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Figure 1 Three example candidate spike ripple events

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1 Figure 1 Three example candidate spike ripple events
Figure 1 Three example candidate spike ripple events. Each subfigure displays the unfiltered EEG data (blue), the ... Figure 1 Three example candidate spike ripple events. Each subfigure displays the unfiltered EEG data (blue), the bandpass filtered EEG data (100–300 Hz, red), and the spectrogram of the EEG data in an interval surrounding the spike ripple event (dashed vertical lines) with power (in decibels) shown in colour. Both reviewers classified the candidate spike ripple events (A) as a true spike ripple, (B) as a false spike ripple, or (C) the reviewers disagreed on the classification. In (A), a distinct high frequency ‘spectral island’ is visually evident in the spectrogram, and a ripple is visually evident on the spike in the unfiltered data. Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Brain, awz059, The content of this slide may be subject to copyright: please see the slide notes for details.

2 Figure 3 The spike ripple rate is significantly higher in patients with active BECTS, and decreases with each ... Figure 3 The spike ripple rate is significantly higher in patients with active BECTS, and decreases with each seizure-free month. (A) Each circle indicates the spike ripple rate (detections/min) for a subject, which are divided into three categories. All patients with active BECTS (red circles) have non-zero spike ripple rates, whereas no healthy controls and only two seizure-free patients with BECTS have non-zero spike ripple rates. (B) The spike ripple rate versus time since last seizure for all patients with BECTS. Red (grey) circles indicate patients with active (seizure-free) BECTS. The rate decreases with time since last seizure (black curve indicates model fit, mean in solid, 95% CI in dashed lines). Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Brain, awz059, The content of this slide may be subject to copyright: please see the slide notes for details.

3 Figure 2 Spike ripples are more spatially discrete than spikes
Figure 2 Spike ripples are more spatially discrete than spikes. The normalized spike ripple rate and the spike ... Figure 2 Spike ripples are more spatially discrete than spikes. The normalized spike ripple rate and the spike amplitude at the primary channel (1°), secondary channels (2°), and tertiary channels (3°). Each circle indicates one patient, and the bar height indicates the median across patients. As the distance from the primary channel increases, both measures decrease, although the decrease is significantly faster for the spike ripple rate. Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Brain, awz059, The content of this slide may be subject to copyright: please see the slide notes for details.

4 Figure 6 Fully automated spike detection performance
Figure 6 Fully automated spike detection performance. (A) The spike rate is higher in patients with active BECTS. (B) ... Figure 6 Fully automated spike detection performance. (A) The spike rate is higher in patients with active BECTS. (B) A logistic regression model (black curves, mean in solid, 95% CIs in dashed) indicates a significant increase in the odds of active BECTS with increasing spike rate. (C) From the ROC curve (black), the optimal operating point (blue) is used for classification. (D) No relationship between the spike rate and time since last seizure is detected. The black curve indicates a generalized linear model fit with mean (solid) and 95% CIs (dashed). In all figures, red (grey) circles indicate patients with active BECTS (seizure-free BECTS). Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Brain, awz059, The content of this slide may be subject to copyright: please see the slide notes for details.

5 Figure 4 Manually detected spikes performance
Figure 4 Manually detected spikes performance. (A) The spike rate is higher in patients with active BECTS, though most ... Figure 4 Manually detected spikes performance. (A) The spike rate is higher in patients with active BECTS, though most seizure-free subjects have a non-zero spike rate. Each circle indicates the spike rate (events/min) for the three patient categories. (B) No relationship between the spike rate and time since last seizure is detected. The black curve indicates a generalized linear model fit with mean (solid) and 95% CIs (dashed). In both figures, red (grey) circles indicate patients with active BECTS (seizure-free BECTS). Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Brain, awz059, The content of this slide may be subject to copyright: please see the slide notes for details.

6 Figure 5 Analysis of fully automated detection of spike ripple events produces consistent results. (A) The spike ... Figure 5 Analysis of fully automated detection of spike ripple events produces consistent results. (A) The spike ripple rate is higher in patients with active BECTS. Each circle indicates the spike ripple rate (events/min) for the three patient categories. (B) Patients separated into those with active BECTS (red circles) and seizure-free (grey circles). A logistic regression model (black curves, mean in solid, 95% CIs in dashed) indicates a significant increase in the odds of active BECTS with increasing spike ripple rate. (C) From the ROC curve (black), the optimal operating point (blue) is used for classification. (D) The spike ripple rate decreases with time since last seizure. The black curve indicates a generalized linear model fit with mean (solid) and 95% CIs (dashed). Unless provided in the caption above, the following copyright applies to the content of this slide: © The Author(s) (2019). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( Brain, awz059, The content of this slide may be subject to copyright: please see the slide notes for details.

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