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Demonstrates the use of neuroinformatic components as a mechanism for understanding complex disorders, such as dementia, schizophrenia and Alzheimer’s
Detailed explanations, advantages, and disadvantages of traditional and non-invasive imaging methods
Neuroinformatics presents cutting-edge techniques for the synergistic study of neuroinformatics, thereby facilitating the efforts of discovery neuroscience through the sharing of data and the use of computational models. This volume provides the scientific community with the tools and impetus for sharing their research with colleagues around the globe by offering insights, information, and compelling examples of success. Nearly a decade and a half after the launch of the Human Brain Project, this timely volume will help to refocus and enhance current research by informing both new and current Neuroinformatics practitioners. Neuroinformatics is conceptually divided into four sections. The first, Neuroscience Knowledge Management, has outstanding chapters dealing with the critical issues germane to computer science as applied to neuroscience. The second section, Computational Neuronal Modeling and Simulations, presents in-depth expert summaries on specific computational models and simulations as well as approaches to data mining.
The third section, Imaging, focuses on informatics representation and approaches to the structural complexity of the brain using a variety of both traditional and non-invasive imaging methods. The final section, Neuroinformatics in Genetics and Neurodegenerative Diseases, demonstrate the value of using components of neuroinformatics as a way to understand the complex disorders of Dementia, Schizophrenia and Alzheimer’s disease. Neuroinformatics will be an essential text for all those interested in keeping up with the latest issues in neuroinformatics and/or learning about and joining this field of research.
Table of Contents
Neuroscience Knowledge Management
1. Managing Knowledge in Neuroscience
Chiquito J. Crasto and Gordon M. Shepherd
2. Interoperability across Neuroscience Databases
Luis Marenco, Prakash Nadkarni, Maryann Martone and Amarnath Gupta.
3. Database Architectures for Neuroscience Applications
Prakash Nadkarni and Luis Marenco
4. XML for Data Representation and Model Specification in Neuroscience
Sharon M. Crook and Fred W. Howell
5. Creating Neuroscience Ontologies
Douglas M. Bowden, Mark Dubach and Jack Park
Computational Neuronal Modeling and Simulation
6. Model structure analysis in NEURON: toward interoperability among
Michael L. Hines, Tom M. Morse and N. T. Carnevale
7. Constructing Realistic Neural Simulations with GENESIS
James M. Bower and David Beeman
8. Simulator for Neural Networks and Action Potentials (SNNAP):
Description and Applications
Douglas A. Baxter and John H. Byrne
9. Data-mining through simulation: introduction to the Neural Query
William W. Lytton and Mark Stewart
10. Computational exploration of neuron and neural network models in
11. Brain Atlases and Neuroanatomic Imaging
Allan MacKenzie-Graham, Jyl Boline and Arthur W. Toga
12. Brain Mapping with High-Resolution fMRI Technology
13. Brain Spatial Normalization: Indexing Neuroanatomical Databases
William Bug, Carl Gustafson, Allon Shahar, Smadar Gefen, Yingli Fan,
Louise Bertrand and Jonathan Nissanov
14. Workflow Based Approaches to Neuroimaging Analysis
Kate Fissell, MS
15. Databasing receptor distributions in the brain
Rolf Kötter, Jürgen Maier, Karl Zilles, Axel Scheicher and Ahmet Bozkurt
Neuroinformatics in Genetics and Neurodenegerative Disorders
16. An Informatics approach to SystemsNeurogenetics
Glenn D. Rosen, Elissa J. Chesler, Kenneth F. Manly and Robert W.
17. Computational Models of Dementia and Neurological Problems
18. Integrating genetic, functional genomic, and bioinformatics data in
a systems biology approach to complex diseases: application to
Middleton FA, Rosenow C, Vailaya A, Kuchinsky A, Pato MT and Pato CN
19. Alzforum: E-Science for Alzheimer Disease
June Kinoshita and Timothy Clark