Computational principles underlying the recognition of acoustic signals in insects

Abstract

Many animals produce pulse-like signals during acoustic communication. These signals exhibit structure on two time scales: they consist of trains of pulses that are often broadcast in packets—so called chirps. Temporal parameters of the pulse and of the chirp are decisive for female preference. Despite these signals being produced by animals from many different taxa (e.g. frogs, grasshoppers, crickets, bushcrickets, flies), a general framework for their evaluation is still lacking. We propose such a framework, based on a simple and physiologically plausible model. The model consists of feature detectors, whose time-varying output is averaged over the signal and then linearly combined to yield the behavioral preference. We fitted this model to large data sets collected in two species of crickets and found that Gabor filters—known from visual and auditory physiology—explain the preference functions in these two species very well. We further explored the properties of Gabor filters and found a systematic relationship between parameters of the filters and the shape of preference functions. Although these Gabor filters were relatively short, they were also able to explain aspects of the preference for signal parameters on the longer time scale due to the integration step in our model. Our framework explains a wide range of phenomena associated with female preference for a widespread class of signals in an intuitive and physiologically plausible fashion. This approach thus constitutes a valuable tool to understand the functioning and evolution of communication systems in many species.

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References

  1. Akre, K.L., Farris, H.E., Lea, A.M., Page, R.A., Ryan, M.J. (2011). Signal perception in frogs and bats and the evolution of mating signals. Science, 333(6043), 751–752.

    PubMed  Article  CAS  Google Scholar 

  2. Alexander, R.D. (1957). The song relationships of four species of ground crickets (Orthoptera: Gryllidae: Nemobius). Ohio Journal of Science, 57(3), 153–163.

    Google Scholar 

  3. Alexander, R.D. (1962). Evolutionary change in cricket acoustical communication. Evolution, 16, 443–467.

    Article  Google Scholar 

  4. Atencio, C.A., Sharpee, T.O., Schreiner, C.E. (2008). Cooperative nonlinearities in auditory cortical neurons. Neuron, 58, 956–966.

    PubMed  Article  CAS  Google Scholar 

  5. Bush, S.L., & Schul, J. (2005). Pulse-rate recognition in an insect: evidence of a role for oscillatory neurons. Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 192, 1–9.

    Google Scholar 

  6. Carandini, M., & Heeger, D.J. (2012). Normalization as a canonical neural computation. Nature Reviews Neuroscience, 13(1), 51–62.

    Article  CAS  Google Scholar 

  7. Clemens, J., Wohlgemuth, S., Ronacher, B. (2012). Nonlinear com putations underlying temporal and population sparseness in the auditory system of the grasshopper. Journal of Neuroscience, 32(29), 10,053–10,062.

    Article  CAS  Google Scholar 

  8. Creutzig, F., Benda, J., Wohlgemuth, S., Stumpner, A., Ronacher, B., Herz, A.V.M. (2010). Timescale-invariant pattern recognition by feedforward inhibition and parallel signal processing. Neural 697 Computation, 22(6), 1493–1510.

    PubMed  Article  Google Scholar 

  9. Desutter Grandcolas, L., & Robillard, T. (2003). Phylogeny and the evolution of calling songs in Gryllus (Insecta, Orthoptera, Gryllidae). Zoologica Scripta, 32(2), 173–183.

    Article  Google Scholar 

  10. Fairhall, A.L., Burlingame, A.C., Narasimhan, R., Harris, R.A., Puchalla, J.L., Berry, M.J. (2006). Selectivity for multiple stimulus features in retinal ganglion cells. Journal of Neurophysiology, 96, 2724–2738.

    PubMed  Article  Google Scholar 

  11. Gerhardt, C.H., & Huber, F. (2002). Acoustic Communication in Insects and Anurans. Chicago: University of Chicago Press.

    Google Scholar 

  12. Giraud, A.L., & Poeppel, D. (2012). Cortical oscillations and speech processing: emerging computational principles and operations. Nature Neuroscience, 15(4), 511–517.

    PubMed  Article  CAS  Google Scholar 

  13. Grobe, B., Rothbart, M.M., Hanschke, A., Hennig, R.M. (2012). Auditory processing at two time scales by the cricket Gryllus bimaculatus. Journal of Experimental Biology, 215(10), 1681–1690.

    PubMed  Article  Google Scholar 

  14. Hennig, R.M. (2003). Acoustic feature extraction by cross-correlation in crickets? Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 189(8), 589–598.

    Article  CAS  Google Scholar 

  15. Hennig, R.M. (2009). Walking in Fourier’s space: algorithms for the computation of periodicities in song patterns by the cricket Gryllus bimaculatus. Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 195(10), 971–987.

    Article  Google Scholar 

  16. 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: Sensory Neural, and Behavioral Physiology, 180(6), 621–630.

    Article  Google Scholar 

  17. Hoy, R., Hoikkala, A., Kaneshiro, K. (1988). Hawaiian courtship songs: evolutionary innovation in communication signals of Drosophila. Science, 240(4849), 217–219.

    PubMed  Article  CAS  Google Scholar 

  18. Kostarakos, K., & Hedwig, B. (2012). Calling song recognition in female crickets: temporal tuning of identified brain neurons matches behavior. Journal of Neuroscience, 32(28), 9601–9612.

    PubMed  Article  CAS  Google Scholar 

  19. Machens, C.K., Stemmler, M., Prinz, P., Krahe, R., Ronacher, B., Herz, A.V.M. (2001). Representation of acoustic communication signals by insect auditory receptor neurons. Journal of Neuroscience, 21(9), 3215–3227.

    PubMed  CAS  Google Scholar 

  20. Mitchell, M. (1998). An introduction to genetic algorithms (complex adaptive systems) (3rd printing ed.). A Bradford Book.

  21. Nagel, K.I., & Doupe, A.J. (2006). Temporal processing and adaptation in the songbird auditory forebrain. Neuron, 51(6), 845–859.

    PubMed  Article  CAS  Google Scholar 

  22. Otte, D. (1992). Evolution of cricket songs. Journal of Orthoptera Research, 1(1), 25–49.

    Article  Google Scholar 

  23. Phelps, S.M., & Ryan, M.J. (1998). Neural networks predict response biases of female túngara frogs. Proceedings of the Royal Society of London Series B, 265(1393), 279–285.

    PubMed  Article  CAS  Google Scholar 

  24. Pillow, J.W., & Simoncelli, E.P. (2006). Dimensionality reduction in neural models: An information-theoretic generalization of spike-triggered average and covariance analysis. Journal of vision, 6, 414–428.

    PubMed  Article  Google Scholar 

  25. Pillow, J.W., Shlens, J., Paninski, L., Sher, A., Litke, A.M., Chichilnisky, E.J., Simoncelli, E.P. (2008). Spatio-temporal correlations and visual signaling in a complete neuronal population. Nature, 454(7207), 995–999.

    PubMed  Article  CAS  Google Scholar 

  26. Pollack, G.S., & Hoy, R. (1979). Temporal pattern as a cue for species-specific calling song recognition in crickets. Science, 204(4391), 429–432.

    PubMed  Article  CAS  Google Scholar 

  27. Priebe, N.J., & Ferster, D. (2012). Mechanisms of neuronal computation in mammalian visual cortex. Neuron, 75(2), 194–208.

    PubMed  Article  CAS  Google Scholar 

  28. Ronacher, B., & Stumpner, A. (1988). Filtering of behaviourally relevant temporal parameters of a grasshopper’s song by an auditory interneuron. Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 163, 517–523.

    Article  Google Scholar 

  29. Rothbart, M.M., & Hennig, R.M. (2012). The Steppengrille (Gryllus spec./assimilis): Selective filters and signal mismatch on two time scales. PLoS ONE, 7(9), e43975.

    PubMed  Article  CAS  Google Scholar 

  30. Rothbart, M.M., & Hennig, R.M. (2012). Calling song signals and temporal preference functions in the cricket Teleogryllus leo. Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 198(11), 817–825.

    Article  CAS  Google Scholar 

  31. Safi, K., Heinzle, J., Reinhold, K. (2006). Species recognition influences female mate preferences in the common European grasshopper (Chorthippus biguttulus Linnaeus, 1758). Ethology, 112(12), 1225–1230.

    Article  Google Scholar 

  32. 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: Sensory Neural, and Behavioral Physiology, 194(3), 221–233.

    Article  CAS  Google Scholar 

  33. Schneider, E., & Hennig, R.M. (2012). Temporal resolution for calling song signals by female crickets, Gryllus bimaculatus. Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 198(3), 181–191.

    Article  CAS  Google Scholar 

  34. Schreiber, S., Erchova, I., Heinemann, U., Herz, A.V.M. (2004). Subthreshold resonance explains the frequency-dependent integration of periodic as well as random stimuli in the entorhinal cortex. Journal of Neurophysiology, 92(1), 408–415.

    PubMed  Article  Google Scholar 

  35. Schul, J. (1998). Song recognition by temporal cues in a group of closely related bushcricket species (genus Tettigonia ). Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 183(3), 401–410.

    Article  Google Scholar 

  36. Smith, E.C., & Lewicki, M.S. (2006). Efficient auditory coding. Nature, 439(7079), 978–982.

    PubMed  Article  CAS  Google Scholar 

  37. von Helversen, D. (1972). Gesang des M’́annchens und Lautschema des Weibchens bei der Feldheuschrecke Chorthippus biguttulus (Orthoptera, Acrididae). Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 81(4), 381–422.

    Article  Google Scholar 

  38. Webb, B., Wessnitzer, J., Bush, S.L., Schul, J., Buchli, J., Ijspeert, A. (2007). Resonant neurons and bushcricket behaviour. Journal of Comparative Physiology A: Sensory Neural, and Behavioral Physiology, 193(2), 285–288.

    Article  Google Scholar 

  39. Weissman, D.B., Gray, D.A., Pham, H.T., Tijssen, P. (2012). Billions and billions sold: Pet-feeder crickets (Orthoptera: Gryllidae), commercial cricket farms, an epizootic densovirus, and government regulations make for a potential disaster. Zootaxa, 3504, 67–88.

    Google Scholar 

  40. Zorovic, M., & Hedwig, B. (2011). Processing of species-specific auditory patterns in the cricket brain by ascending, local and descending neurons during standing and walking. Journal of Neurophysiology, 105, 2181–2194.

    PubMed  Article  CAS  Google Scholar 

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Acknowledgment

We thank Klaus-Gerhardt Heller for valuable discussions.

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Correspondence to Jan Clemens.

Additional information

This work was funded by grants from the Federal Ministry of Education and Research, Germany (01GQ1001A) and the Deutsche Forschungsgemeinschaft (SFB618, GK1589/1).

Action Editor: Israel Nelken

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Clemens, J., Hennig, R.M. Computational principles underlying the recognition of acoustic signals in insects. J Comput Neurosci 35, 75–85 (2013). https://doi.org/10.1007/s10827-013-0441-0

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Keywords

  • Perceptual decision making
  • Insect
  • Song
  • Linear-nonlinear model
  • Gabor filter