Fig. 1

Head-fixed larvae respond to virtual prey with distinctive swimming movements.

(A) Overlay of 50 frames (167 ms) of high-speed video showing examples of behavior in head fixed larvae. Larvae performed forward swims in response to a 3° dot. j-turns were observed when the same dot was to the right or left. Spontaneous swims were often observed in the absence of any stimulus. (B) Example video frame showing points assigned by the digitization algorithm. (C) The position of the tip of the tail over time for the videos in (A). (D) The distribution of tail beat amplitudes for each bout in expert-classified prey capture and spontaneous swim videos. (E) Duration of the longest bend greater than 20° during each bout. (F) Overview of support vector machine (SVM) based bout classification procedure, displaying only two parameters (maximum tail bend and mean tail tip deflection) for clarity. Bouts are extracted using a threshold on the normalized and smoothed first derivative of tail bend angles. Values for each parameter are calculated for all bouts and used to train an SVM. The SVM is then used to classify unlabeled bouts. See Figure 1—figure supplement 1 for plots of each of the five parameters, and accuracy of the SVM vs number of parameters.