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. 2011 Jun 28;6(6):e21606. doi: 10.1371/journal.pone.0021606

Figure 7. EDHMM UDS classification from a scalp EEG recording.

Figure 7

A) The sliding-window density estimate of the LF-amplitude is shown for an example EEG recording. Log probability density is depicted as the color map, with the violet and green traces showing the time-varying state-conditional means. The regions indicated by the vertical black lines show the locations within the data where the example traces in panels C and D were taken, and the white vertical lines indicate desynchronized epochs. B) The overall amplitude distribution, along with the UP and DOWN state component distributions, fit using a (static) Gaussian mixture model. The two values of the fixed threshold used for the “threshold-crossing” algorithm, chosen using the Np and SMM approaches, are shown by the finely and coarsely dashed black horizontal lines respectively. C) An example EEG trace (blue) from the region indicated by the black lines. The Viterbi state sequence from the EDHMM is shown in brown. For comparison, the state sequence classified using the Np threshold-crossing method is shown in light blue. D) Another example EEG trace comparing the EDHMM UDS classification with the SMM threshold-crossing method.