Analysis of neurophysiological brain functioning /

The analysis of neurophysiological brain functioning is a highly interdisciplinary field of research. In addition to the traditional areas of psychology and neurobiology, various other scientific disciplines, such as physics, mathematics, computer science, and engineering, are involved. The book rev...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Uhl, Christian, 1965 July 5-
Format: eBook
Language:English
Published: Berlin ; New York : Springer, [1999]
Series:Springer series in synergetics.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:The analysis of neurophysiological brain functioning is a highly interdisciplinary field of research. In addition to the traditional areas of psychology and neurobiology, various other scientific disciplines, such as physics, mathematics, computer science, and engineering, are involved. The book reviews a wide spectrum of model-based analyses of neurophysiological brain functioning. In the first part, physical and physiological models and synergetic concepts are presented. The second part focuses on analysis methods and their applications to EEG/MEG data sets. It reviews methods of source localization, the investigation of synchronization processes, and spatio-temporal modeling based on dynamical systems theory. The book includes contributions by well-known scientists including, among others, Hermann Haken, Scott Kelso and Paul Nunez. It is written for students and scientists from all the above-mentioned fields.
Item Description:Electronic resource.
Physical Description:1 online resource (viii, 310 pages) : illustrations (some color).
Format:Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
Bibliography:Includes bibliographical references and index.
ISBN:9783642600074 (electronic bk.)
3642600077 (electronic bk.)
ISSN:0172-7389