RESEARCH: (For a more complete review see the article in Scholarpedia)

Much of the study of the behavior that enhances the survival and reproduction of an animal is focused on its neural control. The generation of a behavior, however, involves strong interactions between the nervous system, the morphology and the environment. The functional morphology and biomechanics of a peripheral system impose constraints on the neural control, and also provide opportunities for the emergence of complexity in behavior. A wonderful exam­ple of this rich interplay is birdsong, where neural instructions drive a highly nonlinear physical system, the syrinx, capable of generating acoustic signals that range from simple whistles to most complex sounds. By complex sounds we denote irregular vocalizations, mostly per­ceived as rough sounds. They can be found not only in birdsong but also in humans in newborn cries, some vocalizations of infants, and as the result of different voice-disorders.


Many acoustic features of song are not independently controlled, but are determined by the biomechanics of the vocal organ. Moreover, many of those features do not depend on the details of the models but on the dynamical mechanisms involved. Here we display a bifurcation diagram corresponding to a model for a zebra finch synrix.


A good model should allow us to classify, hierarchically, the importance of different parameters in order to achieve a particular solution. We build biomimetic synthesizers with programmable DSP (digital signal processors) which integrate equations for the avian vocal organ, and drive them with experimentally recorded physiological parameters. Here we show a zebra finch song, as well as numerical and electronic integrations of a model where the parameters are air sac pressure and muscle activity recorded during song.
The goal of our proposed research is to understand the mechanisms involved in the generation of complex sounds, which are commonly found in birdsong and to characterize the role of the peripheral system in this process. Existing physiological data, combined with data we collect in these species, allow us to dissect the respective roles of peripheral mechanisms and neural instructions in the generation of complex sounds.
By combining techniques from nonlinear dynamics, biomechanics and experimental tecniques, we aim at unveiling which part of the complexity in birdsong is associated to complex neural instructions, what part is associated to the interaction between a nervous system and a nonlinear device, and the dynamical origin of some physiological instructions driving the vocal organ. Among other applications, we use this knowledge to produce physiologically driven biomimetic devices.


The air sac pressure patterns of canaries during song are not arbitrary time series: their topological features are identical to subharmonic solutions of a low dimensional nonlinear forced system. We are interested in the dynamical mechanisms involved in generating low dimensional average activities by large ensembles of dynamical units.