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.
Similar content being viewed by others
References
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.
Alexander, R.D. (1957). The song relationships of four species of ground crickets (Orthoptera: Gryllidae: Nemobius). Ohio Journal of Science, 57(3), 153–163.
Alexander, R.D. (1962). Evolutionary change in cricket acoustical communication. Evolution, 16, 443–467.
Atencio, C.A., Sharpee, T.O., Schreiner, C.E. (2008). Cooperative nonlinearities in auditory cortical neurons. Neuron, 58, 956–966.
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.
Carandini, M., & Heeger, D.J. (2012). Normalization as a canonical neural computation. Nature Reviews Neuroscience, 13(1), 51–62.
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.
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.
Desutter Grandcolas, L., & Robillard, T. (2003). Phylogeny and the evolution of calling songs in Gryllus (Insecta, Orthoptera, Gryllidae). Zoologica Scripta, 32(2), 173–183.
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.
Gerhardt, C.H., & Huber, F. (2002). Acoustic Communication in Insects and Anurans. Chicago: University of Chicago Press.
Giraud, A.L., & Poeppel, D. (2012). Cortical oscillations and speech processing: emerging computational principles and operations. Nature Neuroscience, 15(4), 511–517.
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.
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.
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.
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.
Hoy, R., Hoikkala, A., Kaneshiro, K. (1988). Hawaiian courtship songs: evolutionary innovation in communication signals of Drosophila. Science, 240(4849), 217–219.
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.
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.
Mitchell, M. (1998). An introduction to genetic algorithms (complex adaptive systems) (3rd printing ed.). A Bradford Book.
Nagel, K.I., & Doupe, A.J. (2006). Temporal processing and adaptation in the songbird auditory forebrain. Neuron, 51(6), 845–859.
Otte, D. (1992). Evolution of cricket songs. Journal of Orthoptera Research, 1(1), 25–49.
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.
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.
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.
Pollack, G.S., & Hoy, R. (1979). Temporal pattern as a cue for species-specific calling song recognition in crickets. Science, 204(4391), 429–432.
Priebe, N.J., & Ferster, D. (2012). Mechanisms of neuronal computation in mammalian visual cortex. Neuron, 75(2), 194–208.
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.
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.
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.
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.
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.
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.
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.
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.
Smith, E.C., & Lewicki, M.S. (2006). Efficient auditory coding. Nature, 439(7079), 978–982.
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.
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.
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.
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.
Acknowledgment
We thank Klaus-Gerhardt Heller for valuable discussions.
Author information
Authors and Affiliations
Corresponding author
Additional information
Action Editor: Israel Nelken
This work was funded by grants from the Federal Ministry of Education and Research, Germany (01GQ1001A) and the Deutsche Forschungsgemeinschaft (SFB618, GK1589/1).
Rights and permissions
About this article
Cite this article
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
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10827-013-0441-0