Functional Unit Maps for Data-Driven Visualization of High-Density EEG Coherence

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dc.contributor.authorCaat, Michael tenen_US
dc.contributor.authorMaurits, Natasha M.en_US
dc.contributor.authorRoerdink, Jos B. T. M.en_US
dc.contributor.editorK. Museth and T. Moeller and A. Ynnermanen_US
dc.date.accessioned2014-01-31T07:11:07Z
dc.date.available2014-01-31T07:11:07Z
dc.date.issued2007en_US
dc.description.abstractSynchronous 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 hypothesis-driven, or data-driven graph visualizations which are cluttered. In this paper, a new method is presented for data-driven visualization of high-density EEG coherence, which strongly reduces clutter and is referred to as functional unit (FU) map. Starting from an initial graph, with vertices representing electrodes and edges representing significant coherences between electrode signals, we define an FU as a set of electrodes represented by a clique consisting of spatially connected vertices. In an FU map, the spatial relationship between electrodes is preserved, and all electrodes in one FU are assigned an identical gray value. Adjacent FUs are visualized with different gray values and FUs are connected by a line if the average coherence between FUs exceeds a threshold. Results obtained with our visualization are in accordance with known electrophysiological findings. FU maps can be used as a preprocessing step for conventional analysis.en_US
dc.description.seriesinformationEurographics/ IEEE-VGTC Symposium on Visualizationen_US
dc.identifier.isbn978-3-905673-45-6en_US
dc.identifier.issn1727-5296en_US
dc.identifier.urihttps://doi.org/10.2312/VisSym/EuroVis07/259-266en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): E.1 [Data]: Graphs and networks; J.3 [Life and Medical Sciences]: Healthen_US
dc.titleFunctional Unit Maps for Data-Driven Visualization of High-Density EEG Coherenceen_US
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EuroVis07: Joint Eurographics - IEEE VGTC Symposium on Visualization