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Free keywords:
inferior colliculus; vocalizations; neural discrimination; neural correlations; multi-unit cluster; guinea pig; efficient encoding
Abstract:
How complex natural sounds are represented by the main converging center of the auditory midbrain, the central inferior colliculus, is an open question. We applied neural discrimination to determine the variation of detailed encoding of individual vocalizations across the best frequency gradient of the central inferior colliculus. The analysis was based on collective responses from several neurons. These multi-unit spike trains were recorded from guinea pigs exposed to a spectrotemporally rich set of eleven species-specific vocalizations. Spike trains of disparate units from the same recording were combined in order to investigate whether groups of multi-unit clusters represent the whole set of vocalizations more reliably than only one unit, and whether temporal response correlations between them facilitate an unambiguous neural representation of the vocalizations. We found a spatial distribution of the capability to accurately encode groups of vocalizations across the best frequency gradient. Different vocalizations are optimally discriminated at different locations of the best frequency gradient. Furthermore, groups of a few multi-unit clusters yield improved discrimination over only one multi-unit cluster between
all tested vocalizations. However, temporal response correlations between units do not yield better discrimination. Our study is based on a large set of units of simultaneously recorded responses from several guinea pigs and electrode insertion positions. Our findings suggest abroadly distributed code for behaviorally relevant vocalizations in the mammalian inferior colliculus.Responses from a few non-interacting units are sufficient to faithfully represent the whole set of studied vocalizations with diverse spectrotemporal properties.
