Dataset Information

Relationship between the Sequencing and Timing of Vocal Motor Elements in Birdsong.

ABSTRACT: Accurate coordination of the sequencing and timing of motor gestures is important for the performance of complex and evolutionarily relevant behaviors. However, the degree to which motor sequencing and timing are related remains largely unknown. Birdsong is a communicative behavior that consists of discrete vocal motor elements ('syllables') that are sequenced and timed in a precise manner. To reveal the relationship between syllable sequencing and timing, we analyzed how variation in the probability of syllable transitions at branch points, nodes in song with variable sequencing across renditions, correlated with variation in the duration of silent gaps between syllable transitions ('gap durations') for adult Bengalese finch song. We observed a significant negative relationship between transition probability and gap duration: more prevalent transitions were produced with shorter gap durations. We then assessed the degree to which long-term age-dependent changes and acute context-dependent changes to syllable sequencing and timing followed this inverse relationship. Age- but not context-dependent changes to syllable sequencing and timing were inversely related. On average, gap durations at branch points decreased with age, and the magnitude of this decrease was greater for transitions that increased in prevalence than for transitions that decreased in prevalence. In contrast, there was no systematic relationship between acute context-dependent changes to syllable sequencing and timing. Gap durations at branch points decreased when birds produced female-directed courtship song compared to when they produced undirected song, and the magnitude of this decrease was not related to the direction and magnitude of changes to transition probabilities. These analyses suggest that neural mechanisms that regulate syllable sequencing could similarly control syllable timing but also highlight mechanisms that can independently regulate syllable sequencing and timing.

SUBMITTER: Matheson AM

PROVIDER: S-EPMC4674110 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Relationship between the Sequencing and Timing of Vocal Motor Elements in Birdsong.

Matheson Andrew M M AM Sakata Jon T JT

PloS one 20151209 12

Accurate coordination of the sequencing and timing of motor gestures is important for the performance of complex and evolutionarily relevant behaviors. However, the degree to which motor sequencing and timing are related remains largely unknown. Birdsong is a communicative behavior that consists of discrete vocal motor elements ('syllables') that are sequenced and timed in a precise manner. To reveal the relationship between syllable sequencing and timing, we analyzed how variation in the probab ...[more]

PMID: 26650933

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Project description:To investigate mechanisms of action sequencing, we examined the relationship between timing and sequencing of syllables in Bengalese finch song. An individual's song comprises acoustically distinct syllables organized into probabilistic sequences: a given syllable potentially can transition to several different syllables (divergence points), and several different syllables can transition to a given syllable (convergence points). In agreement with previous studies, we found that more probable transitions at divergence points occur with shorter intersyllable gaps. One intuition for this relationship is that selection between syllables reflects a competitive branching process, in which stronger links to one syllable lead to both higher probabilities and shorter latencies for transitions to that syllable vs. competing alternatives. However, we found that simulations of competitive race models result in overlapping winning-time distributions for competing outcomes and fail to replicate the strong negative correlation between probability and gap duration found in song data. Further investigation of song structure revealed strong positive correlation between gap durations for transitions that share a common convergent point. Such transitions are not related by a common competitive process, but instead reflect a common terminal syllable. In contrast to gap durations, transition probabilities were not correlated at convergence points. Together, our data suggest that syllable selection happens early during the gap, with gap timing determined chiefly by the latency to syllable initiation. This may result from a process in which probabilistic sequencing is first stabilized, followed by a shortening of the latency to syllables that are sung more often.NEW & NOTEWORTHY Bengalese finch songs consist of probabilistic sequences of syllables. Previous studies revealed a strong negative correlation between transition probability and the duration of intersyllable gaps. We show here that the negative correlation is inconsistent with previous suggestions that timing at syllable transitions is governed by a race between competing alternatives. Rather, the data suggest that syllable selection happens early during the gap, with gap timing determined chiefly by the latency to syllable initiation.

Project description:Birdsong provides a unique model for understanding the behavioral and neural bases underlying complex sequential behaviors. However, birdsong analyses require laborious effort to make the data quantitatively analyzable. The previous attempts had succeeded to provide some reduction of human efforts involved in birdsong segment classification. The present study was aimed to further reduce human efforts while increasing classification performance. In the current proposal, a linear-kernel support vector machine was employed to minimize the amount of human-generated label samples for reliable element classification in birdsong, and to enable the classifier to handle highly-dimensional acoustic features while avoiding the over-fitting problem. Bengalese finch's songs in which distinct elements (i.e., syllables) were aligned in a complex sequential pattern were used as a representative test case in the neuroscientific research field. Three evaluations were performed to test (1) algorithm validity and accuracy with exploring appropriate classifier settings, (2) capability to provide accuracy with reducing amount of instruction dataset, and (3) capability in classifying large dataset with minimized manual labeling. The results from the evaluation (1) showed that the algorithm is 99.5% reliable in song syllables classification. This accuracy was indeed maintained in evaluation (2), even when the instruction data classified by human were reduced to one-minute excerpt (corresponding to 300-400 syllables) for classifying two-minute excerpt. The reliability remained comparable, 98.7% accuracy, when a large target dataset of whole day recordings (∼30,000 syllables) was used. Use of a linear-kernel support vector machine showed sufficient accuracies with minimized manually generated instruction data in bird song element classification. The methodology proposed would help reducing laborious processes in birdsong analysis without sacrificing reliability, and therefore can help accelerating behavior and studies using songbirds.

Dataset Information

Relationship between the Sequencing and Timing of Vocal Motor Elements in Birdsong.

Publications

Relationship between the Sequencing and Timing of Vocal Motor Elements in Birdsong.

Similar Datasets

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