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Quantitative Neuroscience : Models, Algorithms, Diagnostics, and Therapeutic Applications - Panos M. Pardalos

Quantitative Neuroscience

Models, Algorithms, Diagnostics, and Therapeutic Applications

By: Panos M. Pardalos (Editor), J.Chris Sackellares (Editor), Paul R. Carney (Editor), Leon. D. Iasemidis (Editor)

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Published: 1st January 2004
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Advances in the field of signal processing, nonlinear dynamics, statistics, and optimization theory, combined with marked improvement in instrumenta­ tion and development of computers systems, have made it possible to apply the power of mathematics to the task of understanding the human brain. This verita­ ble revolution already has resulted in widespread availability of high resolution neuroimaging devices in clinical as well as research settings. Breakthroughs in functional imaging are not far behind. Mathematical tech­ niques developed for the study of complex nonlinear systems and chaos already are being used to explore the complex nonlinear dynamics of human brain phys­ iology. Global optimization is being applied to data mining expeditions in an effort to find knowledge in the vast amount of information being generated by neuroimaging and neurophysiological investigations. These breakthroughs in the ability to obtain, store and analyze large datasets offer, for the first time, exciting opportunities to explore the mechanisms underlying normal brain func­ tion as well as the affects of diseases such as epilepsy, sleep disorders, movement disorders, and cognitive disorders that affect millions of people every year. Ap­ plication of these powerful tools to the study of the human brain requires, by necessity, collaboration among scientists, engineers, neurobiologists and clini­ cians. Each discipline brings to the table unique knowledge, unique approaches to problem solving, and a unique language.

Preface
Applications of Global Optimization and Dynamical Systems to Prediction of Epileptic Seizuresp. 1
Nonlinear Neurodynamical Features in an Animal Model of Generalized Epilepsyp. 37
Optimization Techniques for Independent Component Analysis with Applications to EEG Datap. 53
On a New Quantization in Complex Systemsp. 69
The Seizure Prediction Characteristicp. 91
Seizure Prediction Methodsp. 103
Controlling Neurological Disease at the Edge of Instabilityp. 117
Anatomical Connectivity in the Central Nervous System Revealed by Diffusion Tensor Magnetic Resonance Imaging (DT-MRI)p. 145
Epileptic Seizure Detection Using Dynamical Preprocessing (STLmax)p. 171
Role of the Dorsocentral Striatum in Contraleteral Neglect and Recovery from Neglect in Ratsp. 191
Binary and Sparse Checkerboard Visual Stimuli in Multiple Sclerosis Patientsp. 213
Spatiotemporal Transitions in Temporal Lobe Epilepsyp. 223
Nonlinear Dynamical and Statistical Approaches to Investigate Dynamical Transitions Before Epileptic Seizuresp. 239
Testing Whether a Prediction Scheme is Better than Guessp. 251
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9781402077517
ISBN-10: 1402077513
Series: Biocomputing
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 262
Published: 1st January 2004
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 23.5 x 15.5  x 1.91
Weight (kg): 0.58