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The Graph Theoretical Approach in Brain Functional Networks - Theory and Applications (Paperback)
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The Graph Theoretical Approach in Brain Functional Networks - Theory and Applications (Paperback)
Series: Synthesis Lectures on Biomedical Engineering
Expected to ship within 10 - 15 working days
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The present book illustrates the theoretical aspects of several
methodologies related to the possibility of i) enhancing the poor
spatial information of the electroencephalographic (EEG) activity
on the scalp and giving a measure of the electrical activity on the
cortical surface. ii) estimating the directional influences between
any given pair of channels in a multivariate dataset. iii) modeling
the brain networks as graphs. The possible applications are
discussed in three different experimental designs regarding i) the
study of pathological conditions during a motor task, ii) the study
of memory processes during a cognitive task iii) the study of the
instantaneous dynamics throughout the evolution of a motor task in
physiological conditions. The main outcome from all those studies
indicates clearly that the performance of cognitive and motor tasks
as well as the presence of neural diseases can affect the brain
network topology. This evidence gives the power of reflecting
cerebral "states" or "traits" to the mathematical indexes derived
from the graph theory. In particular, the observed structural
changes could critically depend on patterns of synchronization and
desynchronization - i.e. the dynamic binding of neural assemblies -
as also suggested by a wide range of previous electrophysiological
studies. Moreover, the fact that these patterns occur at multiple
frequencies support the evidence that brain functional networks
contain multiple frequency channels along which information is
transmitted. The graph theoretical approach represents an effective
means to evaluate the functional connectivity patterns obtained
from scalp EEG signals. The possibility to describe the complex
brain networks sub-serving different functions in humans by means
of "numbers" is a promising tool toward the generation of a better
understanding of the brain functions. Table of Contents:
Introduction / Brain Functional Connectivity / Graph Theory /
High-Resolution EEG / Cortical Networks in Spinal Cord Injured
Patients / Cortical Networks During a Lifelike Memory Task /
Application to Time-varying Cortical Networks / Conclusions
General
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