Hippocampal Microcircuits: A Computational Modeler's Resource Book

Citation

Cutsuridis V, Graham B, Cobb SR & Vida I (eds.) (2010) Hippocampal Microcircuits: A Computational Modeler's Resource Book. Springer Series in Computational Neuroscience, 5. New York: Springer. http://link.springer.com/book/10.1007/978-1-4419-0996-1/page/1

Abstract
The hippocampus plays an indispensible role in the formation of new memories in the mammalian brain. It is the focus of intense research and our understanding of its physiology, anatomy, and molecular structure has rapidly expanded in recent years. Yet, still much needs to be done to decipher how hippocampal microcircuits are built and function. Here, we present an overview of our current knowledge and a snapshot of ongoing research into these microcircuits. Rich in detail, Hippocampal Microcircuits: A Computational Modeler's Resource Book provides focused and easily accessible reviews on various aspects of the theme. It is an unparalleled resource of information, including both data and techniques that will be an invaluable companion to all those wishing to develop computational models of hippocampal neurons and neuronal networks. The book is divided into two main parts. In the first part, leading experimental neuroscientists discuss data on the electrophysiological, neuroanatomical, and molecular characteristics of hippocampal circuits. The various types of excitatory and inhibitory neurons are reviewed along with their connectivity and synaptic properties. Single cell and ensemble activity patterns are presented from in vitro models, as well as anesthetized and freely moving animals. In the second part, computational neuroscientists describe models of hippocampal microcircuits at various levels of complexity, from single neurons to large-scale networks. Additionally, a chapter is devoted to simulation environments currently used by computational neuroscientists in developing their models. In addition to providing concise reviews and a wealth of data, the chapters also identify central questions and unexplored areas that will define future research in computational neuroscience.