Computational neuroscience

Part I Data Mining 1 Optimization in Reproducing Kernel Hilbert Spaces of Spike Trains. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Ant´onio R. C. Paiva, Il Park, and Jos´e C. Pr´ıncipe 2 Investigating Functional Cooperation in the Human Brain Using Simple Graph-Theoretic Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Michael L. Anderson, Joan Brumbaugh, and Aysu S¸uben 3 Methodological Framework for EEG Feature Selection Based on Spectral and Temporal Profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Vangelis Sakkalis and Michalis Zervakis 4 Blind Source Separation of Concurrent Disease-Related Patterns from EEG in Creutzfeldt–Jakob Disease for Assisting Early Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Chih-I Hung, Po-Shan Wang, Bing-Wen Soong, Shin Teng, Jen-Chuen Hsieh, and Yu-Te Wu 5 Comparison of Supervised Classification Methods with Various Data Preprocessing Procedures for Activation Detection in fMRI Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Mahdi Ramezani and Emad Fatemizadeh 6 Recent Advances of Data Biclustering with Application in Computational Neuroscience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Neng Fan, Nikita Boyko, and Panos M. Pardalos 7 A Genetic Classifier Account for the Regulation of Expression . . . . . . 113 Tsvi Achler and Eyal Amir Part II Modeling 8 Neuroelectromagnetic Source Imaging of Brain Dynamics . . . . . . . . . 127 Rey R. Ram´ırez, David Wipf, and Sylvain Baillet 9 Optimization in Brain? – Modeling Human Behavior and Brain Activation Patterns with Queuing Network and Reinforcement Learning Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Changxu Wu, Marc Berman, and Yili Liu 10 Neural Network Modeling of Voluntary Single-Joint Movement Organization I. Normal Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 Vassilis Cutsuridis 11 Neural Network Modeling of Voluntary Single-Joint Movement Organization II. Parkinson’s Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Vassilis Cutsuridis 12 Parametric Modeling Analysis of Optical Imaging Data on Neuronal Activities in the Brain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Shigeharu Kawai, Yositaka Oku, Yasumasa Okada, Fumikazu Miwakeichi, Makio Ishiguro, and Yoshiyasu Tamura 13 Advances Toward Closed-Loop Deep Brain Stimulation . . . . . . . . . . . 227 Stathis S. Leondopulos and Evangelia Micheli-Tzanakou 14 Molecule-Inspired Methods for Coarse-Grain Multi-System Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Max H. Garzon and Andrew J. Neel Part III Brain Dynamics/Synchronization 15 A Robust Estimation of Information Flow in Coupled Nonlinear Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 Shivkumar Sabesan, Konstantinos Tsakalis, Andreas Spanias, and Leon Iasemidis 16 An Optimization Approach for Finding a Spectrum of Lyapunov Exponents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 Panos M. Pardalos, Vitaliy A. Yatsenko, Alexandre Messo, Altannar Chinchuluun, and Petros Xanthopoulos 17 Dynamical Analysis of the EEG and Treatment of Human Status Epilepticus by Antiepileptic Drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 Aaron Faith, Shivkumar Sabesan, Norman Wang, David Treiman, Joseph Sirven, Konstantinos Tsakalis, and Leon Iasemidis18 Analysis of Multichannel EEG Recordings Based on Generalized Phase Synchronization and Cointegrated VAR . . . . . . . . . . . . . . . . . . 317 Alla R. Kammerdiner and Panos M. Pardalos 19 Antiepileptic Therapy Reduces Coupling Strength Among Brain Cortical Regions in Patients with Unverricht–Lundborg Disease: A Pilot Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 Chang-Chia Liu, Petros Xanthopoulos, Vera Tomaino, Kazutaka Kobayashi, Basim M. Uthman, and Panos M. Pardalos 20 Seizure Monitoring and Alert System for Brain Monitoring in an Intensive Care Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 J. Chris Sackellares, Deng-Shan Shiau, Alla R. Kammerdiner, and Panos M. Pardalos