Object representation and resolution in a computed sensory map

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In the auditory cortex of echolocating bats, the distance to an object is represented in a neuronal map. Neurons in this map only fire action potentials if echoes reflected from objects in the environment (e.g. insects or other prey items) arrive with a specific delay after the bat has emitted a call. In contrast to so-called structural maps, which simply reflect the topographic organization of the epithelial surface of a peripheral sensor (e.g. the retina is represented in the primary visual cortex), this so-called map of target-distance is a computational map. These maps contain a representation of sensory information that is derived from neural computation. Here, the delay between call emission and echo arrival is computed within the neural circuitry of the bats’ auditory system. Computational maps for spatial hearing have also been reported for other vertebrates.This proposal aims to investigate the representation of multiple objects arranged along the spatial depth axis in the map of target-distance in the bat Phyllostomus discolor. Extracellular recordings with single electrodes and multi-electrode arrays are employed to reveal how many simultaneously present objects can be represented in the map, and up to which minimal distance two object can be resolved by single neurons. Further, the influence of the spatial arrangement (i.e., the position of objects in azimuth and elevation) on object resolution and representation will be investigated. The results will give insight into the basic functional principles of computational maps in the auditory system of vertebrates.