The human brain is the first computer to which all others are compared. Yet we know painfully little about how a brain accomplishes its peculiar computations. In particular, consciousness is at once familiar and mysterious, and needs to be understood both for science and for medicine. Boldly, but gently this book introduces a reader to the neural circuitry that achieves consciousness. This amazing interconnection enables consciousness to flow like a stream, intimately relevant to the outside world; and for this to happen, fundamental cues emerge from mental images to bring forth associated recalls. Alas cues can be inconsistent, causing memory failure; fortunately a subliminal cue editor encourages remembering forgotten items. Furthermore, cues generally address several memories, forcing the brain to make a selection. This necessitates another special circuit whose purpose is subliminal editing. The simplified explanations provided in this book make it clear that neurons do far more than ordinary devices, since a single neuron is capable of remarkably dense combinational and sequential logic. Beginning with their interesting and unexpected logical behavior, the reader will genuinely enjoy Dr. Burger's synthesis of a system for biological consciousness, a system that may someday result in credible artificial consciousness.

Gain a new perspective on how the brain works and inspires new avenues for design in computer science and engineering

This unique book is the first of its kind to introduce human memory and basic cognition in terms of physical circuits, beginning with the possibilities of ferroelectric behavior of neural membranes, moving to the logical properties of neural pulses recognized as solitons, and finally exploring the architecture of cognition itself. It encourages invention via the methodical study of brain theory, including electrically reversible neurons, neural networks, associative memory systems within the brain, neural state machines within associative memory, and reversible computers in general. These models use standard analog and digital circuits that, in contrast to models that include non-physical components, may be applied directly toward the goal of constructing a machine with artificial intelligence based on patterns of the brain.

Writing from the circuits and systems perspective, the author reaches across specialized disciplines including neuroscience, psychology, and physics to achieve uncommon coverage of:

Neural membranes

Neural pulses and neural memory

Circuits and systems for memorizing and recalling

Dendritic processing and human learning

Artificial learning in artificial neural networks

The asset of reversibility in man and machine

Electrically reversible nanoprocessors

Reversible arithmetic

Hamiltonian circuit finders

Quantum versus classical

Each chapter introduces and develops new material and ends with exercises for readers to put their skills into practice. Appendices are provided for non-experts who want a quick overview of brain anatomy, brain psychology, and brain scanning. The nature of this book, with its summaries of major bodies of knowledge, makes it a most valuable reference for professionals, researchers, and students with career goals in artificial intelligence, intelligent systems, neural networks, computer architecture, and neuroscience.

A solutions manual is available for instructors; to obtain a copy please email the editorial department at [email protected].