This collection of fifteen previously published papers, some of them not widely available, have been carefully chosen and annotated by Rall's colleagues and other leading neuroscientists. Wilfrid Rall was a pioneer in establishing the integrative functions of neuronal dendrites that have provided a foundation for neurobiology in general and computational neuroscience in particular. This collection of fifteen previously published papers, some of them not widely available, have been carefully chosen and annotated by Rall's colleagues and other leading neuroscientists. It brings together Rall's work over more than forty years, including his first papers extending cable theory to complex dendritic trees, his ground-breaking paper introducing compartmental analysis to computational neuroscience, and his studies of synaptic integration in motoneurons, dendrodendritic interactions, plasticity of dendritic spines, and active dendritic properties. Today it is well known that the brain's synaptic information is processed mostly in the dendrites where many of the plastic changes underlying learning and memory take place. It is particularly timely to look again at the work of a major creator of the field, to appreciate where things started and where they have led, and to correct any misinterpretations of Rall's work. The editors' introduction highlights the major insights that were gained from Rall's studies as well as from those of his collaborators and followers. It asks the questions that Rall proposed during his scientific career and briefly summarizes the answers.

This collection of fifteen previously published papers, some of them not widely available, have been carefully chosen and annotated by Rall's colleagues and other leading neuroscientists.

Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation.Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.

This volume offers an up-to-date overview of essential concepts and modern approaches to computational modelling, including the use of experimental techniques related to or directly inspired by them. The book introduces, at increasing levels of complexity and with the non-specialist in mind, state-of-the-art topics ranging from single-cell and molecular descriptions to circuits and networks. Four major themes are covered, including subcellular modelling of ion channels and signalling pathways at the molecular level, single-cell modelling at different levels of spatial complexity, network modelling from local microcircuits to large-scale simulations of entire brain areas and practical examples. Each chapter presents a systematic overview of a specific topic and provides the reader with the fundamental tools needed to understand the computational modelling of neural dynamics. This book is aimed at experimenters and graduate students with little or no prior knowledge of modelling who are interested in learning about computational models from the single molecule to the inter-areal communication of brain structures. The book will appeal to computational neuroscientists, engineers, physicists and mathematicians interested in contributing to the field of neuroscience. Chapters 6, 10 and 11 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Since the 1970s the cognitive sciences have offered multidisciplinary ways of understanding the mind and cognition. The MIT Encyclopedia of the Cognitive Sciences (MITECS) is a landmark, comprehensive reference work that represents the methodological and theoretical diversity of this changing field. At the core of the encyclopedia are 471 concise entries, from Acquisition and Adaptationism to Wundt and X-bar Theory. Each article, written by a leading researcher in the field, provides an accessible introduction to an important concept in the cognitive sciences, as well as references or further readings. Six extended essays, which collectively serve as a roadmap to the articles, provide overviews of each of six major areas of cognitive science: Philosophy; Psychology; Neurosciences; Computational Intelligence; Linguistics and Language; and Culture, Cognition, and Evolution. For both students and researchers, MITECS will be an indispensable guide to the current state of the cognitive sciences.

An understanding of the nervous system at virtually any level of analysis requires an understanding of its basic building block, the neuron. From Molecules to Networks provides the solid foundation of the morphologic, biochemical, and biophysical properties of nerve cells. All chapters have been thoroughly revised for this second edition to reflect the significant advances of the past 5 years. The new edition expands on the network aspects of cellular neurobiology by adding a new chapter, Information Processing in Neural Networks, and on the relation of cell biological processes to various neurological diseases. The new concluding chapter illustrates how the great strides in understanding the biochemical and biophysical properties of nerve cells have led to fundamental insights into important aspects of neurodegenerative disease. - Written and edited by leading experts in the field, the second edition completely and comprehensively updates all chapters of this unique textbook - Discusses emerging new understanding of non-classical molecules that affect neuronal signaling - Full colour, professional graphics throughout - Includes two new chapters: Information Processing in Neural Networks - describes the principles of operation of neural networks and the key circuit motifs that are common to many networks in the nervous system. Molecular and Cellular Mechanisms of Neurodegenerative Disease - introduces the progress made in the last 20 years in elucidating the cellular and molecular mechanisms underlying brain disorders, including Amyotrophic Lateral Sclerosis (ALS), Parkinson disease, and Alzheimer's disease

With contributions from more than 40 renowned experts, Modeling in the Neurosciences: From Ionic Channels to Neural Networks is essential for those interested in neuronal modeling and quantitative neiroscience. Focusing on new mathematical and computer models, techniques and methods, this monograph represents a cohesive and comprehensive treatment