Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 A tour of the NEURON simulation environment
- 2 The modeling perspective
- 3 Expressing conceptual models in mathematical terms
- 4 Essentials of numerical methods for neural modeling
- 5 Representing neurons with a digital computer
- 6 How to build and use models of individual cells
- 7 How to control simulations
- 8 How to initialize simulations
- 9 How to expand NEURON's library of mechanisms
- 10 Synaptic transmission and artificial spiking cells
- 11 Modeling networks
- 12 hoc, NEURON's interpreter
- 13 Object-oriented programming
- 14 How to modify NEURON itself
- Appendix A1 Mathematical analysis of IntFire4
- Appendix A2 NEURON's built-in editor
- Epilogue
- Index
5 - Representing neurons with a digital computer
Published online by Cambridge University Press: 01 September 2010
- Frontmatter
- Contents
- Preface
- Acknowledgments
- 1 A tour of the NEURON simulation environment
- 2 The modeling perspective
- 3 Expressing conceptual models in mathematical terms
- 4 Essentials of numerical methods for neural modeling
- 5 Representing neurons with a digital computer
- 6 How to build and use models of individual cells
- 7 How to control simulations
- 8 How to initialize simulations
- 9 How to expand NEURON's library of mechanisms
- 10 Synaptic transmission and artificial spiking cells
- 11 Modeling networks
- 12 hoc, NEURON's interpreter
- 13 Object-oriented programming
- 14 How to modify NEURON itself
- Appendix A1 Mathematical analysis of IntFire4
- Appendix A2 NEURON's built-in editor
- Epilogue
- Index
Summary
So saying he procured the plane; and with his old silk handkerchief first dusting the bench, vigorously set to planing away at my bed, the while grinning like an ape. The shavings flew right and left; till at last the plane-iron came bump against an indestructible knot.
Information processing in the nervous system involves the spread and interaction of electrical and chemical signals within and between neurons and glia. From the perspective of the experimentalist working at the level of cells and networks, these signals are continuous variables. They are described by the diffusion equation and the closely related cable equation (Rall 1977; Crank 1979), in which potential (voltage, concentration) and flux (current, movement of solute) are smooth functions of time and space. But everything in a digital computer is inherently discontinuous: memory addresses, data, and instructions are all specified in terms of finite sequences of 0s and 1s, and there are finite limits on the precision with which numbers can be represented. Thus there is no direct parallel between the continuous world of biology and what exists in digital computers, so special effort is required to implement digital computer models of biological neural systems. The aim of this chapter is to show how the NEURON simulation environment makes it easier to bridge this gap.
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- Information
- The NEURON Book , pp. 90 - 127Publisher: Cambridge University PressPrint publication year: 2006