Jihwan Woo

Relationship among the physiologic channel interactions, spectral-ripple discrimination, and vowel identification in cochlear implant users

The hypothesis of this study was that broader patterns of physiological channel interactions in the local region of the cochlea are associated with poorer spectral resolution in the same region. Electrically evoked compound action potentials (ECAPs) were measured for three to six probe electrodes per subject to examine the channel interactions in different regions across the electrode array. To evaluate spectral resolution at a confined location within the cochlea, spectral-ripple discrimination (SRD) was measured using narrowband ripple stimuli with the bandwidth spanning five electrodes: Two electrodes apical and basal to the ECAP probe electrode. The relationship between the physiological channel interactions, spectral resolution in the local cochlear region, and vowel identification was evaluated. Results showed that (1) there was within- and across-subject variability in the widths of ECAP channel interaction functions and in narrowband SRD performance, (2) significant correlations were found between the widths of the ECAP functions and narrowband SRD thresholds, and between mean bandwidths of ECAP functions averaged across multiple probe electrodes and broadband SRD performance across subjects, and (3) the global spectral resolution reflecting the entire electrode array, not the local region, predicts vowel identification.

Cross-Modal and Intra-Modal Characteristics of Visual Function and Speech Perception Performance in Postlingually Deafened, Cochlear Implant Users

Evidence of visual-auditory cross-modal plasticity in deaf individuals has been widely reported. Superior visual abilities of deaf individuals have been shown to result in enhanced reactivity to visual events and/or enhanced peripheral spatial attention. The goal of this study was to investigate the association between visual-auditory cross-modal plasticity and speech perception in post-lingually deafened, adult cochlear implant (CI) users. Post-lingually deafened adults with CIs (N = 14) and a group of normal hearing, adult controls (N = 12) participated in this study. The CI participants were divided into a good performer group (good CI, N = 7) and a poor performer group (poor CI, N = 7) based on word recognition scores. Visual evoked potentials (VEP) were recorded from the temporal and occipital cortex to assess reactivity. Visual field (VF) testing was used to assess spatial attention and Goldmann perimetry measures were analyzed to identify differences across groups in the VF. The association of the amplitude of the P1 VEP response over the right temporal or occipital cortex among three groups (control, good CI, poor CI) was analyzed. In addition, the association between VF by different stimuli and word perception score was evaluated. The P1 VEP amplitude recorded from the right temporal cortex was larger in the group of poorly performing CI users than the group of good performers. The P1 amplitude recorded from electrodes near the occipital cortex was smaller for the poor performing group. P1 VEP amplitude in right temporal lobe was negatively correlated with speech perception outcomes for the CI participants (r = -0.736, P = 0.003). However, P1 VEP amplitude measures recorded from near the occipital cortex had a positive correlation with speech perception outcome in the CI participants (r = 0.775, P = 0.001). In VF analysis, CI users showed narrowed central VF (VF to low intensity stimuli). However, their far peripheral VF (VF to high intensity stimuli) was not different from the controls. In addition, the extent of their central VF was positively correlated with speech perception outcome (r = 0.669, P = 0.009). Persistent visual activation in right temporal cortex even after CI causes negative effect on outcome in post-lingual deaf adults. We interpret these results to suggest that insufficient intra-modal (visual) compensation by the occipital cortex may cause negative effects on outcome. Based on our results, it appears that a narrowed central VF could help identify CI users with poor outcomes with their device.

Spectrotemporal Modulation Detection and Speech Perception by Cochlear Implant Users.

Spectrotemporal modulation (STM) detection performance was examined for cochlear implant (CI) users. The test involved discriminating between an unmodulated steady noise and a modulated stimulus. The modulated stimulus presents frequency modulation patterns that change in frequency over time. In order to examine STM detection performance for different modulation conditions, two different temporal modulation rates (5 and 10 Hz) and three different spectral modulation densities (0.5, 1.0, and 2.0 cycles/octave) were employed, producing a total 6 different STM stimulus conditions. In order to explore how electric hearing constrains STM sensitivity for CI users differently from acoustic hearing, normal-hearing (NH) and hearing-impaired (HI) listeners were also tested on the same tasks. STM detection performance was best in NH subjects, followed by HI subjects. On average, CI subjects showed poorest performance, but some CI subjects showed high levels of STM detection performance that was comparable to acoustic hearing. Significant correlations were found between STM detection performance and speech identification performance in quiet and in noise. In order to understand the relative contribution of spectral and temporal modulation cues to speech perception abilities for CI users, spectral and temporal modulation detection was performed separately and related to STM detection and speech perception performance. The results suggest that that slow spectral modulation rather than slow temporal modulation may be important for determining speech perception capabilities for CI users. Lastly, test–retest reliability for STM detection was good with no learning. The present study demonstrates that STM detection may be a useful tool to evaluate the ability of CI sound processing strategies to deliver clinically pertinent acoustic modulation information.

Effects of Electrode Position on Spatiotemporal Auditory Nerve Fiber Responses: A 3D Computational Model Study

A cochlear implant (CI) is an auditory prosthesis that enables hearing by providing electrical stimuli through an electrode array. It has been previously established that the electrode position can influence CI performance. Thus, electrode position should be considered in order to achieve better CI results. This paper describes how the electrode position influences the auditory nerve fiber (ANF) response to either a single pulse or low- (250 pulses/s) and high-rate (5,000 pulses/s) pulse-trains using a computational model. The field potential in the cochlea was calculated using a three-dimensional finite-element model, and the ANF response was simulated using a biophysical ANF model. The effects were evaluated in terms of the dynamic range, stochasticity, and spike excitation pattern. The relative spread, threshold, jitter, and initiated node were analyzed for single-pulse response; and the dynamic range, threshold, initiated node, and interspike interval were analyzed for pulse-train stimuli responses. Electrode position was found to significantly affect the spatiotemporal pattern of the ANF response, and this effect was significantly dependent on the stimulus rate. We believe that these modeling results can provide guidance regarding perimodiolar and lateral insertion of CIs in clinical settings and help understand CI performance.

Study on Electric Stimulus Pattern in Cochlear Implant Using a Computer Model

A cochlear implant system uses charge-balanced biphasic pulses that are known to reduce tissue damage than monophasic pulses. In this study, we investigated effect of pulse pattern on neural responses using a computer model, based on the Hodgkin-Huxley equation. Electric pulse phase, pulse duration, and phase gap have been systematically varied to characterize auditory nerve responses. The results show that neural responses, dynamic range and threshold are represented as a function of stimulus patterns and duration. The results could greatly extend to develop more efficient cochlear implant stimulation.

Effects of physiological internal noise on model predictions of concurrent vowel identification for normal-hearing listeners

Previous studies have shown that concurrent vowel identification improves with increasing temporal onset asynchrony of the vowels, even if the vowels have the same fundamental frequency. The current study investigated the possible underlying neural processing involved in concurrent vowel perception. The individual vowel stimuli from a previously published study were used as inputs for a phenomenological auditory-nerve (AN) model. Spectrotemporal representations of simulated neural excitation patterns were constructed (i.e., neurograms) and then matched quantitatively with the neurograms of the single vowels using the Neurogram Similarity Index Measure (NSIM). A novel computational decision model was used to predict concurrent vowel identification. To facilitate optimum matches between the model predictions and the behavioral human data, internal noise was added at either neurogram generation or neurogram matching using the NSIM procedure. The best fit to the behavioral data was achieved with a signal-to-noise ratio (SNR) of 8 dB for internal noise added at the neurogram but with a much smaller amount of internal noise (SNR of 60 dB) for internal noise added at the level of the NSIM computations. The results suggest that accurate modeling of concurrent vowel data from listeners with normal hearing may partly depend on internal noise and where internal noise is hypothesized to occur during the concurrent vowel identification process.

Objective Test of Cochlear Dead Region: Electrophysiologic Approach using Acoustic Change Complex

The goal of this study was to develop an objective and neurophysiologic method of identifying the presence of cochlear dead region (CDR) by combining acoustic change complex (ACC) responses with threshold-equalizing noise (TEN) test. The goal of the first study was to confirm whether ACC could be evoked with TEN stimuli and to also optimize the test conditions. The goal of the second study was to determine whether the TEN-ACC test is capable of detecting CDR(s). The ACC responses were successfully recorded from all study participants. Both behaviorally and electrophysiologically obtained masked thresholds (TEN threshold and TEN-ACC threshold) were similar and below 10 and 12 dB SNR in NH listeners, respectively. HI listeners were divided into HI (non-CDR) and CDR groups based on the behavioral TEN test. For the non-CDR group, TEN-ACC thresholds were below 12 dB which were similar to NH listeners. However, for the CDR group, TEN-ACC thresholds were significantly higher (≥12 dB SNR) than those in the NH and HI groups, indicating that CDR(s) can be objectively detected using the ACC. Results of this study demonstrate that it is possible to detect the presence of CDR using an electrophysiologic method.

Prediction of vowel identification for cochlear implant using a computational model

A computational biophysical auditory nerve fiber model along with mathematical algorithms are presented that predict vowel identification for cochlear implant (CI) users based on the predicted peripheral neural representations of speech information (i.e., neurogram). Our model simulates the discharge patterns of electrically-stimulated auditory nerve fibers along the length of the cochlea and quantifies the similarity between the neurograms for different speech signals. The effects of background noise (+15, +10, +5, 0, and 5dB SNR) and stimulation rate (900, 1200, and 1800pps/ch) on vowel identification were evaluated and compared to CI subject data to demonstrate the performance of our model. Results from both the computational modeling and clinical test showed that vowel identification performance decreased as background noise increased while vowel identification was not significantly influenced by the stimulation rate. The proposed method, both objective and automated, can be used for a wide range of stimulus conditions, signal processing, and different biological conditions in the implanted ears.

Evaluation of Stimulus Strategy for Cochlear Implant Using Neurogram

Electrical stimulation is delivered to auditory nerve (AN) through the electrodes in cochlear implant system. Neurogram is a spectrogram that includes information of neural response to electrical stimulation. We hypothesized that the similarity between a neurogram and an input-sound spectrogram could show how well a cochlear implant system works. In this study, we evaluated electrical stimulus configuration of CIS strategy using the computational model. The computational model includes stochastic property and anatomical features of cat auditory nerve fiber. To evaluate similarity between a neurogram and an input-sound spectrogram, we calculated Structural Similarity Index (SSIM). The results show that the dynamic range and the stimulation rate per channel influenced SSIM. Finally, we suggested the optimal configuration within the given stimulus CIS. We expect that the results and the evaluating procedure could be employed to improve the performance of a cochlear implant system.