Peter Beim Graben

Lectures in Supercomputational Neuroscience: Dynamics in Complex Brain Networks - Understanding Complex Systems Peter Beim Graben Softcover Reprint of Hardcover 1st Ed. 2008 edition

Jacket Description/Back: 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. Table of Contents: Part I. Neurophysiology -- 1. Foundations of Neurophysics / Peter beim Graben -- 2. Synapses and Neurons: Basic Properties and Their Use in Recognizing Environmental Signals / Henry D. I. Abarbanel, Julie S. Haas, Sachin S. Talathi -- Part II. Complex Networks -- 3. Structural Characterization of Networks Using the Cat Cortex as an Example / Gorka Zamora-Lopez, Changsong Zhou, J&omlet;rgen Kurths -- 4. Organization and Function of Complex Cortical Networks / Claus C. Hilgetag, Marcus Kaiser -- 5. Synchronization Dynamics in Complex Networks / Changsong Zhou, Lucia Zemanova, J&uomlet;rgen Kurths -- 6. Synchronization Analysis of Neuronal Networks by Means of Recurrence Plots / Andre Bergner, Maria Carmen Romano, J&uomlet;rgen Kurths, Marco Thiel -- Part III. Cognition and Higher Perception -- 7. Neural and Cognitive Modeling with Networks of Leaky Integrator Units / Peter beim Graben, Thomas Liebscher, J&uomlet;rgen Kurths -- 8. A Dynamic Model of the Macrocolumn / James J. Wright -- Part IV. Implementations -- 9. Building a Large-Scale Computational Model of a Cortical Neuronal Network / Lucia Zemanova, Changsong Zhou, J&uomlet;rgen Kurths -- 10. Maintaining Causality in Discrete Time Neuronal Network Simulations / Abigail Morrison, Markus Diesmann -- 11. Sequential and Parallel Implementation of Networks / Werner von Bloh -- Part V. Applications -- 12. Parametric Studies on Networks of Morris-Lecar Neurons / Steffen Tietsche, Francesca Sapuppo, Petra Sinn -- 13. Traversing Scales: Large Scale Simulation of the Cat Cortex Using Single Neuron Models / Martin Vejmelka, Ingo Fr&uomlet;nd, Ajay Pillai -- 14. Parallel Computation of Large Neuronal Networks with Structured Connectivity / Marconi Barbosa, Karl Dockendorf, Miguel Escalona, Borja Ibarz, Aris Miliotis, Irene Sendina-Nadal, Gorka Zamora-Lopez, Lucia Zemanova -- Index. Publisher Marketing: Computational Neurosciences 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. "

Contributor Bio:  Kurths, Jurgen Jurgen Kurths has been professor at the University of Potsdam and director of the Interdisciplinary Centre for Nonlinear Dynamics since 1994. He is a fellow of the American Physical Society and fellow of the Fraunhofer Society (Germany), and is currently the chairman for Nonlinear Processes in Geophysics and member of the council in Geophysics of the European Geophysical Society. In 2001 he will be a member of the Editorial Board of the Int. J. of Bifurcation and Chaos. Professor Kurths was director of the group for Nonlinear Dynamics of the Max-Planck Society from 1992 1996. He studied mathematics at Rostock University, and then went on to work at the Solar-Terrestrial Physics Institute, and later the Astrophysical Institute of GDR Academy of Sciences. He obtained his PhD in Physics, and started to work on nonlinear data analysis and chaos in 1984. His main research interests are nonlinear dynamics and their applications to geophysics and physiology and to time series analysis.