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Phase Response Curves in Neuroscience

Theory, Experiment, and Analysis

  • Book
  • © 2012

Overview

Editors:
  1. Nathan W. Schultheiss

    1. Boston, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Astrid A. Prinz

    1. Dept. Biology, Emory University, Atlanta, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Robert J. Butera

    1. School of Electrical &, Computer Engineering, Georgia Institute of Technology, Atlanta, USA

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  • 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)

  1. Front Matter

    Pages i-xiii
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  2. Foundations of Phase Response Analysis

    1. Front Matter

      Pages 1-1
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  3. Foundations of Phase Response Analysis Introduction to Part 1

    1. The Theory of Weakly Coupled Oscillators

      • Michael A. Schwemmer, Timothy J. Lewis
      Pages 3-31

    2. Phase Resetting Neural Oscillators: Topological Theory Versus the RealWorld

      • Trine Krogh-Madsen, Robert Butera, G. Bard Ermentrout, Leon Glass
      Pages 33-51

    3. A Theoretical Framework for the Dynamics of Multiple Intrinsic Oscillators in Single Neurons

      • Michiel W. H. Remme, Máté Lengyel, Boris S. Gutkin
      Pages 53-72

    4. History of the Application of the Phase Resetting Curve to Neurons Coupled in a Pulsatile Manner

      • Carmen C. Canavier, Srisairam Achuthan
      Pages 73-91

  4. Estimation of Phase Response Curves

    1. Front Matter

      Pages 93-93
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  5. Estimation of Phase Response Curves Introduction to Part 2

    1. Experimentally Estimating Phase Response Curves of Neurons: Theoretical and Practical Issues

      • Theoden Netoff, Michael A. Schwemmer, Timothy J. Lewis
      Pages 95-129

    2. A Geometric Approach to Phase Resetting Estimation Based on Mapping Temporal to Geometric Phase

      • Sorinel Adrian Oprisan
      Pages 131-162

    3. PRC Estimation with Varying Width Intervals

      • Daniel G. Polhamus, Charles J. Wilson, Carlos A. Paladini
      Pages 163-177

    4. Bayesian Approach to Estimating Phase Response Curves

      • Keisuke Ota, Toru Aonishi
      Pages 179-203

  6. Cellular Mechanisms of Neuronal Phase Response Properties

    1. Front Matter

      Pages 205-206
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  7. Cellular Mechanisms of Neuronal Phase Response Properties Introduction to Part 3

    1. Phase Response Curves to Measure Ion Channel Effects on Neurons

      • G. Bard Ermentrout, Bryce Beverlin II, Theoden Netoff
      Pages 207-236

    2. Cellular Mechanisms Underlying Spike-Time Reliability and Stochastic Synchronization: Insights and Predictions from the Phase-Response Curve

      • Roberto F. Galán
      Pages 237-255

    3. Recovery of Stimuli Encoded with a Hodgkin–Huxley Neuron Using Conditional PRCs

      • Anmo J. Kim, Aurel A. Lazar
      Pages 257-277

    4. Cholinergic Neuromodulation Controls PRC Type in Cortical Pyramidal Neurons

      • Klaus M. Stiefel, Boris S. Gutkin
      Pages 279-305

    5. Continuum of Type I Somatic to Type II Dendritic PRCs; Phase Response Properties of a Morphologically Reconstructed Globus Pallidus Neuron Model

      • Nathan W. Schultheiss
      Pages 307-325

  8. Prediction of Network Activity with Phase Response Curves

    1. Front Matter

      Pages 327-328
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  9. Prediction of Network Activity with Phase Response Curves Introduction to Part4

    1. Understanding Activity in Electrically Coupled Networks Using PRCs and the Theory of Weakly Coupled Oscillators

      • Timothy J. Lewis, Frances K. Skinner
      Pages 329-359

    2. The Role of Intrinsic Cell Properties in Synchrony of Neurons Interacting via Electrical Synapses

      • David Hansel, Germán Mato, Benjamin Pfeuty
      Pages 361-398
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About this book

This book will track advances in the application of phase response (PR) analysis to the study of electrically excitable cells, focusing on applications of PR analysis in the computational neurosciences. This proposal was motivated by discussions with colleagues at the 2007 meeting of the Organization for Computational Neuroscience (OCNS) and further motivated by the success of a workshop at the 2008 OCNS meeting this past July. At that meeting the editors hosted a workshop entitled A dialogue for theoreticians and experimentalists: What is phase response analysis, and what can it tell us about neurons and networks? Invited speakers used mathematical, modeling, and experimental results to illustrate how phase response analysis has been used to reveal or describe neuronal and neuronal population dynamics. This was the most well-attended workshop of the meeting and was standing room only.

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

  • Boston, USA

    Nathan W. Schultheiss

  • Dept. Biology, Emory University, Atlanta, USA

    Astrid A. Prinz

  • 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

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