Bird song dynamics: Studies in vocal diversity

The sound of birdsong can bring unrivalled joy to the attentive listener. Yet, such a pleasing melody is the result of complex biological mechanisms.

Understanding the physical and neurological processes that contribute to birdsong is an area of much interest among neurologists and neurobiologists. Considerable work has been undertaken to understand these processes. For example, it was discovered that 60 per cent of bird species can vocalise instinctively when isolated from others of its species, while the other 40 per cent require a tutor – a remarkable distinction which may hint at fundamental neurological difference between these bird species. However, it is uncommon for a complex biological process such as birdsong to be studied from a pure physics perspective.

Image: Pixabay

Gabriel Mindlin, a non-linear dynamical physicist from the University of Buenos Aires in Argentina, recently published his study of the dynamics of birdsong in the scientific journal Chaos. Mindlin and his team were keen to explore whether the song produced by the intricate avian vocal chords was governed by a set of simple and reproducible instructions. While the field of biology may accept the vast and incomprehensible nature of organic systems, physicists often seek a simple and elegant model to explain complex behaviour.

On this matter, Mindlin stated, “I was prepared to accept that many of the complexities of the behaviour could be associated to the fact that the vocal device was a nonlinear device and therefore even with simple parameters, you could describe complex behaviour.” The team studied the structure of song production in songbirds, and were able to draw out key features of all species of songbird using mathematical modelling. From this, it was determined that it was possible to build a uni-fying model of songbird melodies, with differences between species being attributed to the region of parameter space in which they operate.

Further, some features are present in the songs of all species. From this, Mindlin and his team were able to build models of songbird melody parameter space. In order to convince their colleagues in biology, Mindlin used their models to create synthetic birdsongs that were then tested by measuring the neural responses of zebra finches. The results were compared to the neural reactions of the zebra finches when responding to recordings of real birdsongs. It was found that the synthetic songs provoked very similar neural responses to the real songs, suggesting that the mathematical model was accurately mimicking a recognisable language for the zebra finches and rousing a true reaction. These results offer a fascinating, new insight in the mechanics of sound production in birds, including the dynamics of the birds’ vocal organs and the relationships between the physical mechanisms leading to sound production and the neural structures that control these physical mechanisms.

There is something quite remarkable about the intricate nature of birdsong being so perfectly reproduced by the integration of a periodically forced two-dimension dynamical system. Further studies utilising non-linear physics to explore biological systems include analysis of cardio-respiratory oscillations of humans in low-oxygen environments at Lancaster University, and the study of the movement of insects at the University of Texas. It is certainly an indication that the study of non-linear dynamics has the potential to offer a great deal of insight into the complex worlds of biology and neuroscience.

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