Background During mate choice, individuals must classify potential mates according to species identity and relative attractiveness. In many species, females do so by evaluating variation in the signals produced by males. Male túngara frogs (Physalaemus pustulosus) can produce single note calls (whines) and multi-note calls (whine-chucks). While the whine alone is sufficient for species recognition, females greatly prefer the whine-chuck when given a choice. Methodology/Principal Findings To better understand how the brain responds to variation in male mating signals, we mapped neural activity patterns evoked by interspecific and intraspecific variation in mating calls in túngara frogs by measuring expression of egr-1. We predicted that egr-1 responses to conspecific calls would identify brain regions that are potentially important for species recognition and that at least some of those brain regions would vary in their egr-1 responses to mating calls that vary in attractiveness. We measured egr-1 in the auditory brainstem and its forebrain targets and found that conspecific whine-chucks elicited greater egr-1 expression than heterospecific whines in all but three regions. We found no evidence that preferred whine-chuck calls elicited greater egr-1 expression than conspecific whines in any of eleven brain regions examined, in contrast to predictions that mating preferences in túngara frogs emerge from greater responses in the auditory system. Conclusions Although selectivity for species-specific signals is apparent throughout the túngara frog brain, further studies are necessary to elucidate how neural activity patterns vary with the attractiveness of conspecific mating calls.
Neural Activity Patterns in Response to Interspecific and Intraspecific Variation in Mating Calls in the Túngara Frog
Mukta Chakraborty,L. Mangiamele,S. Burmeister
Published 2010 in PLoS ONE
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- Publication year
2010
- Venue
PLoS ONE
- Publication date
2010-09-22
- Fields of study
Biology, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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