Neuronal Noise / Edition 1 available in Hardcover
- Pub. Date:
- Springer US
Neuronal Noise covers many aspects of noise in neurons, with an emphasis on synaptic noise. It includes a combination of experimental, theoretical and computational results to show how noise is inherent to neuronal activity, and how noise can be important for neuronal computations. The goal of this book is to provide students and young researchers with an overview of the important methods and concepts that have emerged from research in this area. It also provides the specialist with a summary of the large body of sometimes contrasting experimental data, and the different theories proposed to explore the computational power that various forms of "noise" can confer to neurons.
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 shastic differential equations.- B Distributed Generator Algorithm.- C The Fokker-Planck formalism.- D The RT-NEURON interface for dynamic-clamp.- References.- Index.