Behavioral discrimination and time-series phenotyping of birdsong performance.

ABSTRACT: Variation in the acoustic structure of vocal signals is important to communicate social information. However, relatively little is known about the features that receivers extract to decipher relevant social information. Here, we took an expansive, bottom-up approach to delineate the feature space that could be important for processing social information in zebra finch song. Using operant techniques, we discovered that female zebra finches can consistently discriminate brief song phrases ("motifs") from different social contexts. We then applied machine learning algorithms to classify motifs based on thousands of time-series features and to uncover acoustic features for motif discrimination. In addition to highlighting classic acoustic features, the resulting algorithm revealed novel featur

SUBMITTER: Paul A 

PROVIDER: S-EPMC8049717 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature