This book examines what seems to be the basic challenge in neuroscience today: understanding how experience generated by the human brain is related to the physical world we live in. The 25 short chapters present the argument and evidence that brains address this problem on a wholly trial and error basis.
The goal is to encourage neuroscientists, computer scientists, philosophers, and other interested readers to consider this concept of neural function and its implications, not least of which is the conclusion that brains don't "compute."
Autorentext
Dale Purves is the George B. Geller Professor of Neurobiology Emeritus in the Duke Institute for Brain Sciences where he remains Research Professor with additional appointments in the department of Psychology and Brain Sciences and the department of Philosophy at Duke University. After earning a B.A. from Yale, an M.D. from Harvard and additional postdoctoral training at Harvard and University College London, he joined the faculty at Washington University School of Medicine in 1973. In 1990 he became the founding chair of the Department of Neurobiology at Duke Medical Center and was subsequently Director of Duke's Center for Cognitive Neuroscience. He also served as the Director of the Neuroscience and Behavioral Disorders Program at the Duke-NUS Graduate Medical School in Singapore .
Best known for his work on neural development and synaptic plasticity, Purves' research during the last 20 years has sought to explain visual perception and auditory perception in the context of music. He is a member of the National Academy of Sciences, the National Academy of Medicine, a fellow of the American Academy of Arts and Sciences and is the author, and co-author or editor of 18 previous books on neuroscience.Inhalt
Preface
PART I. TWO REALITIES
Chapter 1. Solving Problems
Chapter 2. Objective and Subjective Reality
PART II. Computation
Chapter 3. Algorithms
Chapter 4. Coding for Computers
PART III. ARTIFICIAL NEURAL NETWORKS
Chapter 5. Neural Networks
Chapter 6. The Resurrection of Neural Networks
Chapter 7. Reinforcement Learning
Part IV. perception
Chapter 8. What We Perceive
Chapter 9. Lines and Intervals
Chapter 10. Angles
Chapter 11. Lightness and Darkness
Chapter 12. Empirical Ranking
Chapter 13. Color
Chapter 14. Colorimetry
Chapter 15. Motion Speed
Chapter 16. Motion Direction
Chapter 17. Size
Chapter 18. Stereopsis
PART V. Linking OBJECTIVE AND SUBJECTIVE
Chapter 19. Stimuli and Behavior
Chapter 20. Associations
Chapter 21. Mechanisms
Chapter 22. Reflexes
PART VI. THEORIES
Chapter 23. Feature Detection
Chapter 24. Statistical Inference
Chapter 25. Information Theory
PART VII. SELF AWARENESS
Chapter 26. Awareness
Chapter 27. Summing Up