ObjectiveTo investigate the performance of monaural and binaural beamforming technology with an additional noise reduction algorithm, in cochlear implant recipients.MethodThis experimental study was conducted as a single subject repeated measures design within a large German cochlear implant centre. Twelve experienced users of an Advanced Bionics HiRes90K or CII implant with a Harmony speech processor were enrolled. The cochlear implant processor of each subject was connected to one of two bilaterally placed state-of-the-art hearing aids (Phonak Ambra) providing three alternative directional processing options: an omnidirectional setting, an adaptive monaural beamformer, and a binaural beamformer. A further noise reduction algorithm (ClearVoice) was applied to the signal on the cochlear implant processor itself. The speech signal was presented from 0° and speech shaped noise presented from loudspeakers placed at ±70°, ±135° and 180°. The Oldenburg sentence test was used to determine the signal-to-noise ratio at which subjects scored 50% correct.ResultsBoth the adaptive and binaural beamformer were significantly better than the omnidirectional condition (5.3 dB±1.2 dB and 7.1 dB±1.6 dB (p<0.001) respectively). The best score was achieved with the binaural beamformer in combination with the ClearVoice noise reduction algorithm, with a significant improvement in SRT of 7.9 dB±2.4 dB (p<0.001) over the omnidirectional alone condition.ConclusionsThe study showed that the binaural beamformer implemented in the Phonak Ambra hearing aid could be used in conjunction with a Harmony speech processor to produce substantial average improvements in SRT of 7.1 dB. The monaural, adaptive beamformer provided an averaged SRT improvement of 5.3 dB.

When tested in challenging and realistic noise environments, the Naida CI UltraZoom adaptive beamformer resulted in significantly lower mean SRTs than when the T-Mic alone was used.

Although such adaptation is thought to improve coding of relevant stimulus features, the relationship between adaptation at the neural and behavioral levels remains to be established. Here we describe improved discrimination performance for an auditory spatial cue (interaural time differences, ITDs) following adaptation to stimulus statistics. Physiological recordings in the midbrain of anesthetized guinea pigs and measurement of discrimination performance in humans both demonstrate improved coding of the most prevalent ITDs in a distribution, but with highest accuracy maintained for ITDs corresponding to frontal locations, suggesting the existence of a fovea for auditory space. A biologically plausible model accounting for the physiological data suggests that neural tuning is stabilized by inhibition to maintain high discriminability for frontal locations. The data support the notion that adaptive coding in the midbrain is a key element of behaviorally efficient sound localization in dynamic acoustic environments.adaptation; interaural time difference; midbrain; neural model; psychophysics MOST SPECIES EVOLVE in complex environments containing diverse sources of sensory information over a very wide range of intensities, frequencies, and locations. Sensory systems must efficiently encode over this wide range of possible stimulus values, given a limited availability of coding resources. One means by which neural systems can overcome this challenge is to adapt on a behavioral timescale in order to represent with particular efficiency the subset of natural stimuli in the current environment. Such adaptive coding is observed across a wide range of species and stimulus modalities and is apparent in the responses of single neurons (Dean et al. 2005;Fairhall et al. 2001;Ohzawa et al. 1982) and across populations of neurons (Dean et al. 2005(Dean et al. , 2008Watkins and Barbour 2008). Fisher information (FI) represents one possible measure of coding quality that can be used to evaluate adaptive coding (Dean et al. 2005).Nevertheless, despite the apparent advantage adaptive coding would confer on sensory processing, the link between adaptive coding at the neural level and performance in sensory tasks is difficult to establish. Psychophysical assessment of adapted neural systems is often considered with respect to perceptual illusions such as afterimages (McCollough 1965) At the cognitive level, the term "cuing" is employed to describe the influence of prior stimulation on sensory performance, for example, in reducing reaction times required to localize a sound source in a given spatial hemifield (Spence and Driver 1994).However, none of these concepts-aftereffects, mislocalization, or cuing-is easily reconciled with the concept of adaptive coding at the neural level. This normally describes the rapid adjustment of neural tuning properties to better represent the prevailing stimulus environment (Garcia-Lazaro et al. 2007;Maravall et al. 2007; Nagel and Doupe 2006) rather than neural fatigue or higher, perhaps attentiona...

Dealing with environmental noises presents a major issue for cochlear implant (CI) users. Hence, digital noise reduction (DNR) schemes have become important features of CI systems. Many noises like for example clinking glasses or slamming doors, have impulsive onsets and decay quickly. Common DNR algorithms cannot handle this type of noise in an appropriate way. In this study, we investigated the effect of an algorithm specially designed for such noises with 12 CI users (age range: 45 to 75 years). Speech scores in noise and quiet as well as subjective ratings of speech clarity, comfort and overall preference were measured. The main finding was a significant improvement of up to 1.7 dB of the speech reception threshold in noise as well as increased speech clarity. Speech in quiet was not negatively affected by the algorithm. The study revealed that the tested algorithm has the potential to improve CI listening. However, further research is needed regarding the effectiveness and suitability of the algorithm in daily use.

A previously-tested transient noise reduction (TNR) algorithm for cochlear implant (CI) users was modified to detect and attenuate transients independently across multiple frequency-bands. Since speech and transient noise are often spectrally distinct, we hypothesized that benefits in speech intelligibility can be achieved over the earlier single-band design. Fifteen experienced CI users (49 to 72 years) were tested unilaterally using pre-processed stimuli delivered directly to a speech processor. Speech intelligibility in transient and soft stationary noise, subjective sound quality and the recognition of warning signals was investigated in three processing conditions: no TNR (TNRoff), single-band TNR (TNRsgl) and multi-band TNR (TNRmult). Notably, TNRmult improved speech reception thresholds (SRTs) in cafeteria noise and office noise by up to 3 dB over both TNRoff and TNRsgl, and yielded higher comfort and clarity ratings in cafeteria noise. Our results indicate that multi-band transient noise reduction may be advantageous compared to a single-band approach, and reveal a substantial overall potential for TNR to improve speech perception and listening comfort in CI users.