A Neural Correlate of Stochastic Echo Imaging

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Abstract
Bats quickly navigate through a highly structured environment relying on echolocation. Large natural objects in the environment, like bushes or trees, produce complex stochastic echoes, which can be characterized by the echo roughness. Previous work has shown that bats can use echo roughness to classify the stochastic properties of natural objects. This study provides both psychophysical and electrophysiological data to identify a neural correlate of statistical echo analysis in the bat Phyllostomus discolor. Psychophysical results show that the bats require a fixed minimum roughness of 2.5 (in units of base 10 logarithm of the stimulus fourth moment) for roughness discrimination. Electrophysiological results reveal a subpopulation of 15 of 94 recorded cortical units, located in an anterior region of auditory cortex, whose rate responses changed significantly with echo roughness. It is shown that the behavioral ability to discriminate differences in the statistics of complex echoes can be quantitatively predicted by the neural responses of this subpopulation of auditory-cortical neurons.