Computational Neuroendocrinology

Neuroendocrinology with its well defined functions, inputs, and outputs, is one of the most fertile grounds for computational modeling in neuroscience. But modeling is often seen as something of a dark art. This book aims to display the power of modeling approaches in neuroendocrinology, and to showcase its potential for understanding these complex systems.
 
A recurring theme in neuroendocrinology is rhythms.  How are rhythms generated, and what purpose do they serve? Are these two questions inextricably intertwined? 

This book is written for innocents, presuming no math beyond high school or computing beyond calculators. It seeks to lead the curious into the thinking of the modeler, providing the tools to the reader to understand models, and even develop their own, giving life to paper diagrams. The diverse chapters, from ion channels to networks, systems, and hormonal rhythms, each tell the story of a model serving to join the hard won dots of experimentation, mapping a new understanding, and revealing hidden knowledge.

This is the third volume in the Masterclass in Neuroendocrinology Series, a co–publication between Wiley and the INF (International Neuroendocrine Federation) that aims to illustrate highest standards and encourage the use of the latest technologies in basic and clinical research and hopes to provide inspiration for further exploration into the exciting field of neuroendocrinology.

Series Editors: John A. Russell, University of Edinburgh, UK
and William E. Armstrong, The University of Tennessee, USA

List of Contributors

Series Preface

About the Companion Website

1. Bridging Between Experiments and Equations: A Tutorial on Modeling Excitability (David McCobb and Mary Lou Zeeman)

2. Ion Channels and Electrical Activity in Pituitary Cells: A Modeling Perspective (Richard Bertram, Joël Tabak and Stanko S. Stojilkovic)

3. Endoplasmic Reticulum– and Plasma Membrane–Driven Calcium Oscillations (Arthur Sherman)

4. Mathematical Models of GnRH Neurons (James Sneyd)

5. Modeling Spiking in the Magnocellular Vasopressin Neuron (Duncan J. MacGregor and Gareth Leng)

6. Modeling Endocrine Cell Network Topology (David J. Hodson, Francois Molino and Patrice Mollard)

7. Modelling the Milk–Ejection Reflex (Gareth Leng and Jianfeng Feng)

8. Dynamics of the HPA Axis: A Systems Modelling Approach (John R. Terry, Jamie J. Walker, Francesca Spiga and Stafford L. Lightman)

9. Modeling the Dynamics of Gonadotropin–Releasing Hormone (GnRH) Secretion in the Course of an Ovarian Cycle (Frédérique Clément and Alexandre Vidal)

Glossary

Index