Computational Neuroscience, Volume 123

1st Edition

Serial Volume Editors: Kim Blackwell
Hardcover ISBN: 9780123978974
eBook ISBN: 9780123979087
Imprint: Academic Press
Published Date: 4th March 2014
Page Count: 440
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Table of Contents

  • Contributors
  • Preface
  • Chapter One: Markov Modeling of Ion Channels: Implications for Understanding Disease
    • Abstract
    • 1 Why Do We Need Modeling?
    • 2 Markov Models Built Based on Whole-Cell Patch-Clamp Data
    • 3 Practical Considerations for Fitting Models to Data
    • 4 Conclusion and Outlook
    • Acknowledgments

  • Chapter Two: Ionic Mechanisms in Peripheral Pain
    • Abstract
    • 1 Biological Background
    • 2 Modeling of Peripheral Pain
    • 3 In Silico Pharmacology
    • 4 Conclusion

  • Chapter Three: Implications of Cellular Models of Dopamine Neurons for Schizophrenia
    • Abstract
    • 1 Dopamine Neuron Electrophysiology
    • 2 Depolarization Block Hypothesis of Antipsychotic Drug Action
    • 3 Computational Model of Pacemaking and Depolarization Block
    • 4 Availability of Sodium Current Controls Entry into DP Block
    • 5 The Ether-a-Go-Go-Related Gene Potassium Channel and Schizophrenia
    • 6 ERG Conductance Both Delays Entry into and Speeds Recovery from Depolarization Block
    • 7 Computational Model of Bursting and DP Block
    • 8 Conclusions
    • Acknowledgment
    • Appendix Full Model Equations and Parameters

  • Chapter Four: The Role of IP3 Receptor Channel Clustering in Ca2 + Wave Propagation During Oocyte Maturation
    • Abstract
    • 1 Introduction
    • 2 Methods
    • 3 Results
    • 4 Discussion
    • Acknowledgment

  • Chapter Five: Modeling Mitochondrial Function and Its Role in Disease
    • Abstract
    • 1 Introduction
    • 2 Energy Metabolism
    • 3 Mitochondrial Signaling
    • 4 Mitochondria in Disease
    • 5 Models of Mitochondrial Energy Metabolism
    • 6 Models of Mitochondrial Signaling
    • 7 Con


Progress in Molecular Biology and Translational Science provides a forum for discussion of new discoveries, approaches, and ideas in molecular biology. It contains contributions from leaders in their fields and abundant references. This volume brings together different aspects of, and approaches to, molecular and multi-scale modeling, with applications to a diverse range of neurological diseases.

Mathematical and computational modeling offers a powerful approach for examining the interaction between molecular pathways and ionic channels in producing neuron electrical activity. It is well accepted that non-linear interactions among diverse ionic channels can produce unexpected neuron behavior and hinder a deep understanding of how ion channel mutations bring about abnormal behavior and disease. Interactions with the diverse signaling pathways activated by G protein coupled receptors or calcium influx adds an additional level of complexity. Modeling is an approach to integrate myriad data sources into a cohesive and quantitative model in order to evaluate hypotheses about neuron function. In particular, a validated model developed using in vitro data allows simulations of the response to in vivo like spatio-temporal patterns of synaptic input. Incorporating molecular signaling pathways into an electrical model, allows a greater range of models to be developed, ones that can predict the response to pharmaceuticals, many of which target neuromodulator pathways.

Key Features

  • Contributions from leading authorities
  • Informs and updates on all the latest developments in the field


Cell and molecular biologists; neuroscientists


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© Academic Press 2014
Academic Press
eBook ISBN:
Hardcover ISBN:


Praise for the series:
"Full of interest not only for the molecular biologist-for whom the numerous references will be invaluable-but will also appeal to a much wider circle of biologists, and in fact to all those who are concerned with the living cell." --British Medical Journal

About the Serial Volume Editors

Kim Blackwell Serial Volume Editor

Affiliations and Expertise

Molecular Neuroscience Department, Krasnow Institute for Advanced Study, George Mason University, USA