Auditory steady state responses and cochlear implants: Modeling the artifact-response mixture in the perspective of denoising

Faten Mina 1, 2, * Virginie Attina 1, 2 Yvan Duroc 1 Evelyne Veuillet 1, 2 Eric Truy 1, 3 Hung Thai-Van 1, 2
* Auteur correspondant
1 CRNL - Centre de recherche en neurosciences de Lyon
2 Service d'audiologie et d'explorations otoneurologiques [Hôpital Edouard Herriot, Lyon]
3 Département ENT [HCL Hospices Civils de Lyon]
Abstract : Auditory steady state responses (ASSRs) in cochlear implant (CI) patients are contaminated by the spread of a continuous CI electrical stimulation artifact. The aim of this work was to model the electrophysiological mixture of the CI artifact and the corresponding evoked potentials on scalp electrodes in order to evaluate the performance of denoising algorithms in eliminating the CI artifact in a controlled environment. The basis of the proposed computational framework is a neural mass model representing the nodes of the auditory pathways. Six main contributors to auditory evoked potentials from the cochlear level and up to the auditory cortex were taken into consideration. The simulated dynamics were then projected into a 3-layer realistic head model. 32-channel scalp recordings of the CI artifact-response were then generated by solving the electromagnetic forward problem. As an application, the framework's simulated 32-channel datasets were used to compare the performance of 4 commonly used Independent Component Analysis (ICA) algorithms: info-max, extended infomax, jade and fastICA in eliminating the CI artifact. As expected, two major components were detectable in the simulated datasets, a low frequency component at the modulation frequency and a pulsatile high frequency component related to the stimulation frequency. The first can be attributed to the phase-locked ASSR and the second to the stimulation artifact. Among the ICA algorithms tested, simulations showed that infomax was the most efficient and reliable in denoising the CI artifact-response mixture. Denoising algorithms can induce undesirable deformation of the signal of interest in real CI patient recordings. The proposed framework is a valuable tool for evaluating these algorithms in a controllable environment ahead of experimental or clinical applications.
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PLoS ONE, Public Library of Science, 2017, 12 (3), pp.eCollection 2017. 〈10.1371/journal.pone.0174462.s015〉
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Faten Mina, Virginie Attina, Yvan Duroc, Evelyne Veuillet, Eric Truy, et al.. Auditory steady state responses and cochlear implants: Modeling the artifact-response mixture in the perspective of denoising. PLoS ONE, Public Library of Science, 2017, 12 (3), pp.eCollection 2017. 〈10.1371/journal.pone.0174462.s015〉. 〈inserm-01526074〉

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