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Computational Neuroscience - 1st Edition - ISBN: 9780123978974, 9780123979087

Computational Neuroscience, Volume 123

1st Edition

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Serial Volume Editor: 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 Concluding Remarks
    • Acknowledgments
  • Chapter Six: Mathematical Modeling of Neuronal Polarization During Development
    • Abstract
    • 1 Biological Background
    • 2 Biophysical Model
    • 3 Mathematical Analysis
    • 4 Mechanism of Neuronal Polarization
    • 5 Discussion
    • Acknowledgments
  • Chapter Seven: Multiscale Modeling of Cell Shape from the Actin Cytoskeleton
    • Abstract
    • 1 Introduction
    • 2 Cell Spreading
    • 3 Actin Cytoskeleton
    • 4 Biochemical Signaling to the Actin Cytoskeleton
    • 5 Different Approaches for Computationally Modeling the Actin Cytoskeleton
    • 6 Computational Geometry Approach for Modeling Cell Spreading
    • 7 Computational Implementation
    • 8 Comparison of Experiments and Simulated Cell Spreading
    • 9 Conclusions and Perspectives
    • Acknowledgments
  • Chapter Eight: Computational Modeling of Diffusion in the Cerebellum
    • Abstract
    • 1 Introduction
    • 2 Diffusion in the Cerebellum
    • 3 Diffusion: Theory
    • 4 Modeling Diffusion
    • 5 Summary
    • Acknowledgments
  • Chapter Nine: Astrocyte–Neuron Interactions: From Experimental Research-Based Models to Translational Medicine
    • Abstract
    • 1 Introduction
    • 2 Models and Simulations of Cells and Networks
    • 3 Computational Models of Astrocyte–Neuron Interactions in Information Processing
    • 4 Toward Understanding Brain Disorders Using Computational Models Involving Astrocyte–Neuron Interactions
    • 5 Conclusions
    • Acknowledgment
  • Chapter Ten: Dynamic Metabolic Control of an Ion Channel
    • Abstract
    • 1 Background and History of Channel Modulation and KCNQ Current
    • 2 Modeling Approach
    • 3 Modeling Receptor and G-Protein Activation
    • 4 Activation of PLC, Modulation of Channels, and Deactivation of G-Proteins
    • 5 PLC Messengers
    • 6 Phosphoinositide Metabolism and Compartments
  • Chapter Eleven: Modeling Molecular Pathways of Neuronal Ischemia
    • Abstract
    • 1 Critical Initiator Events in Ischemic Pathways
    • 2 Models of Molecular Pathways in Ischemia
    • 3 Pitfalls and Outlook
  • Chapter Twelve: Modeling Intracellular Signaling Underlying Striatal Function in Health and Disease
    • Abstract
    • 1 Introduction
    • 2 Modeling Biochemical Reaction Cascades
    • 3 A Modeling Example
    • 4 Subcellular Models Representing Striatal Signaling
    • 5 The Way Forward: Multiscale Modeling and Data Integration
    • Acknowledgments
  • Chapter Thirteen: Data-Driven Modeling of Synaptic Transmission and Integration
    • Abstract
    • 1 Introduction
    • 2 Constructing Synaptic Conductance Waveforms from Voltage-Clamp Recordings
    • 3 Empirical Models of Voltage-Dependent Mg2 + Block of the NMDA Receptor
    • 4 Construction of Presynaptic Spike Trains with Refractoriness and Pseudo-Random Timing
    • 5 Synaptic Integration in a Simple Conductance-Based Integrate-and-Fire Neuron
    • 6 Short-Term Synaptic Depression and Facilitation
    • 7 Simulating Trial-to-Trial Stochasticity
    • 8 Going Microscopic
    • 9 Simulators and Standardized Model Descriptions
    • 10 Summary
    • Acknowledgments
  • Chapter Fourteen: Multiscale Modeling and Synaptic Plasticity
    • Abstract
    • 1 Introduction
    • 2 Events in Synaptic Plasticity
    • 3 Multiscale Processes in Plasticity
    • 4 Numerical Frameworks for Multiscale Modeling in Plasticity
    • 5 Multiscale Model Specification
    • 6 Conclusion
  • Index


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


No. of pages:
© Academic Press 2014
4th March 2014
Academic Press
Hardcover ISBN:
eBook 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

Ratings and Reviews

About the Serial Volume Editor

Kim Blackwell

Affiliations and Expertise

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