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Neurophysiology has told us a lot about how neurons work; neural network theory is about how neurons work "together" to process information. In this highly readable book, Manfred Spitzer provides a basic, nonmathematical introduction to neural networks and their clinical applications. Part I explains the fundamental theory of neural networks and how neural network models work. Part II covers the principles of network functioning and how computer simulations of neural networks have profound consequences for our understanding of how the brain works. Part III covers applications of network models (e.g., to knowledge representation, language, and mental disorders such as schizophrenia and Alzheimer's disease) that shed new light on normal and abnormal states of mind. Finally, Spitzer concludes with his thoughts on the ramifications of neural networks for the understanding of neuropsychology and human nature.
Seductive on-screen views of brain activity open up a closed realm by rendering the mind visible. A new enlightenment beckons. A new stupidity, too, a new confusion of the moral and mechanical, if we don't listen carefully to sane and discriminating voices like Spitzer's. * Daily Telegraph * Spitzer... has written a highly readable introduction to 'traditional' neural-net models.... * Nature *
| Preface | |
| Acknowledgments | |
| Introduction | |
| History | |
| Neural Networks In Intensive-Care Units | |
| Enlightenment! | |
| Brains Versus Computers | |
| Speed | |
| Reliability | |
| Architecture | |
| Recap | |
| Basics | |
| Neuronal Teamwork | |
| Neurons as Information-Processing Units | |
| A Simple Network for Pattern Recognition | |
| Shared Labor by Parallel Processing | |
| Language Acquisition by Children and Networks | |
| Computer Simulations of Higher Cognitive Functions | |
| DECtalk versus NETtalk | |
| Beethoven, Karajan, Sony, and the Human Genome | |
| Recap | |
| Learning | |
| Association and Hebbian Learning | |
| Learning Synapses | |
| Excursus: Glutamate and the 1992 Molecule of the Year | |
| Supervised Learning | |
| Age and the Learning Constant | |
| Reality as the Basic Set and Experience as a Part Subset | |
| The Accuracy Of A Prediction Increases With The Square Root Of The Number Of Observations | |
| Why Children Play | |
| Practice, Don't Preach | |
| Computer Models And Biological Neurons | |
| Shape From Shading | |
| Recap | |
| Vectors in the Head | |
| Vectors | |
| Codes | |
| Symbols versus Vectors | |
| Colors as Vectors | |
| Codes as Optimization Strategies | |
| Vector Populations and the Population Vector | |
| Observing Neurons During Learning | |
| Recap | |
| Principles | |
| Maps in the Cortex | |
| Anatomy of the Cortex | |
| Isocortex--The General Purpose Machine | |
| Columns of Information Processing | |
| Self-Organizing Feature Maps | |
| Example: A Simulated Network for Letter Recognition | |
| Similarity and Frequency | |
| Receptive Fields | |
| Cortical Topography | |
| Biological Example: The Auditory Cortex of the Bat | |
| Networks of Maps: Modularity | |
| Recap | |
| Hidden Layers The Exclusive-Or | |
| Abstraction and Type Formation | |
| Learning by the Feedback of Errors | |
| Hidden Layers in the Brain | |
| Cortico-Cortical Connections | |
| Analysis and Synthesis | |
| Ping-Pong Style Information Processing | |
| Autism | |
| Brains as Engines for the Estimation of Functions | |
| Recap | |
| Neuroplasticity | |
| Artificial Ears | |
| Hearing, Too, Depends on Context | |
| Rewiring Maps | |
| Animal Studies on Neuroplasticity | |
| Importance of the Input | |
| Selective Attention | |
| The Higher the Level, the More Adaptive the Area | |
| Phantoms and Amputated Networks | |
| Subjective Experience | |
| Cortical-Phantom Genesis | |
| Peripheral Phantom Genesis | |
| Simulating Phantoms by Amputating Networks | |
| Noise | |
| Noise and Neuroplasticity | |
| Turning a Conundrum into a Parsimonious Theory | |
| The Cortex Plays the First Violin | |
| Therapeutic Application: Plastic Understanding of Spoken Language | |
| Neuroplasticity and Thought | |
| Recap | |
| Feedback | |
| Connectivity Across the Board: Hopfield Networks | |
| Attractors | |
| Auditory Hallucinations | |
| Elman Networks | |
| Working Memory | |
| Development of the Frontal Lobes | |
| Interaction of Brain Development and Learning | |
| Pidgin and Creole Languages | |
| Recap | |
| Applications | |
| Representing Knowledge | |
| Static Rules versus Dynamic Processes | |
| Piaget and Stages of Development | |
| Memory | |
| Living without the Hippocampus | |
| Memory in the Network | |
| Single Events versus Generality | |
| Catastrophic Interference | |
| Race Against Decay | |
| The Hippocampus as the Trainer of the Cortex | |
| A Neural Network Model of Alzheimer's Disease | |
| Recap | |
| Semantic Networks | |
| Understanding and Speaking | |
| Associations: What Comes to Mind, and Why | |
| Rhymes, Fatigue, and Attention | |
| Associative Networks | |
| Self-Organizing Semantic Networks | |
| Language Is Used | |
| Semantic Maps in the Head | |
| Missing Vegetables Only | |
| Category-Specific Activation in Functional Magnetic Resonance Imaging | |
| Measuring Associations within Networks | |
| Recap | |
| Postscript on Aschaffenburg and Jung or, Whether Rhyming Is Priming Depends upon Timing | |
| The Disordered Mind | |
| The Birth of Schizophrenia | |
| Madness and Craziness | |
| Dysfunctional Lexical Access | |
| Indirect Associations | |
| What Pauses during Speech Reveal about Thoughts | |
| Remote Ideas | |
| Dopamine, Neuromodulation, Signal, and Noise | |
| Neuromodulation | |
| Noise: Not a Bug, but a Feature | |
| Formal Thought Disorder as the Result of Decreased Signal-to-Noise | |
| Intermediate Result | |
| Meaning Electrified: EEG and Semantics | |
| Associative and Working Memory | |
| Metaphors and Concretism | |
| Delusions | |
| Acute Delusions and Neuromodulation | |
| Chronic Delusions and Neuroplasticity | |
| Recap | |
| Thoughts and Impressions | |
| Back to the Basics: What Are Models? | |
| Principles | |
| Realistic and | |
| Abstract Models | |
| Models in Medicine | |
| Computational Models of Emotions? | |
| The Depression Spiral | |
| Temperament, Character, and Personality | |
| What Is Good for Children | |
| Stability and Teddy Bear | |
| Psychotherapy | |
| User's Manual for Your Brain | |
| Glossary | |
| References | |
| Index | |
| Table of Contents provided by Publisher. All Rights Reserved. |
ISBN: 9780262692366
ISBN-10: 0262692368
Series: The Mind within the Net
Audience:
Professional
For Ages: 18+ years old
Format:
Paperback
Language:
English
Number Of Pages: 376
Published: 28th February 2000
Publisher: MIT Press Ltd
Country of Publication: US
Dimensions (cm): 22.9 x 15.2
x 2.3
Weight (kg): 0.57
