Computational Neuroscience

  • Wanpracha Chaovalitwongse
  • Panos M. Pardalos
  • Petros Xanthopoulos

Part of the Springer Optimization and Its Applications book series (SOIA, volume 38)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Data Mining

  3. Modeling

    1. Front Matter
      Pages 125-125
    2. Rey R. Ramírez, David Wipf, Sylvain Baillet
      Pages 127-155
    3. Shigeharu Kawai, Yositaka Oku, Yasumasa Okada, Fumikazu Miwakeichi, Makio Ishiguro, Yoshiyasu Tamura
      Pages 213-225
    4. Stathis S. Leondopulos, Evangelia Micheli-Tzanakou
      Pages 227-253
    5. Max H. Garzon, Andrew J. Neel
      Pages 255-267
  4. Brain Dynamics/Synchronization

    1. Front Matter
      Pages 269-269
    2. Shivkumar Sabesan, Konstantinos Tsakalis, Andreas Spanias, Leon Iasemidis
      Pages 271-283
    3. Panos M. Pardalos, Vitaliy A. Yatsenko, Alexandre Messo, Altannar Chinchuluun, Petros Xanthopoulos
      Pages 285-303
    4. Aaron Faith, Shivkumar Sabesan, Norman Wang, David Treiman, Joseph Sirven, Konstantinos Tsakalis et al.
      Pages 305-315
    5. Chang-Chia Liu, Petros Xanthopoulos, Vera Tomaino, Kazutaka Kobayashi, Basim M. Uthman, Panos M. Pardalos
      Pages 341-355
    6. J. Chris Sackellares, Deng-Shan Shiau, Alla R. Kammerdiner, Panos M. Pardalos
      Pages 357-369

About this book


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.


Master Patient Index biomedical engineering computational neuroscience data mining human brain function human neurophysiological systems modern neuroscience problems neuronal excitability synaptic transmission

Editors and affiliations

  • Wanpracha Chaovalitwongse
    • 1
  • Panos M. Pardalos
    • 2
  • Petros Xanthopoulos
    • 3
  1. 1.Department of Industrial and Systems, EngineeringRutgers State University of New JerseyPiscatawayUSA
  2. 2.Dept. Industrial & Systems, EngineeringUniversity of FloridaGainesvilleUSA
  3. 3., Dept. of Industrial & Systems Eng.University of FloridaGainesvilleUSA

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