Computational Neuroanatomy


Book Description

Computational neuroanatomy is an emerging field that utilizes various non-invasive brain imaging modalities, such as MRI and DTI, in quantifying the spatiotemporal dynamics of the human brain structures in both normal and clinical populations. This discipline emerged about twenty years ago and has made substantial progress in the past decade. The main goals of this book are to provide an overview of various mathematical, statistical and computational methodologies used in the field to a wide range of researchers and students, and to address important yet technically challenging topics in further detail.




Computational Neuroanatomy


Book Description

In Computational Neuroanatomy: Principles and Methods, the path-breaking investigators who founded the field review the principles and key techniques available to begin the creation of anatomically accurate and complete models of the brain. Combining the vast, data-rich field of anatomy with the computational power of novel hardware, software, and computer graphics, these pioneering investigators lead the reader from the subcellular details of dendritic branching and firing to system-level assemblies and models.




Statistical and Computational Methods in Brain Image Analysis


Book Description

The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLAB® and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author’s website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics.







Principles of Computational Modelling in Neuroscience


Book Description

Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.




Brain Network Analysis


Book Description

This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.




Research Methods for Cognitive Neuroscience


Book Description

This fresh, new textbook provides a thorough and student-friendly guide to the different techniques used in cognitive neuroscience. Given the breadth of neuroimaging techniques available today, this text is invaluable, serving as an approachable text for students, researchers, and writers. This text provides the right level of detail for those who wish to understand the basics of neuroimaging and also provides more advanced material in order to learn further about particular techniques. With a conversational, student-friendly writing style, Aaron Newman introduces the key principles of neuroimaging techniques, the relevant theory and the recent changes in the field.




Computational Neuroanatomy: The Methods


Book Description

Computational neuroanatomy is an emerging field that utilizes various non-invasive brain imaging modalities, such as MRI and DTI, in quantifying the spatiotemporal dynamics of the human brain structures in both normal and clinical populations. This discipline emerged about twenty years ago and has made substantial progress in the past decade. The main goals of this book are to provide an overview of various mathematical, statistical and computational methodologies used in the field to a wide range of researchers and students, and to address important yet technically challenging topics in further detail.




Neuroanatomy of Language Regions of the Human Brain


Book Description

Many studies of the neural bases of language processes are now conducted with functional and structural neuroimaging. Research is often compromised because of difficulties in identifying the core structures in the face of the complex morphology of these regions of the brain. Although there are many books on the cognitive aspects of language and also on neurolinguistics and aphasiology, Neuroanatomy of Language Regions of the Human Brain is the first anatomical atlas that focuses on the core regions of the cerebral cortex involved in language processing. This atlas is a richly illustrated guide for scientists interested in the gross morphology of the sulci and gyri of the core language regions, in the cytoarchitecture of the relevant cortical areas, and in the connectivity of these areas. Data from diffusion MRI and resting-state connectivity are integrated iwth critical experimental anatomical data about homologous areas in the macaque monkey to provide the latest information on the connectivity of the language-relevant cortical areas of the brain. Although the anatomical connectivity data from studies on the macaque monkey provide the most detailed information, they are often neglected because of difficulties in interpreting the terminology used and in making the monkey-to-human comparison. This atlas helps investigators interpret this important source of information. Neuroanatomy of Language Regions of the Human Brain will assist investigators of the neural bases of language in increasing the anatomical sophistication of their research adn in evaluating studies of language and the brain. - Abundantly illustrated with photographs, 3-D MRI reconstructions, and sections to represent the morphology of the sulci and gyri in the frontal, temporal, and parietal regions involved in language processing - Photomicrographs showing the cytoarchitecture of cortical areas involved in language processing - Series of coronal, sagittal, and horizontal sections identifying the sulci and gyri to assist language investigators using structural and functional neuroimaging techniques - All images accompanied by brief commentaries to help users navigate the complexities of the anatomy - Integration of data from diffusion MRI and resting-state connectivity with critical experimental anatomical data on the connectivity of homologous areas in the macaque monkey




The Computing Dendrite


Book Description

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.