Neuronal Noise
Neuronal Noise combines experimental, theoretical and computational results to show how noise is inherent to neuronal activity, and how noise can be important for neuronal computations. The book covers many aspects of noise in neurons, with an emphasis on the largest source of noise: synaptic noise...
| Main Authors: | , |
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| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Boston, MA :
Springer US,
2012.
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| Series: | Springer Series in Computational Neuroscience ;
8 |
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Table of Contents:
- 1 Introduction
- 2 Basics
- 3 Synaptic noise
- 4 Models of synaptic noise
- 5 Integrative properties in the presence of noise6 Recreating synaptic noise using dynamic-clamp
- 7 The mathematics of synaptic noise
- 8 Analyzing synaptic noise
- 9 Case studies
- 10 Conclusions and perspectives A Numerical integration of stochastic differential equations
- B Distributed Generator Algorithm
- C The Fokker-Planck formalism
- D The RT-NEURON interface for dynamic-clamp
- References
- Index.