title: Neural representation of calling songs and their behavioral relevance in the grasshopper auditory system.
abstract: Acoustic communication plays a key role for mate attraction in grasshoppers. Males use songs to advertise themselves to females. Females evaluate the song pattern, a repetitive structure of sound syllables separated by short pauses, to recognize a conspecific male and as proxy to its fitness. In their natural habitat females often receive songs with degraded temporal structure. Perturbations may, for example, result from the overlap with other songs. We studied the response behavior of females to songs that show different signal degradations. A perturbation of an otherwise attractive song at later positions in the syllable diminished the behavioral response, whereas the same perturbation at the onset of a syllable did not affect song attractiveness. We applied naïve Bayes classifiers to the spike trains of identified neurons in the auditory pathway to explore how sensory evidence about the acoustic stimulus and its attractiveness is represented in the neuronal responses. We find that populations of three or more neurons were sufficient to reliably decode the acoustic stimulus and to predict its behavioral relevance from the single-trial integrated firing rate. A simple model of decision making simulates the female response behavior. It computes for each syllable the likelihood for the presence of an attractive song pattern as evidenced by the population firing rate. Integration across syllables allows the likelihood to reach a decision threshold and to elicit the behavioral response. The close match between model performance and animal behavior shows that a spike rate code is sufficient to enable song pattern recognition.
authors.affiliation: Neuroinformatics and Theoretical Neuroscience, Department of Biology, Chemistry and Pharmacy, Institute of Biology, Freie Universität Berlin Berlin, Germany.
authors.forename: Gundula
authors.initials: G
authors.lastname: Meckenhäuser
authors.affiliation: Behavioural Physiology Group, Department of Biology, Humboldt-Universität zu Berlin Berlin, Germany.
authors.forename: Stefanie
authors.initials: S
authors.lastname: Krämer
authors.affiliation: Neuroinformatics and Theoretical Neuroscience, Department of Biology, Chemistry and Pharmacy, Institute of Biology, Freie Universität Berlin Berlin, Germany ; Bernstein Center for Computational Neuroscience Berlin, Germany.
authors.forename: Farzad
authors.initials: F
authors.lastname: Farkhooi
authors.affiliation: Behavioural Physiology Group, Department of Biology, Humboldt-Universität zu Berlin Berlin, Germany.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Ronacher
authors.affiliation: Bernstein Center for Computational Neuroscience Berlin, Germany.
authors.forename: Martin P
authors.initials: MP
authors.lastname: Nawrot
keywords: acoustic communication; decision making; naïve Bayes classifier; neural information processing; pattern recognition; population coding