Neural cross-correlation and signal decorrelation: insights into coding of auditory space.

The auditory systems of humans and many other species use the difference in the time of arrival of acoustic signals at the two ears to compute the lateral position of sound sources. This computation is assumed to initially occur in an assembly of neurons organized along a frequency-by-delay surface. Mathematically, the computations are equivalent to a two-dimensional cross-correlation of the input signals at the two ears, with the position of the peak activity along this surface designating the position of the source in space. In this study, partially correlated signals to the two ears are used to probe the mechanisms for encoding spatial cues in stationary or dynamic (moving) signals. It is demonstrated that a cross-correlation model of the auditory periphery coupled with statistical decision theory can predict the patterns of performance by human subjects for both stationary and motion stimuli as a function of stimulus decorrelation. Implications of these findings for the existence of a unique cortical motion system are discussed.