Quantitative Neurophysiology

Book description

Quantitative Neurophysiology is supplementary text for a junior or senior level course in neuroengineering. It may also serve as an quick-start for graduate students in engineering, physics or neuroscience as well as for faculty interested in becoming familiar with the basics of quantitative neuroscience. The first chapter is a review of the structure of the neuron and anatomy of the brain. Chapters 2-6 derive the theory of active and passive membranes, electrical propagation in axons and dendrites and the dynamics of the synapse. Chapter 7 is an introduction to modeling networks of neurons and artificial neural networks. Chapter 8 and 9 address the recording and decoding of extracellular potentials. The final chapter has descriptions of a number of more advanced or new topics in neuroengineering. Throughout the text, vocabulary is introduced which will enable students to read more advanced literature and communicate with other scientists and engineers working in the neurosciences. Numerical methods are outlined so students with programming knowledge can implement the models presented in the text. Analogies are used to clarify topics and reinforce key concepts. Finally, homework and simulation problems are available at the end of each chapter.

Table of contents

  1. Synthesis Lectures on Biomedical Engineering
  2. Contents
  3. Preface (1/2)
  4. Preface (2/2)
  5. Neural Anatomy
    1. The Neuron
    2. Glial Cells
    3. The Brain
      1. From Neuron to Nuclei
      2. Brain Systems
      3. Blood Brain Barrier
      4. Directions in the Brain
      5. Inputs and Outputs
      6. Dynamic Brain Systems
  6. Passive Membranes
    1. Cellular Electrophysiology
      1. Cellular Voltages
      2. Cellular Currents
      3. Membrane Circuit Analog
      4. The Membrane Capacitance
    2. Stimulating the Passive Membrane
      1. Finding Membrane Properties from Vm(t)
      2. The Passive Membrane
    3. Strength-Duration Relationship
      1. A Fluid Analogy
    4. The Membrane at Rest
      1. The Forces Driving Ion Movement
      2. A Helium Balloon Analogy
      3. Definition of Resting Membrane Voltage
      4. Fick's Law and Chemical Gradients
      5. Ohm's Law and Electrical Gradients
      6. The Nernst Equation
      7. The Goldman-Hodgkin-Katz Equation
    5. Deviations from Rest
    6. Numerical Methods: The Euler Method
  7. Active Membranes
    1. The Hodgkin-Huxley Model
      1. The Parallel Conductance Model
      2. The Leakage Current
      3. Nonlinear Currents and the Voltage Clamp
      4. The Sodium Current
      5. The Potassium Current
      6. Steady-State and Time Constants
      7. A Game of Tag
    2. The Hodgkin-Huxley Action Potential
      1. Phase 0 - Rest
      2. Phase 1 - Activation
      3. Phase 2 - Repolarization
      4. Phase 3 - Hyperpolarization
    3. Properties of Neuronal Action Potentials
      1. All Or None
      2. Refractory Periods
      3. Anode Break
      4. Accommodation
    4. Complex Ionic Models
      1. More Currents
      2. The Traub Model of the Pyramidal Neuron
      3. Complex Gating
      4. Gating Dependence on pH, Temperature and Concentrations
      5. Changes in Nernst Potentials
      6. Intracellular Compartments and Buffers
    5. Phenomenological Models
      1. Fitzhugh-Naghumo Model
      2. Hindmarsh-Rose Model
      3. Integrate and Fire Model
    6. Numerical Methods: Template for an Active Membrane
  8. Propagation
    1. Passive Propagation in Dendrites
      1. The Core Conductor Model
      2. A Simplification
      3. Units and Relationships
      4. An Applied Stimulus
      5. Steady-State Solution
      6. Finding the Length Constant
      7. Time and Space Dependent Solution
    2. Active Propagation in Axons
      1. Uniform Propagation
      2. Saltatory Conduction
    3. Pass the Paper Please
    4. Numerical Methods: The Finite and Discrete Cable
    5. Numerical Methods: Template for Cable Propagation
  9. Neural Branches
    1. Lumped Models
      1. The Rall Model
      2. The Ball and Stick Model
    2. Multicompartment Models
      1. A Simple Compartment
      2. Change in Fiber Radius
      3. Branches
      4. The Soma
      5. Axon Collaterals and Semi-Active Dendrites
    3. Numerical Methods: Matrix Formulation
  10. Synapses
    1. Neurotransmitters
    2. The Pre-Synapse
    3. Neurotransmitter Diffusion and Clearance
    4. The Post-Synapse
      1. The Post-Synaptic Current
      2. Excitatory, Inhibitory and Silent Synapses
      3. Neurotransmitter Gating
      4. Multiple Gating Mechanism
      5. Second Messenger Gating
    5. Synaptic Summation
    6. Simplified Models of the Synapse
    7. The Many Mechanisms of Diseases and Drugs
    8. Synaptic Plasticity and Memory
  11. Networks of Neurons
    1. Networks of Neurons
      1. The Traub Pyramidal Neuron
      2. Conduction down the Axon and Synaptic Connections
      3. Interneurons
    2. Model Behavior
      1. All or None Synaptic Induced Firing
      2. Suppression of Neuronal Firing
      3. The Importance of Delays
      4. Central Pattern Generators
    3. Artificial Neural Networks
      1. The Perceptron and Single Layer Networks
    4. Multi-Layered Networks
      1. Backpropagation
      2. Momentum and Thermal Noise
      3. Training and Use
      4. Energy Surfaces and Sheets
      5. Network Structure and Connectivity
      6. Recurrent and Unsupervised Networks
    5. Numerical Methods
  12. Extracellular Recording and Stimulation
    1. Maxwell's Equations Applied to Neurons
      1. Forward and Inverse Problems
    2. Extracellular Potential Recordings
      1. Extracellular Potentials Generated by an Active Cable
      2. Current Sources in a Complex Domain
    3. The Electroenchephogram (EEG)
    4. Practical Aspects of Recording Neural Potentials
      1. Electrodes
      2. Recording Preparations
      3. Filtering, Amplification and Digitization
    5. Extracellular Stimulation
    6. Numerical Methods: Computing e in a Cable
  13. The Neural Code
    1. Neural Encoding
      1. The Membrane as a Frequency Detector
      2. The Synapse as a Frequency Detector
    2. Neural Decoding
      1. One Electrode, Many Recordings
      2. Eavesdropping
      3. Spike Sorting
      4. Time Binning and Firing Frequency
      5. A Graphical Representation
      6. Windowing
    3. Tuning Curves
  14. Applications
    1. Science and Science Fiction
    2. Neural Imaging
      1. Optical Recordings
      2. Functional Magnetic Resonance Imaging
      3. Diffusion Tensor Imaging
    3. Neural Stimulation
      1. Cortical Stimuli during Surgery
      2. Deep Brain Pacing
      3. Magnetic Recordings and Simulation
    4. Drug and Genetic Therapies
    5. Brain Machine Interface
    6. Growing Neural Tissue
      1. Nerve Guides
      2. A Biological Flight Simulator
    7. Artificial Intelligence
    8. Conclusion
  15. Suggested Readings
  16. Biography
  17. Index (1/2)
  18. Index (2/2)

Product information

  • Title: Quantitative Neurophysiology
  • Author(s): Joseph V. Tranquillo
  • Release date: January 2008
  • Publisher(s): Morgan & Claypool Publishers
  • ISBN: 9781598296754