Density-based clustering in the state space.

<p>Sketch of the steps involved in the density-based clustering of multi-dimensional time series through the mean shift algorithm. The time-binned <i>N</i>-dimensional data (‘spikes’) in panel A define a density profile in a <i>N</i>-dimensional space, interpreted as sampling a stationary probability distribution (panel B), from which an effective energy landscape can be defined (panel C). Panel D illustrates how the mean-shift operates to find the local maxima of the density distribution. Blue dot: current position of a point to be moved by the algorithm. Big yellow area: the chosen neighbourhood of the blue point. Green dots: neighbouring points of the blue point. Red dots: points that are not neighbours of the blue point. Small yellow dot: the new position of the blue point is given by the algorithm as the center of mass of its neighbouring points. See [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0174918#sec002" target="_blank">Materials and methods</a>] for details.