From Synchronisation to Networks: Assessment of Functional Connectivity in the Brain

  • Cornelis J. Stam
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 2)


There is increasing evidence from basic research that statistical correlations between electroencephalographic (EEG) and magnetoencephalographic (MEG) rhythms recorded from different brain areas, either ‘at rest’ or during a specific task, contain a wealth of information on functional interactions between brain regions (Buzsaki, 2006; Varela et al., 2001). In fact, synchronisation of oscillatory brain activity in various frequency bands may be one of the key mechanisms used by the brain to integrate information processed in multiple specialised local brain areas. Many new signal analysis tools have become available in recent years to study such synchronisation patterns and their disruption in various neurological and neuropsychiatric diseases. The study of functional interaction patterns in the brain is even beginning to show some remarkable similarities between the brain and other complex networks, such as the Internet (Reijneveld et al., 2007). In this chapter, we give a brief introduction of concepts underlying functional connectivity and network analysis in EEG and MEG, the major tools that are used, their methodological aspects and shortcomings and the application to neurological disorders. The introduction is focused on presenting the concepts and ideas behind the methods; for technical details, we refer to more extensive review papers.


Functional Connectivity Random Graph Degree Distribution Cluster Coefficient Phase Synchronisation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Clinical NeurophysiologyVU University Medical CenterAmsterdamThe Netherlands

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