Data Mining.- Optimization in Reproducing Kernel Hilbert Spaces of Spike Trains.- Investigating Functional Cooperation in the Human Brain Using Simple Graph-Theoretic Methods.- Methodological Framework for EEG Feature Selection Based on Spectral and Temporal Profiles.- Blind Source Separation of Concurrent Disease-Related Patterns from EEG in Creutzfeldt-Jakob Disease for Assisting Early Diagnosis.- Comparison of Supervised Classification Methods with Various Data Preprocessing Procedures for Activation Detection in fMRI Data.- Recent Advances of Data Biclustering with Application in Computational Neuroscience.- A Genetic Classifier Account for the Regulation of Expression.- Modeling.- Neuroelectromagnetic Source Imaging of Brain Dynamics.- Optimization in Brain? - Modeling Human Behavior and Brain Activation Patterns with Queuing Network and Reinforcement Learning Algorithms.- Neural Network Modeling of Voluntary Single-Joint Movement Organization I. Normal Conditions.- Neural Network Modeling of Voluntary Single-Joint Movement Organization II. Parkinson's Disease.- Parametric Modeling Analysis of Optical Imaging Data on Neuronal Activities in the Brain.- Advances Toward Closed-Loop Deep Brain Stimulation.- Molecule-Inspired Methods for Coarse-Grain Multi-System Optimization.- Brain Dynamics/Synchronization.- A Robust Estimation of Information Flow in Coupled Nonlinear Systems.- An Optimization Approach for Finding a Spectrum of Lyapunov Exponents.- Dynamical Analysis of the EEG and Treatment of Human Status Epilepticus by Antiepileptic Drugs.- Analysis of Multichannel EEG Recordings Based on Generalized Phase Synchronization and Cointegrated VAR.- Antiepileptic Therapy Reduces Coupling Strength Among Brain Cortical Regions in Patients with Unverricht-Lundborg Disease: A Pilot Study.- Seizure Monitoring and Alert System for Brain Monitoring in an Intensive Care Unit.
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.
Presents major results and latest trends in the field of computational neuroscience
Provides a collection of selected contributions giving a state-of-the-art account of recent developments in the field
Includes chapters written by experts in their respective disciplines