Birds and models: Not as different as you might think

For some time, the Sturdy laboratory group has been studying chickadee vocal production and perception using a variety of approaches. These include, among others, bioacoustic analyses of vocalizations, operant conditioning studies, and, more recently, artificial neural networks. This multidisciplinary approach has been very fruitful. The addition of artificial neural networks to the standard empirical approaches has significantly enhanced the understanding of songbird behavior and has provided models of bird operant conditioning behavior, perception, and cognition, allowed the investigation of questions that would be difficult to carry out with animal studies, honed research questions and foci, and has inspired further empirical studies. This talk will provide a longitudinal review of these and related research findings capitalizing on this data-model∕model-data interplay. Topics discussed will include models of bird note type perception, models that have directed the formation of hypotheses about important perceptual features in note types, and models that have inspired further empirical studies of note type perception and have been used to explore a classic cognitive phenomenon, peak-shift, in a multimodal, note-type continuum.