"The Book of GENESIS" is in two parts. Firstly, a collection of contributed articles describes projects created using the GENESIS system, and then a step-by-step tutorial explains how the software works and how best to manipulate it so as to achieve maximum use. As a result, this publication may be seen as a reference guide, a textbook for course use, and as a resource to which readers can turn for ideas on how to devise their own models and applications. The accompanying cross-platform CD-ROM contains the full source code for GENESIS and its graphical interface, XODUS; the GENESIS Reference…mehr
"The Book of GENESIS" is in two parts. Firstly, a collection of contributed articles describes projects created using the GENESIS system, and then a step-by-step tutorial explains how the software works and how best to manipulate it so as to achieve maximum use. As a result, this publication may be seen as a reference guide, a textbook for course use, and as a resource to which readers can turn for ideas on how to devise their own models and applications. The accompanying cross-platform CD-ROM contains the full source code for GENESIS and its graphical interface, XODUS; the GENESIS Reference Manual in hypertext, plain text and Postscript formats; numerous tutorial simulations and example simulation scripts, including all of those used in the book. As a bonus, also included on the CD are a number of items which are not part of the standard distribution of GENESIS. The GENESIS system will continue to be made available through the Cal Tech World Wide Web site, as well, at: www.bbb.caltech.edu/GENESIS.
The Book of GENESIS , in its new, 2nd edition, remains an invaluable modeling and simulation resource and tool for a wide audience of neuroscience students, researchers and professionals. The addition of new chapter materials in the book, and the availability of a cross-platform CD-ROM containing all of the source code to the latest version of the GENESIS software, version 2.1, as well as many other important new components to the GENESIS system, give this new edition significant added-value for current and prospective users.
Inhaltsangabe
'I Neurobiological Tutorials with GENESIS.- 1 Introduction.- 1.1 Computational Neuroscience.- 1.2 Using This Book.- 2 Compartmental Modeling.- 2.1 Modeling Neurons.- 2.1.1 Detailed Compartmental Models.- 2.1.2 Equivalent Cylinder Models.- 2.1.3 Single and Few Compartment Models.- 2.2 Equivalent Circuit of a Single Compartment.- 2.3 Axonal Connections, Synapses and Networks.- 2.4 Simulation Accuracy.- 2.4.1 Choice of Numerical Integration Technique.- 2.4.2 Integration Time Step.- 2.4.3 Accuracy of GENESIS.- 3 Neural Modeling with GENESIS.- 3.1 What Is GENESIS?.- 3.1.1 Why Use a General Simulator?.- 3.1.2 GENESIS Design Features.- 3.1.3 GENESIS Development.- 3.2 Introduction to the Tutorials.- 3.3 Introduction to the GENESIS Graphical Interface.- 3.3.1 Starting the Simulation.- 3.3.2 The Control Panel.- 3.3.3 Using Help Menus.- 3.3.4 Displaying the Simulation Results.- 4 The Hodgkin-Huxley Model.- 4.1 Introduction.- 4.2 Historical Background.- 4.3 The Mathematical Model.- 4.3.1 Electrical Equivalent Circuit.- 4.3.2 HH Conventions.- 4.3.3 The Ionic Current.- 4.4 Voltage Clamp Experiments.- 4.4.1 Characterizing the K Conductance.- 4.5 GENESIS: Voltage Clamp Experiments.- 4.6 Parameterizing the Rate Constants.- 4.7 Inactivation of the Na Conductance.- 4.8 Current Injection Experiments.- 4.9 Exercises.- 5 Cable and Compartmental Models of Dendritic Trees.- 5.1 Introduction.- 5.2 Background.- 5.2.1 Dendritic Trees: Anatomy, Physiology and Synaptology.- 5.2.2 Summary.- 5.3 The One-Dimensional Cable Equation.- 5.3.1 Basic Concepts and Assumptions.- 5.3.2 The Cable Equation.- 5.4 Solution of the Cable Equation for Several Cases.- 5.4.1 Steady-State Voltage Attenuation with Distance.- 5.4.2 Voltage Decay with Time.- 5.4.3 Functional Significance of ? and ?m.- 5.4.4 The Input Resistance Rin and "Trees Equivalent to a Cylinder".- 5.4.5 Summary of Main Results from the Cable Equation.- 5.5 Compartmental Modeling Approach.- 5.6 Compartmental Modeling Experiments.- 5.7 Main Insights for Passive Dendrites with Synapses.- 5.8 Biophysics of Excitable Dendrites.- 5.9 Computational Function of Dendrites.- 5.10 Exercises.- 6 Temporal Interactions Between Postsynaptic Potentials.- 6.1 Introduction.- 6.2 Electrical Model of a Patch of Membrane.- 6.2.1 Voltage Response of Passive Membrane to a Current Pulse.- 6.3 Response to Activation of Synaptic Channels.- 6.3.1 The Postsynaptic Current.- 6.3.2 The Postsynaptic Potential.- 6.3.3 Smooth Synaptic Conductance Change: The "Alpha Function".- 6.4 A Remark on Synaptic Excitation and Inhibition.- 6.5 GENESIS Experiments with PSPs.- 6.5.1 Temporal Summation of Postsynaptic Potentials.- 6.5.2 Nonlinear Summation of Postsynaptic Potentials.- 6.6 Concluding Remarks.- 6.7 Exercises and Projects.- 7 Ion Channels in Bursting Neurons.- 7.1 Introduction.- 7.2 General Properties of Molluscan Neurons.- 7.3 Ionic Conductances - The Dance of the Ions.- 7.3.1 Action Potential Related Conductances.- 7.3.2 Control of Bursting Properties.- 7.4 A Model Molluscan Neuron.- 7.4.1 Adrift in Parameter Space.- 7.4.2 Implementation of the Model.- 7.4.3 Modeling the Channels.- 7.5 The Molluscan Neuron Simulation.- 7.5.1 Using Neurokit.- 7.5.2 Understanding the Results.- 7.6 The Traub Model CA3 Pyramidal Cell.- 7.6.1 Experiments with the Traub Model.- 7.6.2 Firing Patterns.- 7.7 Exercises.- 8 Central Pattern Generators.- 8.1 Introduction.- 8.2 Two-Neuron Oscillators.- 8.2.1 Phase Equation Model of Coupled Oscillators.- 8.2.2 Simulation Parameters.- 8.2.3 Initial Conditions.- 8.2.4 Synaptic Coupling.- 8.2.5 Non-Phase Equation Models.- 8.3 Four-Neuron Oscillators.- 8.3.1 Chains of Coupled Oscillators.- 8.3.2 Simulation Parameters.- 8.3.3 Modeling Gaits.- 8.4 Summary.- 8.5 Exercises.- 9 Dynamics of Cerebral Cortical Networks.- 9.1 Introduction.- 9.2 Piriform Cortex.- 9.3 Structure of the Model.- 9.3.1 Cellular Complexity.- 9.3.2 Network Ci
'I Neurobiological Tutorials with GENESIS.- 1 Introduction.- 1.1 Computational Neuroscience.- 1.2 Using This Book.- 2 Compartmental Modeling.- 2.1 Modeling Neurons.- 2.1.1 Detailed Compartmental Models.- 2.1.2 Equivalent Cylinder Models.- 2.1.3 Single and Few Compartment Models.- 2.2 Equivalent Circuit of a Single Compartment.- 2.3 Axonal Connections, Synapses and Networks.- 2.4 Simulation Accuracy.- 2.4.1 Choice of Numerical Integration Technique.- 2.4.2 Integration Time Step.- 2.4.3 Accuracy of GENESIS.- 3 Neural Modeling with GENESIS.- 3.1 What Is GENESIS?.- 3.1.1 Why Use a General Simulator?.- 3.1.2 GENESIS Design Features.- 3.1.3 GENESIS Development.- 3.2 Introduction to the Tutorials.- 3.3 Introduction to the GENESIS Graphical Interface.- 3.3.1 Starting the Simulation.- 3.3.2 The Control Panel.- 3.3.3 Using Help Menus.- 3.3.4 Displaying the Simulation Results.- 4 The Hodgkin-Huxley Model.- 4.1 Introduction.- 4.2 Historical Background.- 4.3 The Mathematical Model.- 4.3.1 Electrical Equivalent Circuit.- 4.3.2 HH Conventions.- 4.3.3 The Ionic Current.- 4.4 Voltage Clamp Experiments.- 4.4.1 Characterizing the K Conductance.- 4.5 GENESIS: Voltage Clamp Experiments.- 4.6 Parameterizing the Rate Constants.- 4.7 Inactivation of the Na Conductance.- 4.8 Current Injection Experiments.- 4.9 Exercises.- 5 Cable and Compartmental Models of Dendritic Trees.- 5.1 Introduction.- 5.2 Background.- 5.2.1 Dendritic Trees: Anatomy, Physiology and Synaptology.- 5.2.2 Summary.- 5.3 The One-Dimensional Cable Equation.- 5.3.1 Basic Concepts and Assumptions.- 5.3.2 The Cable Equation.- 5.4 Solution of the Cable Equation for Several Cases.- 5.4.1 Steady-State Voltage Attenuation with Distance.- 5.4.2 Voltage Decay with Time.- 5.4.3 Functional Significance of ? and ?m.- 5.4.4 The Input Resistance Rin and "Trees Equivalent to a Cylinder".- 5.4.5 Summary of Main Results from the Cable Equation.- 5.5 Compartmental Modeling Approach.- 5.6 Compartmental Modeling Experiments.- 5.7 Main Insights for Passive Dendrites with Synapses.- 5.8 Biophysics of Excitable Dendrites.- 5.9 Computational Function of Dendrites.- 5.10 Exercises.- 6 Temporal Interactions Between Postsynaptic Potentials.- 6.1 Introduction.- 6.2 Electrical Model of a Patch of Membrane.- 6.2.1 Voltage Response of Passive Membrane to a Current Pulse.- 6.3 Response to Activation of Synaptic Channels.- 6.3.1 The Postsynaptic Current.- 6.3.2 The Postsynaptic Potential.- 6.3.3 Smooth Synaptic Conductance Change: The "Alpha Function".- 6.4 A Remark on Synaptic Excitation and Inhibition.- 6.5 GENESIS Experiments with PSPs.- 6.5.1 Temporal Summation of Postsynaptic Potentials.- 6.5.2 Nonlinear Summation of Postsynaptic Potentials.- 6.6 Concluding Remarks.- 6.7 Exercises and Projects.- 7 Ion Channels in Bursting Neurons.- 7.1 Introduction.- 7.2 General Properties of Molluscan Neurons.- 7.3 Ionic Conductances - The Dance of the Ions.- 7.3.1 Action Potential Related Conductances.- 7.3.2 Control of Bursting Properties.- 7.4 A Model Molluscan Neuron.- 7.4.1 Adrift in Parameter Space.- 7.4.2 Implementation of the Model.- 7.4.3 Modeling the Channels.- 7.5 The Molluscan Neuron Simulation.- 7.5.1 Using Neurokit.- 7.5.2 Understanding the Results.- 7.6 The Traub Model CA3 Pyramidal Cell.- 7.6.1 Experiments with the Traub Model.- 7.6.2 Firing Patterns.- 7.7 Exercises.- 8 Central Pattern Generators.- 8.1 Introduction.- 8.2 Two-Neuron Oscillators.- 8.2.1 Phase Equation Model of Coupled Oscillators.- 8.2.2 Simulation Parameters.- 8.2.3 Initial Conditions.- 8.2.4 Synaptic Coupling.- 8.2.5 Non-Phase Equation Models.- 8.3 Four-Neuron Oscillators.- 8.3.1 Chains of Coupled Oscillators.- 8.3.2 Simulation Parameters.- 8.3.3 Modeling Gaits.- 8.4 Summary.- 8.5 Exercises.- 9 Dynamics of Cerebral Cortical Networks.- 9.1 Introduction.- 9.2 Piriform Cortex.- 9.3 Structure of the Model.- 9.3.1 Cellular Complexity.- 9.3.2 Network Ci
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