) the literature on mechanistic explanation. Kohar begins with an introduction to the mechanistic theory of explanation, focusing on the analysis of mechanistic constitution as the basis of explanatory relevance in constitutive mechanistic explanation. He argues that any viable analysis of representational contents implies that content is not constitutively relevant to cognitive phenomena. The author also addresses objections against his argument and concludes with an examination of the consequences of his account for both traditional cognitive neuroscience and non-representationalist alternatives. This book is of interest to readers in philosophy of mind, cognitive science and neuroscience.

Experimental evidence in humans and other mammalians indicates that complex neurodynamics is crucial for the emergence of higher-level intelligence. Dynamical neural systems with encoding in limit cycle and non-convergent attractors have gained increasing popularity in the past decade. The role of synchronization, desynchronization, and intermittent synchronization on cognition has been studied extensively by various authors, in particular by authors contributing to the present volume. This book addresses dynamical aspects of brain functions and cognition.

Neuroscience Without Representations: Building a Brain-in-a-World View describes a non-representational characterization of the brain that also provides an accounting on how humans can rely on symbolic systems and its conditions of application to deal with the representational requirements of human knowledge. Applying an evolutionary perspective to cognition, as well as assuming certain tenets from what is known as “4E cognition (embodied, embedded, extended, and enactive cognition theories), this volume presents arguments to support a non-representational view of the brain while also outlining how non-representational brains can nevertheless be representationally knowledgeable. As both views in isolation have limitations, Dr. Vilarroya takes these ideas in a combined approach that is supported upon detailed analyses of compelling recent studies. Further, this presents a detailed guide on how to implement the alternative notion of neural representation in a research plan. Readers will gain a better understanding of the centrality of the notion of representation in neuroscientific theories and what it means for a brain to represent something, what makes a neural activity a representation, and what is represented. Presents original arguments to support a non-representational view of the brain and outlines how non-representational brains can also be representationally knowledgeable Describes the basics of an alternative to the notion of neural representation Details the reasons underlying the unsuitability of notion of neural representation to address the brain as a cognitive organ Offers detailed analyses of relevant studies from a variety of fields, including cognitive neuroscience, evolutionary biology, behavioral sciences and biological anthropology Provides details to help guide design, implementation and interpretation of empirical studies in this field

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.

This second edition presents the enormous progress made in recent years in the many subfields related to the two great questions : how does the brain work? and, How can we build intelligent machines? This second edition greatly increases the coverage of models of fundamental neurobiology, cognitive neuroscience, and neural network approaches to language. (Midwest).

1. Introdudion This volume collects together the refereed versions of 25 papers presented at the 5th Neural Computation and Psychology Workshop (NCPW5), held at the University of Birmingham from the 8th until the lOth of September 1998. The NCPW is a well-established, lively forum, which brings together researchers from a range of disciplines (artificial intelligence, mathematics, cognitive science, computer science, neurobiology, philosophy and psychology), all of whom are interested in the application of neurally-inspired (connectionist) models to topics in psychology. The theme of the 5th workshop in the series was Connectionist models in cognitive neuroscience', and the workshop aimed to bring together papers focused on the inter-relations between functional (psychological) accounts of cognition and neural accounts of underlying brain processes, linked by connectionist models. From the very beginnings of modern psychology, with the work of William James and his contemporaries, researchers have believed it important to relate behavioural analyses to neurological underpinnings. However, with the advent of connectionist modelling, where models are at least inspired by neuronal processes, this enterprise has received a new boost. With this volume, we hope that this volume adds one further mosaic stone to this ambitious objective, of unifying functional and neuronal accounts of performance.

The development of cognitive science is one of the most remarkable and fascinating intellectual achievements of the modern era. It brings together psychology, neuroscience, artificial intelligence, computing, philosophy, linguistics, and anthropology in the project of understanding the mind by modelling its workings. Oxford University Press now presents a masterful history of cognitive science, told by one of its most eminent practitioners.