Editors:
- Tracks advances in the application of phase response (PR) analysis to the study of electrically excitable cells
- Focuses on applications of PR analysis in the computational neurosciences
- Uses mathematical, modeling, and experimental results to illustrate how phase response analysis has been used to reveal or describe neuronal and neuronal population dynamics
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Series in Computational Neuroscience (NEUROSCI, volume 6)
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Table of contents (20 chapters)
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Front Matter
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Foundations of Phase Response Analysis
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Front Matter
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Foundations of Phase Response Analysis Introduction to Part 1
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Estimation of Phase Response Curves
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Front Matter
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Estimation of Phase Response Curves Introduction to Part 2
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Cellular Mechanisms of Neuronal Phase Response Properties
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Front Matter
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Cellular Mechanisms of Neuronal Phase Response Properties Introduction to Part 3
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Prediction of Network Activity with Phase Response Curves
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Front Matter
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Prediction of Network Activity with Phase Response Curves Introduction to Part4
About this book
Reviews
From the book reviews:
“This is a very good work on phase response neural modeling involving both single neuron and population neurons networks. Good descriptions of the cortical, subcortical, and brain stem networks is spendidly done and I highly recommend this book for both beginning and advanced physiologists. PRCs and the fourth dimensional models are well described. Students, fellows, and senior investigators will find it illuminating.” (Joseph J. Grenier, Amazon.com, September, 2014)Editors and Affiliations
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Boston, USA
Nathan W. Schultheiss
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Dept. Biology, Emory University, Atlanta, USA
Astrid A. Prinz
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School of Electrical &, Computer Engineering, Georgia Institute of Technology, Atlanta, USA
Robert J. Butera
Bibliographic Information
Book Title: Phase Response Curves in Neuroscience
Book Subtitle: Theory, Experiment, and Analysis
Editors: Nathan W. Schultheiss, Astrid A. Prinz, Robert J. Butera
Series Title: Springer Series in Computational Neuroscience
DOI: https://doi.org/10.1007/978-1-4614-0739-3
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: 978-1-4614-0738-6Published: 22 December 2011
Softcover ISBN: 978-1-4939-0154-8Published: 03 March 2014
eBook ISBN: 978-1-4614-0739-3Published: 23 December 2011
Series ISSN: 2197-1900
Series E-ISSN: 2197-1919
Edition Number: 1
Number of Pages: XIV, 518
Topics: Neurosciences, Neurology