Neuronal dendritic trees are complex structures that endow the cell with powerful computing capabilities and allow for high neural interconnectivity. Studying the function of dendritic structures has a long tradition in theoretical neuroscience, starting with the pioneering work by Wilfrid Rall in the 1950s. Recent advances in experimental techniques allow us to study dendrites with a new perspective and in greater detail. The goal of this volume is to provide a résumé of the state-of-the-art in experimental, computational, and mathematical investigations into the functions of dendrites in a variety of neural systems. The book first looks at morphological properties of dendrites and summarizes the approaches to measure dendrite morphology quantitatively and to actually generate synthetic dendrite morphologies in computer models. This morphological characterization ranges from the study of fractal principles to describe dendrite topologies, to the consequences of optimization principles for dendrite shape. Individual approaches are collected to study the aspects of dendrite shape that relate directly to underlying circuit constraints and computation. The second main theme focuses on how dendrites contribute to the computations that neurons perform. What role do dendritic morphology and the distributions of synapses and membrane properties over the dendritic tree have in determining the output of a neuron in response to its input? A wide range of studies is brought together, with topics ranging from general to system-specific phenomena—some having a strong experimental component, and others being fully theoretical. The studies come from many different neural systems and animal species ranging from invertebrates to mammals. With this broad focus, an overview is given of the diversity of mechanisms that dendrites can employ to shape neural computations.

Dendrites form the major receiving part of neurons. This text presents a survey of knowledge on dendrites, from their morphology and development, through to their electrical chemical, and computational properties.

Dendrites are complex neuronal structures that receive and integrate synaptic input from other nerve cells. They therefore play a critical role in brain function. Although dendrites were discovered over a century ago, due to the development of powerful new techniques there has been a dramatic resurgence of interest in the properties and function of these beautiful structures. This is the third edition of the first book devoted exclusively to dendrites. It contains a comprehensive survey of the current state of dendritic research across a wide range of topics, from dendritic morphology, evolution, development, and plasticity through to the electrical, biochemical and computational properties of dendrites, and finally to the key role of dendrites in brain disease. The third edition has been thoroughly revised, with the addition of a number of new chapters and comprehensive updates or rewrites of existing chapters by leading experts. "Dendrites" will be of interest to researchers and students in neuroscience and related fields, as well as to anyone interested in how the brain works.

This volume presents the growth of macrostructures in first-order nonequilibrium phase transitions in physical, chemical and biological multicomponent systems. Nonequilibrium thermodynamics and modern problems of crystallization synergetics are discussed. An introduction to computer physics of dendrites is also given. Wonderful variety in growth structures appears to be the consequence of different nonequilibrium alloy crystallization conditions and concerns problems of crystallization synergetics. This book has computer simulation results of the origin and development of the observed variety of primary macroscopic growth structures — cells, dendrites and grains should be regarded as one of the fundamental problems of alloy crystallization. Special attention is paid to the physical nature of phenomena of dendrite formation in alloys.

The two-volume set LNAI 11288 and 11289 constitutes the proceedings of the 17th Mexican International Conference on Artificial Intelligence, MICAI 2018, held in Guadalajara, Mexico, in October 2018. The total of 62 papers presented in these two volumes was carefully reviewed and selected from 149 submissions. The contributions are organized in topical as follows: Part I: evolutionary and nature-inspired intelligence; machine learning; fuzzy logic and uncertainty management. Part II: knowledge representation, reasoning, and optimization; natural language processing; and robotics and computer vision.

This book is the story of the marriage of a new techl}ology, computers, with an old problem, the study of neuroanatomical structures using the light microscope. It is aimed toward you, the neuroanatomist, who until now have used computers primarily for word processing but now wish to use them also to collect and analyze your laboratory data. Mter reading the book, you will be better equipped to use a computer system for data collection and analysis, to employ a programmer who might develop a system for you, or to evaluate the systems available in the marketplace. To start toward this goal, a glossary first presents commonly used terms in computer assisted neuroanatomy. This, on its own, will aid you as it merges the jargon of the two different fields. Then, Chapter 1 presents a historical review to describe the manual tasks involved in presenting and measuring anatomic structures. This review lays a base line of the tasks that were done before computers and the amount of skill and time needed to perform the tasks. In Chapters 2 and 3, you will find basic information about laboratory computers and programs to the depth required for you to use the machines easily and talk with some fluency to computer engineers, programmers, and salesmen. Chapters 4, 5, and 6 present the use of computers to reconstruct anatomic structures, i.e., to enter them into a computer memory, where they are later displayed and analyzed.

Methods in Neurosciences, Volume 10: Computers and Computations in the Neurosciences discusses the use of computers in the neurosciences. The book deals with data collection, analysis, and modeling, with emphasis on the use of computers. Section I involves data collection using a personal microcomputer system. One paper presents a tutorial on using a PC-based motor control composed of an electronic circuit to adjust the motion of a light microscope stage through a software program. Other papers discuss computer methods in nuclei cartography and a computer-assisted quantitative receptor autoradiography in studying receptor density distribution. Section II deals with data analysis and some computer programs for kinetic modeling of gene expression in neurons. The book also discusses a computerized analysis of opioid receptor heterogeneity by ligand binding in test animals using computerized programs instead of employing manual or graphical methods. Computerized curve-fitting allows the researcher to utilize a more precise mathematical model to describe the binding of one ligand to one class of sites. Section III evaluates data modeling and simulations and describes the practicality of using computers to design model ion channels. Another paper discusses a graphical interaction program called MEMPOT to simulate an electrophysiological investigation of the properties of the membrane potential in stimulated cells. The book also presents a quantitative data gathered from computer simulation of the factors that affect neuronal density per measured sections. The book is suitable for microbiologists, biochemists, neuroscientists, and researchers in the field of medical research, as well as for advanced computer programmers in medical research work.