Extended Data Figure 10. Behavioral change based on random spectrogram segments.

We recomputed all main analyses with a random segmentation of behavior that does require alignment to syllable onsets. This segmentation scheme can be applied to behavior that does not fall into temporally discrete syllables. Here each data point corresponds to a randomly chosen 68ms spectrogram snippet drawn from a period of singing. Not all song was sampled, as we used 1,000,000 non-overlapping segments for each bird (see Methods).

(a) Vocalizations of the example bird (e.g. Fig. 1a) from day 76 and example segments used for the analysis.

(b) t-SNE visualization for random segments from the example bird, based on nearest neighbors defined with respect to the Euclidean distance (left panel) and average spectrograms for different locations in the (t-SNE) embedding (right panel; analogous to Fig. 2b). Clusters corresponding to individual syllables are elongated compared to Fig. 2a. Variation along one direction within the cluster tends to account for production time (color), while variation along another direction tends to reflect the timing of segments relative to syllable onsets.

(c) Embedding from Fig. 2a (bottom) and embedding of random 68ms segments (top). Points in both embeddings are colored by cluster identity defined on onset-aligned spectrogram segments covering entire syllables (bottom). The color of each point corresponding to a random snippet (top) corresponds to the cluster identity of the surrounding syllable. Some clusters in the embedding based on random segments contain points assigned to two different syllables (e.g. black and green colors);

(d) Repertoire dating averaged over birds, analogous to Fig. 3a,b.

(e) Stratified mixing matrix averaged over birds, analogous to Fig. 3g. The mixing values are highly correlated with those in Fig. 3g (variance explained = 89%)

(f) Stratified behavioral trajectories based on (e), as in Fig. 3h-k. The results in (d-f) largely reproduce the corresponding findings obtained with onset-aligned 68ms spectrogram segments (Fig. 3) as well as with other song parameterizations (Extended Data Fig. 9). Nonetheless, the overall effect sizes are reduced, likely due to the additional variability introduced by the random position of segments relative to syllable onsets. In (d), vertical separation between 5^th and 95^th percentiles is increased and slope of 50^th percentile is reduced, suggesting a noisier representation of the direction of slow change (see Extended Data Fig. 5e) compared to onset-aligned 68ms segments (Fig. 3).