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Meta-Analysis
. 2013 Feb;133(2):EL101-7.
doi: 10.1121/1.4776772.

Mapping procedures can produce non-centered auditory images in bilateral cochlear implantees

Affiliations
Meta-Analysis

Mapping procedures can produce non-centered auditory images in bilateral cochlear implantees

Matthew J Goupell et al. J Acoust Soc Am. 2013 Feb.

Abstract

Good localization accuracy depends on an auditory spatial map that provides consistent binaural information across frequency and level. This study investigated whether mapping bilateral cochlear implants (CIs) independently contributes to distorted perceptual spatial maps. In a meta-analysis, interaural level differences necessary to perceptually center sound images were calculated for 127 pitch-matched pairs of electrodes; many needed large current adjustments to be perceptually centered. In a separate experiment, lateralization was also found to be inconsistent across levels. These findings suggest that auditory spatial maps are distorted in the mapping process, which likely reduces localization accuracy and target-noise separation in bilateral CIs.

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Figures

Figure 1
Figure 1
Histograms for the offset necessary to center an auditory image elicited by a 100-pps (open bars) and 1000-pps (closed bars) pulse train with respect to C level in both ears, either in CUs or percentage of the dynamic range (%DR). Zero offsets are shown in the center. (a) shows boxes that change by a factor of 2. Therefore, offsets of –64 to –32 are shown for the leftmost bar, –32 to –16 for the next bar,…, 0 for the center bar, 1 to 2 CUs for the next bar to the right, 2 to 4 CUs for the next bar to the right, and so on. (b) shows linear spacing in 10%DR units.
Figure 2
Figure 2
(Color online) Lateralization data as a function of ILD at different stimulation levels. Individual listeners are shown in different panels. Symbols represent the average response and error bars show ±1 standard deviation. Filled symbols show where the error bars at 0-CU ILD do not overlap zero lateralization. Solid curved lines are cumulative Gaussian fits to the average data.

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