Low dimensional models to study neural systems for motor control in songbirds Event as iCalendar

(Seminars)

08 December 2017

3:30 - 4:30pm

Venue: Ground floor seminar room (G10)

Location: 70 Symonds St, Auckland Central

Note the date and time change from the usual schedule.

An ABI seminar by Dr Ana Amador, Department of Physics, University of Buenos Aires and CONICET, Argentina.

Abstract

Birdsong is a complex motor activity that emerges from the interaction between the peripheral system (PS), the central nervous system (CNS) and the environment. The similarities to human speech, both in production and learning, have positioned songbirds as unique animal models for studying this learned motor skill.

In this work, we developed a low dimensional dynamical system model of the vocal apparatus in which inputs could be related to physiological variables, the output being a synthetic song (SYN) that could be compared with the recorded birdsong (BOS). To go beyond sound comparison, we measured neural activity highly tuned to BOS and found that the patterns of response to BOS and SYN were remarkably similar. This work related motor gestures to neural activity, making specific predictions on the timing. To study the dynamical emergence of this feature, we developed a neural model in which the variables were the average activities of different neural populations within the nuclei of the song system. This model can reproduce the measured respiratory patterns and matched the specific predictions on the timing of the neural activity during their production. In this talk, I will present experimental data in accordance with the dynamical model. This interdisciplinary work shows how low dimensional models for the PS and CNS can be a valuable tool for studying the neuroscience of generation and control of complex motor tasks.