Neural Excitation Patterns Research Articles

The association of intraoperative electric field and neural excitation patterns of the cochlear implant with patient-related factors of age, gender, cochlear diameter, and postoperative speech measures

The association of intraoperative electric field and neural excitation patterns of the cochlear implant with patient-related factors of age, gender, cochlear diameter, and postoperative speech measures

The human auditory system and audio

This work reviews the human auditory system, elucidating some of the specialized mechanisms and non-linear pathways along the chain of events between physical sound and its perception. Customary relationships between frequency, time, and phase—such as the uncertainty principle—that hold for linear systems, do not apply straightforwardly to the hearing process. Auditory temporal resolution for certain processes can be a hundredth of the period of the signal, and can extend down to the microseconds time scale. The astonishingly large number of variations that correspond to the neural excitation pattern of 30,000 auditory nerve fibers, originating from 3500 inner hair cells, explicates the vast capacity of the auditory system for the resolution of sonic detail. And the ear is sensitive enough to detect a basilar-membrane amplitude at the level of a picometer, or about a hundred times smaller than an atom. This article surveys and provide new insights into some of the impressive capabilities of the human auditory system and explores their relationship to fidelity in reproduced sound.

Relationship between electrode position and temporal modulation sensitivity in cochlear implant users: Are close electrodes always better?

Temporal modulation sensitivity has been studied extensively for cochlear implant (CI) users due to its strong correlation to speech recognition outcomes. Previous studies reported that temporal modulation detection thresholds (MDTs) vary across the tonotopic axis and attributed this variation to patchy neural survival. However, correlates of neural health identified in animal models depend on electrode position in humans. Nonetheless, the relationship between MDT and electrode location has not been explored. We tested 13 ears for the effect of distance on modulation sensitivity, specifically targeting the question of whether electrodes closer to the modiolus are universally beneficial. Participants in this study were postlingually deafened and users of Cochlear Nucleus CIs. The distance of each electrode from the medial wall (MW) of the cochlea and mid-modiolar axis (MMA) was measured from scans obtained using computerized tomography (CT) imaging. The distance measures were correlated with slopes of spatial tuning curves measured on selected electrodes to investigate if electrode position accounts, at least in part, for the width of neural excitation. In accordance with previous findings, electrode position explained 24% of the variance in slopes of the spatial tuning curves. All functioning electrodes were also measured for MDTs. Five ears showed a positive correlation between MDTs and at least one distance measure across the array; 6 ears showed negative correlations and the remaining two ears showed no relationship. The ears showing positive MDT-distance correlations, thus benefiting from electrodes being close to the neural elements, were those who performed better on the two speech recognition measures, i.e., speech reception thresholds (SRTs) and recognition of the AzBio sentences. These results could suggest that ears able to take advantage of the proximal placement of electrodes are likely to have better speech recognition outcomes. Previous histological studies of humans demonstrated that speech recognition is correlated with spiral ganglion cell counts. Alternatively, ears with good speech recognition outcomes may have good overall neural health, which is a precondition for close electrodes to produce spatially confined neural excitation patterns that facilitate modulation sensitivity. These findings suggest that the methods to reduce channel interaction, e.g., perimodiolar electrode array or current focusing, may only be beneficial for a subgroup of CI users. Additionally, it suggests that estimating neural survival preoperatively is important for choosing the most appropriate electrode array type (perimodiolar vs. lateral wall) for optimal implant function.

Estimating human neural tuning curves at low-level sound from human psychophysical masking data and the cochlea-frequency maps

We proposed a three-slope method to estimate human frequency tuning curves at low sound levels. As a starting point, cat neural excitation patterns (Allen and Fahey, 1993) are derived from Liberman’s cat cochlea neural tuning curves data (Liberman, 1978) in a mathematical way. A three-slope structure inspired by (Rhode,1978) is proposed to represent neural excitation patterns. The aim of this paper is to estimate the three-slope structure for human neural excitation patterns and then transform human neural excitation patterns into human tuning curves by using a human cochlea-frequency map (Greenwood, 1990). In 1993, Allen and Fahey introduced the concept of the second cochlea map, which was shown to be highly correlated with both neural excitation patterns and distortion product otoacoustic emissions (DPOAE). Thus, three slopes of human neural excitation patterns may be estimated via the second cochlea map and human masking data (Wegel and Lane, 1924). In the present study, slopes are estimated from limited existing psychophysical data, which can be improved with more accurate experimental data in the future.

The relation between polarity sensitivity and neural degeneration in a computational model of cochlear implant stimulation

The main aim of this computational modelling study was to test the validity of the hypothesis that sensitivity to the polarity of cochlear implant stimulation can be interpreted as a measure of neural health. For this purpose, the effects of stimulus polarity on neural excitation patterns were investigated in a volume conduction model of the implanted human cochlea, which was coupled with a deterministic active nerve fibre model based on characteristics of human auditory neurons. The nerve fibres were modelled in three stages of neural degeneration: intact, with shortened peripheral terminal nodes and with complete loss of the peripheral processes. The model simulated neural responses to monophasic, biphasic, triphasic and pseudomonophasic pulses of both polarities. Polarity sensitivity was quantified as the so-called polarity effect (PE), which is defined as the dB difference between cathodic and anodic thresholds.Results showed that anodic pulses mostly excited the auditory neurons in their central axons, while cathodic stimuli generally excited neurons in their peripheral processes or near their cell bodies. As a consequence, cathodic thresholds were more affected by neural degeneration than anodic thresholds. Neural degeneration did not have a consistent effect on the modelled PE values, though there were notable effects of electrode contact insertion angle and distance from the modiolus. Furthermore, determining PE values using charge-balanced multiphasic pulses as approximations of monophasic stimuli produced different results than those obtained with true monophasic pulses, at a degree that depended on the specific pulse shape; in general, pulses with lower secondary phase amplitudes showed polarity sensitivities closer to those obtained with true monophasic pulses.The main conclusion of this study is that polarity sensitivity is not a reliable indicator of neural health; neural degeneration affects simulated polarity sensitivity, but its effect is not consistently related to the degree of degeneration. Polarity sensitivity is not simply a product of the state of the neurons, but also depends on spatial factors.

Recognition of stimulus received by recurrent neural network

The study is concerned with the comparison of two methods for identification of stimulus received by artificial neural network using neural activity pattern that corresponds to the period of storing information about this stimulus in the working memory. We used simple recurrent neural networks learned to pass the delayed matching-to-sample test. Neural activity was detected at the period of pause between receiving stimuli. The analysis of neural excitation patterns showed that neural networks encoded variables that were relevant for the task during the delayed matching-to-sample test, and their activity patterns were dynamic. The method of centroids allowed identifying the type of the received stimuli with efficiency up to 75% while the method of neural network-based decoder showed 100% efficiency. In addition, this method was applied to determine the minimal set of neurons whose activity was the most significant for stimulus recognition.

An iterative deconvolution model to extract the temporal firing properties of the auditory nerve fibers in human eCAPs

The electrically evoked compound action potential (eCAP) has been widely studied for its clinical value for the evaluation of the surviving auditory nerve (AN) cells. However, many unknowns remain about the temporal firing properties of the AN fibers that underlie the eCAP in CI recipients. These temporal properties may contain valuable information about the condition of the AN. Here, we propose an iterative deconvolution model for estimating the human evoked unitary response (UR) and for extracting the compound discharge latency distribution (CDLD) from eCAP recordings, under the assumption that all AN fibers have the same UR. In this model, an eCAP is modeled by convolving a parameterized UR and a parameterized CDLD model. Both the UR and CDLD are optimized with an iterative deconvolution fitting error minimization routine to minimize the error between the modeled eCAP and the recorded eCAP.•This method first estimates the human UR from eCAP recordings. The human eCAP is unknown at the time of this writing. The UR is subsequently used to extract the underlying temporal neural excitation pattern (the CDLD) that reflects the contributions from individual AN fibers in human eCAPs.•By calculating the CDLD, the synchronicity of AN fibers can be evaluated.

Longitudinal effect of deactivating stimulation sites based on low-rate thresholds on speech recognition in cochlear implant users

Objective: The objective of the current study was to examine the longitudinal effect of deactivating stimulation sites estimated to produce broad neural excitation on speech recognition.Design: Spatial patterns of neural excitation were estimated based on a previously established psychophysical measure, that is, detection threshold for low-rate pulse trains. Stimulation sites with relatively poor thresholds were deactivated in an experimental map. The acute effect was evaluated, in quiet and in noise, immediately after the experimental map was created (baseline), after the subjects practiced with the experimental map for two months (treatment), and after the subjects’ daily map was switched back again to the clinical map for another two months (withdrawal).Study sample: Eight Cochlear Nucleus device users participated in the study.Results: For both listening in noise and in quiet, the greatest effect of deactivation was observed after the subjects were given time to adapt to the new frequency allocations. The effect was comparable for listening in fluctuating and steady-state noises. All subjects benefited from deactivation for listening in noise, but subjects with greater variability in thresholds were more likely to benefit from deactivation for listening in quiet.Conclusion: The benefit of electrode deactivation for speech recognition can increase with practice.

Difference limens for noise bandwidth discrimination in listeners with normal and impaired hearing

Frequency-lowering (FL) in hearing aids is often used to move inaudible high-frequency energy from sibilant fricatives to spectral regions where hearing better. Clinically, FL settings that maximize the spectral separation between these sounds, which can be modeled as bands of noise, are assumed to maximize discrimination between them and other speech contrasts. The purpose of this study was to quantify the minimum spectral differences for normal-hearing and hearing-impaired listeners to discriminate between bands of frozen noise. Noise bands corresponded to the average frequency and bandwidth of sibilant fricatives after undergoing FL using settings appropriate for mild-to-moderate, moderately-severe, and severely-profound hearing losses. Noise bands differed on the low- and/or the high-frequency edges. Discrimination in normal-hearing listeners was constant across presentation level and the three frequency ranges. Discrimination was also better for high-frequency edge differences. Neural excitation patterns generated from an auditory nerve model account for these findings. Neural excitation patterns generated for the three severities of hearing loss indicate that hearing-impaired listeners will rely heavily on spectral differences on the low-frequency edge and indicate that sibilant fricatives processed with FL will not be able to be discriminated solely on the basis of high-frequency edge differences. [Grant supported by Sonova USA, Inc.] Frequency-lowering (FL) in hearing aids is often used to move inaudible high-frequency energy from sibilant fricatives to spectral regions where hearing better. Clinically, FL settings that maximize the spectral separation between these sounds, which can be modeled as bands of noise, are assumed to maximize discrimination between them and other speech contrasts. The purpose of this study was to quantify the minimum spectral differences for normal-hearing and hearing-impaired listeners to discriminate between bands of frozen noise. Noise bands corresponded to the average frequency and bandwidth of sibilant fricatives after undergoing FL using settings appropriate for mild-to-moderate, moderately-severe, and severely-profound hearing losses. Noise bands differed on the low- and/or the high-frequency edges. Discrimination in normal-hearing listeners was constant across presentation level and the three frequency ranges. Discrimination was also better for high-frequency edge differences. Neural excitation patt...

Pulse-rate discrimination deficit in cochlear implant users: is the upper limit of pitch peripheral or central?

Cochlear implant (CI) users do not reliably associate an increase in pulse rate above 300 pulses per second (pps) with an increase in pitch. The locus of this upper limit of pitch remains unknown. The present study tested the hypothesis that this deficit resides at least initially at the auditory nerve. The hypothesis was tested by comparing pulse rate discrimination in different neural excitation patterns, in which a large versus small population of auditory nerve fibers was activated. If poorer pulse rate discrimination was found under conditions where narrower spread of neural excitation (SOE) was anticipated where a relatively small neural population was activated, then it would support the hypothesis that the rate processing deficit found in CI users is related to peripheral neural degeneration. Nine listeners (12 ears) implanted with the Cochlear Americas Nucleus® devices participated in the study. Different SOE conditions were created by (1) selecting electrodes that showed narrow versus broad forward-masked psychophysical spatial tuning curves, and (2) by measuring these electrodes in monopolar (MP) and narrow bipolar (BP0) electrode configurations. Rate discrimination difference limen (DL) was measured at the selected electrodes in two electrode configurations at three base rates (200, 300 and 500 pps). Consistent with the prediction, group mean DL was better (1) at stimulation sites measured with broader tuning, and (2) in MP relative to BP stimulation. These effects were more salient at the more challenging base rates. There was a weak relationship between rate discrimination (above thresholds) and the effect of rate on detection thresholds. Finally, rate discrimination at rates above the known upper limit (i.e., 500 pps) was correlated with duration of deafness and highly predicted the subjects’ speech recognition performance in noise. These findings support that pulse rate discrimination depends, at least partially, on neural conditions at the auditory periphery and this peripheral limit predicts speech recognition outcomes with a CI.

Focused electrical stimulation using a single current source

Objective. Cochlear implants, while providing significant benefits to recipients, remain limited due to broad neural activation. Focussed multipolar stimulation (FMP) is an advanced stimulation strategy that uses multiple current sources to produce highly focussed patterns of neural excitation in order to overcome these shortcomings. Approach. This report presents single-source multipolar stimulation (SSMPS), a novel form of stimulation based on a single current source and a passive current divider. Compared to conventional FMP with multiple current sources, SSMPS can be implemented as a modular addition to conventional (i.e. single) current source stimulation systems facilitating charge balance within the cochlea. As with FMP, SSMPS requires the determination of a transimpedance matrix to allow for focusing of the stimulation. The first part of this study therefore investigated the effects of varying the probe stimulus (e.g. current level and pulse width) on the measurement of the transimpedance matrix. SSMPS was then studied using in vitro based measurements of voltages at non-stimulated electrodes along an electrode array in normal saline. The voltage reduction with reference to monopolar stimulation was compared to tripolar and common ground stimulation, two clinically established stimulation modes. Finally, a proof of principle in vivo test of SSMPS in a feline model was performed. Main results. A probe stimulus of at least 40 nC is required to reliably measure the transimpedance matrix. In vitro stimulation using SSMPS resulted in a significantly greater voltage reduction compared to monopolar, tripolar and common ground stimulation. Interestingly, matching measurement and stimulation parameters did not lead to an improved focussing performance. Compared to monopolar stimulation, SSMPS resulted in reduced spread of neural activity in the inferior colliculus, albeit with increased thresholds. Significance. The present study demonstrates that SSMPS successfully limits the broadening of the excitatory field along the electrode array and a subsequent reduction in the spread of neural excitation.

Temporal Modulation Detection Depends on Sharpness of Spatial Tuning.

Prior research has shown that in electrical hearing, cochlear implant (CI) users' speech recognition performance is related in part to their ability to detect temporal modulation (i.e., modulation sensitivity). Previous studies have also shown better speech recognition when selectively stimulating sites with good modulation sensitivity rather than all stimulation sites. Site selection based on channel interaction measures, such as those using imaging or psychophysical estimates of spread of neural excitation, has also been shown to improve speech recognition. This led to the question of whether temporal modulation sensitivity and spatial selectivity of neural excitation are two related variables. In the present study, CI users' modulation sensitivity was compared for sites with relatively broad or narrow neural excitation patterns. This was achieved by measuring temporal modulation detection thresholds (MDTs) at stimulation sites that were significantly different in their sharpness of the psychophysical spatial tuning curves (PTCs) and measuring MDTs at the same sites in monopolar (MP) and bipolar (BP) stimulation modes. Nine postlingually deafened subjects implanted with Cochlear Nucleus® device took part in the study. Results showed a significant correlation between the sharpness of PTCs and MDTs, indicating that modulation detection benefits from a more spatially restricted neural activation pattern. There was a significant interaction between stimulation site and mode. That is, using BP stimulation only improved MDTs at stimulation sites with broad PTCs but had no effect or sometimes a detrimental effect on MDTs at stimulation sites with sharp PTCs. This interaction could suggest that a criterion number of nerve fibers isneeded to achieve optimal temporal resolution, and, to achieve optimized speech recognition outcomes, individualized selection of site-specific current focusing strategies may be necessary. These results also suggest that the removal of stimulation sites measured with poor MDTs might improve both temporal and spectral resolution.

An oscillatory template pitch model

Traditional approaches to explaining missing fundamental and pitch-shift phenomena have relied on either the fitting of harmonic templates to spectral information (generally assumed to correspond to a neural excitation pattern), or by performing an autocorrelation-based calculation on temporal information. In this paper, an alternative approach relying on the dynamics of phase-locking oscillators is proposed. Rather than applying some decoding procedure, such as spectral analysis or autocorrelation, a pitch estimate is given by the state (firing frequency) of an appropriately excited oscillator in a template structure operating on peripheral information. This approach is shown to reproduce many of the classical pitch shift-phenomena. In addition to a direct implementation in terms of phase-locking oscillators, a simplified model consisting of arrays of adaptive templates, operating directly on timing information, is also presented. This latter approach offers a straightforward way to tune the model in acc...

Evaluating Multipulse Integration as a Neural-Health Correlate in Human Cochlear Implant Users: Effects of Stimulation Mode.

Previous psychophysical studies have shown that a steep detection-threshold-versus-stimulation-rate function (multipulse integration; MPI) is associated with laterally positioned electrodes producing a broad neural excitation pattern. These findings are consistent with steep MPI depending on either a certain width of neural excitation allowing a large population of neurons operating at a low point on their dynamic range to respond to an increase in stimulation rate or a certain slope of excitation pattern that allows recruitment of neurons at the excitation periphery. Results of the current study provide additional support for these mechanisms by demonstrating significantly flattened MPI functions in narrow bipolar than monopolar stimulation. The study further examined the relationship between the steepness of the psychometric functions for detection (d' versus log current level) and MPI. In contrast to findings in monopolar stimulation, current data measured in bipolar stimulation suggest that steepness of the psychometric functions explained a moderate amount of the across-site variance in MPI. Steepness of the psychometric functions, however, cannot explain why MPI flattened in bipolar stimulation, since slopes of the psychometric functions were comparable in the two stimulation modes. Lastly, our results show that across-site mean MPI measured in monopolar and bipolar stimulation correlated with speech recognition in opposite signs, with steeper monopolar MPI being associated with poorer performance but steeper bipolar MPI being associated with better performance. If steeper MPI requires broad stimulation of the cochlea, the correlation between monopolar MPI and speech recognition can be interpreted as the detrimental effect of poor spectral resolution on speech recognition. Assuming bipolar stimulation produces narrow excitation, and MPI measured in bipolar stimulation reflects primarily responses of the on-site neurons, the correlation between bipolar MPI and speech recognition can be understood in light of the importance of neural survival for speech recognition.

Deactivating stimulation sites based on low-rate thresholds improves spectral ripple and speech reception thresholds in cochlear implant users.

The study examined whether the benefit of deactivating stimulation sites estimated to have broad neural excitation was attributed to improved spectral resolution in cochlear implant users. The subjects' spatial neural excitation pattern was estimated by measuring low-rate detection thresholds across the array [see Zhou (2016). PLoS One 11, e0165476]. Spectral resolution, as assessed by spectral-ripple discrimination thresholds, significantly improved after deactivation of five high-threshold sites. The magnitude of improvement in spectral-ripple discrimination thresholds predicted the magnitude of improvement in speech reception thresholds after deactivation. Results suggested that a smaller number of relatively independent channels provide a better outcome than using all channels that might interact.

Monopolar Detection Thresholds Predict Spatial Selectivity of Neural Excitation in Cochlear Implants: Implications for Speech Recognition.

The objectives of the study were to (1) investigate the potential of using monopolar psychophysical detection thresholds for estimating spatial selectivity of neural excitation with cochlear implants and to (2) examine the effect of site removal on speech recognition based on the threshold measure. Detection thresholds were measured in Cochlear Nucleus® device users using monopolar stimulation for pulse trains that were of (a) low rate and long duration, (b) high rate and short duration, and (c) high rate and long duration. Spatial selectivity of neural excitation was estimated by a forward-masking paradigm, where the probe threshold elevation in the presence of a forward masker was measured as a function of masker-probe separation. The strength of the correlation between the monopolar thresholds and the slopes of the masking patterns systematically reduced as neural response of the threshold stimulus involved interpulse interactions (refractoriness and sub-threshold adaptation), and spike-rate adaptation. Detection threshold for the low-rate stimulus most strongly correlated with the spread of forward masking patterns and the correlation reduced for long and high rate pulse trains. The low-rate thresholds were then measured for all electrodes across the array for each subject. Subsequently, speech recognition was tested with experimental maps that deactivated five stimulation sites with the highest thresholds and five randomly chosen ones. Performance with deactivating the high-threshold sites was better than performance with the subjects’ clinical map used every day with all electrodes active, in both quiet and background noise. Performance with random deactivation was on average poorer than that with the clinical map but the difference was not significant. These results suggested that the monopolar low-rate thresholds are related to the spatial neural excitation patterns in cochlear implant users and can be used to select sites for more optimal speech recognition performance.

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.

Constructing a three-dimensional electrical model of a living cochlear implant user's cochlea.

Hearing performance varies greatly among users of cochlear implants. Current three-dimensional cochlear models that predict the electrical fields inside a stimulated cochlea and their effect on neural excitation are generally based on a generic human or guinea pig cochlear shape that does not take inter-user morphological variations into account. This precludes prediction of user-specific performance. The aim of this study is to develop a model of the implanted cochlea of a specific living human individual and to assess if the inclusion of morphological variations in cochlear models affects predicted outcomes significantly. Five three-dimensional electric volume conduction models of the implanted cochleae of individual living users were constructed from standard CT scan data. These models were embedded in head models that include monopolar return electrodes in accurate anatomic positions. Potential distributions and neural excitation patterns were predicted for each of the models. Modeled potential distributions and neural excitation profiles (threshold amplitudes, center frequencies, and bandwidths) are affected by user-specific cochlear morphology and electrode placement within the cochlea. This work suggests that the use of user-specific models is indicated when more detailed analysis is required than what is available from generic models. Copyright © 2015 John Wiley & Sons, Ltd.

Peripheral and Central Contributions to Cortical Responses in Cochlear Implant Users.

The primary goal of this study was to describe relationships between peripheral and central electrophysiologic measures of auditory processing within individual cochlear implant (CI) users. The distinctiveness of neural excitation patterns resulting from the stimulation of different electrodes, referred to as 'spatial selectivity,' was evaluated. The hypothesis was that if central representations of spatial interactions differed across participants semi-independently of peripheral input, then the within-subject relationships between peripheral and central electrophysiologic measures of spatial selectivity would reflect those differences. Cross-subject differences attributable to processing central to the auditory nerve may help explain why peripheral electrophysiologic measures of spatial selectivity have not been found to correlate with speech perception. Eleven adults participated in this and a companion study. All were peri- or post-lingually deafened with more than 1 year of CI experience. Peripheral spatial selectivity was evaluated at 13 cochlear locations using 13 electrodes as probes to elicit electrically evoked compound action potentials (ECAPs). Masker electrodes were varied across the array for each probe electrode to derive channel-interaction functions. The same 13 electrodes were used to evaluate spatial selectivity represented at a cortical level. Electrode pairs were stimulated sequentially to elicit the auditory change complex (ACC), an obligatory cortical potential suggestive of discrimination. For each participant, the relationship between ECAP channel-interaction functions (quantified as channel-separation indices) and ACC N1-P2 amplitudes was modeled using the saturating exponential function y = a * (1-e). Both a and b coefficients were varied using a least-squares approach to optimize the fits. Electrophysiologic measures of spatial selectivity assessed at peripheral (ECAP) and central (ACC) levels varied across participants. The results indicate that differences in ACC amplitudes observed across participants for the same stimulus conditions were not solely the result of differences in peripheral excitation patterns. This finding supports the view that processing at multiple points along the auditory neural pathway from the periphery to the cortex may vary across individuals with different etiologies and auditory experiences. The distinctiveness of neural excitation resulting from electrical stimulation varies across CI recipients, and this variability was observed in both peripheral and cortical electrophysiologic measures. The ACC amplitude differences observed across participants were partially independent from differences in peripheral neural spatial selectivity. These findings are clinically relevant because they imply that there may be limits (1) to the predictive ability of peripheral measures and (2) in the extent to which improving the selectivity of electrical stimulation via programming options (e.g., current focusing/steering) will result in more specific central neural excitation patterns or will improve speech perception.

Hybrid neuromusculoskeletal modeling to best track joint moments using a balance between muscle excitations derived from electromyograms and optimization

Current electromyography (EMG)-driven musculoskeletal models are used to estimate joint moments measured from an individual׳s extremities during dynamic movement with varying levels of accuracy. The main benefit is the underlying musculoskeletal dynamics is simulated as a function of realistic, subject-specific, neural-excitation patterns provided by the EMG data. The main disadvantage is surface EMG cannot provide information on deeply located muscles. Furthermore, EMG data may be affected by cross-talk, recording and post-processing artifacts that could adversely influence the EMG׳s information content. This limits the EMG-driven model׳s ability to calculate the multi-muscle dynamics and the resulting joint moments about multiple degrees of freedom. We present a hybrid neuromusculoskeletal model that combines calibration, subject-specificity, EMG-driven and static optimization methods together. In this, the joint moment tracking errors are minimized by balancing the information content extracted from the experimental EMG data and from that generated by a static optimization method. Using movement data from five healthy male subjects during walking and running we explored the hybrid model׳s best configuration to minimally adjust recorded EMGs and predict missing EMGs while attaining the best tracking of joint moments. Minimally adjusted and predicted excitations substantially improved the experimental joint moment tracking accuracy than current EMG-driven models. The ability of the hybrid model to predict missing muscle EMGs was also examined. The proposed hybrid model enables muscle-driven simulations of human movement while enforcing physiological constraints on muscle excitation patterns. This might have important implications for studying pathological movement for which EMG recordings are limited.