ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2013
Feature extraction and integration underlying perceptual decision making during courtship behavior.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Structured random receptive fields enable informative sensory encodings.PLoS computational biology · 2022Article
- A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets.eLife · 2021Article
- Sex-specific speed-accuracy trade-offs shape neural processing of acoustic signals in a grasshopper.Proceedings. Biological sciences · 2021Article
- Innate releasing mechanisms and fixed action patterns: basic ethological concepts as drivers for neuroethological studies on acoustic communication in Orthoptera.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2019Review
- Statistics of Natural Communication Signals Observed in the Wild Identify Important Yet Neglected Stimulus Regimes in Weakly Electric Fish.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
- Robustness of an innate releasing mechanism against degradation of acoustic communication signals in the grasshopper Chorthippus biguttulus.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2018Article
- Relative weighting of acoustic information during mating decisions in grasshoppers indicates signatures of sexual selection.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2017Article
- Article
- Computational themes of peripheral processing in the auditory pathway of insects.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2015Review
- Computational principles underlying recognition of acoustic signals in grasshoppers and crickets.Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology · 2015Review
- Asymmetrical integration of sensory information during mating decisions in grasshoppers.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
- From microseconds to seconds and minutes-time computation in insect hearing.Frontiers in physiology · 2014Review
- Neural representation of calling songs and their behavioral relevance in the grasshopper auditory system.Frontiers in systems neuroscience · 2014Article
- Time and timing in the acoustic recognition system of crickets.Frontiers in physiology · 2014Article
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2 authors.
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Abstract
Traditionally, perceptual decision making is studied in trained animals and carefully controlled tasks. Here, we sought to elucidate the stimulus features and their combination underlying a naturalistic behavior--female decision making during acoustic courtship in grasshoppers. Using behavioral data, we developed a model in which stimulus features were extracted by physiologically plausible models of sensory neurons from the time-varying stimulus. This sensory evidence was integrated over the stimulus duration and combined to predict the behavior. We show that decisions were determined by the interaction of an excitatory and a suppressive stimulus feature. The observed increase of behavioral response with stimulus intensity was the result of an increase of the excitatory feature's gain that was not controlled by an equivalent increase of the suppressive feature. Differences in how these two features were combined could explain interindividual variability. In addition, the mapping between the two stimulus features and different parameters of the song led us to re-evaluate the cues underlying acoustic communication. Our framework provided a rich and plausible explanation of behavior in terms of two stimulus cues that were extracted by models of sensory neurons and combined through excitatory-inhibitory interactions. We thus were able to link single neuron's feature selectivity and network computations with decision making in a natural task. This data-driven approach has the potential to advance our understanding of decision making in other systems and can inform the search for the neural correlates of behavior.
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