Simulating intracochlear electrocochleography with a combined model of acoustic hearing and electric current spread in the cochlea

ZH-ECochG Bode Plot: A Novel Approach to Visualize Electrocochleographic Data in Cochlear Implant Users

Background: Various representations exist in the literature to visualize electrocochleography (ECochG) recordings along the basilar membrane (BM). This lack of generalization complicates comparisons within and between cochlear implant (CI) users, as well as between publications. This study synthesized the visual representations available in the literature via a systematic review and provides a novel approach to visualize ECochG data in CI users. Methods: A systematic review was conducted within PubMed and EMBASE to evaluate studies investigating ECochG and CI. Figures that visualized ECochG responses were selected and analyzed. A novel visualization of individual ECochG data, the ZH-ECochG Bode plot (ZH = Zurich), was devised, and the recordings from three CI recipients were used to demonstrate and assess the new framework. Results: Within the database search, 74 articles with a total of 115 figures met the inclusion criteria. Analysis revealed various types of representations using different axes; their advantages were incorporated into the novel visualization framework. The ZH-ECochG Bode plot visualizes the amplitude and phase of the ECochG recordings along the different tonotopic regions and angular insertion depths of the recording sites. The graph includes the pre- and postoperative audiograms to enable a comparison of ECochG responses with the audiometric profile, and allows different measurements to be shown in the same graph. Conclusions: The ZH-ECochG Bode plot provides a generalized visual representation of ECochG data, using well-defined axes. This will facilitate the investigation of the complex ECochG potentials generated along the BM and allows for better comparisons of ECochG recordings within and among CI users and publications. The scripts used to construct the ZH-ECochG Bode plot are provided by the authors.

Real-Time Feature Extraction From Electrocochleography With Impedance Measurements During Cochlear Implantation Using Linear State-Space Models

Electrocochleography (ECochG) is increasingly used to monitor the inner ear function of cochlear implant (CI) patients during surgery. Current ECochG-based trauma detection shows low sensitivity and specificity and depends on visual analysis by experts. Trauma detection could be improved by including electric impedance data recorded simultaneously with the ECochG. However, combined recordings are rarely used because the impedance measurements produce artifacts in the ECochG. In this study, we propose a framework for automated real-time analysis of intraoperative ECochG signals using Autonomous Linear State-Space Models (ALSSMs). We developed ALSSM based algorithms for noise reduction, artifact removal, and feature extraction in ECochG. Feature extraction includes local amplitude and phase estimations and a confidence metric over the presence of a physiological response in a recording. We tested the algorithms in a controlled sensitivity analysis using simulations and validated them with real patient data recorded during surgeries. The results from simulation data show that the ALSSM method provides improved accuracy in the amplitude estimation together with a more robust confidence metric of ECochG signals compared to the state-of-the-art methods based on the fast Fourier transform (FFT). Tests with patient data showed promising clinical applicability and consistency with the findings from the simulations. We showed that ALSSMs are a valid tool for real-time analysis of ECochG recordings. Removal of artifacts using ALSSMs enables simultaneous recording of ECochG and impedance data. The proposed feature extraction method provides the means to automate the assessment of ECochG. Further validation of the algorithms in clinical data is needed.

Multi-Frequency Electrocochleography and Electrode Scan to Identify Electrode Insertion Trauma during Cochlear Implantation

Intraoperative electrocochleography (ECOG) is performed using a single low-frequency acoustic stimulus (e.g., 500 Hz) to monitor cochlear microphonics (CM) during cochlear implant (CI) electrode insertion. A decrease in CM amplitude is commonly associated with cochlear trauma and is used to guide electrode placement. However, advancement of the recording electrode beyond the sites of CM generation can also lead to a decrease in CM amplitude and is sometimes interpreted as cochlear trauma, resulting in unnecessary electrode manipulation and increased risk of cochlear trauma during CI electrode placement. In the present study, multi-frequency ECOG was used to monitor CM during CI electrode placement. The intraoperative CM tracings were compared with electrode scan measurements, where CM was measured for each of the intracochlear electrodes. Comparison between the peak CM amplitude measured during electrode placement and electrode scan measurements was used to differentiate between different mechanisms for decrease in CM amplitude during CI electrode insertion. Analysis of the data shows that both multi-frequency electrocochleography and electrode scan could potentially be used to differentiate between different mechanisms for decreasing CM amplitude and providing appropriate feedback to the surgeon during CI electrode placement.

Classification of Acoustic Hearing Preservation After Cochlear Implantation Using Electrocochleography

The objective to preserve residual hearing during cochlear implantation has recently led to the use of intracochlear electrocochleography (ECochG) as an intraoperative monitoring tool. Currently, a decrease in the amplitude of the difference between responses to alternating-polarity stimuli (DIF response), predominantly reflecting the hair cell response, is used for providing feedback. Including other ECochG response components, such as phase changes and harmonic distortions, could improve the accuracy of surgical feedback. The objectives of the present study were (1) to compare simultaneously recorded stepwise intracochlear and extracochlear ECochG responses to 500 Hz tone bursts, (2) to explore patterns in features extracted from the intracochlear ECochG recordings relating to hearing preservation or hearing loss, and (3) to design support vector machine (SVM) and random forest (RF) classifiers of acoustic hearing preservation that treat each subject as a sample and use all intracochlear ECochG recordings made during electrode array insertion for classification. Forty subjects undergoing cochlear implant (CI) surgery at the Oslo University Hospital, St. Thomas' Hearing Implant Centre, or the University Hospital of Zurich were prospectively enrolled. In this cohort, DIF response amplitude decreases did not relate to postoperative acoustic hearing preservation. Exploratory analysis of the feature set extracted from the ECochG responses and preoperative audiogram showed that the features were not discriminative between outcome classes. The SVM and RF classifiers that were trained on these features could not distinguish cases with hearing loss and hearing preservation. These findings suggest that hearing loss following CI surgery is not always reflected in intraoperative ECochG recordings.

A Computational Model of a Single Auditory Nerve Fiber for Electric-Acoustic Stimulation

Cochlear implant (CI) recipients with preserved acoustic low-frequency hearing in the implanted ear are a growing group among traditional CI users who benefit from hybrid electric-acoustic stimulation (EAS). However, combined ipsilateral electric and acoustic stimulation also introduces interactions between the two modalities that can affect the performance of EAS users. A computational model of a single auditory nerve fiber that is excited by EAS was developed to study the interaction between electric and acoustic stimulation. Two existing models of sole electric or acoustic stimulation were coupled to simulate responses to combined EAS. Different methods of combining both models were implemented. In the coupled model variant, the refractoriness of the simulated fiber leads to suppressive interaction between electrically evoked and acoustically evoked spikes as well as spontaneous activity. The second model variant is an uncoupled EAS model without electric-acoustic interaction. By comparing predictions between the coupled and the noninteracting EAS model, it was possible to infer electric-acoustic interaction at the level of the auditory nerve. The EAS model was used to simulate fiber populations with realistic inter-unit variability, where each unit was represented by the single-fiber model. Predicted thresholds and dynamic ranges, spike rates, latencies, jitter, and vector strengths were compared to empirical data. The presented EAS model provides a framework for future studies of peripheral electric-acoustic interaction.