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. Written by a team of internationally renowned researchers Both print and enhanced e-book versions are available Illustrated in full colour throughout This is the fourth volume in a new Series 'Masterclass in Neuroendocrinology' , 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

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.* Written by a team of internationally renowned researchers* Both print and enhanced e-book versions are available* Illustrated in full colour throughoutThis is the fourth volume in a new Series 'Masterclass in Neuroendocrinology' , 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, viiSeries Preface, ixPreface, xiAbout the Companion Website, xv1 Bridging Between Experiments and Equations: A Tutorial on Modeling Excitability, 1David P. McCobb and Mary Lou Zeeman2 Ion Channels and Electrical Activity in Pituitary Cells: A Modeling Perspective, 80Richard Bertram, Joël Tabak, and Stanko S. Stojilkovic3 Endoplasmic Reticulum- and Plasma-Membrane-Driven Calcium Oscillations, 111Arthur Sherman4 A Mathematical Model of Gonadotropin-Releasing Hormone Neurons, 142James Sneyd, Wen Duan, and Allan Herbison5 Modeling Spiking and Secretion in the Magnocellular Vasopressin Neuron, 166Duncan J. MacGregor and Gareth Leng6 Modeling Endocrine Cell Network Topology, 206David J. Hodson, Francois Molino, and Patrice Mollard7 Modeling the Milk-Ejection Reflex, 227Gareth Leng and Jianfeng Feng8 Dynamics of the HPA Axis: A Systems Modeling Approach, 252John R. Terry, Jamie J. Walker, Francesca Spiga, and Stafford L. Lightman9 Modeling the Dynamics of Gonadotropin-Releasing Hormone (GnRH) Secretion in the Course of an Ovarian Cycle, 284Frédérique Clément and Alexandre VidalGlossary, 305Index, 315