Hippocampal microcircuits: a computational modeler's sourcebook (Series in computational neuroscience) with CD-ROM, 2010 A Computational Modeler's Resource Book Springer Series in Computational Neuroscience Series, Vol. 5

The hippocampus is thought to play a role in the short-term storage of declarative memories in the human brain. Our understanding of its anatomy, physiology and molecular structure has expanded rapidly in recent years. Yet much still needs to be done to decipher the function of the detailed microcircuits. This overview of our current knowledge of the hippocampus also provides a snapshot of the state of the art of ongoing research into these microcircuits. Rich in detail, Hippocampal Microcircuits: A Computational Modeler's Resource Book provides succinct and focused reviews of experimental results. It is an unparalleled resource of data and methodology that will be invaluable to anyone wishing to develop computational models of the microcircuits of the hippocampus. The editors have divided the material into two thematic areas. Covering the subject's experimental background, leading neuroscientists discuss the morphological, physiological and molecular characteristics as well as the connectivity and synaptic properties of the various cell types found in the hippocampus. Here, ensemble activity, related to behavior, on the part of morphologically identified neurons in anesthetized and freely moving animals, lead to insights into the functions of hippocampal areas. In the second section, on computational analysis, computational neuroscientists present models of hippocampal microcircuits at various levels of detail, including single-cell and network levels. A full chapter is devoted to the single-neuron and network simulation environments currently used by computational neuroscientists in developing their models. In addition to the above, the chapters also identify outstanding questions and areas in need of further clarification that will guide future research by computational neuroscientists.

Preface Part I 1. Introduction-Experimental background 2. Connectivity of the hippocampus 3. Cell morphologies 4. Physiological properties of hippocampal neurons 5. Glutamatergic neurotransmission in the hippocampus 6. Fast and slow GABAergic transmission in hippocampal circuits 7. Synaptic plasticity at hippocampal synapses 8. Neuromodulation of hippocampal cells and circuits 9. Neuronal Activity Patterns during Hippocampal Network Oscillations in Vitro 10. Neuronal Activity Patterns of Anaesthetized Animals 11. Spatial and behavioral correlates of hippocampal neuronal activity: A primer for computational analysis Part II 12. Introduction-Computational Analysis 13. The making of a detailed CA1 pyramidal neuron model 14. CA3 cells: Detailed and simplified pyramidal cell models 15. Entorhinal cortex cells 16. Single Neuron Models: Interneurons 17. Gamma and Theta Rhythms in Biophysical Models of Hippocampal Circuits 18. Associative memory models 19. Microcircuit model of the dentate gyrus in epilepsy 20. Multi-level models 21. Biophysics-based models of LTP/LTD 22. A phenomenological calcium-based model of STDP 23. Computer simulation environments

From the reviews:'Chapters offer a treasure trove of useful up-to-date and timely information, and extensive references, that should be valuable for those who model, and also for those who do not. ... In summary, this book was intended to provide a set of resources, I think the Editors and the chapter authors have done an excellent job at achieving this goal.' (Roger D. Traub, Hippocampus, 2010)'Hippocampal microcircuits: a computational modelers resource book serves to ease the process of mastering the literature within one of the most productive and active fields of neuroscience. ... the book contains accessible and comprehensive reviews of experimental data on the hippocampus. ... This book will prove highly valuable as a resource both for expert modelers as well as for new researcher constructing their first model of hippocampal cells and circuits.' (Michael E. Hasselmo, Frontiers in Computational Neuroscience, Vol. 5 (2), January, 2011)