Analysis of Neurophysiological Brain Functioning

314 Pages·1999·11.631 MB·English

by  D. Yves von Cramon (auth.), Dr. Christian Uhl (eds.)

Analysis of Neurophysiological Brain Functioning
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Springer Series in Synergetics
Editor: Hermann Haken
An ever increasing number of scientific disciplines deal with complex systems. These are systems that
are composed of many parts which interact with one another in a more or less complicated manner.
One of the most striking features of many such systems is their ability to spontaneously form spatial
or temporal structures. A great variety of these structures are found, in both the inanimate and the
living world. In the inanimate world of physics and chemistry, examples include the growth of crystals,
coherent oscillations oflaser light, and the spiral structures formed in fluids and chemical reactions. In
biology we encounter the growth of plants and animals (morphogenesis) and the evolution of species.
In medicine we observe, for instance, the electromagnetic activity of the brain with its pronounced
spatio-temporal structures. Psychology deals with characteristic features of human behavior ranging
from simple pattern recognition tasks to complex patterns of social behavior. Examples from sociology
include the formation of public opinion and cooperation or competition between social groups.
In recent decades, it has become increasingly evident that all these seemingly quite different kinds
of structure formation have a number of important features in common. The task of studying analo
gies as well as differences between structure formation in these different fields has proved to be an
ambitious but highly rewarding endeavor. The Springer Series in Synergetics provides a forum for
interdisciplinary research and discussions on this fascinating new scientific challenge. It deals with
both experimental and theoretical aspects. The scientific community and the interested layman are
becoming ever more conscious of concepts such as self-organization, instabilities, deterministic chaos,
nonlinearity, dynamical systems, stochastic processes, and complexity. All of these concepts are facets
of a field that tackles complex systems, namely synergetics. Students, research workers, university
teachers, and interested laymen can find the details and latest developments in the Springer Series in
Synergetics, which publishes textbooks, monographs and, occasionally, proceedings. As witnessed by
the previously published volumes, this series has always been at the forefront of modern research in the
above mentioned fields. It includes textbooks on all aspects of this rapidly growing field, books which
provide a sound basis for the study of complex systems.
A selection of volumes in the Springer Series in Synergetics:
Synergetics An Introduction 3rd Edition Neuronal Cooperativity
ByH. Haken Editor: J. Kriiger
Chemical Oscillations, Waves, and Turbulence Synergetic Computers and Cognition
By Y. Kuramoto A Top-Down Approach to Neural Nets
ByH. Haken
Temporal Disorder
in Human Oscillatory Systems Rhythms in Physiological Systems
Editors: L. Rensing, U. an der Heiden, Editors: H. Haken, H. P. Koepchen
M.e. Mackey
Self-organization and Clinical
Computational Systems - Natural and Artificial Psychology Empirical Approaches
Editor: H. Haken to Synergetics in Psychology
Editors: W. Tschacher, G. Schiepek, E. J. Brunner
From Chemical to Biological
Organization Editors: M. Markus, S. e. Miiller, Principles of Brain Functioning
G. Nicolis A Synergetic Approach to Brain Activity,
Behavior and Cognition
Information and Self-Organization
ByH. Haken
A Macroscopic Approach to Complex Systems
ByH. Haken Brain Function and Oscillations
Volume I: Brain Oscillations.
Neural and Synergetic Computers
Principles and Approaches
Editor: H. Haken
Volume II: Integrative Brain Function.
Synergetics of Cognition Neurophysiology and Cognitive Processes
Editors: H. Haken, M. Stadler ByE. Ba~ar
Theories of Immune Networks
Editors: H. Atlan, 1. R. Cohen
Christian UhI (Ed.)
Analysis
of Neurophysiological
Brain Functioning
With 120 Figures, 35 in Colour
Springer
Dr. Christian UbI
Max-Planck-Institute of Cognitive Neuroscience
Stephanstrasse 1a
D-04103 Leipzig, Germany
Series Editor:
Professor Dr. Dr. h.c.mult. Hermann Haken
Institut fiir Theoretische Physik und Synergetik der Universitat Stuttgart
D-70550 Stuttgart, Germany
and
Center for Complex Systems, Florida Atlantic University
Boca Raton, FL 33431, USA
ISSN 0172-7389
ISBN 978-3-642-64219-7 Springer-Verlag Berlin Heidelberg New York
Library of Congress Cataloging-in-Publication Data
Analysis of neurophysiological brain functioning 1 Christian Uhl (ed.). p.cm. --(Springer series in syner
getics, ISSN 0172-7389) Includes bibliographical references. ISBN 978·3·642-64219-7 (hardcover: alk. paper). 1.
Neurophysiology --Research --Methodology. 2. Brain --Mathematical models. 3. Cognitive neuroscience
--methodology. 4. System theory. I. UhI, Christian, 1965- . II. Series.
[DNLM: 1. Brain --physiology congresses. WL 300A533 19991 QP356.A69 1999 612.8'2-dc21 DNMLIDLC
for Library of Congress 98-41692
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Preface
The analysis of neurophysiological brain functioning is a highly interdisci
plinary field of research. In addition to the traditional areas of psychology
and neurobiology, various other scientific disciplines, such as physics, math
ematics, computer science and engineering are involved. This is on the one
hand due to the sophisticated technical equipment and the enormous amount
of data "produced" by mQdern EEG /MEG labs. On -the other hand, new
concepts stemming from physics and related fields influence the field of Neu
roscience. In order to learn about different models of brain functioning, we
have organized a workshop at the Max-Planck-Institute of Cognitive Neuro
science, (Leipzig, December 1997) to gather researchers from various fields
dealing with human brain functioning. To collect the different perspectives
of an understanding of brain functioning and to review models and concepts
as well as methods and applications, I have asked the participants to con
tribute to the present book. To avoid a collection of isolated contributions,
some of the contributers have written a joint chapter dealing with a broader
topic. As a result the book reviews a wide spectrum of model-based analyses
of neurophysiological brain functioning. It addresses students and scientists
from all the above mentioned fields.
After the "Introductory Remarks" by D. Yves von Cramon, Director at
the Max-Planck-Institute of Cognitive Neuroscience - the host institution
of the above mentioned workshop - the present book splits into two parts:
Part I dealing with "Concepts & Models" and Part II with "Methods & Ap
plications" .
In the first part, physical and physiological models and synergetic con
cepts are presented: Hermann Haken re:views basic concepts of Synergetics,
dealing with the emergence of macroscopic patterns due to microscopic in
teractions, and its applications to the understanding of brain functioning.
In the chapter by Paul Nunez neocortical dynamics are discussed aiming at
establishing a foundation for more physiologically based cognitive theories.
Scott Kelso and coworkers present in a chapter of three parts their strat
egy adopted toward the brain-behavior relation: experiments, methods to
analyze and visualize the spatio-temporal brain activity and a neurophysio
logical model to connect neural and behavioral levels of description. Finally
in the last chapter of this part, Roger Cerf and coworkers review the concept
VI Preface
of low-dimensional cortical activity observed by analyzing scaled structures
that emerge in short episodes of EEG signals.
The second part of the present book focuses on methods and applications
of analyzing EEG/MEG data sets. In the first chapter of this part, different
approaches dealing with spatial analyses are summarized: so-called spatio
temporal dipole models, distributed sources and statistical properties of the
spatial distribution of spontaneous EEG /MEG data. The following chapter
then deals with temporal aspects: two methods to analyze the time evolu
tion of synchronization processes are presented based on different aspects:
coherences and phase locking. Finally, in the last chapter, a new concept of
analyzing EEG /MEG data is reviewed with links to both source modeling
based on "components" and stochastic descriptions of temporal fluctuations.
I would like to use this opportunity for acknowledgments: My warmest
appreciations go to Hermann Haken for his support to publish the present
book in Springer Series in Synergetics and for the great opportunity to work
at his institute in a stimulating and creative atmosphere for nearly 5 years:
I am also very grateful to Rudolf Friedrich for valuable support and helpful
discussions in Stuttgart and for his still ongoing cooperation. From the Max
Planck-Institute of Cognitive Neuroscience I would like to thank D. Yves
von Cramon and Frithjof Kruggel for long and stimulating discussions and
their support to organize the workshop. Concerning the organization of the
workshop I especially thank Axel Hutt and Marjan Admiraal for their help
as well as all colleagues from the Max-Planck-Institute.
Finally I would like to thank the staff of Springer-Verlag, in particular
Prof. W. Beiglbock, Mrs. Sabine Lehr, Mrs. Edwina Pfendbach and Mrs.
Brigitte Reichel-Mayer for their cooperation.
Leipzig, July 1998 Christian Uhl
Table of Contents
Model-Based Analysis of Neurophysiological Brain Function:
Introductory Remarks
D. Yves von Cramon . . . . . . . . . . . . . . . . . . . . . . . . . . .. 1
Part I Models & Concepts
What Can Synergetics Contribute to the Understanding
of Brain Functioning?
Hermann Haken ........................... 7
A Preliminary Physiology of Macro-Neocortical Dynamics
and Brain Function
PaulL. Nunez ............................ 41
Traversing Scales of Brain and Behavioral Organization
I. Concepts and Experiments
J.A. Scott Kelso, Armin Fuchs, and Viktor K. Jirsa 73
II. Analysis and Reconstruction
Armin Fuchs, Viktor K. Jirsa, and J.A. Scott Kelso 90
III. Theoretical Modeling
Viktor K. Jirsa, J.A. Scott Kelso, aI?-d Armin Fuchs 107
EEG-Detected Episodes
of Low-Dimensional Self-Organized Cortical Activity
and the Concept of a Brain Attractor
R. Cerf, E.H. El Ouasdad, and M. El Amri . . . . . . . . . . . . . .. 126
VIII Table of Contents
Part II Methods & Applications
Source Modeling . . . . . . . . . . . . .. 147
Spatio-Temporal Dipole Analysis
Thomas R. Knosche . . . . . . . . . . . . . . . . . . . . . .. 150
Distributed Source Models:
Standard Solutions and New Developments
Rolando Grave de Peralta Menendez, and Sara Gonzalez Andino. 176
The Spatial Distribution
of Spontaneous EEG and MEG
Jan C. De Munck, and Bob W. Van Dijk . . . . . . . . . . . . .. 202
Neurophysiological Brain Function
and Synchronization Processes ........... 229
Dynamic Topographic Spectral Analysis
of Cognitive Processes
Barbel Schack . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 230
Complex Phase Synchronization
in Neurophysiological Data
Peter Tass, Jiirgen Kurths, Michael Rosenblum, Jorg Weule,
Arkady Pikovsky, Jens Volkmann, Alfons Schnitzler,
and Hans-Joachim Freund. . . . . . . . . . . . . . . . . . . . . .. 252
Spatio-Temporal Modeling
Based on Dynamical Systems Theory
Christian Uhl, and Rudolf Friedrich 274
Subject Index .......... . 307
Model-Based Analysis of Neurophysiological
Brain Function: Introductory Remarks
D. Yves von Cramon
Max-Planck-Institute of Cognitive Neuroscience, Stephanstrasse la,
D-04l03 Leipzig, Germany
The analysis of neurophysiological brain functioning has become a highly in
terdisciplinary task: A large number of research professionals coming from
outside the field of neuroscience (physicists, engineers, computer scientists,
etc.) have to get involved, in order to design and perform accurate experi
ments, to develop and maintain sophisticated technical equipment, and, last
but not least, to analyze and visualize the recorded signals. Since successful
EEG and MEG studies, especially in the cognitive domain, require such a
manifold expertise, as well as a significant financial investment, it is clearly
necessary to take care to identify the most appropriate concepts, models and
tools.
The last few decades, among them the "Decade of the Brain", have pro
vided us with innumerable anatomical, physiological, and chemical data re
lating to brain function at a microscopic (sub millimeter to millimeter) scale.
However, despite the tremendous progress basic neurosciences have made,
disappointingly little is known of the macroscopic functionality of the cor
tex. That is to say, the role in macroscopic neural function played by larger
cortical compartments has remained more or less a mystery. We have and
will continue to learn many important details from examinations at the mi
croscopic level. However, I fear that at this scale we will not be able to
obtain significant information relating to the neural correlates which are of
real interest to the cognitive neuroscientists. That is for instance, data which
will enable us to identify the functional components of working memory or
the mechanisms involved in language comprehension. These primarily corti
cal functions depend upon highly integrated complex systems which are far
more readily investigated at the macroscopic level. It can, however, be as
sumed that EEG /MEG measures at the" macroscopic scale are influenced by
the microscopic processes in a "bottom-up" manner. This means, in other
words, that large-scale models in humans may be improved by incorporating
knowledge relating to microscopical function.
The spatial resolution of conventional EEG differentiates activity between
larger cortical areas with a linear scale of about 5 cm. More sophisticated EEG
and MEG methods, however, seem able to obtain 1 cm resolution, which
is close to the theoretical limits set by the physical separation of sensors
and brain current sources. These high-resolution methods may enable us to
C. Uhl (ed.), Analysis of Neurophysiological Brain Functioning
© Springer-Verlag Berlin Heidelberg 1999
2 D. Yves von Cramon
separate functionally and morphologically meaningful subunits of those larger
cortical areas.
From the point of view of neuroanatomy, an intermediate spatial scale
ranging from a few millimeters up to 1-2 centimeters needs further clarifica
tion. Anatomists have identified, in hierarchical order, a microscopic world of
'minicolumns', 'cortico-cortical columns' and 'macrocolumns' - all structural
units in the submillimeter and millimeter range. Somewhat surprisingly, the
next larger anatomically defined structures are cortical areas, defined for in
stance by cytoarchitectonic features such as the classical Brodmann areas or
by patterns of intracortical myelinated fibers or intracortical vasculature.
The intermediate dimension of brain organization which, in analogy to
synergetics, could be denoted as the 'mesoscopic' scale, seems to correspond
with what is rather vaguely conceptualized as neuronal cell assemblies binding
together a multitude of functionally associated macrocolumns. These meso
scopic subunits, although not yet properly define~, do indeed seem to exist
and can be described. in terms of the neural correlates of 'activation areas'
identified in neuroimaging (PET, fMRI) studies. These activation areas are
obviously larger than single macro columns but in most cases substantially
smaller than Brodmann areas. It is most likely that the so-called 'conver
gence zones', which exist as synaptic patterns within multi-layered neuron
ensembles in association cortices, correspond to the mesoscopic brain struc
tures.
I propose that a Brodmann area is composed of several mesoscopic areas
(including convergence zones) representing function units or 'building stones'
for a diversity of cognitive (and other cerebral) functions. It seems plausible
to assume that various activation areas within a large cortical area of the
Brodmann type constitute a certain class or category of cortical functions
whatever dimensions or features they may have in common.
Simultaneous measurements of EEG and fMRI, which now have become
technically feasible, will allow us to study the electrophysiological (neural)
dimension of haemodynamically-defined mesoscopic cortical areas. They may
provide us with completely new insights into the nature of spatio-temporal
cooperation between cortical modules and their behavioral correlates at the
mesoscopic level.
I would like to touch briefly on a second issue which will playa major role
in this book - that is, the debate concerning the validity of the various map
ping techniques, e.g. amplitude mapping (the most widespread method so
far) and the mapping of spectral parameters, such as spectral power and co
herence mappings. In the case of amplitude mapping, averaged event-related
potentials or fields represent the basis for either statistical procedures with
latency, amplitude and topography as considered factors, or for source local
ization techniques and dynamical systems based on so-called spatio-temporal
models. Our own work here in Leipzig has made use of both techniques. Al
though not at all an expert in this field of research, I have, following many