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Frequency-channel dependent selectivity for temporal call characteristics in gray treefrogs, Hyla versicolor
Author(s) -
Michael S. Reichert,
Gerlinde Höbel
Publication year - 2017
Publication title -
journal of experimental biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.367
H-Index - 185
eISSN - 1477-9145
pISSN - 0022-0949
DOI - 10.1242/jeb.152330
Subject(s) - hyla , gray (unit) , frequency selectivity , biology , channel (broadcasting) , zoology , computer science , telecommunications , medicine , electronic engineering , engineering , radiology
Sensory receptors transmit information on multiple stimulus dimensions. Much remains to be understood about how the processing of different signal characteristics is partitioned and integrated in different areas of the nervous system. Amphibian hearing involves two morphologically distinct inner-ear organs that process different components of the frequency spectrum. Many anuran signals contain two frequency peaks, each one matching the sensitivity of one of these two organs. We hypothesized that the processing of temporal characteristics of acoustic signals would differ in these two frequency channels, perhaps because of differences in the response properties of the two inner-ear organs. We tested this hypothesis in the gray treefrog, Hyla versicolor ; male advertisement calls of this species contain a bimodal frequency spectrum. We generated synthetic male advertisement calls in which we independently manipulated the pattern of amplitude modulation in the low-frequency peak or the high-frequency peak and measured the attractiveness of these stimuli to females in single-speaker and two-speaker phonotaxis tests. We obtained multiple lines of evidence that females were more selective for fine-temporal characteristics in the high-frequency peak. We discuss the potential implications of frequency channel-dependent temporal processing for signal evolution and suggest that additional neurophysiological investigations of the anuran auditory periphery will give important insights into how the nervous system partitions the encoding of multiple characteristics of complex signals.

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