Figure 2.

(A) Independent component analysis (ICA) returns four basis shapes that explain 97.6% of the variance in the dataset. The graph shows an x-y coordinate representation of the modes with the resampled basis shapes in gray. (B) The fraction of the variance explained along the worm by including an increasing number of basis shapes suggests that the modes can each explain a different part of the worm well. (C) Bivariate histograms for the amplitudes of basis shapes (wild type worm, 15 min, frame rate: 30 Hz). Top row: forward locomotion only, bottom row: all data. Basis shapes 1 and 2 from ICA form a ring in both cases (especially clear when only the forward locomotion is counted), suggesting an oscillatory behavior between them. Similarly, two basis shapes from principal component analysis (PCA) are known to explain an oscillatory behavior, but they also include other information, as evidenced by a lack of clear, continuous ring in their histograms.