Ana Amador

Frequency modulation during song in a suboscine does not require vocal muscles

The physiology of sound production in suboscines is poorly investigated. Suboscines are thought to develop song innately unlike the closely related oscines. Comparing phonatory mechanisms might therefore provide interesting insight into the evolution of vocal learning. Here we investigate sound production and control of sound frequency in the Great Kiskadee (Pitangus sulfuratus) by recording air sac pressure and vocalizations during spontaneously generated song. In all the songs and calls recorded, the modulations of the fundamental frequency are highly correlated to air sac pressure. To test whether this relationship reflects frequency control by changing respiratory activity or indicates synchronized vocal control, we denervated the syringeal muscles by bilateral resection of the tracheosyringeal nerve. After denervation, the strong correlation between fundamental frequency and air sac pressure patterns remained unchanged. A single linear regression relates sound frequency to air sac pressure in the intact and denervated birds. This surprising lack of control by syringeal muscles of frequency in Kiskadees, in strong contrast to songbirds, poses the question of how air sac pressure regulates sound frequency. To explore this question theoretically, we assume a nonlinear restitution force for the oscillating membrane folds in a two mass model of sound production. This nonlinear restitution force is essential to reproduce the frequency modulations of the observed vocalizations.

Beyond harmonic sounds in a simple model for birdsong production.

In this work we present an analysis of the dynamics displayed by a simple bidimensional model of labial oscillations during birdsong production. We show that the same model capable of generating tonal sounds can present, for a wide range of parameters, solutions which are spectrally rich. The role of physiologically sensible parameters is discussed in each oscillatory regime, allowing us to interpret previously reported data.

Automatic reconstruction of physiological gestures used in a model of birdsong production

Highly coordinated learned behaviors are key to understanding neural processes integrating the body and the environment. Birdsong production is a widely studied example of such behavior in which numerous thoracic muscles control respiratory inspiration and expiration: the muscles of the syrinx control syringeal membrane tension, while upper vocal tract morphology controls resonances that modulate the vocal system output. All these muscles have to be coordinated in precise sequences to generate the elaborate vocalizations that characterize an individuals song. Previously we used a low-dimensional description of the biomechanics of birdsong production to investigate the associated neural codes, an approach that complements traditional spectrographic analysis. The prior study used algorithmic yet manual procedures to model singing behavior. In the present work, we present an automatic procedure to extract low-dimensional motor gestures that could predict vocal behavior. We recorded zebra finch songs and generated synthetic copies automatically, using a biomechanical model for the vocal apparatus and vocal tract. This dynamical model described song as a sequence of physiological parameters the birds control during singing. To validate this procedure, we recorded electrophysiological activity of the telencephalic nucleus HVC. HVC neurons were highly selective to the auditory presentation of the birds own song (BOS) and gave similar selective responses to the automatically generated synthetic model of song (AUTO). Our results demonstrate meaningful dimensionality reduction in terms of physiological parameters that individual birds could actually control. Furthermore, this methodology can be extended to other vocal systems to study fine motor control.

A Dynamic Analysis of Tuberculosis Dissemination to Improve Control and Surveillance

Background Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes.

An integrated model for motor control of song in Serinus canaria

Birdsong is a learned motor behavior controlled by an interconnected structure of neural nuclei. This pathway is bilaterally organized, with anatomically indistinguishable structures in each brain hemisphere. In this work, we present a computational model whose variables are the average activities of different neural nuclei of the song system of oscine birds. Two of the variables are linked to the air sac pressure and the tension of the labia during canary song production. We show that these time dependent gestures are capable of driving a model of the vocal organ to synthesize realistic canary like songs.

NONLINEAR DYNAMICS AND THE SYNTHESIS OF ZEBRA FINCH SONG

Behavior emerges as the interaction between a nervous system, a peripheral biomechanical device and the environment. In birdsong production, this observation is particularly important: songbirds are an adequate animal model to unveil how brain structures reconfigure themselves during learning of a complex behavior as song. Therefore, it is important to understand which features of behavior are controlled by independent tuning of neurophysiological parameters, and which are constrained by the biomechanics of the peripheral vocal organ. In this work, we show that many of the acoustic features in the Zebra finch song are in fact conditioned by the biomechanics involved.

Gating related activity in a syringeal muscle allows the reconstruction of zebra finches songs

Birdsong production involves the simultaneous and precise control of a set of muscles that change the configuration and dynamics of the vocal organ. Although it has been reported that each one of the different muscles is primarily involved in the control of one acoustic feature, recent advances have shown that they act synergistically to achieve the dynamical state necessary for phonation. In this work, we present a set of criteria that allow the extraction of gating-related information from the electromyographic activity of the syringealis ventralis muscle, a muscle that has been shown to be involved in frequency modulation. Using dynamical models of the muscle and syringeal dynamics, we obtain a full reconstruction of the zebra finch song using only the activity of this muscle.

Difference between the vocalizations of two sister species of pigeons explained in dynamical terms

Vocal communication is an unique example, where the nonlinear nature of the periphery can give rise to complex sounds even when driven by simple neural instructions. In this work we studied the case of two close-related bird species, Patagioenasmaculosa and Patagioenaspicazuro, whose vocalizations differ only in the timbre. The temporal modulation of the fundamental frequency is similar in both cases, differing only in the existence of sidebands around the fundamental frequency in the P. maculosa. We tested the hypothesis that the qualitative difference between these vocalizations lies in the nonlinear nature of the syrinx. In particular, we propose that the roughness of maculosa’s vocalizations is due to an asymmetry between the right and left vibratory membranes, whose nonlinear dynamics generate the sound. To test the hypothesis, we generated a biomechanical model for vocal production with an asymmetric parameter Q with which we can control the level of asymmetry between these membranes. Using this model we generated synthetic vocalizations with the principal acoustic features of both species. In addition, we confirmed the anatomical predictions by making post mortem inspection of the syrinxes, showing that the species with tonal song (picazuro) has a more symmetrical pair of membranes compared to maculosa.

Neural coding of sound envelope structure in songbirds

Songbirds are a well-established animal model to study the neural basis of learning, perception and production of complex vocalizations. In this system, telencephalic neurons in HVC present a state-dependent, highly selective response to auditory presentations of the bird’s own song (BOS). This property provides an opportunity to study the neural code behind a complex motor behavior. In this work, we explore whether changes in the temporal structure of the sound envelope can drive changes in the neural responses of highly selective HVC units. We generated an envelope-modified BOS (MOD) by reversing each syllable’s envelope but leaving the overall temporal structure of syllable spectra unchanged, which resulted in a subtle modification for each song syllable. We conducted in vivo electrophysiological recordings of HVC neurons in anaesthetized zebra finches (Taeniopygia guttata). Units analyzed presented a high BOS selectivity and lower response to MOD, but preserved the profile response shape. These results show that the temporal evolution of the sound envelope is being sensed by the avian song system and suggest that the biomechanical properties of the vocal apparatus could play a role in enhancing subtle sound differences.