Predicting plasticity: acute context-dependent changes to vocal performance predict long-term age-dependent changes

Abstract

Understanding the factors that predict and guide variation in behavioral change can lend insight into mechanisms of motor plasticity and individual differences in behavior. The performance of adult birdsong changes with age in a manner that is similar to rapid context-dependent changes to song. To reveal mechanisms of vocal plasticity, we analyzed the degree to which variation in the direction and magnitude of age-dependent changes to Bengalese finch song could be predicted by variation in context-dependent changes. Using a repeated-measures design, we found that variation in age-dependent changes to the timing, sequencing, and structure of vocal elements ("syllables") was significantly predicted by variation in context-dependent changes. In particular, the degree to which the duration of intersyllable gaps, syllable sequencing at branch points, and fundamental frequency of syllables within spontaneous [undirected (UD)] songs changed over time was correlated with the degree to which these features changed from UD song to female-directed (FD) song in young-adult finches (FDyoung). As such, the structure of some temporal features of UD songs converged over time onto the structure of FDyoung songs. This convergence suggested that the FDyoung song could serve as a stable target for vocal motor plasticity. Consequently, we analyzed the stability of FD song and found that the temporal structure of FD song changed significantly over time in a manner similar to UD song. Because FD song is considered a state of heightened performance, these data suggest that age-dependent changes could reflect practice-related improvements in vocal motor performance.

Keywords: Bengalese finch; birdsong; sequencing; social context; tempo.

Fig. 1.

Adult Bengalese finch song. A spectrogram (time on the x-axis, frequency on the y-axis, darkness as amplitude) of a rendition of Bengalese finch song. Labels for syllables are located above the spectrogram. As with other Bengalese finches, this bird produces both variable (branch point) and stereotyped sequences within his song. The sequence “cd” (white bars) is an example of a branch point because it can be followed by a “b” (black bar), “e” (gray bar), or “q” (transition to q is not observed in this rendition). In contrast, the sequence “mnop” (black line) is a stereotyped sequence in which syllables are always produced in this order. Scale bar, 200 ms.

Fig. 2.

Context-dependent changes to syllable sequencing predicted age-dependent changes to syllable sequencing. A: transition entropy, a measure of sequence variability, decreased significantly across social context and age. Plotted is the mean (±SE) transition entropy of branch points for the undirected and female-directed young-adult (UD_young and FD_young, respectively) and UD older-adult (UD_older) songs of individual birds (n = 46 branch points), with raw data values plotted in gray. Transition entropy is significantly lower for FD_young and UD_older song than for UD_young song and not different between FD_young and UD_older song. *P < 0.05, significantly different than UD_young song. B: there is a significant, positive relationship between the magnitude of change (Δ) in entropy caused by social context and by age (P = 0.0430). Plotted is the difference in transition entropy across context (FD_young − UD_young) and the difference across age (UD_older − UD_young). C: an example of context- and age-dependent changes to syllable sequencing at branch points. The bird can produce the syllables q (black bar), b (gray bars), and e (white bars), following the branch-point sequence cd (same bird depicted in Fig. 1). Social context and age led to a virtual elimination of the transition to q and increases in transitions to b and e. D: another example of context- and age-dependent changes to syllable sequencing at branch points. The bird produced the syllables “g” (black bars) and b (white bars) following the branch point “fa,” and the changes to both transitions across context and age were comparable. E: context-dependent changes to transition probabilities for all branch points were significantly correlated with age-dependent changes to transition probabilities (P < 0.0001). Plotted are the differences in transition probabilities across context (FD_young − UD_young) and across age (UD_older − UD_young).

Fig. 3.

Context-dependent changes to syllable timing predicted age-dependent changes to syllable timing. A: spectrogram of a stereotyped sequence used to analyze context- and age-dependent changes to song tempo. Labels for syllables are located above the spectrogram, and syllables (lines) and intersyllable gaps (empty boxes) are highlighted under the spectrogram. Histograms display sequence durations (middle) and the total duration of gaps within the sequence (right) across renditions, and triangles indicate the mean duration for each condition. Dashed lines correspond to the mean duration for UD_young song. In this example, both sequence and gap durations were shorter for both FD_young and UD_older song than for UD_young song. B: sequence (left) and gap (right) durations change significantly across social context and age, and the magnitudes of context- and age-dependent changes to sequence and gap durations were not significantly different (n = 14 sequences). Plotted are the percent changes to sequence and gap durations across context (UD_young to FD_young) and age (UD_young to UD_older). *P < 0.05 indicates that the mean percent change was significantly different than 0 (t-test). C: context-dependent changes to gap durations (percent change) are correlated with age-dependent changes (P = 0.0174). Plotted are the percent changes to gap durations across context (UD_young to FD_young) and across age (UD_young to UD_older). D: context-dependent changes to sequence durations (percent change) were not correlated with age-dependent changes (P = 0.8141). This lack of correlation at the sequence level (despite the correlation at the gap level) is likely due to the lack of correlation in syllable durations (P = 0.5492) as well as the fact that syllables contribute more to sequence durations than gaps.

Fig. 4.

Context-dependent changes to fundamental frequency (FF) predicted age-related variation in FF (n = 33 syllables in 14 males). A: social context but not age affected the variability of FF. Plotted are normalized interquartile region (normIQR) values for each individual syllable, with lines indicating the mean ± SE for each condition. Groups with different letters indicate groups that are significantly different. B: distributions of FF across renditions for an individual syllable with flat, harmonic structure. Triangles indicate the mean FF for each condition, and the dashed line corresponds to the mean FF for UD_young song to help visualize context- and age-dependent changes. The mean FF of this syllable increased across both social contexts (from UD_young to FD_young) and age (from UD_young to UD_older). The variability of FF for this syllable decreased across both social contexts and age. C: distributions of FF across renditions for another syllable. The mean FF of this syllable decreased across both context and age. The variability of FF for this syllable decreased slightly across context and increased with age. D: variation in the magnitude of change in the mean FF across social context (percent change from UD_young to FD_young) predicts variation in the magnitude of change across age (percent change from UD_young to UD_older; P = 0.0049). Open circles represent example syllables depicted in B and C. E: overall, there was no significant relationship between the magnitude of context-dependent changes (percent change from UD_young to FD_young) to the variability (normIQR) of FF and the magnitude of age-dependent changes (percent change from UD_young to UD_older; P = 0.5308). However, after the removal of the value for a single outlying syllable, the relationship between context- and age-dependent changes to normIQR was significant (P = 0.0342). Open circles represent syllables summarized in B and C.

Fig. 5.

The testing of the “target” and “performance” models of vocal motor change. A: predictions of the target and performance models. The performance but not the target model predicts that features that changed significantly over time for UD song (syllable sequencing and tempo) should similarly change for FD song. As such, the performance model predicts that gap durations and sequence variability of FD song (black circles) should decrease over time. The target model predicts that these features of FD song should remain the same over time. Dashed gray lines represent UD_young and UD_older songs and highlight the decrease for UD song over time. B: the transition entropy of branch points decreased from FD_young to FD_older songs [Tukey's honestly significant difference (HSD); P = 0.0241], indicating age-dependent changes to syllable sequencing in FD song. Whereas analyses were performed using a factorial design (see results), depicted in this panel (as well as subsequent panels of this figure) are changes to song features for FD song with age. We depict the FD_young-FD_older contrast because this contrast is central for the comparison of target and performance models and plot changes instead of mean values for each condition, as differences in mean values are difficult to see for some features because of the large range of values (see materials and methods). C: gap durations decreased from FD_young to FD_older song (Tukey's HSD; P = 0.0085), demonstrating an age-dependent increase to the tempo of FD song. D: the variability (normIQR) of FF does not change significantly from FD_young to FD_older song (Tukey's HSD; P = 0.7680). E: mean FF does not change significantly from FD_young to FD_older song (Tukey's HSD; P = 0.9833). *P < 0.05 indicates features of FD song that change significantly over time.