Temporal weighting of auditory spatial cues

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DESCRIPTION (provided by applicant): This research will examine how listeners combine auditory spatial information across different types of binaural cues (interaural time differences [ITD] and interaural level differences [ILD]), over time, and across frequency in order to better understand the dynamic processes underlying spatial hearing in reverberant environments. ITD and ILD provide the major set of cues that allow listeners to localize sounds in space and to segregate competing sound sources. In ideal situations, the cues agree across frequency and between the two cue types, and therefore provide redundant information about auditory space. Echoes and reverberation, however, distort these cues over time, degrading localization and speech understanding. Whereas the normal binaural system compensates by emphasizing robust aspects of the sound (such as ITD at onset), listeners who are aging, hearing-impaired, or using cochlear implants continue to experience difficulty in the presence of echoes and reverberation. Identifying the specific nature of these auditory processing deficits is difficult because so little is known about the compensatory mechanisms at work in normal-hearing listeners. Past research has investigated how the influence of spatial cues varies over the time-course of a sound (thereby emphasizing sound onsets), and across its frequency spectrum (typically emphasizing spatial information carried by low frequencies) but a key question remains unanswered: does the time-course of binaural processing vary across frequency or when multiple frequencies are present? Conversely, do the relative contributions of high- and low-frequencies change over the duration of a stimulus? The specific aims of the proposed study address this question by mapping the time-course of listeners' sensitivity to interaural differences for sounds varying in frequency, bandwidth, and the agreement of binaural cues across frequency. Listeners will judge the spatial positions of sounds with time-varying ITD and/or ILD, and multiple regression will be used to measure the dependence of those judgments on ITD and/or ILD. Regression coefficients will be used to construct temporal weighting functions (TWFs) that illustrate the dynamics of neural mechanisms for integration of ITD and ILD over time and across frequency.