A neural network-based analysis of acoustic courtship signals and female responses in Chorthippus biguttulus grasshoppers.

In many animal species, male acoustic courtship signals are evaluated by females for mate choice. At the behavioural level, this phenomenon has been well studied. However, although several song characteristics have been determined to affect the attractiveness of a given song, the mechanisms of the evaluation process remain largely unclear. Here, we present a simple neural network model for analysing and evaluating courtship songs of Chorthippus biguttulus males in real-time. The model achieves a high predictive power of the attractiveness of artificial songs as assigned by real Chorthippus biguttulus females: about 87% of the variance can be explained. It also allows us to determine the relative contribution of different song characteristics to overall attractiveness and how each of the song components influences female responsiveness. In general, the obtained results closely match those of empirical studies. Therefore, our model may be used to obtain a first estimate of male song attractiveness and may thus complement actual testing of female responsiveness in the laboratory. In addition, the model allows including and testing novel song parameters to generate new hypotheses for further experimental studies. The supplemental material of this article contains the article's data in an active, re-usable format.