Abstract
Various mechanisms have been proposed as the neural basis for pulse-rate recognition in insects and anurans, including models employing high- and low-pass filters, autocorrelation, and neural resonance. We used the katydid Tettigonia cantans to test these models by measuring female responsiveness on a walking compensator to stimuli varying in temporal pattern. Each model predicts secondary responses to certain stimuli other than the standard conspecific pulse rate. Females responded strongly to stimuli with a pulse-rate equal to half the standard rate, but not to stimuli with double the standard rate. When every second pulse or interval was varied in length, females responded only when the resulting stimuli were rhythmic with respect to the period of the standard signal. These results provide evidence rejecting the use of either high-/low-pass filter networks or autocorrelation mechanisms. We suggest that rate recognition in this species relies on the resonant properties of neurons involved in signal recognition. According to this model, signals with a pulse rate equal to the resonant frequency of the neurons stimulate the female to respond. The results are discussed with regard to both neural and evolutionary implications of resonance as a mechanism for signal recognition.
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Acknowledgements
This study was inspired by insightful discussions with Dagmar von Helversen. We will remember Dagmar as an outstanding scientist and a great friend. She and Otto von Helversen provided important input while planning the experiments. Albert Feng, Carl Gerhardt, Gary Rose, and one anonymous referee supplied helpful comments on the manuscript. The experiments comply with the “Principles of animal care,” publication No. 86–23, revised 1985 of the National Institute of Health, and also with the current laws of the United States of America. This work was supported in part by NSF grant IBN-0324290 to JS.
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In memory of Dagmar von Helversen (1944–2003)
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Bush, S.L., Schul, J. Pulse-rate recognition in an insect: evidence of a role for oscillatory neurons. J Comp Physiol A 192, 113–121 (2006). https://doi.org/10.1007/s00359-005-0053-x
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DOI: https://doi.org/10.1007/s00359-005-0053-x