28 research outputs found
Neuronal precision and the limits for acoustic signal recognition in a small neuronal network
Recognition of acoustic signals may be impeded by two factors: extrinsic noise, which degrades sounds before they arrive at the receiver’s ears, and intrinsic neuronal noise, which reveals itself in the trial-to-trial variability of the responses to identical sounds. Here we analyzed how these two noise sources affect the recognition of acoustic signals from potential mates in grasshoppers. By progressively corrupting the envelope of a female song, we determined the critical degradation level at which males failed to recognize a courtship call in behavioral experiments. Using the same stimuli, we recorded intracellularly from auditory neurons at three different processing levels, and quantified the corresponding changes in spike train patterns by a spike train metric, which assigns a distance between spike trains. Unexpectedly, for most neurons, intrinsic variability accounted for the main part of the metric distance between spike trains, even at the strongest degradation levels. At consecutive levels of processing, intrinsic variability increased, while the sensitivity to external noise decreased. We followed two approaches to determine critical degradation levels from spike train dissimilarities, and compared the results with the limits of signal recognition measured in behaving animals
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Fast intensity adaptation enhances the encoding of sound in Drosophila
Complex auditory stimuli such as courtship song are sensed by mechanosensory neurons (JONs) in Drosophila antennae. Here the authors report two forms of adaptation in JONs that correct for antennal position (mean) as well as background sound intensity (variance) to maintain sensitivity to natural sensory stimuli