Computational Neuroscience / Edition 1

Computational Neuroscience / Edition 1

ISBN-10:
038788629X
ISBN-13:
9780387886299
Pub. Date:
05/12/2010
Publisher:
Springer New York
ISBN-10:
038788629X
ISBN-13:
9780387886299
Pub. Date:
05/12/2010
Publisher:
Springer New York
Computational Neuroscience / Edition 1

Computational Neuroscience / Edition 1

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Overview

Springer Optimization and its Applications publishes undergraduate and graduate textbooks, monographs and state-of-the-art expository works that focus on algorithms for solving optimization problems and applications involving such problems. Some of the topics include optimization, network flow problems, optimal control, multi-objective programming, approximation and heuristic approaches.

The human brain is among the most complex systems known to mankind. Neuroscientists seek to understand brain function through detailed analysis of neuronal excitability and synaptic transmission. Only in the last few years has it become feasible to capture simultaneous responses from a large enough number of neurons to empirically test the theories of human brain function computationally. This book is comprised of state-of-the-art experiments and computational techniques that provide new insights and improve our understanding of the human brain.

This volume includes contributions from diverse disciplines including electrical engineering, biomedical engineering, industrial engineering, and medicine, bridging a vital gap between the mathematical sciences and neuroscience research. Covering a wide range of research topics, this volume demonstrates how various methods from data mining, signal processing, optimization and cutting-edge medical techniques can be used to tackle the most challenging problems in modern neuroscience.

The results presented in this book are of great interest and value to scientists, graduate students, researchers and medical practitioners interested in the most recent developments in computational neuroscience.


Product Details

ISBN-13: 9780387886299
Publisher: Springer New York
Publication date: 05/12/2010
Series: Springer Optimization and Its Applications , #38
Edition description: 2010
Pages: 396
Product dimensions: 6.30(w) x 9.20(h) x 1.00(d)

Table of Contents

Part I Data Mining

1 Optimization in Reproducing Kernel Hilbert Spaces of Spike Trains António R. C. Paiva Il Park José C. Príncipe 3

2 Investigating Functional Cooperation in the Human Brain Using Simple Graph-Theoretic Methods Michael L. Anderson Joan Brumbaugh Aysu Suben 31

3 Methodological Framework for EEG Feature Selection Based on Spectral and Temporal Profiles Vangelis Sakkalis Michalis Zervakis 43

4 Blind Source Separation of Concurrent Disease-Related Patterns from EEG in Creutzfeldt-Jakob Disease for Assisting Early Diagnosis Chih-I Hung Po-Shan Wang Bing-Wen Soong Shin Teng Jen-Chuen Hsieh Yu-Te Wu 57

5 Comparison of Supervised Classification Methods with Various Data Preprocessing Procedures for Activation Detection in fMRI Data Mahdi Ramezani Emad Fatemizadeh 75

6 Recent Advances of Data Biclustering with Application in Computational Neuroscience Neng Fan Nikita Boyko Panos M. Pardalos 85

7 A Genetic Classifier Account for the Regulation of Expression Tsvi Achler Eyal Amir 113

Part II Modeling

8 Neuroelectromagnetic Source Imaging of Brain Dynamics Rey R. Ramírez David Wipf Sylvain Baillet 127

9 Optimization in Brain? - Modeling Human Behavior and Brain Activation Patterns with Queuing Network and Reinforcement Learning Algorithms Changxu Wu Marc Berman Yili Liu 157

10 Neural Network Modeling of Voluntary Single-Joint Movement Organization I. Normal Conditions Vassilis Cutsuridis 181

11 Neural Network Modeling of Voluntary Single-Joint Movement Organization II. Parkinson's Disease Vassilis Cutsuridis 193

12 Parametric Modeling Analysis of Optical Imaging Data on Neuronal Activities in the Brain Shigeharu Kawai Yositaka Oku Yasumasa Okada Fumikazu Miwakeichi Makio Ishiguro Yoshiyasu Tamura 213

13 Advances Toward Closed-Loop Deep Brain Stimulation Stathis S. Leondopulos Evangelia Micheli-Tzanakou 227

14 Molecule-Inspired Methods for Coarse-Grain Multi-System Optimization Max H. Garzon Andrew J. Neel 255

Part III Brain Dynamics/Synchronization

15 A Robust Estimation of Information Flow in Coupled Nonlinear Systems Shivkumar Sabesan Konstantinos Tsakalis Andreas Spanias Leon Iasemidis 271

16 An Optimization Approach for Finding a Spectrum of Lyapunov Exponents Panos M. Pardalos Vitaliy A. Yatsenko Alexandre Messo Altannar Chinchuluun Petros Xanthopoulos 285

17 Dynamical Analysis of the EEG and Treatment of Human Status Epilepticus by Antiepileptic Drugs Aaron Faith Shivkumar Sabesan Norman Wang David Treiman Joseph Sirven Konstantinos Tsakalis Leon Iasemidis 305

18 Analysis of Multichannel EEG Recordings Based on Generalized Phase Synchronization and Cointegrated VAR Alla R. Kammerdiner Panos M. Pardalos 317

19 Antiepileptic Therapy Reduces Coupling Strength Among Brain Cortical Regions in Patients with Unverricht-Lundborg Disease: A Pilot Study Chang-Chia Liu Petros Xanthopoulos Vera Tomaino Kazutaka Kobayashi Basim M. Uthman Panos M. Pardalos 341

20 Seizure Monitoring and Alert System for Brain Monitoring in an Intensive Care Unit J. Chris Sackellares Deng-Shan Shiau Alla R. Kammerdiner Panos M. Pardalos 357

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