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. 2019 Oct 10;142(12):3892–3905. doi: 10.1093/brain/awz303

Figure 3.

Figure 3

Time-varying network synchronizability is predictive of surgical outcome. (A) Median base network synchronizability in good outcome patients (blue) and poor outcome patients (red) for broadband intracranial EEG (IEEG). ***P < 0.001. Shaded areas show 95% confidence intervals. (B) Patients with lesional MRI have higher pre-ictal synchronizability than non-lesional (NL) patients. *P < 0.05 (lesional, pre-ictal: min = 0.42, 25%ile = 0.55, median = 0.60, 75%ile = 0.67, max = 0.74; NL, pre-ictal: min = 0.33, 25%ile = 0.59, median = 0.63, 75%ile = 0.67, max = 0.85; lesional, ictal: min = 0.40, 25%ile = 0.51, median = 0.55, 75%ile = 0.61, max = 0.70; NL, ictal: min = 0.40, 25%ile = 0.51, median = 0.56, 75%ile = 0.60, max = 0.74). (C) ROC curves were constructed by calculating difference in s(t) from pre-ictal to ictal periods and sweeping the threshold for classification. Broadband IEEG predicts surgical outcome significantly better than other bands as assessed by the DeLong test, which statistically compares ROC curves generated from correlated data.