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A typical data-driven visualization of electroencephalography (EEG) coherence is a graph layout, with vertices representing electrodes and edges representing significant coherences between electrode signals. A drawback of this layout is its visual clutter for multichannel EEG. To reduce clutter, we define a functional unit (FU) as a data-driven region of(More)
The purpose of the present study is to examine the effects of mental fatigue and motivation on neural network dynamics activated during task switching. Mental fatigue was induced by 2 h of continuous performance; after which subjects were motivated by using social comparison and monetary reward as motivating factors to perform well for an additional 20 min.(More)
Synchronous electrical activity in different brain regions is generally assumed to imply functional relationships between these regions. A measure for this synchrony is electroencephalogra-phy (EEG) coherence, computed between pairs of signals as a function of frequency. Existing high-density EEG coherence visualizations are generally either(More)
Electroencephalography (EEG) coherence provides a quantitative measure of functional brain connectivity which is calculated between pairs of signals as a function of frequency. Without hypotheses, traditional coherence analysis would be cumbersome for high-density EEG which employs a large number of electrodes. One problem is to find the most relevant(More)
The field of visualization assists data interpretation in many areas, but some types of data are not manageable by existing visualization techniques. This holds in particular for time-varying multichannel EEG data. No existing technique can simultaneously visualize information from all channels in use and all time steps. To address this problem, a new(More)
Synchronous electrical activity in dierent brain regions is generally assumed to imply functional relationships between these regions. A measure for this synchrony is electroencephalography (EEG) coherence. Recently, we developed a new method for data-driven visualization of high-density EEG coherence, avoiding the visual clutter of conventional data-driven(More)
The field of visualization assists data interpretation in many areas, but does not manage all types of data equally well. This holds, in particular, for time-varying multichannel EEG data. No existing method can successfully visualize simultaneous information from all channels in use at all time steps. To address this problem, a new visualization method is(More)
Electroencephalography (EEG) coherence provides a quantitative measure of functional brain connectivity which is calculated between pairs of signals as a function of frequency. Without hypotheses, traditional coherence analysis would be cumbersome for high-density EEG which employs a large number of electrodes. One problem is to find the most relevant(More)
Synchronous electrical activity in different brain regions is generally assumed to imply functional relationships between these regions. A measure for this synchrony is electroencephalography (EEG) coherence, computed between pairs of signals as a function of frequency. Existing high-density EEG coherence visualizations are generally either(More)
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