Multiplication-like sound localization models are subjected to phase ambiguities for high-frequency tonal stimuli as multiplication creates several equivalent response peaks in tuning curves. By increasing the bandwidth of the stimulus, phase ambiguities can be reduced, which is often referred to as side peak suppression. In this study we present a Jeffress-based sound localization model, and determine side peak suppression analytically. The results were verified with an implementation of the same model, and compared to physiological data of barn owls. Three types of stimuli were analyzed: pure-tone stimuli, two-tone complexes with varying frequency distances, and noise signals with variable bandwidths. As an additional parameter we also determined the half-width of the main response peak to examine the scaling of tuning curves in azimuth. Results showed that side peak suppression did not only depend on bandwidth, but also on the center frequency and the distance of the side peak to the main response peak. In particular, the analytical model predicted that side peak suppression is a function of relative bandwidth, whereas half-width is inversely proportional to center frequency, with a proportionality factor depending on relative bandwidth. The analytical approach and the implementation yielded equivalent tuning curves (deviation < 1%). Moreover, the electrophysiological data recorded in barn owls closely matched the predicted tuning curves.

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