Figure 10.

Automatic dichotomization of the centroid set and detection of the ictal state transition times. Top panel: Color‐coded, example posterior membership profile $p(z^n|{\mathbf{p}}^1,\dots ,{\mathbf{p}}^N)$ during the preictal and ictal periods (for K = 6 centroids). x‐axis gives the time window n in seconds, y‐axis the centroid index. The procedure described in the main text produces an ictal centroid subset $C_{\text{ict}}=\{2,3,4,5\}$, whose posterior membership probability $p_{C_{\text{ict}}}^n=\sum _{k\in C_{\text{ict}}}p(z^n=k|{\mathbf{P}}_{\text{obs}})$ increases sharply at $n_{\text{ctso}}=182\mathrm{s}$, that is, 2 s after the clinical seizure onset at $n_{\text{ict}}=180\mathrm{s}$ (bottom panel, the large value of $p_{C_{\text{ict}}}^n$ at $n\approx 0$ is due to the prior probability of the Markov chain for z ⁰). Within the ictal period individual centroids $k\in C_{\text{ict}}$ each become activated with increased membership probability during four distinct states with transition times at $n_1,n_2,n_3$. Likewise C _ict, the transition times $n_{\text{ctso}},n_1,n_2,$ and n ₃ are also detected in an automated manner by procedures described in the main text. [Color figure can be viewed at http://wileyonlinelibrary.com]