Figure 2 - data

<b>Figure</b><b>2. </b><b>Training design and performance of ML models.</b> <b>b)</b>LFP example of the new test set and the corresponding model outputs per window of analysis. Note different duration of true events. Setting a threshold allows defining the windows containing detected events. Colored ticks represent detections by the different models. Two different thresholds (dark and light gray) can influence what events are detected. Note how detections marked with arrows are dismissed when the threshold increases. Since SWRs constitute about 1-4% of the total recording duration, performance is computed using positive detections; that is windows without GT or detected events are not computed for performance.