Neuronal Noise

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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. It provides 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 different theories proposed to explore the computational power that various forms of "noise" can confer to neurons.

Author(s): Alain Destexhe, Michelle Rudolph-Lilith (auth.)
Series: Springer Series in Computational Neuroscience 8
Edition: 1
Publisher: Springer US
Year: 2012

Language: English
Pages: 458
Tags: Neurosciences; Neurobiology

Front Matter....Pages i-xviii
Introduction....Pages 1-5
Basics....Pages 7-27
Synaptic Noise....Pages 29-65
Models of Synaptic Noise....Pages 67-110
Integrative Properties in the Presence of Noise....Pages 111-183
Recreating Synaptic Noise Using Dynamic-Clamp....Pages 185-241
The Mathematics of Synaptic Noise....Pages 243-290
Analyzing Synaptic Noise....Pages 291-333
Case Studies....Pages 335-386
Conclusions and Perspectives....Pages 387-404
Back Matter....Pages 405-458