Master's project talks

We reconstruct the physiological parameters that control an avian vocal organ during birdsong production using recorded song. The procedure involves fitting the time dependent parameters of an avian vocal organ model. Computationally, the model is implemented as a dynamical system ruling the behavior of the oscillating labia that modulate the air flow during sound production, together with the equations describing the dynamics of pressure fluctuations in the vocal tract. We tested our procedure for Zebra finch song with, simultaneously recorded physiological parameters: air sac pressure and the electromyographic activity of the left and right ventral syringeal muscles. A comparison of the reconstructed instructions with measured physiological parameters during song shows a high degree of correlation. Integrating the model with reconstructed parameters leads to the synthesis of highly realistic songs.

Birds evolved a novel vocal organ, the syrinx, that exhibits a high anatomical diversity. In the few species investigated, the syrinx can contain up to three pairs of functional syringeal vocal folds, acting as independent sound sources, and eight pairs of muscles. This rich variety in vocal structures and motor control results in a wide range of nonlinear phenomena (NLPs) and interactions that are distinct to avian vocal physiology, with many fascinating mechanisms yet to be discovered. Here, we review the occurrence of classical signatures of nonlinear dynamics, such as NLPs, including frequency jumps and transitions to chaos in birds. However, birds employ several additional unique tricks and transitions of inherent nonlinear dynamical nature that further enrich their vocal dynamics and are relevant for understanding the motor control of their vocalizations. Particularly, saddle-node in limit cycle (SNILC) bifurcations can switch sounds from tonal to harmonically rich and change the physiological control of fundamental frequency. In mammalian phonation, these bifurcations are mostly explored in the context of register transitions but could be equally relevant to altering vocal fold dynamical behaviour. Due to their diverse anatomy compared to mammals, birds provide unique opportunities to explore rich nonlinear dynamics in vocal production.This article is part of the theme issue ‘Nonlinear phenomena in vertebrate vocalizations: mechanisms and communicative functions’.

Quantitative biomechanical models can identify control parameters that are used during movements, and movement parameters that are encoded by premotor neurons. We fit a mathematical dynamical systems model including subsyringeal pressure, syringeal biomechanics and upper-vocal-tract filtering to the songs of zebra finches. This reduces the dimensionality of singing dynamics, described as trajectories (motor ‘gestures’) in a space of syringeal pressure and tension. Here we assess model performance by characterizing the auditory response ‘replay’ of song premotor HVC neurons to the presentation of song variants in sleeping birds, and by examining HVC activity in singing birds. HVC projection neurons were excited and interneurons were suppressed within a few milliseconds of the extreme time points of the gesture trajectories. Thus, the HVC precisely encodes vocal motor output through activity at the times of extreme points of movement trajectories. We propose that the sequential activity of HVC neurons is used as a ‘forward’ model, representing the sequence of gestures in song to make predictions on expected behaviour and evaluate feedback.

In recent years birdsong has developed into an extremely interesting problem for researchers in several branches of the scientific community. The reason is that of the approximately 10,000 species of birds known to exist, some 4000 share with humans (and just a few other species in the animal kingdom) a remarkable feature: their acquisition of vocalization requires a certain degree of exposure to a tutor. Between the complex neural architecture involved in the process and the song itself, stands a delicate apparatus that the bird must control with incredible precision. This book deals with the physical mechanisms at work in the production of birdsong, the acoustic effects that the avian vocal organ is capable of generating, and the nature of the neural instructions needed to drive it. The book provides fascinating reading for physicists, biologists and general readers alike.

Animal vocalizations comprise a rich array of complex sounds that exhibit nonlinear phenomena (NLP), which have fascinated researchers for decades. From the melodic songs of birds to the clicks and whistles of dolphins, many species have been found to produce nonlinear vocalizations, offering a valuable perspective on the mechanisms underlying sound production and potential adaptive functions. By leveraging on the principles of oscillator theory and nonlinear dynamics, animal vocalizations, which are based on coupled oscillators, can be described and conveniently classified. We review the basic ingredients for self-sustained oscillations and how different NLP can emerge. We discuss important terms in the context of oscillator theory: attractor types, phase space, bifurcations and Arnold tongue diagrams. Through a comparative analysis of observed NLP and bifurcation diagrams, our study reviews how the tools of nonlinear dynamics can provide insights into the intricate complexity of animal vocalizations, as well as into the evolutionary pressures and adaptive strategies that have shaped the diverse communication systems of the animal kingdom.This article is part of the theme issue, ‘Nonlinear phenomena in vertebrate vocalizations: mechanisms and communicative functions’.

As human infants grow, their vocalizations change from cries, to babbles, to words. This pattern has been presumed to be absent from other primates. Indeed, the development of bird song is often regarded as a closer approximation of human language development. Takahashi et al., however, observed that marmoset cries and calls in the first 2 months after birth mature in much the same way as they do in humans (see the Perspective by Margoliash and Tchernichovski). Calls changed as the infants’ vocal structures grew and were influenced by feedback from their parents. Science, this issue p. 734; see also p. 688 Young marmosets, like young humans, use cues from adults as they develop vocalizations. [Also see Perspective by Margoliash and Tchernichovski] Human vocal development occurs through two parallel interactive processes that transform infant cries into more mature vocalizations, such as cooing sounds and babbling. First, natural categories of sounds change as the vocal apparatus matures. Second, parental vocal feedback sensitizes infants to certain features of those sounds, and the sounds are modified accordingly. Paradoxically, our closest living ancestors, nonhuman primates, are thought to undergo few or no production-related acoustic changes during development, and any such changes are thought to be impervious to social feedback. Using early and dense sampling, quantitative tracking of acoustic changes, and biomechanical modeling, we showed that vocalizations in infant marmoset monkeys undergo dramatic changes that cannot be solely attributed to simple consequences of growth. Using parental interaction experiments, we found that contingent parental feedback influences the rate of vocal development. These findings overturn decades-old ideas about primate vocalizations and show that marmoset monkeys are a compelling model system for early vocal development in humans.