Visual support for knowledge discovery in neuroscience: EEG coherence analysis of mental fatigue

Understanding the brain, its function and malfunction, is one of the most important and urgent targets of modern science.

Using the most sophisticated technologies neuroscientists now perform experiments ranging from studies on the genome to brain imaging under different conditions. This results in very large quantities of heterogeneous data, which are produced at ever increasing rates.

Electroencephalography (EEG) coherence provides a quantitative measure of functional brain connectivity.Traditional coherence analysis is cumbersome for high-density EEG which employs a large number of electrodes.

One problem is to find the most relevant functional brain regions (functional units) and coherences between those regions. The corresponding data are acquired under various experimental conditions, both in single subjects and groups of subjects.

Visualization of brain connectivity networks for three subjects from high-density EEG data in two frequency bands.

An example application concerns mental fatigue. In order to avoid a priori assumptions about the localization of functional units, a data-driven approach is most appropriate. Using efficient computational techniques, interactive visualization of multichannel EEG coherence becomes possible.

The presented visualization provides a very economical data summary of extensive experimental results, which otherwise would be very difficult and time-consuming to assess and which supports visual knowledge discovery. This is a great help for neuroscientist and clinicians who are analysing the results of EEG experiments.

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High-Density EEG Coherence Analysis Using Functional Units Applied to Mental Fatigue