Binaural Sensitivity Tests

Binaural sensitivity was predictive of the listeners’ ability to differentiate between target locations because ITD- and ILD-JND were negatively correlated with listeners’ ability to

differentiate between targets without head movement (Section 3.3.1). Interaural level

difference sensitivities of both real and simulated BiCI users found in the present study were similar to previous studies. Grantham et al. (2008) assessed ILD sensitivity in BiCI

users with the AGC circuitry both active and inactive. Sensitivity to ILD was most similar between the AGC inactive condition of that study and the present study’s

simulated BiCI users (range of ~1 – 3 dB versus range of 1.78 – 2.78 dB respectively); in contrast, ILD-JND in the AGC active condition was worse (range of ~1 – 11 dB) when compared to the present study’s simulated BiCI users. These findings suggest that the simulation was representative of simulated BiCI users’ sensitivities to ILD when the AGC is inactive, which is expected given that no attempt to simulate AGC-circuitry or loudness compressive functions were made. Senn et al. (2005) also found good ILD sensitivity in BiCI users listening to white noise bursts (mean ITD-JND of 1.2 dB). These findings are congruent with what was observed in simulated users. In contrast, findings from Senn et al. (2005) regarding ITD sensitivity in BiCI users listening to white noise bursts are not congruent with the findings of the present study because real BiCI users’ sensitivities were better (range of 600 to > 1000 µs) than simulated BiCI users’ sensitivities (1060 to 3270 µs). Sensitivity of real BiCI users in Senn et al. (2005) may have been greater because electrodes were directly stimulated via computer interface; therefore, the timing of stimulation with fine-structure information at each of the ears may have been correlated for real users, whereas in the present study no correlation in timing of stimulation was present between the ears. Regardless of the differences between ITD-JND values between these two studies, ITD sensitivity was poor for both the real and simulated BiCI users.

The negative correlation between ILD sensitivity and the ability to discriminate between target positions when no head movement was available is not surprising because we know CI users have access to ILD information and that normally hearing listeners use ILD when ITD cues are unavailable for localization. The negative correlation is not surprising because the device simulations either preserved ILD information, in the case of binaurally matched listeners (i.e. simulated BiCI and BiEAS), or ILD information was degraded, in the case of binaurally mismatched listeners (i.e. simulated CI+HA and EAS+HA). Therefore, the fact that simulated BiCI and BiEAS users were able to differentiate between target positions when no head movement was available was not surprising, becausece ILDs were preserved in the simulation. In addition, simulated CI+HA and EAS+HA users’ poor performance without head movement is also not

surprising because these listeners were likely only able to use monaural level cues in the CI-like signal to differentiate target positions. Given that level roving was applied, monaural level cues were minimized for simulated CI+HA and EAS+HA users, thus making it difficult for them to differentiate between target locations.

The positive correlation between ITD sensitivity and sound localization performance without head movement cues was expected because simulated users who have bilateral access to fine-structure (BiEAS and EAS+HA users) are expected to localize based on ITD information. In contrast, CI+HA and BiCI users do not have access to bilateral fine- structure and therefore, would not be expected to localize based on ITD information. Even though a positive correlation between ITD-JND and front/back errors without head movement was not surprising, it was surprising that the correlation between ITD

sensitivity and front/back error rates was different from what was predicted for EAS+HA and BiCI users. First, EAS+HA users’ ITD sensitivity and static localization

performance were poor. This is likely explained by either unbalanced stimulation within

(EAS) or between (EAS+HA) devices or by observer weighting of large false ILD cues

(see Section 4.1.1 for explanation) Second, despite the fact that simulated BiCI users’

ITD sensitivities were too poor for localization, they were still better than what was observed in simulated CI+HA users. This is surprising because neither group of

simulated users has binaural access to low-frequency information. Consequently, neither simulated BiCI nor CI+HA users should be able to make use of on-going-ITD cues when localizing the target. However, BiCI users may have access to onset and offset ITD cues which CI+HA users would not because of different processing times of each device. Sensitivity to ITD, but not ILD, was predictive of the benefit derived from head

movement in reducing front/back errors. The lack of correlation between ILD sensitivity and head movement benefit for front/back error rates is likely due to the fact that some simulated users with good sensitivity to ILD had low front/back error rates (BiEAS and BiCI) while some simulated users had high front/back error rates (EAS+HA and CI+HA). Interaural time difference thresholds were positively correlated with front/back error rates

when limited head movement was available (Section 3.3.2). Together these findings

when head movement cues were available. These findings are congruent with other studies that suggest that head movement benefit is likely derived from the ability to track changing ITD cues (Macpherson & Kerr, 2008; Best et al., 2010). Given that ITD sensitivity is likely correlated with front/back discrimination in head movement

conditions, it was predicted that simulated BiEAS and EAS+HA users’ front/back error rates would be lower relative to simulated BiCI and CI+HA users. Surprisingly, only simulated BiEAS users’ front/back error rates were low and their ITD sensitivity was good. This is surprising because it would be expected that EAS+HA users would perform similarly to BiEAS users given that they both have access to fine-structure ITD cues. However, simulated EAS+HA users had neither low front/back error rates nor good ITD sensitivity, and in fact they performed worse than the BiCI users. Possible lack of audibility in the low-frequency signal does not explain the EAS+HA users’

performance because the low-frequency signal was audible to BiEAS users who performed well. These findings suggest that simulated EAS+HA users may not have been able to attend to fine-structure ITDs present in the bilateral HA signal. As no attempt was made to balance loudness between the CI and HA components, the CI-like component in the ear stimulated by EAS likely had greater perceptual saliency.

Consequently, the listener may be placing a greater weight on the unilateral high-

frequency information which carries a large, false ILD (see Section 4.1.1) rather than the

low-frequency ITD. This would explain simulated EAS+HA users’ performance in the controlled movement condition, in which most listeners tended to show lateral bias such that responses were focused in the right hemifield (ipsilateral to the ear stimulated with EAS).