Synopses & Reviews
Understanding how the human brain represents, stores, and processes information is one of the greatest unsolved mysteries of science today. The cerebral cortex is the seat of most of the mental capabilities that distinguish humans from other animals and, once understood, it will almost certainly lead to a better knowledge of other brain nuclei. Although neuroscience research has been underway for 150 years, very little progress has been made. What is needed is a key concept that will trigger a full understanding of existing information, and will also help to identify future directions for research. This book aims to help identify this key concept. Including contributions from leading experts in the field, it provides an overview of different conceptual frameworks that indicate how some pieces of the neuroscience puzzle fit together. It offers a representative selection of current ideas, concepts, analyses, calculations and computer experiments, and also looks at important advances such as the application of new modeling methodologies. Computational Models for Neuroscience will be essential reading for anyone who needs to keep up-to-date with the latest ideas in computational neuroscience, machine intelligence, and intelligent systems. It will also be useful background reading for advanced undergraduates and postgraduates taking courses in neuroscience and psychology.
Synopsis
Formal study of neuroscience (broadly defined) has been underway for millennia. For example, writing 2,350 years ago, Aristotle asserted that association - of which he defined three specific varieties - lies at the center of human cognition. Over the past two centuries, the simultaneous rapid advancements of technology and (conse- quently) per capita economic output have fueled an exponentially increasing effort in neuroscience research. Today, thanks to the accumulated efforts of hundreds of thousands of scientists, we possess an enormous body of knowledge about the mind and brain. Unfortunately, much of this knowledge is in the form of isolated factoids. In terms of "big picture" understanding, surprisingly little progress has been made since Aristotle. In some arenas we have probably suffered negative progress because certain neuroscience and neurophilosophy precepts have clouded our self-knowledge; causing us to become largely oblivious to some of the most profound and fundamental aspects of our nature (such as the highly distinctive propensity of all higher mammals to automatically seg- ment all aspects of the world into distinct holistic objects and the massive reorganiza- tion of large portions of our brains that ensues when we encounter completely new environments and life situations). At this epoch, neuroscience is like a huge collection of small, jagged, jigsaw puz- zle pieces piled in a mound in a large warehouse (with neuroscientists going in and tossing more pieces onto the mound every month).
Synopsis
The cerebral cortex is the area of the brain where almost all of the mental capabilities that distinguish humans from other animals are based. Understanding how it works is vital to the progress in many areas of medicine and science, including the development of more efficient and flexible neural networks. Although extensive research has been carried out over the last 150 years, very little real progress has been made. This book provides a unique overview of work by key researchers, and shows how current research can be used to develop and improve computational models for neural networks.
Table of Contents
List of Contributors.- The NeuroInteractive Paradigm: Dynamical Mechanics and the Emergence of Higher Cortical Function.- The Cortical Pyramidal Cell as a Set of Interacting Error Backpropagating Dendrites: Mechanism for Discovering Nature's Order.- Performance of Intelligence Systems Governed by Internally Generated Goals.- A Theory of Thalamocortex.- Elementary Principles of Non-Linear Synaptic Transmission.- The Development of Cortical Models to Enable Neural-Based Cognitive Architectures.- The Behaving Human Neocortex as a Dynamic Network of Networks.- Towards Global Principles of Brain Processing.- The Neural Networks for Language in the Brain: Creating LAD.- Cortical Belief Networks Index.