Data from: Human sound localization depends on sound intensity: implications for sensory coding

Human sound localization is an important computation performed by the
brain. Models of sound localization commonly assume that sound
lateralization from interaural time differences is level invariant. Here
we observe that two prevalent theories of sound localization make opposing
predictions. The labelled-line model encodes location through tuned
representations of spatial location and predicts that perceived direction
is level invariant. In contrast, the hemispheric-difference model encodes
location through spike-rate and predicts that perceived direction becomes
medially biased at low sound levels. Here, behavioral experiments find
that softer sounds are perceived closer to midline than louder sounds,
favoring rate-coding models of human sound localization. Analogously,
visual depth perception, which is based on interocular disparity, depends
on the contrast of the target. The similar results in hearing and vision
suggest that the brain may use a canonical computation of location:
encoding perceived location through population spike rate relative to
baseline.