Biomechanical models to study the neural bases of birdsong production

A. AMADOR

Montevideo

Conferencia; XII International Congress of Neuroethology; 2016

Songbirds are a widely studied example of vocal learning that allows integrating neural and peripheralrecordings with a complex behavior. Although neural activity has been related to song acoustics inauditory playback experiments, the neural code for processing and generating birdsong remainselusive. To address this issue, we worked with a minimal physical model for birdsong production,having as an output a synthetic song. Each syllable was coded in terms of physiological parametersbirds can control, defining in this way motor gestures. To validate this model, we assessed responsesof the premotor forebrain nucleus HVC to song playback in sleeping and anesthetized birds, as HVCneurons exhibit highly selective responses to the bird´s own song (BOS). Remarkably, thebiomechanical model was able to elicit responses strikingly similar to those for BOS. The analysis ofneural activity in terms of the song production model allowed the emergence of a novel hypothesis ofmotor control in songbirds. We confirmed this result with HVC recordings in singing birds, showing thepertinence of working with a low dimensional model that represents an approximation of peripheralmechanics but captures relevant features of behavior.