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| Foreword | |
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| Preface | |
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| Acknowledgments | |
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| Introduction | |
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| For whom is this book? | |
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| What is in the book? | |
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| Do I need a computer for this book? | |
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| Software | |
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| Why learn this now? | |
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| What is the subtext? | |
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| How is the book organized? | |
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| Perspectives | |
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| Computational Neuroscience and You | |
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| Why learn this? | |
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| Brain metaphors | |
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| Compare and contrast computer and brain | |
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| Origins of computer science and neuroscience | |
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| Levels | |
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| Levels of organization | |
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| Levels of investigation | |
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| New engineering vs. old engineering | |
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| The neural code | |
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| The goals and methods of computational neuroscience | |
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| Summary and thoughts | |
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| Basic Neuroscience | |
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| Why learn this? | |
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| Microscopic view of the nervous system | |
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| Macroscopic view of the nervous system | |
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| Slicing the brain | |
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| Parts of the brain | |
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| How do we learn about the brain? | |
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| Anatomical methods | |
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| Neurophysiology | |
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| Molecular biology and neuropharmacology | |
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| Psychophysics | |
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| Clinical neurology and neuropsychology | |
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| Ablative diseases | |
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| Intrinsic diseases | |
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| Summary and thoughts | |
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| Computers | |
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| Computer Representations | |
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| Why learn this? | |
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| Calculator or typewriter | |
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| Punch cards and Boolean algebra | |
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| Analog vs. digital representations | |
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| Types of computer representations | |
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| Representation of numbers | |
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| Representation of letters and words | |
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| Representation of pictures | |
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| Neurospeculation | |
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| Summary and thoughts | |
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| The Soul of an Old Machine | |
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| Why learn this? | |
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| The art of the hack | |
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| Software and hardware | |
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| Basic computer design | |
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| Pointers come from computer memory design | |
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| Sequential algorithms come from computer control flow | |
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| CPU: machine commands | |
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| Programs and hacks | |
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| Conditionals | |
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| Pointer manipulation | |
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| A kludge | |
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| A computer virus | |
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| Neurospeculation | |
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| Summary and thoughts | |
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| Cybernetics | |
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| Concept Neurons | |
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| Why learn this? | |
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| History and description of McCulloch-Pitts neurons | |
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| Describing networks by weights and states | |
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| Calculating total-summed-input by dot product | |
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| Calculating state | |
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| From single unit to network of units | |
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| Network architecture | |
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| Summary and thoughts | |
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| Neural Coding | |
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| Why learn this? | |
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| Coding in space: ensemble codes | |
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| Local vs. distributed ensemble coding | |
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| Coding with volts and chemicals: neural state code | |
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| Coding in time: temporal and rate codes | |
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| Temporal integration | |
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| Clocking | |
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| Frequency coding | |
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| Summary and thoughts | |
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| Our Friend the Limulus | |
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| Why learn this? | |
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| The biology | |
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| What we can ignore | |
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| Why the eye lies: the problem | |
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| Design issues | |
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| Making the model small - scaling | |
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| Making the model small - dimensional reduction | |
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| Eliminating edge effects - wraparound | |
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| Presenting the input - parameterization | |
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| Parameterizing the activation function | |
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| Parameterizing the weight matrix | |
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| <$$$> | |
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| State calculation | |
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| Life as a limulus | |
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| Summary and thoughts | |
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| Supervised Learning: Delta Rule and Back-Propagation | |
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| Why learn this? | |
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| Supervised learning | |
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| The delta rule | |
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| The energy analogy | |
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| The delta rule solves AND | |
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| Backward propagation | |
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| Distributed representations | |
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| Distributed representation in eye movement control | |
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| Design of the model | |
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| Results from the model: generalization | |
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| Exploration of the model: hidden unit analysis | |
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| Computer modeling vs. traditional mathematical modeling | |
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| Summary and thoughts | |
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| Associative Memory Networks | |
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| Why learn this? | |
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| Memories in an outer product | |
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| Association across a single synapse | |
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| The outer product of two vectors | |
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| Making hetero- and autoassociative memories | |
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| Limit cycles | |
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| Instantaneous vs. gradual learning and recall | |
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| Critique of the Hopfield network | |
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| Summary and thoughts | |
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| Brains | |
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| From Soap to Volts | |
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| Why learn this? | |
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| Basic cell design | |
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| Morphing soap and salt to batteries and resistors | |
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| Converting the RC circuit into an equation | |
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| Capacitance and current | |
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| Adding up the currents | |
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| Parameter dependence | |
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| Advantages and disadvantages of numerical integration | |
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| Time constant and temporal summations | |
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| Slow potential theory | |
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| Averaging by adding PSPs | |
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| Summary and thoughts | |
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| Hodgkin-Huxley Model | |
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| Why learn this? | |
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| From passive to active | |
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| The resting membrane potential is about -70 mV | |
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| The membrane is insulator, capacitor, and battery | |
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| Synaptic inputs aren't current injections | |
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| History of the action potential | |
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| Hodgkin and Huxley | |
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| The parallel-conductance model | |
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| The circuit | |
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| Currents | |
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| Calculations | |
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| Where do the batteries come from? | |
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| Behavior of the active channels | |
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| Feedback systems | |
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| Particle duality | |
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| Particle dynamics | |
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| The particle equations | |
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| State variables define a state | |
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| Simulation | |
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| Implications for signaling | |
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| The threshold and channel memory | |
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| Rate coding redux | |
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| Summary and thoughts | |
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| Compartment Modeling | |
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| Why learn this? | |
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| Dividing into compartments | |
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| Building the model | |
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| Chemical synapse modeling | |
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| Shunting inhibition | |
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| GABA and glutamate | |
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| Passive neuron model | |
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| Synaptic responses | |
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| Back-propagating spikes and the Hebb synapse | |
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| Summary and thoughts | |
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| From Artificial Neural Network to Realistic Neural Network | |
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| Why learn this? | |
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| Hopfield revisited | |
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| Suppression model for reducing interference | |
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| A digression into philosophy | |
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| Acetylcholine has multiple effects | |
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| The dual-matrix hypothesis | |
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| True confessions | |
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| Summary and thoughts | |
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| Neural Circuits | |
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| Why learn this? | |
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| The basic layout | |
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| Hippocampus | |
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| Thalamus | |
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| Cerebellum | |
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| Basal ganglia | |
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| Neocortex | |
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| Summary and thoughts | |
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| The Basics | |
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| Why learn this? | |
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| Units | |
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| Scientific notation | |
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| Numerical prefixes | |
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| Units and abbreviations | |
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| Unit conversions | |
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| Dimensional analysis | |
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| Binary | |
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| Translating back and forth | |
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| Addition and subtraction | |
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| Octal and hex | |
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| Boolean algebra | |
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| Linear algebra | |
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| What is algebra? Why linear? | |
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| Addition and subtraction | |
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| Dot product | |
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| Orthogonality | |
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| Outer product | |
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| Matrix multiplication | |
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| Numerical calculus | |
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| Infinitesimals | |
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| Numerical solutions | |
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| Mathematical symbols | |
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| Analytic solution to the charging curve | |
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| Electrical engineering | |
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| The three big laws: Ohm, Kirchhoff, and the other one | |
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| Ohm's law | |
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| Capacitance | |
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| Glossary | |
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| Index | |