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Dryad

Data from: Combinatorial signal processing in an insect

Cite this dataset

Speck, Bretta et al. (2020). Data from: Combinatorial signal processing in an insect [Dataset]. Dryad. https://doi.org/10.5061/dryad.r4xgxd28v

Abstract

Human language is combinatorial: phonemes are grouped into syllables, syllables into words, and so on. The capacity for combinatorial processing is present to different degrees in some mammals and birds. We tested for basic combinatorial processing in an insect against two competing hypotheses: beginning rule (where the early signal portions play a stronger role in acceptability); and no rule (where the order of signal elements plays no role in signal acceptability). We worked with Enchenopa treehoppers, whose vibrational signals consist of a whine (W) followed by pulses (P). The combinatorial rule hypothesis predicts females will prefer any stimuli containing the natural-combination (WP or PWP) over reverse-order stimuli (PW). The beginning rule hypothesis predicts that females will prefer stimuli with natural beginnings (WP or W) over stimuli with modified beginnings (PW or PWP). The no rules hypothesis predicts no preferences in stimuli acceptability. In playback experiments using laser vibrometry, females preferred natural-combination signals regardless of the beginning element (WP or PWP) and discriminated against reverse-order signals (PW) or individual elements (W or P). Finding support for the combinatorial rule hypothesis in insects suggests that this capability represents a common solution to the problems presented by complex communication.

Methods

This data was collected during a playback experiment with female Enchenopa binotata treehoppers.  Synthetic playbacks of altered male advertisment signals were given using a piezo-electric controller and actuator (Thorlabs, Newton, NJ, USA) and recorded using a laser vibrometer (Polytec PLV-100; Polytec Inc., Auburn, MA, USA). Responses were tallied and analyzed.

Funding

University of Wisconsin–Milwaukee, Award: Research Growth Initiative Grant to RLR