260 | Exploring the neural encoding of the biomechanics of songbird vocal production: perspective from a biophysical-inspired model

Sensory and Motor Systems

Author: Javier Nahuel Lassa Ortiz | Email: javi.lassa@gmail.com

Javier Nahuel Lassa Ortiz , Gabriel B. Mindlin , Ana Amador


How vocal communication signals are represented in the cortex is a major challenge for behavioral neuroscience. We used a biophysical model based on the biomechanics of vocal production in songbirds. This mathematical model has as an output synthetic songs that are built to be a copy of the recorded songs uttered by songbirds. This model strongly links vocal production and the biomechanics of the bird’s vocal apparatus, allowing us to modify parameters representing the size of the bird’s neck and head. We generated a variety of synthetic songs representing birds of different sizes. We presented auditory stimuli while recording neuronal activity in the sensori-motor neural nucleus HVC (proper name) in sleeping Zebra finches (Taeniopygia guttata). This species has the characteristic that HVC nucleus shows neuronal selectivity towards its own song when they are asleep. We found an increase in neuronal activity in response to some of the synthetic but only basal activity when the synthetic songs corresponded to “monstrous” combinations of parameters, where the relationship between “head size” and “neck length” did not follow natural scaling laws. These findings suggest that HVC could be encoding complex biomechanical information about its own song and that scaling laws are naturally encoded in this telencephalic nucleus. Furthermore, these results highlight the value of having biomechanics-inspired modeling tools to conduct experiments that would otherwise not be possible.