© 2008

Lectures in Supercomputational Neurosciences

Dynamics in Complex Brain Networks

  • Peter beim Graben
  • Changsong Zhou
  • Marco Thiel
  • Jürgen Kurths

Part of the Understanding Complex Systems book series (UCS)

Table of contents

  1. Front Matter
    Pages I-X
  2. Neurophysiology

    1. Front Matter
      Pages 1-1
    2. Peter beim Graben
      Pages 3-48
    3. Henry D.I. Abarbanel, Julie S. Haas, Sachin S. Talathi
      Pages 49-74
  3. Complex Networks

    1. Front Matter
      Pages 75-75
    2. Gorka Zamora-López, Changsong Zhou, Jürgen Kurths
      Pages 77-106
    3. Claus C. Hilgetag, Marcus Kaiser
      Pages 107-133
    4. Changsong Zhou, Lucia Zemanová, Jürgen Kurths
      Pages 135-175
    5. André Bergner, Maria Carmen Romano, Jürgen Kurths, Marco Thiel
      Pages 177-191
  4. Cognition and Higher Perception

    1. Front Matter
      Pages 193-193
    2. Peter beim Graben, Thomas Liebscher, Jürgen Kurths
      Pages 195-223
    3. James J. Wright
      Pages 225-247
  5. Implementations

    1. Front Matter
      Pages 249-249
    2. Lucia Zemanová, Changsong Zhou, Jürgen Kurths
      Pages 251-266
    3. Abigail Morrison, Markus Diesmann
      Pages 267-278
  6. Applications

    1. Front Matter
      Pages 317-317
    2. Steffen Tietsche, Francesca Sapuppo, Petra Sinn
      Pages 319-330
    3. Martin Vejmelka, Ingo Fründ, Ajay Pillai
      Pages 331-342
    4. Marconi Barbosa, Karl Dockendorf, Miguel Escalona, Borja Ibarz, Aris Miliotis, Irene Sendiña-Nadal et al.
      Pages 343-367

About this book


Computational Neuroscience is a burgeoning field of research where only the combined effort of neuroscientists, biologists, psychologists, physicists, mathematicians, computer scientists, engineers and other specialists, e.g. from linguistics and medicine, seem to be able to expand the limits of our knowledge.

The present volume is an introduction, largely from the physicists' perspective, to the subject matter with in-depth contributions by system neuroscientists. A conceptual model for complex networks of neurons is introduced that incorporates many important features of the real brain, such as various types of neurons, various brain areas, inhibitory and excitatory coupling and the plasticity of the network. The computational implementation on supercomputers, which is introduced and discussed in detail in this book, will enable the readers to modify and adapt the algortihm for their own research. Worked-out examples of applications are presented for networks of Morris-Lecar neurons to model the cortical connections of a cat's brain, supported with data from experimental studies.

This book is particularly suited for graduate students and nonspecialists from related fields with a general science background, looking for a substantial but "hands-on" introduction to the subject matter.


Synapse algorithms brain cognition computational neuroscience cortex linguistics modeling neurons neurophysiology neuroscience perception physiology simulation system

Editors and affiliations

  • Peter beim Graben
    • 1
  • Changsong Zhou
    • 2
  • Marco Thiel
    • 3
  • Jürgen Kurths
    • 4
  1. 1.School of Psychology and Clinical Language SciencesUniversity of ReadingWhiteknights, Reading RG6 6AHUnited Kingdom
  2. 2.Department of PhysicsHong Kong Baptist UniversityKowloon Tong, Hong KongChina
  3. 3.School of Engineering and Physical SciencesUniversity of AberdeenAberdeen AB24 3UEUnited Kingdom
  4. 4.Universität Potsdam Institut für Physik LS Theoretische Physik14469 PotsdamGermany

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