Skip to main content
Log in

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

  • Published:
Journal of Computational Neuroscience Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Balakrishnan, R., von Helversen, D., & von Helversen, O. (2001). Song pattern recognition in the grasshopper Chorthippus biguttulus: the mechanism of syllable onset and offset detection. Journal of Comparative Physiology A, 187, 255–264.

    Article  CAS  Google Scholar 

  • Bradbury, J. W., & Vehrencamp, S. (1998). Principles of animal communication. Massachusetts: Sinauer Associates Inc.

    Google Scholar 

  • Brown, W. D., Wideman, J., Andrade, M. C. B., Mason, A. C., & Gwynne, D. T. (1996). Female choice for an indicator of male size in the song of the black-horned tree cricket Oecanthus nigricornis (Orthoptera: Gryllidae: Oecanthinae). Evolution, 50, 2400–2411.

    Article  Google Scholar 

  • Bush, R. R., & Mosteller, F. (1955). Stochastic models for learning. New York: Wiley.

    Google Scholar 

  • Clarke, G. M. (1995). The genetic basis of developmental stability. II. Asymmetry of extreme phenotypes revisited. American Naturalist, 146, 708–725.

    Article  Google Scholar 

  • Connor, J. T., Martin, R. D., & Atlas, L. E. (1994). Recurrent neural networks and robust time series prediction. IEEE Transactions on Neural Networks, 5, 240–254.

    Article  PubMed  CAS  Google Scholar 

  • Crawley, M. J. (1993). GLIM for ecologists. Oxford: Blackwell Scientific.

    Google Scholar 

  • Creutzig, F., Wohlgemuth, S., Stumpner, A., Benda, J., Ronacher, B., & Herz, A. V. (2009). Timescale-invariant representation of acoustic communication signals by a bursting neuron. Journal of Neuroscience, 29, 2575–2580.

    Article  PubMed  CAS  Google Scholar 

  • Creutzig, F., Benda, J., Wohlgemuth, S., Stumpner, A., Ronacher, B., & Herz, A. V. (2010). Timescale-invariant pattern recognition by feedforward inhibition and parallel signal processing. Neural Computation, 22, 1493–1510.

    Article  PubMed  Google Scholar 

  • Dev, A., Agrawal, S. S., & Choudhury, D. R. (2003). Categorization of Hindi phonemes by neural networks. AI & Society, 17, 375–382.

    Article  Google Scholar 

  • Farrell, K. R., Mammone, R. J., & Assaleh, K. T. (1994). Speaker recognition using neural networks and conventional classifiers. IEEE Transactions on Speech and Audio Processing, 2, 194–205.

    Article  Google Scholar 

  • Fisher, R. A. (1930). The genetical theory of natural selection. Oxford: Oxford University Press.

    Google Scholar 

  • Fukushima, K. (1988). Neocognitron: A hierarchical neural network capable of visual pattern recognition. Neural Networks, 1, 119–130.

    Article  Google Scholar 

  • Giles, L. C., Lawrence, S., & Tsoi, A. C. (2001). Noisy time series prediction using a recurrent neural network and grammatical inference. Machine Learning, 44, 161–183.

    Article  Google Scholar 

  • Hampshire, J. B., & Waibel, A. H. (1990). A novel objective function for improved phoneme recognition using time-delay neural networks. IEEE Transactions on Neural Networks, 1, 216–228.

    Article  PubMed  CAS  Google Scholar 

  • Hartmann, G., & Wehner, R. (1995). The ant’s path integration system: a neural architecture. Biological Cybernetics, 73, 483–497.

    Google Scholar 

  • von Helversen, D. (1972). Gesang des Männchens und Lautschema des Weibchens bei der Feldheuschrecke Chorthippus biguttulus (Orthoptera, Acrididae). Journal of Comparative Physiology A, 81, 381–422.

    Article  Google Scholar 

  • von Helversen, O. (1979). Angeborenes Erkennen akustischer Schlüsselreize. Verhandlungen der Deutschen Zoologischen Gesellschaft, 1979, 42–59.

    Google Scholar 

  • von Helversen, D. (1993). Absolute steepness of ramps as an essential cue for auditory pattern recognition by a grasshopper (Orthoptera; Acrididae; Chorthippus biguttulus L.). Journal of Comparative Physiology A, 172, 633–639.

    Article  Google Scholar 

  • von Helversen, D., & von Helversen, O. (1975). Verhaltensgenetische Untersuchungen am akustischen Kommunikationssystem der Feldheuschrecken (Orthoptera, Acrididae). I. Der Gesang von Artbastarden zwischen Chorthippus biguttulus und Ch. mollis. Journal of Comparative Physiology A, 104, 273–299.

    Article  Google Scholar 

  • von Helversen, D., & von Helversen, O. (1983). Species recognition and acoustic localization in acridid grasshoppers: a behavioural approach. In F. Huber & H. Markl (Eds.), Neuroethology and Behavioral Physiology (pp. 95–107). Berlin: Springer-Verlag.

    Google Scholar 

  • von Helversen, D., & von Helversen, O. (1994). Forces driving coevolution of song and song recognition in grasshoppers. In K. Schildberger & N. Elsner (Eds.), Neural basis of behavioural adaptations (pp. 253–284). Stuttgart: Fortschr d Zool.

    Google Scholar 

  • von Helversen, D., & von Helversen, O. (1997). Recognition of sex in the acoustic communication of the grasshopper Chorthippus biguttulus (Orthoptera, Acrididae). Journal of Comparative Physiology A, 180, 373–386.

    Article  Google Scholar 

  • von Helversen, D., & von Helversen, O. (1998). Acoustic pattern recognition in a grasshopper: processing in the time or frequency domain? Biological Cybernetics, 79, 467–476.

    Article  Google Scholar 

  • Hennig, R. M., & Weber, T. (1997). Filtering of temporal parameters of the calling song by cricket females of two closely related species: a behavioral analysis. Journal of Comparative Physiology A, 180, 621–630.

    Article  Google Scholar 

  • Hennig, R. M., Franz, A., & Stumpner, A. (2004). Processing of auditory information in insects. Microscopy Research and Technique, 63, 351–374.

    Article  PubMed  CAS  Google Scholar 

  • Klappert, K., & Reinhold, K. (2003). Acoustic preference functions and sexual selection on the male calling song in the grasshopper Chorthippus biguttulus. Animal Behaviour, 65, 225–233.

    Article  Google Scholar 

  • Kriegbaum, H. (1989). Female choice in the grasshopper Chorthippus biguttulus: mating success is related to song characteristics of the male. Naturwissenschaften, 76, 81–82.

    Article  Google Scholar 

  • Machens, C. K., Martin, B., Stemmler, M. B., Prinz, P., Krahe, R., Ronacher, B., et al. (2001). Representation of acoustic communication signals by insect auditory receptor neurons. Journal of Neuroscience, 21, 3215–3227.

    PubMed  CAS  Google Scholar 

  • Machens, C. K., Schütze, H., Franz, A., Kolesnikova, O., Stemmler, M. B., Ronacher, B., et al. (2003). Single auditory neurons rapidly discriminate conspecific communication signals. Nature Neuroscience, 6, 341–342.

    Article  PubMed  CAS  Google Scholar 

  • Minsky, M., & Papert, S. (1969). Perceptrons. Cambridge: MIT.

    Google Scholar 

  • Neuhofer, D., Wohlgemuth, S., Stumpner, A., & Ronacher, B. (2008). Evolutionarily conserved coding properties of auditory neurons across grasshopper species. Proceedings of the Royal Society B, 275, 1965–1974.

    Article  PubMed  Google Scholar 

  • Parsons, P. A. (1992). Fluctuating asymmetry: a biological monitor of environmental and genomic stress. Heredity, 68, 361–364.

    Article  PubMed  Google Scholar 

  • Phelps, M. S., & Ryan, M. J. (1998). Neural networks predict response biases of female túngara frogs. Proceeedings of the Royal Society B, 265, 279–285.

    Article  CAS  Google Scholar 

  • Phung, S. L., & Bouzerdoum, A. (2007). A pyramidal neural network for visual pattern recognition. IEEE Transactions on Neural Networks, 18, 329–343.

    Article  PubMed  Google Scholar 

  • Reinhold, K., Jacoby, K. J., & Reinhold, K. (2002). Dissecting the repeatability of female choice in the grasshopper Chorthippus biguttulus. Animal Behaviour, 64, 245–250.

    Article  Google Scholar 

  • Ronacher, B., & Krahe, R. (2000). Temporal integration vs. parallel processing: coping with the variability of neuronal messages in directional hearing of insects. European Journal of Neuroscience, 12, 2147–2156.

    Article  PubMed  CAS  Google Scholar 

  • Ronacher, B., Wohlgemuth, S., Vogel, A., & Krahe, R. (2008). Discrimination of acoustic communication signals by grasshoppers (Chorthippus biguttulus): temporal resolution, temporal integration, and the impact of intrinsic noise. Journal of Comparative Psychology, 122, 252–263.

    Article  PubMed  Google Scholar 

  • Rosenblatt, F. (1958). The perceptron: a probabilistic model for information storage and organization in the brain. Psychological Review, 65, 386–408.

    Article  PubMed  CAS  Google Scholar 

  • Rumelhart, D. E., & McClelland, J. L. (1986). Parallel distributed processing: explorations in the microstructure of cognition. Volume I. Cambridge: MIT.

    Google Scholar 

  • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323, 533–536.

    Article  Google Scholar 

  • Ryan, M. J. (1985). The tungara frog: a study in sexual selection and communication. Chicago: University of Chicago Press.

    Google Scholar 

  • Safi, K., Heinzle, J., & Reinhold, K. (2006). Species recognition influences female mate preferences in the common European grasshopper (Chorthippus biguttulus Linnaeus, 1758). Ethology, 112, 1225–1230.

    Article  Google Scholar 

  • Schildberger, K. (1984). Temporal selectivity of identified auditory neurons in the cricket brain. Journal of Comparative Physiology A, 155, 171–185.

    Article  Google Scholar 

  • Schmidt, A., Ronacher, B., & Hennig, R. M. (2008). The role of frequency, phase and time for processing of amplitude modulated signals by grasshoppers. Journal of Comparative Physiology A, 194, 221–233.

    Article  CAS  Google Scholar 

  • Stumpner, A., & Ronacher, B. (1991). Auditory interneurones in the metathoracic ganglion of the grasshopper Chorthippus biguttulus. I. Morphological and physiological characterization. Journal of Experimental Biology, 158, 391–410.

    Google Scholar 

  • Uncini, A. (2003). Audio signal processing by neural networks. Neurocomputing, 55, 593–625.

    Article  Google Scholar 

  • Waibel, A., Hanazawa, T., Hinton, G., Shikano, K., & Lang, K. J. (1989). Phoneme recognition using time-delay neural networks. IEEE Transactions on Acoustics, Speech, and Signal Processing, 37, 328–339.

    Article  Google Scholar 

  • Weber, T., & Thorson, J. (1989). Phonotactic behavior of walking crickets. In F. Huber, T. E. Moore, & W. Loher (Eds.), Cricket behavior and neurobiology (pp. 310–339). Ithaca: Cornell University Press.

    Google Scholar 

  • Zahavi, A. (1975). Mate selection—a selection for a handicap. Journal of Theoretical Biology, 53, 205–214.

    Article  PubMed  CAS  Google Scholar 

  • Zell, A. (2000). Simulation neuronaler Netze. München: Oldenbourg Verlag.

    Google Scholar 

Download references

Acknowledgements

We thank Eva M. Buchkremer for helpful suggestions and discussion on the model and the manuscript. Till Bockemühl also provided helpful comments on an early version of the model. Holk Cruse made useful comments on a previous version of the manuscript. Matthias Hennig provided the original data for our analysis, and he as well as three anonymous reviewers also made numerous helpful and constructive suggestions for improvement of the manuscript. Funding by the Volkswagen Foundation to MK is gratefully acknowledged. The source code will be made available upon request.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Klaus Reinhold.

Additional information

Action Editor: Catherine E. Carr

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(XLS 162 kb)

ESM 2

(XLS 711 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wittmann, J.P., Kolss, M. & Reinhold, K. A neural network-based analysis of acoustic courtship signals and female responses in Chorthippus biguttulus grasshoppers. J Comput Neurosci 31, 105–115 (2011). https://doi.org/10.1007/s10827-010-0299-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10827-010-0299-3

Keywords

Navigation