Watershed-Based Visualization of High-Density EEG Coherence
نویسنده
چکیده
Synchronous electrical activity in di erent 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 methods. It uses the concept of maximal clique detection, having time complexity O(3) with n the number of vertices. Here, a more e cient clustering method is used with time complexity O(n log n), based on a watershed algorithm which is modi ed to detect cliques in a greedy way. Here, it obtains a speedup of factor 400 while results are similar, making interactive visualization of high-density EEG coherence feasible.
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