Data for evaluation of unsupervised learning algorithms for the classification of behavior

Experiments were carried out in adult C57BL/6J (Charles River) male and female mice. Mice were maintained under standard housing conditions with a 12-hour light cycle and with ad libitum access to food and water. All animal experiments had received approval from the local ethical board, Stockholms Norra Djurförsöksetiska Nämnd, and were performed in accordance with the European Communities Council Directive 2010/63. The open field test was conducted in a 40cm x 40cm arena (Ugo Basil®), with recordings made from a top-down view using a Basler acA1920-155um camera. Each mouse was recorded for 10 minutes, and a total of 54 mice were used for analysis. For body part tracking we used DeepLabCut (version 2.3.3) [Mathis et al, 2018, Nath et al, 2019]. Specifically, we labeled 5 frames taken from 42 videos/animals (210 frames in total, then 95% (200 frames) was used for training) with 11 body part markers (keypoints): nose, head-center, neck, ear left, ear right, body-center, body-center left, body-center right, hip left, hip right and tailbase. We used a ResNet-50 neural network with default parameters for 200,000 number of training iterations. For the final model the test error was: 3.16 pixels, train: 2.83 pixels (image size was 650 by 600). This network was then used to analyze videos from similar experimental settings. For VAME analysis we used default settings for z_dim parameter and set time window to 15 frames corresponding to 500 ms of behavior. For B-SOiD analysis we used default values for minimum cluster size that ranged between 0.5% and 1%, that provided the highest score in random forest accuracy > 0.95. For Keypoint MoSeq we used kappa = 1e6, which also yielded median motif duration of 520 ms. For BFA we applied a default pipeline. To evaluate the performance of the unsupervised classification, we have performed manual labeling of 3000 frames from 3 mice (1000 frames each). Videos were annotated with the following behavioral classification labels: turn right, turn left, walk, stand and sniff, unsupported rear, walk and sniff, supported rear, groom, look up and down, pause. Three experts agreed on the manually-labeled behavioral classification in each frame.