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.

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.

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 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.

It seems particularly appropriate that this pioneering collection of papers should be dedicated to Donald Sholl since those of us who count, measure, and reconstruct elements of the neural en~emble are all very much in his debt. Sholl was certainly not the first to attempt quantification of certain aspects of brain structure. No computers were available to him for the kind of answers he sought, and some of his answers - or rather his interpretations - may not stand the test of time. But we remember him because of the questions he asked and for the reasons he asked them. At a time when the entire family of Golgi techniques was in almost total eclipse, he had the judgment to rely on them. And in a period when the canonical neuron was a perfect sphere (the enormous dendritic superstructure being almost forgotten), he was one of a very few who looked to dendrite extension and pattern as a prime clue to the overall problem of neuronal connectivity.

The novelty of this book's approach lies in addressing the impact of neurobiological factors as well as psychological influences on brain recovery. There is growing evidence that emotional, motivational, and cognitive factors along with personality traits play a crucial role in brain plasticity, resilience, and recovery. Topics include synaptic and neuronal plasticity, development of brain reserves, biological markers, environmental factors, psychological profile, emotional resilience, and personality traits. By combining the latest research on neural mechanisms and on psychological resilience the authors hope that this book can lead to the development of better treatment strategies for functional recovery from brain damage.

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.

As science continues to advance, researchers are continually gaining new insights into the way living beings behave and function, and into the composition of the smallest molecules. Most of these biological processes have been imitated by many scientific disciplines with the purpose of trying to solve different problems, one of which is artificial intelligence. Advancing Artificial Intelligence through Biological Process Applications presents recent advances in the study of certain biological processes related to information processing that are applied to artificial intelligence. Describing the benefits of recently discovered and existing techniques to adaptive artificial intelligence and biology, this book will be a highly valued addition to libraries in the neuroscience, molecular biology, and behavioral science spheres.