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Unifying information theory and machine learning in a model of electrode discrimination in cochlear implants.

ABSTRACT: Despite the development and success of cochlear implants over several decades, wide inter-subject variability in speech perception is reported. This suggests that cochlear implant user-dependent factors limit speech perception at the individual level. Clinical studies have demonstrated the importance of the number, placement, and insertion depths of electrodes on speech recognition abilities. However, these do not account for all inter-subject variability and to what extent these factors affect speech recognition abilities has not been studied. In this paper, an information theoretic method and machine learning technique are unified in a model to investigate the extent to which key factors limit cochlear implant electrode discrimination. The framework uses a neural network classifier to predict which electrode is stimulated for a given simulated activation pattern of the auditory nerve, and mutual information is then estimated between the actual stimulated electrode and predicted ones. We also investigate how and to what extent the choices of parameters affect the performance of the model. The advantages of this framework include i) electrode discrimination ability is quantified using information theory, ii) it provides a flexible framework that may be used to investigate the key factors that limit the performance of cochlear implant users, and iii) it provides insights for future modeling studies of other types of neural prostheses.

SUBMITTER: Gao X

PROVIDER: S-EPMC8451994 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Music perception of cochlear implants (CI) users is constrained by the absence of salient musical pitch cues crucial for melody identification, but is made possible by timing cues that are largely preserved by current devices. While musical timing cues, including beats and rhythms, are a potential route to music learning, it is not known what extent they are perceptible to CI users in complex sound scenes, especially when pitch and timbral features can co-occur and obscure these musical features. The task at hand, then, becomes one of optimizing the available timing cues for young CI users by exploring ways that they might be perceived and encoded simultaneously across multiple modalities. Accordingly, we examined whether training tasks that engage active music listening through dance might enhance the song identification skills of deaf children with CIs. Nine CI children learned new songs in two training conditions: (a) listening only (auditory learning), and (2) listening and dancing (auditory-motor learning). We examined children's ability to identify original song excerpts, as well as mistuned, and piano versions from a closed-set task. While CI children were less accurate than their normal hearing peers, they showed greater song identification accuracies in versions that preserved the original instrumental beats following learning that engaged active listening with dance. The observed performance advantage is further qualified by a medium effect size, indicating that the gains afforded by auditory-motor learning are practically meaningful. Furthermore, kinematic analyses of body movements showed that CI children synchronized to temporal structures in music in a manner that was comparable to normal hearing age-matched peers. Our findings are the first to indicate that input from CI devices enables good auditory-motor integration of timing cues in child CI users for the purposes of listening and dancing to music. Beyond the heightened arousal from active engagement with music, our findings indicate that a more robust representation or memory of musical timing features was made possible by multimodal processing. Methods that encourage CI children to entrain, or track musical timing with body movements, may be particularly effective in consolidating musical knowledge than methods that engage listening only.

Project description:ObjectivesThe primary objective of this study was to quantify differences in evoked potential correlates of spiral ganglion neuron (SGN) density between younger and older individuals with cochlear implants (CIs) using the electrically evoked compound action potential (ECAP). In human temporal bone studies and in animal models, SGN density is the lowest in older subjects and in those who experienced long durations of deafness during life. SGN density also varies as a function of age at implantation and hearing loss etiology. Taken together, it is likely that younger listeners who were deafened and implanted during childhood have denser populations of SGNs than older individuals who were deafened and implanted later in life. In animals, ECAP amplitudes, amplitude growth function (AGF) slopes, and their sensitivity to stimulus interphase gap (IPG) are predictive of SGN density. The authors hypothesized that younger listeners who were deafened and implanted as children would demonstrate larger ECAP amplitudes, steeper AGF slopes, and greater IPG sensitivity than older, adult-deafened and implanted listeners.DesignData were obtained from 22 implanted ears (18 individuals). Thirteen ears (9 individuals) were deafened and implanted as children (child-implanted group), and nine ears (9 individuals) were deafened and implanted as adults (adult-implanted group). The groups differed significantly on a number of demographic variables that are implicitly related to SGN density: (1) chronological age; (2) age at implantation; and (3) duration of preimplantation hearing loss. ECAP amplitudes, AGF linear slopes, and thresholds were assessed on a subset of electrodes in each ear in response to two IPGs (7 and 30 µsec). Speech recognition was assessed using a medial vowel identification task.ResultsCompared with the adult-implanted listeners, individuals in the child-implanted group demonstrated larger changes in ECAP amplitude when the IPG of the stimulus was increased from 7 to 30 µsec (i.e., greater IPG sensitivity). On average, child-implanted participants also had larger ECAP amplitudes and steeper AGF linear slopes than the adult-implanted participants, irrespective of IPG. IPG sensitivity for AGF linear slope and ECAP threshold did not differ between age groups. Vowel recognition performance was not correlated with any of the ECAP measures assessed in this study.ConclusionsThe results of this study support the theory that young CI listeners who were deafened and implanted during childhood may have denser neural populations than older listeners who were deafened and implanted as adults. Potential between-group differences in SGN integrity emphasize a need to investigate optimized CI programming parameters for younger and older listeners.

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Unifying information theory and machine learning in a model of electrode discrimination in cochlear implants.

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