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IntroductionSubjects with mild to moderate hearing loss today often receive hearing aids (HA) with open-fitting (OF). In OF, direct sound reaches the eardrums with minimal damping. Due to the required processing delay in digital HA, the amplified HA sound follows some milliseconds later. This process occurs in both ears symmetrically in bilateral HA provision and is likely to have no or minor detrimental effect on binaural hearing. However, the delayed and amplified sound are only present in one ear in cases of unilateral hearing loss provided with one HA. This processing alters interaural timing differences in the resulting ear signals.MethodsIn the present study, an experiment with normal-hearing subjects to investigate speech intelligibility in noise with direct and delayed sound was performed to mimic unilateral and bilateral HA provision with OF.ResultsThe outcomes reveal that these delays affect speech reception thresholds (SRT) in the unilateral OF simulation when presenting speech and noise from different spatial directions. A significant decrease in the median SRT from –18.1 to –14.7 dB SNR is observed when typical HA processing delays are applied. On the other hand, SRT was independent of the delay between direct and delayed sound in the bilateral OF simulation.DiscussionThe significant effect emphasizes the development of rapid processing algorithms for unilateral HA provision.

Magnetic stimulation of peripheral nerves is evoked by electric field gradients caused by high-intensity, pulsed magnetic fields created from a coil. Currents required for stimulation are very high, therefore devices are large, expensive, and often too complex for many applications like rehabilitation therapy. For repetitive stimulation, coil heating due to power loss poses a further limitation. The geometry of the magnetic coil determines field depth and focality, making it the most important factor that determines the current required for neuronal excitation. However, the comparison between different coil geometries is difficult and depends on the specific application. Especially the distance between nerve and coil plays a crucial role. In this investigation, the electric field distribution of 14 different coil geometries was calculated for a typical peripheral nerve stimulation with a 27 mm distance between axon and coil. Coil parameters like field strength and focality were determined with electromagnetic field simulations. In a second analysis, the activating function along the axon was calculated, which quantifies the efficiency of neuronal stimulation. Moreover, coil designs were evaluated concerning power efficacy based on ohmic losses. Our results indicate that power efficacy of magnetic neurostimulation can be improved significantly by up to 40% with optimized coil designs.

After hearing loss retrograde degeneration of spiral ganglion neurons (SGNs) has been described. Studies modeling the effects of degeneration mostly omitted peripheral processes (dendrites). Recent experimental observations indicated that degenerating SGNs manifested also a reduced diameter of their dendrites. We simulated populations of 400 SGNs inside a high resolution cochlear model with a cochlear implant, based on μCT scans of a human temporal bone. Cochlear implant stimuli were delivered as biphasic pulses in a monopolar configuration. Three SGN situations were simulated, based on our previous measurements of human SGN dendrites: (A) SGNs with intact dendrites (before degeneration), (B) degenerating SGNs, dendrites with a smaller diameter but original length, (C) degenerating SGNs, dendrites omitted. SGN fibers were mapped to characteristic frequency, and place pitch was estimated from excitation profiles. Results from degenerating SGNs (B, C) were similar. Most action potentials were initiated in the somatic area for all cases (A, B, C), except for areas near stimulating electrodes in the apex with intact SGNs (A), where action potentials were initiated in the distal dendrite. In most cases, degenerating SGNs had lower thresholds than intact SGNs (A) (down to –2 dB). Excitation profiles showed increased ectopic activation, i.e., activation of unintended neuronal regions, as well as similar neuronal regions excited by different apical electrodes, for degenerating SGNs (B, C). The estimated pitch showed cases of pitch reversals in apical electrodes for intact SGNs (A), as well as mostly identical pitches evoked by the four most apical electrodes for degenerating SGNs (B, C). In conclusion, neuronal excitation profiles to electrical stimulation exhibited similar traits in both ways of modeling SGN degeneration. Models showed degeneration of dendrites caused increased ectopic activation, as well as similar excitation profiles and pitch evoked by different apical electrodes. Therefore, insertion of electrodes beyond approximately 450° may not provide any benefit if SGN dendrites are degenerated.

Virtual reality environments offer great opportunities to study the performance of brain-computer interfaces (BCIs) in real-world contexts. As real-world stimuli are typically multimodal, their neuronal integration elicits complex response patterns. To investigate the effect of additional auditory cues on the processing of visual information, we used virtual reality to mimic safety-related events in an industrial environment while we concomitantly recorded electroencephalography (EEG) signals. We simulated a box traveling on a conveyor belt system where two types of stimuli – an exploding and a burning box – interrupt regular operation. The recordings from 16 subjects were divided into two subsets, a visual-only and an audio-visual experiment. In the visual-only experiment, the response patterns for both stimuli elicited a similar pattern – a visual evoked potential (VEP) followed by an event-related potential (ERP) over the occipital-parietal lobe. Moreover, we found the perceived severity of the event to be reflected in the signal amplitude. Interestingly, the additional auditory cues had a twofold effect on the previous findings: The P1 component was significantly suppressed in the case of the exploding box stimulus, whereas the N2c showed an enhancement for the burning box stimulus. This result highlights the impact of multisensory integration on the performance of realistic BCI applications. Indeed, we observed alterations in the offline classification accuracy for a detection task based on a mixed feature extraction (variance, power spectral density, and discrete wavelet transform) and a support vector machine classifier. In the case of the explosion, the accuracy slightly decreased by –1.64% p. in an audio-visual experiment compared to the visual-only. Contrarily, the classification accuracy for the burning box increased by 5.58% p. when additional auditory cues were present. Hence, we conclude, that especially in challenging detection tasks, it is favorable to consider the potential of multisensory integration when BCIs are supposed to operate under (multimodal) real-world conditions.

We estimated the electrically-evoked auditory brainstem response thresholds (eABR THRs) in response to multi-pulses with high burst rate of 10,000 pulses-per-second (pps). Growth functions of wave eV amplitudes, root mean square (RMS) values, peak of phase-locking value (PLV), and the lowest valid data point (LVDP) were calculated in 1-, 2-, 4-, 8-, and 16-pulses conditions. The growth functions were then fitted and extrapolated with linear and exponential functions to find eABR THRs. The estimated THRs were compared to psychophysical THRs determined for multi-pulse conditions as well as to the clinical THRs measured behaviorally at the rate of 1,000 pps. The growth functions of features showed shallower growth slopes when the number of pulses increased. eABR THRs estimated in 4-, 8-, and 16-pulses conditions were closer to the clinical THRs, when compared to 1- and 2-pulses conditions. However, the smallest difference between estimated eABR THRs and clinical THRs was not always achieved from the same number of pulses. The smallest absolute difference of 30.3 μA was found for the linear fittings on growth functions of eABR RMS values in 4-pulses condition. Pearson’s correlation coefficients (PCCs) between eABR THRs and psychophysical THRs were significant and relatively large in all but 16-pulses conditions. The PCCs between eABR THRs and clinical THRs, however, were smaller and in less cases significant. Results of this study showed that eABRs to multi-pulse stimulation could, to some extent, represent clinical stimulation paradigms, and thus in comparison to single pulses, could estimate clinical THRs with smaller errors.

We investigated the effects of electric multi-pulse stimulation on electrically evoked auditory brainstem responses (eABRs). Multi-pulses with a high burst rate of 10,000 pps were assembled from pulses of 45-μs phase duration. Conditions of 1, 2, 4, 8, and 16 pulses were investigated. Psychophysical thresholds (THRs) and most comfortable levels (MCLs) in multi-pulse conditions were measured. Psychophysical temporal integration functions (slopes of THRs/MCLs as a function of number of pulses) were −1.30 and −0.93 dB/doubling of the number of pulses, which correspond to the doubling of pulse duration. A total of 15 eABR conditions with different numbers of pulses and amplitudes were measured. The morphology of eABRs to multi-pulse stimuli did not differ from those to conventional single pulses. eABR wave eV amplitudes and latencies were analyzed extensively. At a fixed stimulation amplitude, an increasing number of pulses caused increasing wave eV amplitudes up to a certain, subject-dependent number of pulses. Then, amplitudes either saturated or even decreased. This contradicted the conventional amplitude growth functions and also contradicted psychophysical results. We showed that destructive interference could be a possible reason for such a finding, where peaks and troughs of responses to the first pulses were suppressed by those of successive pulses in the train. This study provides data on psychophysical THRs and MCLs and corresponding eABR responses for stimulation with single-pulse and multi-pulse stimuli with increasing duration. Therefore, it provides insights how pulse trains integrate at the level of the brainstem.

Background: Many detailed features of the cochlear anatomy have not been included in existing 3D cochlear models, including the microstructures inside the modiolar bone, which in turn determines the path of auditory nerve fibers (ANFs).Method: We captured the intricate modiolar microstructures in a 3D human cochlea model reconstructed from μCT scans. A new algorithm was developed to reconstruct ANFs running through the microstructures within the model. Using the finite element method, we calculated the electrical potential as well as its first and second spatial derivatives along each ANF elicited by the cochlear implant electrodes. Simulation results of electrical potential was validated against intracochlear potential measurements. Comparison was then made with a simplified model without the microstructures within the cochlea.Results: When the stimulus was delivered from an electrode located deeper in the apex, the extent of the auditory nerve influenced by a higher electric potential grew larger; at the same time, the maximal potential value at the auditory nerve also became larger. The electric potential decayed at a faster rate toward the base of the cochlea than toward the apex. Compared to the cochlear model incorporating the modiolar microstructures, the simplified version resulted in relatively small differences in electric potential. However, in terms of the first and second derivatives of electric potential along the fibers, which are relevant for the initiation of action potentials, the two models exhibited large differences: maxima in both derivatives with the detailed model were larger by a factor of 1.5 (first derivative) and 2 (second derivative) in the exemplary fibers. More importantly, these maxima occurred at different locations, and opposite signs were found for the values of second derivatives between the two models at parts along the fibers. Hence, while one model predicts depolarization and spike initiation at a given location, the other may instead predict a hyperpolarization.Conclusions: Although a cochlear model with fewer details seems sufficient for analysing the current spread in the cochlear ducts, a detailed-segmented cochlear model is required for the reconstruction of ANF trajectories through the modiolus, as well as the prediction of firing thresholds and spike initiation sites.

Background: Multi-compartment cable models of auditory nerve fibers have been developed to assist in the improvement of cochlear implants. With the advancement of computational technology and the results obtained from in vivo and in vitro experiments, these models have evolved to incorporate a considerable degree of morphological and physiological details. They have also been combined with three-dimensional volume conduction models of the cochlea to simulate neural responses to electrical stimulation. However, no specific rules have been provided on choosing the appropriate cable model, and most models adopted in recent studies were chosen without a specific reason or by inheritance.Methods: Three of the most cited biophysical multi-compartment cable models of the human auditory nerve, i.e., Rattay et al. (2001b), Briaire and Frijns (2005), and Smit et al. (2010), were implemented in this study. Several properties of single fibers were compared among the three models, including threshold, conduction velocity, action potential shape, latency, refractory properties, as well as stochastic and temporal behaviors. Experimental results regarding these properties were also included as a reference for comparison.Results: For monophasic single-pulse stimulation, the ratio of anodic vs. cathodic thresholds in all models was within the experimental range despite a much larger ratio in the model by Briaire and Frijns. For biphasic pulse-train stimulation, thresholds as a function of both pulse rate and pulse duration differed between the models, but none matched the experimental observations even coarsely. Similarly, for all other properties including the conduction velocity, action potential shape, and latency, the models presented different outcomes and not all of them fell within the range observed in experiments.Conclusions: While all three models presented similar values in certain single fiber properties to those obtained in experiments, none matched all experimental observations satisfactorily. In particular, the adaptation and temporal integration behaviors were completely missing in all models. Further extensions and analyses are required to explain and simulate realistic auditory nerve fiber responses to electrical stimulation.

The mammalian auditory system is able to extract temporal and spectral features from sound signals at the two ears. One important cue for localization of low-frequency sound sources in the horizontal plane are inter-aural time differences (ITDs) which are first analyzed in the medial superior olive (MSO) in the brainstem. Neural recordings of ITD tuning curves at various stages along the auditory pathway suggest that ITDs in the mammalian brainstem are not represented in form of a Jeffress-type place code. An alternative is the hemispheric opponent-channel code, according to which ITDs are encoded as the difference in the responses of the MSO nuclei in the two hemispheres. In this study, we present a physiologically-plausible, spiking neuron network model of the mammalian MSO circuit and apply two different methods of extracting ITDs from arbitrary sound signals. The network model is driven by a functional model of the auditory periphery and physiological models of the cochlear nucleus and the MSO. Using a linear opponent-channel decoder, we show that the network is able to detect changes in ITD with a precision down to 10 μs and that the sensitivity of the decoder depends on the slope of the ITD-rate functions. A second approach uses an artificial neuronal network to predict ITDs directly from the spiking output of the MSO and ANF model. Using this predictor, we show that the MSO-network is able to reliably encode static and time-dependent ITDs over a large frequency range, also for complex signals like speech.