Computing the Brain: A Guide to NeuroinformaticsMichael A. Arbib, Jeffrey S. Grethe Computing the Brain provides readers with an integrated view of current informatics research related to the field of neuroscience. This book clearly defines the new work being done in neuroinformatics and offers information on resources available on the Web to researchers using this new technology. It contains chapters that should appeal to a multidisciplinary audience with introductory chapters for the nonexpert reader. Neuroscientists will find this book an excellent introduction to informatics technologies and the use of these technologies in their research. Computer scientists will be interested in exploring how these technologies might benefit the neuroscience community. Key Features * An integrated view of neuroinformatics for a multidisciplinary audience * Explores and explains new work being done in neuroinformatics * Cross-disciplinary with chapters for computer scientists and neuroscientists * An excellent tool for graduate students coming to neuroinformatics research from diverse disciplines and for neuroscientists seeking a comprehensive introduction to the subject * Discusses, in-depth, the structuring of masses of data by a variety of computational models * Clearly defines computational neuroscience - the use of computational techniques and metaphors to investigate relations between neural structure and function * Offers a guide to resources and algorithms that can be found on the Web * Written by internationally renowned experts in the field |
From inside the book
Results 1-5 of 68
Page v
... Modules and Simulation 72 74 1.1.5 Data Management and Summary Databases 1.1.6 The NeuroInformatics Workbench 19 2.2.3 The NSL System 83 26 References 27 2.2.4 Simulating a Model - The Maximum Selector Model 2.2.5 Maximum Selector Model ...
... Modules and Simulation 72 74 1.1.5 Data Management and Summary Databases 1.1.6 The NeuroInformatics Workbench 19 2.2.3 The NSL System 83 26 References 27 2.2.4 Simulating a Model - The Maximum Selector Model 2.2.5 Maximum Selector Model ...
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Contents
PART | 5 |
CHAPTER 1 | 6 |
References | 13 |
References | 27 |
References | 38 |
231 | 67 |
Michael A Arbib 3 43 71 103 255 287 297 337 and Computer Science Department University | 68 |
Cyrus Shahabi 179 189 ern California Los Angeles California 900892520 | 71 |
2 | 239 |
1 | 245 |
References | 254 |
Abstract | 255 |
PART 4 | 278 |
2 | 293 |
247 | 299 |
References | 308 |
PART 3 | 72 |
Ying Shu 91 Xiaping Xie 91 117 | 91 |
PART 2 | 130 |
Richard F Thompson Jeffrey S Grethe Ted Berger | 169 |
Abstract | 179 |
137 | 200 |
References | 213 |
Rabi Simantov 217 Southern California Los Angeles California 90089 | 217 |
MODELING AND SIMULATION | 237 |
Storage Systems | 322 |
4 | 335 |
ATLASBASED DATABASES | 345 |
350 | |
343 | 363 |
APPENDIX | 369 |
372 | |
375 | |
Other editions - View all
Computing the Brain: A Guide to Neuroinformatics Michael A. Arbib,Jeffrey S. Grethe Limited preview - 2001 |
Common terms and phrases
activity allows anatomical annotations Arbib atlas level axon basal ganglia behavior Brain Maps brain regions brain structures Browser cerebellar cerebellar cortex cerebellum Chapter classical conditioning clump component database computational concepts connections contains cortex data model data types database model database system defined described developed display document dynamic example experiment experimental exported federated database systems federation fiber Figure function granule cell hippocampus homology implementation Informix input interaction interface layers Manager membrane ment microcomplex module monkey mossy fiber motor NeuARt neural network neuroanatomical neurochemical NeuroCore database Neuroinformatics neurons neuroscience objects ontology output parameters parietal protocol Purkinje cell query rat brain receptors Repositories represent retrieved saccade schema simulation slice spatial specific stored superior colliculus Swanson synaptic Synthetic PET tion uniqueID owner University of Southern USC Brain Project USCBP visual
Popular passages
Page 350 - Goldman-Rakic, PS (1989). Posterior parietal cortex in rhesus monkey. II. Evidence for segregated corticocortical networks linking sensory and limbic areas with the frontal lobe, journal of Comparative Neurology, 287, 422-445.
References to this book
Rough Set Theory: A True Landmark in Data Analysis Ajith Abraham,Rafael Falcón,Rafael Bello Limited preview - 2009 |