This book offers the first detailed, comprehensible scientific presentation of Confabulation Theory, addressing a pressing scientific question: How does brain information processing, or cognition, work? With only elementary mathematics as a prerequisite, this book will prove accessible to technologists, scientists, and the educated public.

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).

Confabulation theory offers the first complete detailed explanation of the mechanism of cognition, i.e., thinking, an essential information processing capability of all enbrained Earth animals (bees, octopi, trout, ravens, humans, et al.). Concentrating on the human case, this book offers an hypothesis for the neuronal implementation of cognition, and explores the mathematics and methods of application of its mechanism. Thinking turns out to be starkly alien in comparison with all known technological approaches to information processing. While probably not yet scientifically testable, confabulation theory seems consistent with the facts of neuroscience. Beyond science, any complete detailed explanation of cognition can be investigated by applying it technologically. Multiple experiments of this nature are described in this book in complete detail. The results suggest that confabulation theory can provide the universal platform for building intelligent machines. In short, this book explains how thinking works and establishes the foundation for building machines that think.

Because of the theory s implications for philosophy, education, medicine, anthropology and social science, this book will also be of interest to scientists in those domains."

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.