Synopses & Reviews
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.
Synopsis
Inspired by response to a workshop at the 2008 OCNS meeting, this book tracks 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.
Synopsis
Neuronal phase response curves (PRCs) summarize the relationship between the timing of inputs within a neuron's spike cycle and output spike timing, as so are efficient encapsulations of the input-output processing of individual neurons to singular perturbations.
Synopsis
Neuronal phase response curves (PRCs) summarize the relationship between the timing of inputs within a neuron's spike cycle and output spike timing, as so are efficient encapsulations of the input-output processing of individual neurons to singular perturbations.
Table of Contents
Preface.- Part 1; Foundations of Phase Response Analysis.- Introduction to Part 1.- Chapter 1. The theory of weakly coupled oscillators.- Chapter 2. Phase resetting neural oscillators: Topological theory versus the real world.- Chapter 3. A theoretical framework for the dynamics of multiple intrinsic oscillators in single neurons.- Chapter 4. History of the application of the phase resetting curve to neurons coupled in a pulsatile manner.- Part 2; Estimation of Phase Response Curves.- Introduction to Part 2.- Chapter 5. Experimentally estimating phase response curves of neurons: Theoretical and practical issues.- Chapter 6. A geometric approach to phase resetting estimation based on mapping temporal to geometric phase.- Chapter 7. PRC estimation with varying width intervals.- Chapter 8. Bayesian approach to estimating phase response curves.- Part 3; Cellular Mechanisms of Neuronal Phase Response Properties.- Introduction to Part 3.- Chapter 9. Phase response curves to measure ion channel effects on neurons.- Chapter 10. Cellular mechanisms underlying spike-time reliability and stochastic synchronization: Insights and predictions from the phase-response curve.- Chapter 11. Recovery of stimuli encoded with a Hodgkin-Huxley neuron using conditional PRCs.- Chapter 12. Cholinergic neuromodulation controls PRC type in cortical pyramidal neurons.- Chapter 13. Continuum of type I somatic to type II dendritic PRCs; Simulatingin vitro and in vivo phase