Overview
- Neuronal Noise combines experimental, theoretical and computational results to show how noise is inherent to neuronal activity
- The book covers many aspects of noise in neurons, with an emphasis on the largest source of noise: synaptic noise
- Provides students and young researchers with an overview of the important methods and concepts that have emerged from research in this area
Part of the book series: Springer Series in Computational Neuroscience (NEUROSCI, volume 8)
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Table of contents (10 chapters)
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Neuronal Noise
Authors: Alain Destexhe, Michelle Rudolph-Lilith
Series Title: Springer Series in Computational Neuroscience
DOI: https://doi.org/10.1007/978-0-387-79020-6
Publisher: Springer New York, NY
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Hardcover ISBN: 978-0-387-79019-0Published: 06 January 2012
Softcover ISBN: 978-1-4899-9029-7Published: 23 February 2014
eBook ISBN: 978-0-387-79020-6Published: 07 January 2012
Series ISSN: 2197-1900
Series E-ISSN: 2197-1919
Edition Number: 1
Number of Pages: XVIII, 458
Topics: Neurosciences, Neurobiology